hypothesis for stress

Tools and Resources
Customer Services
Affective Science
Biological Foundations of Psychology
Clinical Psychology: Disorders and Therapies
Cognitive Psychology/Neuroscience
Developmental Psychology
Educational/School Psychology
Forensic Psychology
Health Psychology
History and Systems of Psychology
Individual Differences
Methods and Approaches in Psychology
Neuropsychology
Organizational and Institutional Psychology
Personality
Psychology and Other Disciplines
Social Psychology
Sports Psychology
Share This Facebook LinkedIn Twitter

Article contents

Stress and coping theory across the adult lifespan.

Agus Surachman Agus Surachman Department of Human Development and Family Studies, Pennsylvania State University
and David M. Almeida David M. Almeida Department of Human Development and Family Studies, Pennsylvania State University
https://doi.org/10.1093/acrefore/9780190236557.013.341
Published online: 30 July 2018

Stress is a broad and complex phenomenon characterized by environmental demands, internal psychological processes, and physical outcomes. The study of stress is multifaceted and commonly divided into three theoretical perspectives: social, psychological, and biological. The social stress perspective emphasizes how stressful life experiences are embedded into social structures and hierarchies. The psychological stress perspective highlights internal processes that occur during stressful situations, such as individual appraisals of the threat and harm of the stressors and of the ways of coping with such stressors. Finally, the biological stress perspective focuses on the acute and long-term physiological changes that result from stressors and their associated psychological appraisals. Stress and coping are inherently intertwined with adult development.

social stress
psychological stress
biological stress
life events
chronic stressors
daily stressors

What Is Stress?

While stress is difficult to define (Contrada, 2011 ), stress researchers tend to share a common interest in a process by which external, environmental, or psychosocial demands surpass an individual’s adaptive capacity and result in biological and psychological changes that have the potential to jeopardize one’s health and well-being (Cohen, Kessler, & Gordon, 1997 ; Contrada, 2011 ). Stress can thus be viewed as a process delineated by three components (Almeida, Piazza, Stawski, & Klein, 2011 ; Cohen et al., 1997 ; Wheaton, 1994 ; Wheaton & Montazer, 2010 ): stressors (external or environmental demands), stress appraisals (the perceived severity of stressors), and distress (affective, behavioral, or biological responses to stressors).

Each of these components is emphasized in one of three theoretical stress perspectives: social, psychological, and biological (Cohen et al., 1997 ). The social stress perspective highlights the way that environmental or external demands precipitate individuals’ stress and how such demands are contingent upon contextual factors or social circumstances (Wheaton & Montazer, 2010 ). The psychological stress perspective focuses on individuals’ appraisals of stressors and the availability of coping resources to manage the overwhelming demands of such stressors (Cohen & Janicki-Deverts, 2012 ; Lazarus, 1999 ). Finally, the biological stress perspective highlights how and when physiological systems become activated by stress processes that may risk individuals’ physical health (Cohen et al., 1997 ). The purpose of this article is to describe each of these theoretical perspectives and their relevance to aging research.

Social Stress Perspective

The social stress perspective primarily focuses on the origins of stressful life experiences (Aneshensel, 1992 ; Pearlin, 2009 ). According to the social stress perspective, the experience of stressors is structurally constrained (Wheaton, 1999 ; Pearlin, 2009 ). Exposure to external demands is not random, but rather embedded in an individual’s position in society, social structure, social organizations, roles, and other social constructs (Aneshensel, 1992 ; Wheaton, 1999 ). Two central themes have emerged from the social stress perspective: (a) the differentiation of categories of stressor types and (b) the ways that social structures link to individuals’ experiences of stressors.

Categories of Stressors

Stressors are commonly divided into five categories: life events, chronic stressors, daily stressors, trauma, and nonevents (Wheaton, 1994 , 1999 ; Wheaton & Montazer, 2010 ).

Life Events

Life events , also known as life change events or event stressors , are discrete, observable stressor events that have a clear onset and offset (Wheaton & Montazer, 2010 ). Some examples of life event stressors are the death of a spouse, divorce, and job loss. The modern study of social stress started with the analysis of life events, partly because the easily verifiable nature of these events make it possible to operationalize the concept of stress itself (Wheaton, 1994 ; Wheaton & Montazer, 2010 ). One challenge of this research is identifying a pool of all possible life events that an individual might experience (Aneshensel, 1992 ). For example, items in the stressful life event scales often mix life events with traumas and daily stressors (Aldwin & Yancura, 2011 ).

Life event representation is an important issue for aging researchers. For example, an early study found an inverse association between age and exposure to life events, with older individuals showing fewer life events than their younger counterparts (Rabkin & Struening, 1976 ). Such a result runs counter to the general assumption that late life is associated with higher stressors due to the development of chronic illnesses and higher levels of bereavement (Aldwin & Yancura, 2011 ). However, further analysis showed that the Social Readjustment Rating Scale (Holmes & Rahe, 1967 ) that was used by Rabkin and Struening in their study consisted of items that included life events pertaining to younger individuals, such as marriage, birth, divorce, graduation, and job loss (Aldwin & Yancura, 2011 ). Analysis of life events using items designed for older individuals showed that there was no association between age and exposure to life events (Aldwin, 1990 ). Another study of life events showed that different sociohistorical experiences (e.g., wars, terrorist attacks, and economic downturn) influenced different levels of reported life events, indicating significant period effects (Chukwourji, Nwoke, & Ebere, 2017 ; Elder & Shananhan, 2006 ; Pruchno, Heid, & Wilson-Genderson, 2017 ). More longitudinal studies are needed to disentangle the influence of age and sociohistorical experiences on the reporting of stressful life events.

Chronic Stressors

The concept of chronic stressors , from a social stress perspective, originated from a study of chronic role strain by Pearlin and Schooler ( 1978 ) that articulated the importance of chronic disruptions in important social roles (e.g., marriage, work, and parenting) for health and well-being. Additional work by Wheaton and Montazer ( 2010 ) refined these ideas by providing three defining characteristics of chronic stressors that set them apart from event stressors:

Chronic stressors develop slowly and insidiously as continuous problems related to social roles and the social environment. In addition, chronic stressors may or may not start out as events.

The duration of the stressors from onset to offset is usually longer than the duration of life events.

Chronic stressors include both regular problems and issues related to daily roles and more specific problems, making them less self-limiting than life events.

Although chronic stressors are often tied to social roles, they also can include ambient stressors , which are not role bound, such as time pressure, financial problems, or living in a noisy place (Kershaw et al., 2015 ; Henderson, Child, Moore, Moore, & Kaczynski, 2016 ; Wheaton & Montazer, 2010 ). Table 1 provides a description of seven types of problems that are considered chronic stressors (Wheaton, 1997 ).

Most studies of stress involving older adults focused on chronic stressors (Aldwin & Yancura, 2011 ; Grzywacz, Almeida, Neupert, & Ettner, 2004 ). However, more research is needed to investigate age differences across adulthood in the prevalence and duration of chronic stressors (Aldwin & Yancura, 2011 ). Different age groups might have different sources of chronic stressors, which might lead to a similar rate of prevalence and duration of chronic stress (e.g., chronic diseases among older adults, as opposed to economic hardships among younger individuals).

Table 1. Problems Considered as Chronic Stressors

Daily stressors.

Daily stressors , or daily hassles , are often mistaken as chronic stressors (Kanner, Coyne, Schaefer, & Lazarus, 1981 ). The defining characteristics of daily stressors, which separate them from chronic stressors, are their duration and magnitude of severity. DeLongis, Folkman, and Lazarus ( 1988 ) characterized a daily stressor or daily hassle as a short-duration experience of a stressor, such as having an argument with a partner or getting caught in a traffic jam. In addition, Almeida ( 2005 ) defined daily stressors as relatively minor events experienced in day-to-day living. Table 2 provides example questions from the Daily Inventory of Stressful Events (DISE), used by researchers to ascertain information about the frequency of people’s daily stressors.

Compared to life events, daily stressors tend to have a more proximal effect on well-being (Almeida, 2005 ; Almeida et al., 2011 ). Daily stressors produce spikes in psychological distress during a particular day, while life events create prolonged bouts of distress (Almeida, 2005 ; Almeida et al., 2011 ). Daily stress also may have prolonged health effects when piled up across days, which in turn creates persistent irritations, frustrations, and overloads, including chronic physical and psychological distress, chronic conditions and functional impairment, and mortality (Chiang, Turiano, Mroczek, & Miller, 2018 ; Lazarus, 1999 ; Leger, Charles, Ayanian, & Almeida, 2015 ; Pearlin, Menaghan, Lieberman, & Mullan, 1981 ; Piazza, Charles, Sliwinski, Mogle, & Almeida, 2013 ; Zautra, 2003 ).

Such a pileup of stressors (i.e., accumulation of stressor exposure or total number of stressors that an individual experiences) is more problematic if the stressors experienced are less diverse (i.e., low evenness of the type of daily stressors that an individual experiences). Higher levels of stressor exposure that are accompanied by lower levels of stressor diversity indicate a depletion of specific types of resources and may indicate the chronicity of the stressors (see Koffer, Ram, Conroy, Pincus, & Almeida, 2016 , for an extensive discussion of stressor diversity).

The experience of daily stress differs across adulthood. Based on Midlife in the United States (MIDUS) data, a national longitudinal study of health and well-being ( http://midus.wisc.edu ), adults in the United States report at least one stressor on 40% of study days, and multiple stressors on 10% of study days (Almeida, Wethington, & Kessler, 2002 ). In general, studies show that the type and frequency of daily stressors differ by age (Aldwin, Sutton, Chiara, & Spiro, 1996 ; Almeida & Horn, 2004 ; Chiriboga, 1997 ). Mroczek and Almeida ( 2004 ) found that older adults reported fewer daily stressors, measured using DISE (see Table 2 ), and less stressor-related daily negative affect than younger individuals; however, older participants reported a higher level of severity in the reported stressors. Finally, Stawski, Sliwinski, Almeida, and Smyth ( 2008 ) found that there were no age differences in daily stressor-related negative affect.

Stressors sometimes can be categorized as traumatic. Trauma is defined by the Diagnostic and Statistical Manual of Mental Disorders (4th edition) as “events that involved actual or threatened death or serious injury, or a threat to the physical integrity of self or others . . . the person’s response [to the events] involved intense fear, helplessness, or horror” (APA, 1994 , pp. 427–428). However, according to Wheaton and Montazer ( 2010 ), not all traumas happen as events. Physical abuse that happens one time during childhood might fit the definition of a traumatic event. On the other hand, repeated and regular experiences of physical abuse might be better categorized as a chronic traumatic experience. Another important defining characteristic of trauma is its greater severity compared to other types of stressors. As a consequence, traumas might have a greater impact on long-term health and well-being.

Table 2. Questions From the DISE

Note : A “Yes” answer to each stem question is followed up with questions, including (a) a series of open-ended “probe” questions that ascertain a description of the stressful event, (b) a question regarding the perceived severity of the stressor, and (c) a list of structured primary appraisal questions inquiring about goals and values that were “at risk” because of the event (Almeida et al., 2002 ).

Source : Almeida et al. ( 2002 )

According to Ozer, Best, Lipsey, and Weiss ( 2003 ), most people experience at least one violent or life-threatening situation during their lives. Among older adults, car accidents are the most common source of trauma (Weintraub & Ruskin, 1999 ). In addition, a study by Wheaton, Roszell, and Hall ( 1997 ) indicated that being sent away from home in childhood is the least common trauma (prevalence rate = 3.5%) and the death of a spouse, child, or other loved one is the most common traumatic experience (prevalence rate = 50%). Using the Traumatic Life Events Questionnaire (TLEQ) shown in Table 3 , Ogle, Rubin, Berntsen, and Siegler ( 2013 ) found that nondisclosed childhood physical abuse is the least common trauma, and unexpected death, illness, or accident involving a loved one is the most common trauma.

Table 3. The TLEQ and Its Prevalence Among Adults in the United States

Note: n = 3,208.

Sources: Kubany et al. ( 2000 ); Ogle et al. ( 2013 ).

The last category of stressors are nonevents , defined as anticipated events or experiences that do not happen in reality (Gersten, Langer, Eisenberg, & Orzeck, 1974 ; Neugarten, Moore, & Lowe, 1965 ). Normative expectations play an important role in the stressfulness of nonevents such as not getting married by a certain age or not getting an anticipated promotion at a certain career stage (Frost & LeBlanc, 2014 ). Schuth, Posselt, and Breckwoldt ( 1992 ) studied miscarriage in the first trimester as a nonevent stressor. According to Wheaton and Montazer ( 2010 ), nonevents that have no tie to normative timing are more similar to chronic stressors, such as expecting a loan for low-income housing, but not receiving one.

Social Stress and Health: Exposure Versus Vulnerability

There are two hypotheses that researchers draw on to explain how social structures link to stressors and health outcomes: the exposure hypothesis and the vulnerability hypothesis (Aneshensel, 1992 ; Turner, Wheaton, & Lloyd, 1995 ). These competing hypotheses focus on disentangling whether exposure or vulnerability to stressors leads to disease risk. Stressor exposure is the likelihood that a person will be exposed to stressors given her or his social location, such as socioeconomic status (SES) or gender, and individual characteristics, such as personality (Almeida et al., 2011 ). On the other hand, vulnerability to stressors relates to the concept of reactivity , which is the likelihood that one will show physical or psychological reactions to experienced environmental demands or stressors (Almeida, 2005 ; Bolger & Zuckerman, 1995 ; Cacioppo, 1998 ).

There is considerable evidence supporting the idea of differentiated exposure to stressors based on sociodemographic, psychosocial, and situational characteristics as an explanation of why some people are healthier than others. For example, researchers have found that SES (Evans & Kim, 2010 ; Turner et al., 1995 ; Turner & Avison, 2003 ), age (Aldwin, 1990 ; Almeida & Horn, 2004 ; Hamarat et al., 2001 ), personality (Bouchard, 2003 ; Ebstrup, Eplov, Pisinger, & Jørgensen, 2011 ; Penley & Tomaka, 2002 ), and social support (Brewin, MacCarthy, & Frunham, 1989 ; Felsten, 1991 ; Huang, Costeines, Kaufman, & Ayala, 2014 ; Kwag, Martin, Russell, Franke, & Kohut, 2011 ) play critical roles in differentiating individuals’ experiences of stressor exposure.

However, there is also substantial evidence to support the vulnerability hypothesis. For example, a recent analysis of exposure and vulnerability to daily stressors showed that SES was not associated with exposure to daily stressors. However, individuals with lower SES were more reactive to the daily stressors that they experienced (Almeida, Neupert, Banks, & Serido, 2005 ; Grzywacz et al., 2004 ; Surachman, Wardecker, Chow, & Almeida, 2018 ). There are at least four speculated reasons for this (Grzywacz et al., 2004 ; Surachman et al., 2018 ), including (a) the experience of chronic stressors may desensitize individuals with lower SES in their reactions to minor day-to-day stressors; (b) the possibility of gender and racial differences that obscure the systematic variation in exposure to daily stressors; (c) individuals with lower SES may be less reflective and articulate when reporting their daily stressors; and (d) individuals from lower SES may encounter similar types of daily stressors, indicating a low number of daily stressors encountered and lower levels of daily stressor diversity.

Psychological Stress Perspective

The psychological stress perspective focuses on an individual’s perception and evaluation of the potential damage caused by external environmental demands (Cohen et al., 1997 ). The two concepts that are fundamental to the psychological stress perspective are appraisal and coping (Krohne, 2002 ). The stress appraisal model, developed by Lazarus & Folkman ( 1984 ) is the most influential psychological stress model. According to this perspective, the way that we evaluate external events (i.e., stressors) determines our degree of stress. Specifically, Lazarus and Folkman ( 1984 , p. 19) define psychological stress as “a particular relationship between the person and the environment that is appraised by the person as taxing or exceeding his or her resources and endangering his or her well-being.”

Psychological Stress and Appraisal

Arnold ( 1960 ) was the first theorist to use the term appraisal in the context of emotion and personality. Appraisal became the central concept of Lazarus’s psychological stress theory. The term appraisal refers to the continuous evaluation by individuals of their relationship with the external environment with respect to their implications for well-being (Lazarus, 1999 ).

Lazarus ( 1999 ) emphasizes the importance of differentiating the act of appraisal and appraising. The former focuses on the evaluative product, while the latter is the act of making the evaluation. Lazarus also distinguishes primary and secondary appraisal and appraising. The distinction is based on different sources of information in each evaluation process (Krohne, 2002 ). Primary appraisal refers to the evaluation of whether external events are relevant to one’s values, goal commitments, beliefs about the self and the world, and situational intentions. Stress occurs when external events threaten these key features of well-being during primary appraisal. There are three different stress conditions: harm/loss (damage that has already happened), threat (the possibility of damage in the future), and challenge (the possibility for growth). The primary appraisal has three main components: goal relevance , goal congruence , and type of ego development (Lazarus, 1999 ).

Secondary appraisal reflects evaluative processes that assess resources for dealing with or managing stress. During secondary appraisal, individuals provide judgments about who or what is responsible for a harm, threat, challenge, or benefit in order to place the blame or credit for an outcome issue. It is important to point out that the primary and secondary appraisal processes do not operate independently; instead, they reciprocally influence each other over time (Lazarus, 1999 ).

There are at least three criticisms regarding the concept of appraisal by Lazarus (Smith & Kirby, 2011 ). First, the labeling of appraisal as primary and secondary is misleading, as people often mistakenly assume that they reflect a sequence. Second, the definition of psychological stress is unclear, especially related to how much demand is considered as taxing one’s resources. Lazarus’s definition of stress is relatively restrictive to extreme conditions (i.e., environmental demands exceed resources). Third, it is not clear whether the three types of appraisal (i.e., harm/loss, threat, and challenge) are shaped purely by primary appraisal or by the combination of primary and secondary appraisal.

Coping Processes

Coping processes are very similar to stress appraisal processes. According to Lazarus and Folkman ( 1984 , p. 141), coping is defined as “constantly changing cognitive and behavioral efforts to manage specific external and/or internal demands that are appraised as taxing or exceeding the resources of the person.” According to this approach, coping follows stress appraisal and involves specific cognitive and behavioral strategies to manage stressful experiences and their consequences (Aldwin & Yancura, 2011 ). According to the definition of coping by Lazarus and Folkman ( 1984 ), coping efforts do not include their outcome or effectiveness. Every form of coping can be both effective and maladaptive (Smith & Kirby, 2011 ). Thus, coping also can be defined as the efforts to manage stressful situations, regardless of the effectiveness of those efforts (Lazarus & Folkman, 1984 ; Smith & Kirby, 2011 ). Indeed, the study of coping is intended to discriminate factors associated with adaptive versus maladaptive coping (Smith & Kirby, 2011 ).

According to Lazarus and Folkman ( 1984 ), coping can be categorized into two types: problem-focused coping (managing or changing the source of stress) and emotion-focused coping (regulation of stressful emotions). Brown and Nicassio ( 1987 ) offer an alternative classification of coping, which is active versus passive coping. In addition, Jensen, Turner, Romano, and Strom ( 1995 ) classify coping into cognitive versus behavioral types. Finally, Compas and colleagues ( 2001 , 2006 ) differentiate coping into three different categories: primary-control engagement (e.g., problem solving, changing the situation, and emotion regulation), secondary-control engagement (e.g., positive thinking, acceptance, and distraction), and disengagement coping.

There are clear signs that active/primary-control and accommodative/secondary-control coping are associated with adaptive outcomes such as better emotional well-being and physical health (Compas et al., 2006 ; Moskowitz, Hult, Bussolari, & Acree, 2009 ; Walker, Smith, Garber, & Claar, 2005 ). However, there are numerous null findings linking active/primary-control and accommodative/secondary-control coping and positive outcomes (Compas et al., 2001 ; Smith, Wallston, & Dwyer, 2003 ). Coyne and colleagues have extensively discussed limitations in the study of coping (e.g., Coyne & Racioppo, 2000 ). In general, there are at least two aspects that are needed to be improved in future studies of coping (Smith & Kirby, 2011 ): (a) coping should be studied in a more situated, context-specific manner, in which coping and the outcomes associated with individual incidents are examined; and (b) more studies are needed to focus on the role of control-related appraisals mediating the relationship between these dispositional antecedents and coping behavior.

Stress Appraisal and Coping Across Adulthood

In terms of age differences in stress appraisal, older adults appraise problems as less stressful (Aldwin et al., 1996 ; Folkman, Lazarus, Pimley, & Novacek, 1987 ) than younger adults. One possible explanation for this finding is that older individuals have higher levels of resiliency to stressors because of what they have been through across the life course (Aldwin et al., 1996 ). Major life events that are common to older adults, such as the death of a spouse or family member, make them more tolerant of minor stressors in their daily lives. Another possible explanation is that the lower stress appraisal among older adults is due to environmental changes (Lawton, Kleban, Rajagobal, & Dean, 1992 ). For example, retirement may lead to more leisure time for older adults, and thus fewer stressful experiences (Ginn & Fast, 2006 ; Rosenkoetter, Gams, & Engdahl, 2001 ).

Another example of environmental change is that older adults receive more respect from family members, which make their social experiences more pleasant (Fingerman & Baker, 2006 ). For example, others may be more hesitant to argue with or express their negative emotions with older individuals (Fingerman, Miller, & Charles, 2008 ). These explanations may partly explain why older adults reported fewer stressors with age. However, explanations based on retirement or deference to older adults are less conclusive, given that decreases in stressor appraisal continue long after retirement, and long after people have entered the venerable period (Charles, 2010 ). Two theoretical frameworks are especially useful to look at for their alternative explanations regarding lower stressor appraisal among older adults: socioemotional selectivity theory (Carstensen, Fung, & Charles, 2003 ) and the strength and vulnerability integration (SAVI) model (Charles, 2010 ).

According to socioemotional selectivity theory, time perspective plays a critical role in human goal-directed behavior and motivation (Carstensen, Isaacowitz, & Charles, 1999 ). As individuals get older, they perceive that they have a relatively more limited future compared to younger individuals (Lang & Carstensen, 2002 ). This awareness of limited time left is amplified by the fact that older adults increasingly experience the deaths of friends and family members (Cartensen et al., 2003 ). Change in time perspective is associated with goals among older adults, as they care more about experiencing meaningful relationships and care less about knowledge-related goals (Cartensen et al., 2003 ). According to socioemotional selectivity theory, older individuals achieve this goal by regulating their social contacts and network (Carstensen, Gross, & Fung, 1997 ). Thus, older adults reduce their social contacts in order to optimize emotionally meaningful and gratifying experiences and fewer experiences of negative interchanges (Cartensen et al., 2003 ).

The decrease in social contacts begins relatively early in life, around the 30s (Carstensen, 1992 ), indicating that this decrease is not unique to older individuals (Charles, 2010 ). Empirical studies show that social selection promotes affective well-being, such as increased satisfaction and more positive emotional experiences (Charles & Piazza, 2007 ; Fingerman, Hay, & Birditt, 2004 ). Finally, even though the size of social networks among older adults is decreasing, their social networks are characterized by warm, satisfying, and trusting relationships (Ryff & Keyes, 1995 ).

Charles ( 2010 ) extended the socioemotional selectivity theory by integrating age-related physiological vulnerabilities when considering emotion regulation among older adults. This concept is known as strength and vulnerability integration (SAVI) . According to SAVI, later adulthood is associated with both strengths and vulnerabilities, in which they play important roles in emotion regulation. The strengths include the motivation to maintain meaningful and gratifying relationships due to a change in time perspective (similar to socioemotional selectivity theory), as well as the cognitive-behavioral skills to do so. The vulnerabilities associated with aging include age-related physiological vulnerabilities that affect the recovery process during emotion regulation due to stressful experiences. Thus, increase in age is associated with an enhanced ability to avoid stressors, reappraise them as being less stressful, or both, while at the same time, it is also associated with physiological vulnerabilities that lower the flexibility of response to stress (Almeida et al., 2011 ; Charles 2010 ).

According to SAVI, age-related changes in emotion regulation are less likely to happen during exposure to stressors that cause high levels of physiological arousal. When this happens, older individuals will be less able to employ their emotion regulation strategy due to high physiological cues. After physiological symptoms are normalized, older individuals will report higher levels of well-being again, as their emotional states will be less influenced by their physiological states and more affected by their appraisal of an event. Thus, although the motivation to regulate well-being exists, certain circumstances such as chronic stress and neurological dysregulation may interfere with its efficacy on maintaining well-being (Almeida et al., 2011 ; Charles, 2010 ; Charles & Piazza, 2009 ).

There are mixed results regarding the association between coping strategies and age (Aldwin & Yancura, 2011 ). Folkman et al. ( 1987 ) found that older individuals reported less frequent use of problem-focused coping compared to younger individuals. Similarly, Aldwin et al. ( 1996 ) found a negative association between age and self-reported use of coping strategies. However, when information about coping was administered using semistructured interviews rather than self-report questionnaires, no age differences were found (Aldwin et al., 1996 ). Even when older individuals used fewer coping strategies, their approaches to cope with a problem were as effective as those of younger individuals (Hobfoll, 2001 ). Except among those who suffer from chronic illness, coping efficacy decreases as individuals get older (Barry et al., 2004 ; Logan, Pelletier-Hibbert, & Hodgins, 2006 ). Thus, in addition to the frequency of coping strategies, it is important to incorporate the analysis of coping efficacy when studying stress, coping, and aging (Aldwin & Yancura, 2011 ).

Biological Stress Perspective

This article ends by briefly describing the biological stress perspective, which focuses on the acute and long-term physiological changes that result from social stressors and their associated psychological appraisals. This perspective highlights the activation of physiological systems that are sensitive to stressful situations, especially the sympathetic-adrenal medullary system (SAM) and the hypothalamic-pituitary-adrenocortical axis (HPA) (Cohen et al., 1997 , 2007 ; Koolhaas et al., 2011 ). Repeated or prolonged activation of these physiological systems is referred to as allostatic load , and it can lead to pathogenesis and disease (McEwen, 2013 ).

Activation of the Sympathetic-Adrenal Medullary System and Hypothalamic-Pituitary-Adrenal Axis

The experience of stress activates physiological changes that reflect the body’s adaptation to meet the demands. Quick, short-term activation is governed by the SAM system. Activation of SAM releases catecholamines, which work with the autonomic nervous system to regulate cardiovascular, pulmonary, hepatic, skeletal muscle, and immune systems (Cohen et al., 2007 ). Longer-term adaptations are met by the HPA system. HPA activation leads to the secretion of the hormone cortisol, which regulates anti-inflammatory responses; metabolism of carbohydrate, fat, and protein; and gluconeogenesis (Cohen et al., 2007 ). Continued and repeated activation of the HPA and SAM systems can disrupt their control over other physiological systems, leading to an increased risk of physical and psychological conditions (Cohen et al., 1997 ; McEwen, 1998 ).

Age, Exposure to Stressors, Hypothalamic-Pituitary-Adrenal Axis, and the Sympathetic-Adrenal Medullary System

There is evidence that the SAM system changes as individuals get older (Crimmins, Vasunilashorn, Kim, & Alley, 2008 ). The association between age and the SAM system is moderated by exposure to stressors (Almeida et al., 2011 ). Blood pressure is a good example of the change in the SAM system as individuals get older. After the age of 60, systolic blood pressure tends to be higher, whereas diastolic blood pressure tends to be lower (Franklin et al., 2001 ). Elevated systolic blood pressure among older adults is moderated by acute psychosocial stressors (Uchino, Uno, Holt-Lunstad, & Flinders, 1999 ). The increase in age is also associated with depleted epinephrine (Esler et al., 1995 ) and increased levels of norepinephrine (Barnes, Raskind, Gumbrecht, & Halter, 1982 ). The age-related changes in epinephrine and norepinephrine are also moderated by stressor exposure (Esler et al., 1995 ; Barnes et al., 1982 ), although these results were not replicated in other studies, such as Lindheim et al. ( 1992 ). Finally, the association between age and the SAM system may be stronger among people with physical problems, such as among older adults with cardiovascular disease (Almeida et al., 2011 ; Gillum, Makuc, & Feldman, 1991 ).

The age-related changes in the HPA axis are associated with an altered diurnal pattern and a disruption of the negative feedback loop, which leads to the overproduction of cortisol (Almeida et al., 2011 ). Older age is associated with an attenuated cortisol awakening (Almeida, Piazza, & Stawski, 2009 ) and a higher lowest point of evening cortisol (van Cauter, Leproult, & Kupfer, 1996 ). Similar to the SAM system, exposure to stressors moderates the association between age and the HPA axis (Almeida et al., 2011 ). The association between age and the HPA axis function is also stronger among people with worse health (McEwen, 1998 ).

Allostatic Load

One mechanism that might explain how continued and repeated activation of stress hormones influence health risk is deterioration of brain function. This hypothesis, known as the glucocorticoid cascade hypothesis , refers to the cascade effect of stress hormones on health (McEwen, 1998 , 2013 ; Sapolsky, Krey, & McEwen, 1986 ). Continuous activation of stress hormones gradually deteriorates brain function, leads to a higher level of cortisol, and in turn jeopardizes health. Discussion of the impact of stress on the brain involves two concepts: allostasis and allostatic load (McEwen, 1998 ). Allostasis refers to adapting to a stressful situation and bringing the body back to homeostasis, whereas allostatic load is the cost of frequent or prolonged adaptations on the body and brain. The release of stress hormones is an example of an adaptive physiological response to a stressful experience. However, prolonged exposure to stressful experiences might lead to wear and tear on the HPA axis.

According to McEwen ( 1998 ), there are three types of physiological responses that lead to allostatic load: frequent stress, failed shutdown, and inadequate response. Frequent stress refers to the magnitude and frequency of responses or the frequency and intensity of the hits that lead to allostatic load (McEwen, 1998 ). Failed shutdown refers to chronic activity and failure to shut off this activity, such as with type II diabetes (McEwen, 1998 ). Finally, inadequate response refers to the failure to respond to a challenge, such as autoimmunity and inflammation (McEwen, 1998 ). In general, studies have found that indicators of physiological capacity and physiological reserve decrease as individuals get older, although the rate of decline varies across individuals (Crimmins, Johnston, Hayward, & Seeman, 2003 ; Lipsitz & Goldberger, 1992 ; Manton, Woodbury, & Stallard, 1995 ). Allostatic load index, a composite measure of multiphysical systems related to wear and tear due to stress (for details, see Juster, McEwen, & Lupien, 2010 ), increases with age (Crimmins et al., 2003 ). A higher allostatic load index indicates more physical systems that are in the high-risk category.

Stress and Health: Integrating the Social, Psychological, and Biological Stress Perspectives

One significant development in the study of stress over the past several decades is an increased emphasis on multilevel analysis of stress, which stretches from cells to society (Contrada, 2011 ). Relevant to the discussion in this article, the current trend in this field is the integration of the social, psychological, and biological stress perspectives to better understand the influence of stress on health and well-being. In turn, this knowledge can be utilized to design better intervention programs to improve health and quality of life in general.

Miller, Chen, and Parker ( 2011 ), for example, developed a framework known as biological embedding of the childhood adversity model , which links early-life, chronic stressors to chronic diseases in adulthood. According to this model, chronic stressors during childhood, such as living in poverty, are hypothesized to dysregulate physiological systems (e.g., establishing a pro-inflammatory phenotype in the immune system). Across the life course, this physiological dysregulation is amplified by hormonal dysregulation and behavioral proclivities due to the ongoing chronic stressors, causing chronic inflammation, which in turn is associated with accelerated aging, frailty, and chronic diseases. This model is an excellent example of integrating multiple levels of stress to better understand the etiology of chronic diseases associated with aging.

Another example of a study in this area is Surachman et al. ( 2018 ), which investigates the interaction between structural factors, such as life-course SES and daily stressors, and daily well-being. The results show that childhood SES is directly and indirectly (through adult SES and daily stressor severity) associated with daily well-being in adulthood, especially daily negative affect and daily physical symptoms. These results may have significant public health implications, given that previous empirical findings have shown that higher daily physical symptoms and negative affect due to daily stressors are associated with long-term health outcomes, such as chronic physical and psychological distress (Charles et al., 2013 ; Piazza et al., 2013 ), functional impairment (Leger et al., 2015 ), and mortality risk (Chiang et al., 2018 ). In addition, research on the influence of childhood SES on biological functioning in later life has shown the significance of daily stress processes and daily well-being as potential mechanisms of disparities in chronic diseases (Carroll, Cohen, & Marsland, 2011 ; Desantis, Kuzawa, & Adam, 2015 ; Miller et al., 2011 ).

Stress is a broad and complex phenomenon that links three components: environmental demands, internal psychological processes, and physical outcomes. Each of these components are reflected in three theoretical perspectives of stress. The social perspective is likely to emphasize stressful events (i.e., stressors) and the social context of these events; the psychological perspective focuses on internal evaluations and appraisals; and the biological perspective highlights physiological adaptions to these events and appraisals. To understand the role of stress in aging, it is necessary to appreciate each of these perspectives.

As we age, our social roles direct us to be exposed to a variety of life events, chronic stress, and daily hassles. In addition, the way that we appraise and cope with stress is likely to change as we accumulate a lifetime of experience. Finally, it appears obvious that biological changes accompany age, and such changes will likely be accelerated by the stress we experience. We hope that this article has provided the reader with some guidance on the theory of stress and coping across the adult life course.

Stress hypothesis overload: 131 hypotheses exploring the role of stress in tradeoffs, transitions, and health

Affiliation.

1 Department of Biological Sciences, Texas Tech University, Lubbock, TX, United States. Electronic address: [email protected].
PMID: 31830473
DOI: 10.1016/j.ygcen.2019.113355

Stress is ubiquitous and thus, not surprisingly, many hypotheses and models have been created to better study the role stress plays in life. Stress spans fields and is found in the literature of biology, psychology, psychophysiology, sociology, economics, and medicine, just to name a few. Stress, and the hypothalamic-pituitaryadrenal/interrenal (HPA/I) axis and sympathetic nervous system (SNS), are involved in a multitude of behaviors and physiological processes, including life-history and ecological tradeoffs, developmental transitions, health, and survival. The goal of this review is to highlight and summarize the large number of available hypotheses and models, to aid in comparative and interdisciplinary thinking, and to increase reproducibility by a) discouraging hypothesizing after results are known (HARKing) and b) encouraging a priori hypothesis testing. For this review I collected 214 published hypotheses or models dealing broadly with stress. In the main paper, I summarized and categorized 131 of those hypotheses and models which made direct connections among stress and/or HPA/I and SNS, tradeoffs, transitions, and health. Of those 131, the majority made predictions about reproduction (n = 43), the transition from health to disease (n = 38), development (n = 23), and stress coping (n = 18). Additional hypotheses were classified as stage-spanning or models (n = 37). The additional 83 hypotheses found during searches were tangentially related, or pertained to immune function or oxidative stress, and these are listed separately. Many of the hypotheses share underlying rationale and suggest similar, if not identical, predictions, and are thus not mutually exclusive; some hypotheses spanned classification categories. Some of the hypotheses have been tested multiple times, whereas others have only been examined a few times. It is the hope that multi-disciplinary stress researchers will begin to harmonize their naming of hypotheses in the literature so as to build a clearer picture of how stress impacts various outcomes across fields. The paper concludes with some considerations and recommendations for robust testing of stress hypotheses.

Keywords: Development; Glucocorticoids; HARKing; HPA axis; Reproducibility; Reproduction.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.
Adaptation, Psychological / physiology*
Biobehavioral Sciences
Disease / etiology*
Disease / psychology
Hypothalamo-Hypophyseal System / physiology
Models, Biological*
Oxidative Stress / physiology
Pituitary-Adrenal System / physiology
Reproduction / physiology
Stress, Psychological* / pathology
Stress, Psychological* / physiopathology

Search Menu
Browse content in Arts and Humanities
Browse content in Archaeology
Anglo-Saxon and Medieval Archaeology
Archaeological Methodology and Techniques
Archaeology by Region
Archaeology of Religion
Archaeology of Trade and Exchange
Biblical Archaeology
Contemporary and Public Archaeology
Environmental Archaeology
Historical Archaeology
History and Theory of Archaeology
Industrial Archaeology
Landscape Archaeology
Mortuary Archaeology
Prehistoric Archaeology
Underwater Archaeology
Urban Archaeology
Zooarchaeology
Browse content in Architecture
Architectural Structure and Design
History of Architecture
Residential and Domestic Buildings
Theory of Architecture
Browse content in Art
Art Subjects and Themes
History of Art
Industrial and Commercial Art
Theory of Art
Biographical Studies
Byzantine Studies
Browse content in Classical Studies
Classical History
Classical Philosophy
Classical Mythology
Classical Literature
Classical Reception
Classical Art and Architecture
Classical Oratory and Rhetoric
Greek and Roman Epigraphy
Greek and Roman Law
Greek and Roman Archaeology
Greek and Roman Papyrology
Late Antiquity
Religion in the Ancient World
Digital Humanities
Browse content in History
Colonialism and Imperialism
Diplomatic History
Environmental History
Genealogy, Heraldry, Names, and Honours
Genocide and Ethnic Cleansing
Historical Geography
History by Period
History of Agriculture
History of Education
History of Emotions
History of Gender and Sexuality
Industrial History
Intellectual History
International History
Labour History
Legal and Constitutional History
Local and Family History
Maritime History
Military History
National Liberation and Post-Colonialism
Oral History
Political History
Public History
Regional and National History
Revolutions and Rebellions
Slavery and Abolition of Slavery
Social and Cultural History
Theory, Methods, and Historiography
Urban History
World History
Browse content in Language Teaching and Learning
Language Learning (Specific Skills)
Language Teaching Theory and Methods
Browse content in Linguistics
Applied Linguistics
Cognitive Linguistics
Computational Linguistics
Forensic Linguistics
Grammar, Syntax and Morphology
Historical and Diachronic Linguistics
History of English
Language Acquisition
Language Variation
Language Families
Language Evolution
Language Reference
Lexicography
Linguistic Theories
Linguistic Typology
Linguistic Anthropology
Phonetics and Phonology
Psycholinguistics
Sociolinguistics
Translation and Interpretation
Writing Systems
Browse content in Literature
Bibliography
Children's Literature Studies
Literary Studies (Asian)
Literary Studies (European)
Literary Studies (Eco-criticism)
Literary Studies (Modernism)
Literary Studies (Romanticism)
Literary Studies (American)
Literary Studies - World
Literary Studies (1500 to 1800)
Literary Studies (19th Century)
Literary Studies (20th Century onwards)
Literary Studies (African American Literature)
Literary Studies (British and Irish)
Literary Studies (Early and Medieval)
Literary Studies (Fiction, Novelists, and Prose Writers)
Literary Studies (Gender Studies)
Literary Studies (Graphic Novels)
Literary Studies (History of the Book)
Literary Studies (Plays and Playwrights)
Literary Studies (Poetry and Poets)
Literary Studies (Postcolonial Literature)
Literary Studies (Queer Studies)
Literary Studies (Science Fiction)
Literary Studies (Travel Literature)
Literary Studies (War Literature)
Literary Studies (Women's Writing)
Literary Theory and Cultural Studies
Mythology and Folklore
Shakespeare Studies and Criticism
Browse content in Media Studies
Browse content in Music
Applied Music
Dance and Music
Ethics in Music
Ethnomusicology
Gender and Sexuality in Music
Medicine and Music
Music Cultures
Music and Religion
Music and Culture
Music and Media
Music Education and Pedagogy
Music Theory and Analysis
Musical Scores, Lyrics, and Libretti
Musical Structures, Styles, and Techniques
Musicology and Music History
Performance Practice and Studies
Race and Ethnicity in Music
Sound Studies
Browse content in Performing Arts
Browse content in Philosophy
Aesthetics and Philosophy of Art
Epistemology
Feminist Philosophy
History of Western Philosophy
Metaphysics
Moral Philosophy
Non-Western Philosophy
Philosophy of Science
Philosophy of Action
Philosophy of Law
Philosophy of Religion
Philosophy of Language
Philosophy of Mind
Philosophy of Perception
Philosophy of Mathematics and Logic
Practical Ethics
Social and Political Philosophy
Browse content in Religion
Biblical Studies
Christianity
East Asian Religions
History of Religion
Judaism and Jewish Studies
Qumran Studies
Religion and Education
Religion and Health
Religion and Politics
Religion and Science
Religion and Law
Religion and Art, Literature, and Music
Religious Studies
Browse content in Society and Culture
Cookery, Food, and Drink
Cultural Studies
Customs and Traditions
Ethical Issues and Debates
Hobbies, Games, Arts and Crafts
Lifestyle, Home, and Garden
Natural world, Country Life, and Pets
Popular Beliefs and Controversial Knowledge
Sports and Outdoor Recreation
Technology and Society
Travel and Holiday
Visual Culture
Browse content in Law
Arbitration
Browse content in Company and Commercial Law
Commercial Law
Company Law
Browse content in Comparative Law
Systems of Law
Competition Law
Browse content in Constitutional and Administrative Law
Government Powers
Judicial Review
Local Government Law
Military and Defence Law
Parliamentary and Legislative Practice
Construction Law
Contract Law
Browse content in Criminal Law
Criminal Procedure
Criminal Evidence Law
Sentencing and Punishment
Employment and Labour Law
Environment and Energy Law
Browse content in Financial Law
Banking Law
Insolvency Law
History of Law
Human Rights and Immigration
Intellectual Property Law
Browse content in International Law
Private International Law and Conflict of Laws
Public International Law
IT and Communications Law
Jurisprudence and Philosophy of Law
Law and Politics
Law and Society
Browse content in Legal System and Practice
Courts and Procedure
Legal Skills and Practice
Primary Sources of Law
Regulation of Legal Profession
Medical and Healthcare Law
Browse content in Policing
Criminal Investigation and Detection
Police and Security Services
Police Procedure and Law
Police Regional Planning
Browse content in Property Law
Personal Property Law
Study and Revision
Terrorism and National Security Law
Browse content in Trusts Law
Wills and Probate or Succession
Browse content in Medicine and Health
Browse content in Allied Health Professions
Arts Therapies
Clinical Science
Dietetics and Nutrition
Occupational Therapy
Operating Department Practice
Physiotherapy
Radiography
Speech and Language Therapy
Browse content in Anaesthetics
General Anaesthesia
Neuroanaesthesia
Browse content in Clinical Medicine
Acute Medicine
Cardiovascular Medicine
Clinical Genetics
Clinical Pharmacology and Therapeutics
Dermatology
Endocrinology and Diabetes
Gastroenterology
Genito-urinary Medicine
Geriatric Medicine
Infectious Diseases
Medical Oncology
Medical Toxicology
Pain Medicine
Palliative Medicine
Rehabilitation Medicine
Respiratory Medicine and Pulmonology
Rheumatology
Sleep Medicine
Sports and Exercise Medicine
Clinical Neuroscience
Community Medical Services
Critical Care
Emergency Medicine
Forensic Medicine
Haematology
History of Medicine
Browse content in Medical Dentistry
Oral and Maxillofacial Surgery
Paediatric Dentistry
Restorative Dentistry and Orthodontics
Surgical Dentistry
Medical Ethics
Browse content in Medical Skills
Clinical Skills
Communication Skills
Nursing Skills
Surgical Skills
Medical Statistics and Methodology
Browse content in Neurology
Clinical Neurophysiology
Neuropathology
Nursing Studies
Browse content in Obstetrics and Gynaecology
Gynaecology
Occupational Medicine
Ophthalmology
Otolaryngology (ENT)
Browse content in Paediatrics
Neonatology
Browse content in Pathology
Chemical Pathology
Clinical Cytogenetics and Molecular Genetics
Histopathology
Medical Microbiology and Virology
Patient Education and Information
Browse content in Pharmacology
Psychopharmacology
Browse content in Popular Health
Caring for Others
Complementary and Alternative Medicine
Self-help and Personal Development
Browse content in Preclinical Medicine
Cell Biology
Molecular Biology and Genetics
Reproduction, Growth and Development
Primary Care
Professional Development in Medicine
Browse content in Psychiatry
Addiction Medicine
Child and Adolescent Psychiatry
Forensic Psychiatry
Learning Disabilities
Old Age Psychiatry
Psychotherapy
Browse content in Public Health and Epidemiology
Epidemiology
Public Health
Browse content in Radiology
Clinical Radiology
Interventional Radiology
Nuclear Medicine
Radiation Oncology
Reproductive Medicine
Browse content in Surgery
Cardiothoracic Surgery
Gastro-intestinal and Colorectal Surgery
General Surgery
Neurosurgery
Paediatric Surgery
Peri-operative Care
Plastic and Reconstructive Surgery
Surgical Oncology
Transplant Surgery
Trauma and Orthopaedic Surgery
Vascular Surgery
Browse content in Science and Mathematics
Browse content in Biological Sciences
Aquatic Biology
Biochemistry
Bioinformatics and Computational Biology
Developmental Biology
Ecology and Conservation
Evolutionary Biology
Genetics and Genomics
Microbiology
Molecular and Cell Biology
Natural History
Plant Sciences and Forestry
Research Methods in Life Sciences
Structural Biology
Systems Biology
Zoology and Animal Sciences
Browse content in Chemistry
Analytical Chemistry
Computational Chemistry
Crystallography
Environmental Chemistry
Industrial Chemistry
Inorganic Chemistry
Materials Chemistry
Medicinal Chemistry
Mineralogy and Gems
Organic Chemistry
Physical Chemistry
Polymer Chemistry
Study and Communication Skills in Chemistry
Theoretical Chemistry
Browse content in Computer Science
Artificial Intelligence
Computer Architecture and Logic Design
Game Studies
Human-Computer Interaction
Mathematical Theory of Computation
Programming Languages
Software Engineering
Systems Analysis and Design
Virtual Reality
Browse content in Computing
Business Applications
Computer Security
Computer Games
Computer Networking and Communications
Digital Lifestyle
Graphical and Digital Media Applications
Operating Systems
Browse content in Earth Sciences and Geography
Atmospheric Sciences
Environmental Geography
Geology and the Lithosphere
Maps and Map-making
Meteorology and Climatology
Oceanography and Hydrology
Palaeontology
Physical Geography and Topography
Regional Geography
Soil Science
Urban Geography
Browse content in Engineering and Technology
Agriculture and Farming
Biological Engineering
Civil Engineering, Surveying, and Building
Electronics and Communications Engineering
Energy Technology
Engineering (General)
Environmental Science, Engineering, and Technology
History of Engineering and Technology
Mechanical Engineering and Materials
Technology of Industrial Chemistry
Transport Technology and Trades
Browse content in Environmental Science
Applied Ecology (Environmental Science)
Conservation of the Environment (Environmental Science)
Environmental Sustainability
Environmentalist Thought and Ideology (Environmental Science)
Management of Land and Natural Resources (Environmental Science)
Natural Disasters (Environmental Science)
Nuclear Issues (Environmental Science)
Pollution and Threats to the Environment (Environmental Science)
Social Impact of Environmental Issues (Environmental Science)
History of Science and Technology
Browse content in Materials Science
Ceramics and Glasses
Composite Materials
Metals, Alloying, and Corrosion
Nanotechnology
Browse content in Mathematics
Applied Mathematics
Biomathematics and Statistics
History of Mathematics
Mathematical Education
Mathematical Finance
Mathematical Analysis
Numerical and Computational Mathematics
Probability and Statistics
Pure Mathematics
Browse content in Neuroscience
Cognition and Behavioural Neuroscience
Development of the Nervous System
Disorders of the Nervous System
History of Neuroscience
Invertebrate Neurobiology
Molecular and Cellular Systems
Neuroendocrinology and Autonomic Nervous System
Neuroscientific Techniques
Sensory and Motor Systems
Browse content in Physics
Astronomy and Astrophysics
Atomic, Molecular, and Optical Physics
Biological and Medical Physics
Classical Mechanics
Computational Physics
Condensed Matter Physics
Electromagnetism, Optics, and Acoustics
History of Physics
Mathematical and Statistical Physics
Measurement Science
Nuclear Physics
Particles and Fields
Plasma Physics
Quantum Physics
Relativity and Gravitation
Semiconductor and Mesoscopic Physics
Browse content in Psychology
Affective Sciences
Clinical Psychology
Cognitive Neuroscience
Cognitive Psychology
Criminal and Forensic Psychology
Developmental Psychology
Educational Psychology
Evolutionary Psychology
Health Psychology
History and Systems in Psychology
Music Psychology
Neuropsychology
Organizational Psychology
Psychological Assessment and Testing
Psychology of Human-Technology Interaction
Psychology Professional Development and Training
Research Methods in Psychology
Social Psychology
Browse content in Social Sciences
Browse content in Anthropology
Anthropology of Religion
Human Evolution
Medical Anthropology
Physical Anthropology
Regional Anthropology
Social and Cultural Anthropology
Theory and Practice of Anthropology
Browse content in Business and Management
Business Strategy
Business History
Business Ethics
Business and Government
Business and Technology
Business and the Environment
Comparative Management
Corporate Governance
Corporate Social Responsibility
Entrepreneurship
Health Management
Human Resource Management
Industrial and Employment Relations
Industry Studies
Information and Communication Technologies
International Business
Knowledge Management
Management and Management Techniques
Operations Management
Organizational Theory and Behaviour
Pensions and Pension Management
Public and Nonprofit Management
Strategic Management
Supply Chain Management
Browse content in Criminology and Criminal Justice
Criminal Justice
Criminology
Forms of Crime
International and Comparative Criminology
Youth Violence and Juvenile Justice
Development Studies
Browse content in Economics
Agricultural, Environmental, and Natural Resource Economics
Asian Economics
Behavioural Finance
Behavioural Economics and Neuroeconomics
Econometrics and Mathematical Economics
Economic Systems
Economic Methodology
Economic History
Economic Development and Growth
Financial Markets
Financial Institutions and Services
General Economics and Teaching
Health, Education, and Welfare
History of Economic Thought
International Economics
Labour and Demographic Economics
Law and Economics
Macroeconomics and Monetary Economics
Microeconomics
Public Economics
Urban, Rural, and Regional Economics
Welfare Economics
Browse content in Education
Adult Education and Continuous Learning
Care and Counselling of Students
Early Childhood and Elementary Education
Educational Equipment and Technology
Educational Strategies and Policy
Higher and Further Education
Organization and Management of Education
Philosophy and Theory of Education
Schools Studies
Secondary Education
Teaching of a Specific Subject
Teaching of Specific Groups and Special Educational Needs
Teaching Skills and Techniques
Browse content in Environment
Applied Ecology (Social Science)
Climate Change
Conservation of the Environment (Social Science)
Environmentalist Thought and Ideology (Social Science)
Natural Disasters (Environment)
Social Impact of Environmental Issues (Social Science)
Browse content in Human Geography
Cultural Geography
Economic Geography
Political Geography
Browse content in Interdisciplinary Studies
Communication Studies
Museums, Libraries, and Information Sciences
Browse content in Politics
African Politics
Asian Politics
Chinese Politics
Comparative Politics
Conflict Politics
Elections and Electoral Studies
Environmental Politics
European Union
Foreign Policy
Gender and Politics
Human Rights and Politics
Indian Politics
International Relations
International Organization (Politics)
International Political Economy
Irish Politics
Latin American Politics
Middle Eastern Politics
Political Methodology
Political Communication
Political Philosophy
Political Sociology
Political Theory
Political Behaviour
Political Economy
Political Institutions
Politics and Law
Public Administration
Public Policy
Quantitative Political Methodology
Regional Political Studies
Russian Politics
Security Studies
State and Local Government
UK Politics
US Politics
Browse content in Regional and Area Studies
African Studies
Asian Studies
East Asian Studies
Japanese Studies
Latin American Studies
Middle Eastern Studies
Native American Studies
Scottish Studies
Browse content in Research and Information
Research Methods
Browse content in Social Work
Addictions and Substance Misuse
Adoption and Fostering
Care of the Elderly
Child and Adolescent Social Work
Couple and Family Social Work
Developmental and Physical Disabilities Social Work
Direct Practice and Clinical Social Work
Emergency Services
Human Behaviour and the Social Environment
International and Global Issues in Social Work
Mental and Behavioural Health
Social Justice and Human Rights
Social Policy and Advocacy
Social Work and Crime and Justice
Social Work Macro Practice
Social Work Practice Settings
Social Work Research and Evidence-based Practice
Welfare and Benefit Systems
Browse content in Sociology
Childhood Studies
Community Development
Comparative and Historical Sociology
Economic Sociology
Gender and Sexuality
Gerontology and Ageing
Health, Illness, and Medicine
Marriage and the Family
Migration Studies
Occupations, Professions, and Work
Organizations
Population and Demography
Race and Ethnicity
Social Theory
Social Movements and Social Change
Social Research and Statistics
Social Stratification, Inequality, and Mobility
Sociology of Religion
Sociology of Education
Sport and Leisure
Urban and Rural Studies
Browse content in Warfare and Defence
Defence Strategy, Planning, and Research
Land Forces and Warfare
Military Administration
Military Life and Institutions
Naval Forces and Warfare
Other Warfare and Defence Issues
Peace Studies and Conflict Resolution
Weapons and Equipment

The Oxford Handbook of Stress and Mental Health

< Previous chapter
Next chapter >

22 Psychophysiological Models of Stress

Ellen Zakreski, McGill University, Montreal, QC, Canada

McGill University, Montreal, QC, Canada & University of Constance, Constance, Germany

Published: 12 August 2019
Cite Icon Cite
Permissions Icon Permissions

Psychophysiological models have a long history within stress research of trying to explain the link between stress exposure and psychological and physiological disease. The current chapter tries to offer complementary perspectives on this issue. First, it covers the relevant physiological systems (sympathetic, parasympathetic, enteric nervous system) and their markers (heart rate, heart rate variability, blood pressure), such that the reader receives an overview of the significant factors at play. Second, it provides an overview of the various forms of stress (acute, chronic, and stress during early life periods) that are believed to put the individual at heightened risk to develop stress-related disease. Finally, it presents the theories and models that have emerged over the years that try to explain how the various forms of stress can eventually lead to psychological and physical disease. The chapter ends with a short outlook on some recent work emphasizing the interaction between the various systems at play, and how that by itself can play a role in the origin of stress-related disease.

Introduction

Physiology as a branch of biology generally deals with all the functions and systems within a living organism; thus, it is probably the broadest of all domains. In the context of stress, physiology can refer to stress effects on any biological function or system. Historically, however, psychophysiology has focused on electrical activity of organ function, focusing primarily on the brain and the cardiovascular system. Within the brain, research has focused on spontaneous electrical activity recorded from the scalp (electroencephalogram) and recordings in response to (repeated and averaged) stimulation (event-related potentials). Within the periphery, research has focused on the autonomic nervous system with its sympathetic and parasympathetic branches. This area of research by now has extended over many decades, and various markers have been established to serve as surrogates for the activity and integrity of the autonomic system, including blood pressure (systolic, diastolic, mean arterial), heart rate, heart period, and heart period variability (time domain or frequency-domain-based analyses), plasma catecholamines, and skin conductance. In the context of this chapter, we will cover these traditional markers but will extend to other systems as well, to acknowledge the important interaction among the various stress-reactive systems within the organisms.

The driving question in this context is how stress can lead to acute or chronic changes in the activity of physiological systems, and how these changes are then related to disease. Over the course of this chapter, we will first briefly introduce the various physiological systems that deal with stress—the sympathetic, parasympathetic, and enteric nervous systems—and then provide a more in-depth discussion of the markers of these systems that have been established over the years. Finally, we will discuss the different models that have been proposed to explain the stress–disease link, which include various mechanisms by which stress-related change becomes maladaptive, with the consequence of deteriorating health. One of the core assumptions that the various models share is that maladaptive functioning of the autonomic nervous system (ANS) and other stress response systems increase the likelihood of stress-related illness. As usual, the devil is in the detail, and there is little consensus on what constitutes maladaptation, or even what exactly constitutes stress. Further complicating the matter, stress is a very popular and consequently broad topic that is ill-defined where it is often confused or not clearly delineated what causes it, and what is caused by it in the organism. The topic is also challenging to study because what is perceived as stressful by some might be experienced as merely stimulating by others. Generally accepted definitions for psychological stressors include the notion that it is a situation where the individual feels he or she is missing the resources to adequately deal with the demands of the situation (Lazarus & Folkman, 1984 ), it consists of stimuli that share specific situational characteristics such as uncontrollability, unpredictability, ego involvement, anticipation of negative consequences and novelty (Mason, 1968 ), or, within a social situation, the presence of social evaluative threat (Dickerson & Kemeny, 2004 ; i.e., poor performance in a social context or violation of social norms).

Exposure to these kinds of stressors are normal, and we are all prone to experience these situations frequently, but when the physiological systems that normally help us cope with stressors are overactivated or fail to respond adequately, stress-related illness is believed to occur. Individual differences will lead to variations in the thresholds for falling ill from these stressors, and in the type of illnesses that might arise from them, with stress implicated in a broad array of disorders (e.g., depression, anxieties, schizophrenia, burnout, eating disorders). Within the general pathologies, hypertension, obesity, and metabolic syndrome stand out. The different models that have been proposed over the years are covered in later sections, to separate “classic” approaches from more recent models to explain stress-related disease. The chapter ends with a summary, conclusion, and outlook, including some speculations about where the field might be heading.

Autonomic Nervous System

The ANS controls visceral processes such as heart rate, blood pressure, respiration, perspiration, sexual arousal, digestion, metabolism, and the immune system. Walter Cannon’s seminal work showed how the ANS links visceral processes with emotion (Cannon, 1928 ) and helps adapt the organism’s internal environment according to internal and external demands (Cannon, 1929 ).

Although the ANS is sometimes treated as a unified system, it consists of three structurally and functionally distinct systems: the sympathetic nervous system (SNS), the parasympathetic nervous system (PSNS), and the enteric nervous system (ENS). Understanding the basic physiology of each system is important for understanding the exact role of each of these systems and their relation to stress and health. Thus, we start by providing a brief review of ANS physiology and anatomy. This can only be a short and superficial look, and the interested reader is referred to numerous detailed reviews (Furness, Callaghan, Rivera, & Cho, 2014 ; Shields, 1993 ; Wehrwein, Orer, & Barman, 2016 ).

Sympathetic Nervous System

The sympathetic nervous system (SNS) (Shields, 1993 ; Wehrwein et al., 2016 ) regulates a broad range of visceral processes but is perhaps best known for coordinating the fight-or-flight response. Potential threats activate preganglionic nerve fibers in the interomediolateral column of the spine. Some sympathetic preganglionic fibers project to the adrenal medulla, where they stimulate chromaffin cells to release epinephrine into the blood. Most sympathetic preganglionic fibers meet with postganglionic fibers near the spine whose axons project throughout the body. Postganglionic fibers innervating sweat glands release acetylcholine at their axon terminals, stimulating perspiration. Other postganglionic fibers release norepinephrine near the target tissue. Norepinephrine and epinephrine bind to adrenergic receptors to accelerate heart rate, raise blood pressure, dilate the pupils, and contribute to the release of stored energy.

Parasympathetic Nervous System

The parasympathetic nervous system (PSNS; Shields, 1993 ; Wehrwein et al., 2016 ) regulates many visceral processes, similar to the role of the SNS. The effects of the PSNS on target organs are generally opposite to the effects of SNS activation. Consequently, while the SNS prepares the body for fight or flight, the PSNS is associated with rest and recovery. The structure of the PSNS is similar to the SNS where information travels from the brain to the periphery by a chain of preganglionic and postganglionic nerve fibers. While sympathetic preganglionic fibers exhibit a thoracolumbar outflow pattern, exiting the middle of the spine, parasympathetic preganglionic fibers exhibit a craniosacral outflow pattern. Some parasympathetic preganglionic fibers give rise to the splanchnic nerve at the sacral portion of the spine. Other parasympathetic preganglionic fibers flow through the cranial nerves III, VII, IX, and X. Cranial nerve X, the vagus nerve, represents the largest nerve in the ANS and is a major parasympathetic relay, controlling (among other organs) the heart, gut, and lungs. Parasympathetic preganglionic fibers in the vagus and other nerves travel throughout the body, terminating near the target tissue. Axon terminals of these fibers primarily release acetylcholine. PSNS activation induces slower heart rate, pupil constriction, increased salivation, lacrimation, gut motility, and urination.

Enteric Nervous System

The enteric nervous system (ENS) is a complex network of neurons spread throughout the gut that regulates various aspects of gastrointestinal function, including the microbiome (Furness et al., 2014 ; Yoo & Mazmanian, 2017 ). Once considered part of the PSNS, the ENS is now recognized as a distinct branch of the ANS. Although the ENS is the most complex division of the peripheral nervous system, it is historically the least explored part of the ANS within the context of stress research, although this is changing in recent years. As others review (Carabotti, Scirocco, Maselli, & Severi, 2015 ), recent studies have found associations between chronic stress, altered ENS function, and illness, making the ENS an exciting new frontier for stress research. At this point, however, the ENS is not explicitly taken into consideration by many of the major physiological models of stress, which prioritize the SNS and PSNS. For this reason, the current review focuses on the PSNS and SNS.

Markers of the Autonomic Nervous System

There are numerous theories implicating the ANS in stress-related disease. Since theory and measurement develop in parallel, understanding how ANS function is measured is vital to the interpretation and advancement of these theories. Probably one of the most important limitations of studying the ANS is that many aspects of autonomic function cannot be assessed directly in a noninvasive manner. Researchers examining conscious humans must assess ANS activity indirectly by measuring the end product of ANS activity, for example epinephrine or norepinephrine release, or by recording changes in other physiological processes known to be under autonomic control such as heart rate, heart period variability, or blood pressure. This can present significant challenges since these physiological processes are affected by systems other than the ANS, making interpretation difficult. Often data must be preprocessed to remove artifacts and to obtain specific information about the ANS. Furthermore, there is often discordance among researchers regarding which measures are best and how to interpret them. There are many methods available for assessing ANS function. We review these measures briefly, focusing on measures that are common in stress research, then discuss individual differences in how these markers relate to health and stress.

Blood Pressure

Blood pressure is an indirect marker of both SNS and PSNS activity, although it is considered more of a chronic measure of ANS dysregulation. It is typically operationalized as systolic, diastolic, or mean arterial pressure. Systolic and diastolic pressure describe the maximum and minimum pressure the blood is exerting on the arterial walls when flowing through in response to the heart’s activity. Mean arterial pressure is a combination measure of the two, but with the diastolic pressure weighted double (twice the diastolic pressure plus the systolic pressure divided by three). Diastolic pressure is considered more accurate when aiming to determine blood supply to body tissues and organs. Blood pressure is considered an important marker of ANS activity in the context of chronic stress and cardiovascular disease, as its acute state is strongly influenced by situational factors. As with other stress markers, repeated assessment over time in the context of acute stress testing does exist but is found less common (Juster et al., 2012 ).

High blood pressure, also called hypertension, describes excessive systolic, diastolic, or mean arterial pressure. Untreated hypertension for prolonged periods of time is a known and consistent risk factor for cardiovascular disease, stroke, and vascular dementia (Faraco & Iadecola, 2013 ). As hypertension is typically not associated with any symptoms, the possibility of it arising and manifesting for long periods of time is a serious concern; thus, general physicians will check for it regularly, especially in middle to late adulthood. The cause of hypertension is typically multifactorial, with acute and chronic stressors contributing to it. Other known risk factors are a body mass index (BMI) greater than 25, sedentary lifestyle, bad dietary habits, and excessive alcohol consumption, all of which can also be related to chronic stress (Elliott, 2007 ).

Heart rate (HR) is defined as the average number of heart beats per minute and is inversely related to heart period (HP), defined as the average time between beats. HR/HP can be monitored by electrocardiography (EKG). To record EKG, electrodes are placed on the chest and sometimes also on the arms or legs for reference, and the electrical signal of the heart is measured. Spikes in the EKG trace called R-peaks indicate depolarization of the heart’s ventricles. One R-peak marks one heartbeat. The time between successive R-peaks is called an R-R interval (see Figure 22.1 ). HP is the average R-R interval over time, while HR is the average number of R-peaks per minute. HR/HP provides a cheap, straightforward approximation of physiological arousal yet provides limited insight into ANS function. Since HR/HP depends on both SNS and PSNS, it is difficult to pinpoint the physiological origin of differences in HR/HP between individuals, or within an individual. For instance, faster HR (shorter HP) could reflect higher SNS activity, reduced PSNS activity, or both. One approach to overcome this limitation is to pharmacologically block the PSNS or SNS and then measure the resulting change in HR/HP from baseline. As Chapleau and Sabharwal ( 2011 ) explain, the increase in HR from baseline after administering a parasympathetic blocker (e.g., atropine) indicates PSNS tone, while SNS tone is indicated by the decrease in HR after administering a sympathetic blocker (e.g., propranolol). However, pharmacological interventions are invasive and limit ecological validity.

Illustration of an EKG recording. A heart beat is marked by a prominent upward deflection called an R-peak. The time between two R-peaks is an R-R interval.

Heart Period Variability

The heart’s rhythm is not constant but varies. Heart period variability (HPV), often called heart rate variability, is the amount of variation in R-R intervals over time and reflects the flexibility of the ANS. Total HPV first attracted interest as a prognostic indicator since lower HPV predicts greater morbidity and mortality among heart disease patients (Bigger et al., 1992 ; Huikuri et al., 1999 ; Odemuyiwa et al., 1991 ), making HPV a valuable marker of ANS function. HPV, however, has its limitations. Relations between HPV and ANS function are easily distorted by artifacts such as false heart beats or ectopic beats, so data must be carefully screened for artifacts before further analysis (Camm et al., 1996 ). Furthermore, HPV can be difficult to interpret because, like HR/HP, total HPV depends on both PSNS and SNS (Camm et al., 1996 ). Higher HPV could reflect increased PSNS activity, reduced SNS activity, or both. Information about PSNS activity can be extracted by focusing on specific types of HRV, the so-called high-frequency HPV, or respiratory sinus arrhythmia.

High-Frequency Heart Period Variability or Respiratory Sinus Arrhythmia

High-frequency HPV, also called respiratory sinus arrhythmia (RSA), is attributable to the PSNS since the PSNS is capable of changing HR faster than the SNS (Warner & Cox, 1962 ). There are several reasons for this. First, the nerves conveying parasympathetic input to the heart have more myelin than their sympathetic counterparts, enabling them to carry information faster. Second, parasympathetic postganglionic axon terminals are much closer to the heart than sympathetic axon terminals, so parasympathetic signals reach their target regions in the heart faster. Third, the PSNS employs mainly acetylcholine, which binds to fast-acting ionotropic receptors, while norepinephrine released from the SNS binds to slow-acting metabotropic receptors. Acetylcholine is also rapidly broken down by enzymes so the effects of PSNS activation more rapidly dissipate. Consequently, high-frequency HPV can be regarded as a valid marker of PSNS activity.

High-frequency HPV associated with PSNS activity is often called respiratory sinus arrhythmia (RSA), since rapid changes in R-R intervals result from respiratory gating of vagal outflow to the heart. Inhalation speeds up HR, while exhalation slows HR (Eckberg, 1983 ). RSA is the amount of R-R interval variability arising from respiration. Greater RSA (greater high-frequency HPV) is believed to indicate greater PSNS (vagal) influence over the heart (Berntson, Cacioppo, & Grossman, 2007 ). The association between RSA and vagal tone is not without controversy, however. Some researchers argue that minor changes in respiratory rate and volume may confound relations between RSA and vagal tone and should be controlled for either statistically or experimentally (Grossman & Taylor, 2007 ). Others disagree, arguing that controlling for respiratory parameters is unnecessary and may remove important information about PSNS activity (Lewis, Furman, McCool, & Porges, 2012 ). Potential respiratory confounds are important to stress research because common laboratory stress tasks such as the Trier Social Stress Test (TSST) (Kirschbaum, Pirke, & Hellhammer, 1993 ) require prolonged speaking, which affects breathing.

The Various Ways of Calculating Heart Period Variability and the Lack of Consensus

Diverse opinions exist on what should be the exact method of measurement and interpretation of RSA and other forms of HPV (Berntson et al., 2007 ; Grossman & Taylor, 2007 ; Lewis et al., 2012 ). This lack of consensus, coupled with different research goals and theoretical perspectives, has led to a wide range of recommendations for quantifying HPV (Allen, Chambers, & Towers, 2007 ; Camm et al., 1996 ; Sassi et al., 2015 ; Shaffer & Ginsberg, 2017 ). Some measures capture RSA, so specifically reflect PSNS activity, while others reflect both the PSNS and SNS. HPV measures are generally divided into frequency-domain, geometric, and time-domain measures.

Frequency-domain measures use spectral analysis methods (e.g., Fourier transform) to convert the R-R interval time series into the frequency domain, then calculate the power (variability) within a particular frequency bandwidth (in adults, high-frequency power band is defined as 0.15–0.4 Hz, while low-frequency power band ranges from 0.04 to 0.15 Hz). High-frequency power is R-R interval variability within the bandwidth of normal human respiration (9–24 breaths per minute) and can be used to capture RSA, and thus PSNS activity. Low-frequency HPV was once thought to index SNS activity; however, it is now clear that both PSNS and SNS contribute to low-frequency HPV (Reyes del Paso, Langewitz, Mulder, Van Roon, & Duschek, 2013 ).

Geometric measures of HPV are also available. Poincaré plots visualize complex correlation patterns within the R-R interval series (Kamen & Tonkin, 1995 ). These patterns can be quantified by fitting an ellipse to the Poincaré plot and then measuring dispersion on the SD1 and SD2 planes (Tulppo, Makikallio, Takala, Seppanen, & Huikuri, 1996 ). SD2 (a measure of long-term variability) depends on the SNS and PSNS, while SD1 (a measure of short-term variability) indexes PSNS activity (Kamen, Krum, & Tonkin, 1996 ).

Time-domain measures of HPV are simpler to determine. Examples of time-domain measures include standard deviation between normal R-R intervals (SDNN) and root mean square of successive differences (RMSSD). SDNN measures reflect both SNS and PSNS activity (Camm et al., 1996 ), while RMSSD (Berntson, Lozano, & Chen, 2005 ) reflects RSA and thus indexes PSNS activity.

Although frequency-domain measures are widely used (Allen et al., 2007 ), they make statistical assumptions that may not always be accurate in the context of stress research. For instance, frequency-domain measures assume signal stationarity, an assumption that is violated if the ANS is perturbed by external events (e.g., a stressor). Time-domain measures, however, do not assume stationarity, so in this regard they may be advantageous for stress research. For stress researchers who wish to examine how the PSNS responds to speech-based stress tasks such as the TSST, RMSSD and SD1 may also be preferable over frequency-domain measures, since evidence suggests that RMSSD and SD1 are less susceptible to potential respiratory confounds (Penttila et al., 2001 ; Pitzalis et al., 1996 ), and so are less likely to be contaminated by speech. Type of HPV measure can therefore interact with aspects of the study design (e.g., violations of stationarity assumptions, potential for respiratory confounds) to influence results obtained by a particular study.

Pre-Ejection Period

The SNS can be noninvasively probed by pre-ejection period (PEP) (Newlin & Levenson, 1979 ; Sherwood et al., 1990 ). PEP, an index of beta-adrenergic drive, is the time between contraction of the heart’s ventricles and the opening of the aortic valve. Shorter PEP indexes higher SNS activity. PEP can be measured by combining EKG with impedance cardiography. Like HPV, PEP is easily distorted by artifacts such as false heartbeats, so data should be manually screened before analysis. PEP may also be affected by posture (Houtveen, Groot, & De Geus, 2005 ). This may be relevant for stress research, since common laboratory stress tasks such as the TSST require participants to switch between sitting and standing throughout the task. This can complicate interpretation since it is unclear to what extent a change in PEP during the TSST constitutes a psychological stress response or a posture change response.

Skin Conductance Response

Another noninvasive index of SNS activity is skin conductance response (SCR), also known as galvanic skin conductance. SCR is the change in the electrical properties of the skin resulting from perspiration (Boycsein, 2012 ). Unlike HR/HP or blood pressure, sweat glands are exclusively under sympathetic control, making SCR a cleaner index of SNS activity (Dawson, Schell & Filion, 2007 ). SCR is measured by applying low voltage to the skin through electrodes and then examining the change in conductance. Higher skin conductance response indicates greater SNS activity. Similar to PEP and HPV, SCR is vulnerable to distortion. For instance, the amplitude of one skin conductance response can be biased by the amplitude of the previous response unless certain analytical methods are used (Benedek & Kaernbach, 2010 ). Like PEP and HPV, methods for analyzing SCR and removing artifacts vary between studies, and this variation could contribute to mixed findings.

Plasma Norepinephrine and Epinephrine

The catecholamines norepinephrine and epinephrine can be measured in blood plasma to index SNS activity. As Mills and Dimsdale ( 1992 ) review, there are several methodological limitations associated with plasma catecholamines. First, measuring blood is invasive. Second, catecholamines degrade rapidly, so samples must be frozen immediately. Third, norepinephrine and epinephrine can be difficult to interpret since they are not always correlated with one another, although both are believed to indicate SNS activity. A meta-analysis of stress research (Goldstein & Kopin, 2008 ) found that epinephrine responsivity was strongly associated with adrenocorticotrophin ( r = 0.93), a hormone of the HPA axis, while the association between epinephrine and norepinephrine responsivity to stress was much weaker ( r = 0.40); however, the validity of these findings is questionable because of the author’s use of subjective ratings to establish these relationships. This could partly reflect the fact that norepinephrine and epinephrine respond to different stimuli. For instance, norepinephrine levels increased more in response to physical exercise, while epinephrine was more responsive to psychosocial stress (Dimsdale & Moss, 1980 ). Norepinephrine and epinephrine therefore likely reflect distinct components of the SNS with potentially distinct implications for health and disease. Measuring both catecholamines is therefore not redundant and will likely provide a more comprehensive picture of what the SNS is doing; therefore, it should be the method of choice.

Salivary Alpha-Amylase

Salivary alpha-amylase (Chatterton, Vogelsong, Lu, Ellman, & Hudgens, 1996 ; Nater et al., 2006 ; Nater & Rohleder, 2009 ), an enzyme that breaks down starch and kills bacteria, may index beta-adrenergic sympathetic activity since salivary alpha-amylase has been found to correlate with blood levels of norepinephrine (Thoma, Kirschbaum, Wolf, & Rohleder, 2012 ), and pharmacologically blocking beta-adrenergic receptors suppresses the salivary alpha-amylase response to stress (van Stegeren, Rohleder, Everaerd, & Wolf, 2006 ). Salivary alpha-amylase is appealing because it is less invasive to collect and more chemically stable than plasma catecholamines, and it can be measured in the same saliva sample as other stress-related biomarkers such as cortisol. Compared to other SNS markers, such as PEP or SCR, salivary alpha-amylase can facilitate data collection since participants do not need to be connected to electrical monitoring equipment. Nonetheless, alpha-amylase has some drawbacks. Compared to PEP or SCR, alpha-amylase has reduced temporal resolution since saliva can only be sampled every few minutes. Consequently, researchers using alpha-amylase may miss important changes in SNS activity. A more critical issue is that alpha-amylase may not provide a pure indicator of SNS. Alpha-amylase and plasma norepinephrine do not always correlate (Petrakova et al., 2015 ). Alpha-amylase may further be confounded by PSNS activity (Nagy et al., 2015 ), salivary flow rate, and posture (Bosch, Veerman, de Geus, & Proctor, 2011 ). Consequently, studies using alpha-amylase as a marker of SNS activity may sometimes tell a different story than studies using more pure markers of SNS activity like PEP or SCR.

Links With Stress and Stress-Related Disease

Effects of acute stress.

Normally, the PSNS is more active during rest than the SNS. Individual differences in basal (resting) activity of the PSNS and SNS have been associated with various, typically chronic, stress-related health problems. A review of this literature exceeds the scope of this chapter, but examples include physical disease like metabolic syndrome (Hu, Lamers, Hiles, Penninx, & de Geus, 2016 ), cardiovascular disease (Greenwood, Stoker, & Mary, 1999 ; Odemuyiwa et al., 1991 ; Thayer & Lane, 2007 ), and psychological symptoms such as internalizing problems (e.g., anxiety and depression) (Davis, Suveg, Whitehead, Jones, & Shaffer, 2016 ; Dieleman et al., 2015 ; Ishitobi et al., 2010 ; Shinba, 2014 ), and externalizing problems (e.g., antisocial behavior) (Pine et al., 1996 ; Snoek, Goozen, Matthy, Buitelaar, & Engeland, 2004 ).

The PSNS typically deactivates in response to stress, while the SNS activates. The typical stress response thus manifests as increased HR, blood pressure, salivary alpha-amylase, plasma catecholamines and SCR, shorter PEP, and decreased total HPV and RSA. The autonomic stress response is believed to help the organism survive, at least in the short term, by inhibiting nonessential functions, releasing stored energy, and redirecting resources to where they are needed most. Similar to other stress systems, such as the hypothalamic-pituitary-adrenal (HPA) axis, the ANS is responsive to physical stress (Mastorakos, Pavlatou, Diamanti-Kandarakis, & Chrousos, 2005 ), uncontrollability (Peters et al., 1998 ), and social evaluative threat (Bosch et al., 2009 ); however, the ANS responds faster and for a shorter duration when compared to the HPA axis (Ulrich-Lai & Herman, 2009 ). The ANS also responds to challenges that do not evoke a significant HPA axis response, such as mental effort (Peters et al., 1998 ). Thus, in a way, the ANS acts like a first responder, while the HPA axis represents the second, more profound and sustained response.

Autonomic reactivity to stress is the magnitude of change from baseline during acute stress. Like baseline activity, reactivity is an important functional parameter of the ANS and is associated with many stress-related disorders such as cardiovascular disease, depression, and anxiety.

A change in ANS basal activity or ANS reactivity to stress may be a correlate or predictor of cardiovascular illness. Earlier studies associated higher autonomic reactivity with current and future cardiovascular illness. For instance, cardiovascular reactivity, as indicated by higher heart rate reactivity or blood pressure reactivity, has been found to predict stroke (Everson et al., 2001 ) and hypertension (Carroll et al., 2012 ) and is associated with more carotid plaque and atherosclerosis (Gianaros et al., 2002 ). Higher plasma norepinephrine reactivity, a marker of SNS reactivity, was also found to predict hypertension (Flaa, Eide, Kjeldsen, & Rostrup, 2008 ) and is observed in patients with Tako-Tsubo cardiomyopathy (Smeijers et al., 2015 ). Higher PSNS reactivity, indexed by a greater decrease in RSA during stress, has also been associated with coronary aortic calcification (Gianaros et al., 2005 ); however, the majority of studies associate risk of cardiovascular disease with blunted PSNS reactivity (Ginty, Kraynak, Fisher, & Gianaros, 2017 ). While earlier research suggests that higher reactivity, particularly of the SNS, correlates with current and future cardiovascular problems, a growing number of studies now associate current or future cardiovascular disease with blunted reactivity (less change in activity) of both the SNS and PSNS (Ginty et al., 2017 ).

Here, blunted ANS reactivity predicted cardiovascular disease-related hospitalization, and even death (Sherwood et al., 2017 ). By itself, blunted ANS reactivity has been associated with higher central adiposity (a risk factor for cardiovascular disease), particularly among chronically stressed individuals (Singh & Shen, 2013 ). Blunted cardiovascular reactivity has also been associated with atherosclerosis (Chumaeva et al., 2009 ; Heponiemi et al., 2007 ). Atherosclerosis itself again is associated with blunted SNS and PSNS reactivity, respectively indexed by less change in PEP and RSA (Heponiemi et al., 2007 ). Cardiovascular patients also showed blunted SNS reactivity as indexed by plasma norepinephrine and epinephrine levels (Stanford et al., 1997 ). Taken together, these findings exemplify how relations between cardiovascular disease and ANS reactivity are complex, with some studies observing a positive association between reactivity and disease, while other studies observe the opposite association. However, there is always the possibility that unknown factors cause both ANS changes and the cardiovascular disease process.

In addition, some authors (Sharpley, 2002 ; Taylor, 2010 ) suggest that altered ANS reactivity may be the link between cardiovascular disease and affective disorders, such as depression, since cardiovascular disease and affective disorders tend to co-occur (Hare, Toukhsati, Johansson, & Jaarsma, 2014 ) and share common antecedents (e.g., chronic stress). The ANS also helps mediate the relationship between emotion (affect) with cardiovascular function (Cannon, 1928 ). Consequently, many studies have explored associations between affective disorders and ANS reactivity. As with cardiovascular disease, however, the relationship between affective disorders and ANS is complex and varies between studies. Earlier research tended to associate depression with increased cardiovascular and SNS reactivity. A meta- analysis (Kibler & Ma, 2004 ) found that depression was associated with increased HR and blood pressure reactivity. Similarly, Light, Kothandapani, and Allen ( 1998 ) associated depression with greater SNS reactivity as indexed by PEP. However, and similar to the shift in the literature observed with cardiovascular disease, more recent studies tend to associate depression with blunted cardiovascular and SNS reactivity (Brindle, Ginty, & Conklin, 2013 ; Salomon, Bylsma, White, Panaite, & Rottenberg, 2013 ; Salomon, Clift, Karlsdottir, & Rottenberg, 2009 ). With regard to the PSNS, relations with depression are more consistent. According to a recent meta-analysis (Hamilton & Alloy, 2016 ), depression tends to be associated with blunted RSA.

ANS reactivity has been implicated in numerous other stress-related psychopathologies, including anxiety (Dieleman et al., 2015 ; Hoehn-Saric, McLeod, & Zimmerli, 1989 ), posttraumatic stress disorder (Blechert, Michael, Grossman, Lajtman, & Wilhelm, 2007 ; McFall, Murburg, Ko, & Veith, 1990 ), internalizing problems (Boyce et al., 2001 ; Hastings et al., 2008 ), externalizing problems (Boyce et al., 2001 ; Snoek et al., 2004 ; Waters, Boyce, Eskenazi, & Alkon, 2016 ), and eating disorders (Het et al., 2015 ; Koo-Loeb, Pedersen, & Girdler, 1998 ; Messerli-Burgy, Engesser, Lemmenmeier, Steptoe, & Laederach-Hofmann, 2010 ). Findings on the direction, however, are mixed. Some of these studies associate pathology with higher reactivity (Dieleman et al., 2015 ; McFall et al., 1990 ), while others associate the same pathology with blunted reactivity (Blechert et al., 2007 ; Hoehn-Saric et al., 1989 ; Koo-Loeb et al., 1998 ). Reasons for this inconsistency are not entirely clear and could stem from the diversity of measures used to index autonomic activity, the sensitivity of measures to confounds, or different definitions of what “reactivity” constitutes (i.e., some authors define reactivity as the rate of change, while others define it as magnitude of change).

Chronic Stress

“Chronic stress” is a heterogeneous term whose definition often varies by author and methodological approach. Perhaps a more vague but therefore generally accepted definition is a sustained period of ongoing exposure to stimuli which are perceived as threatening or difficult to cope with (Selye, 1978 ). These stressors can vary in intensity from mild (daily hassles like commuter traffic or a noisy work environment) to severe (bereavement, chronic illness, emotional, sexual or physical abuse).

Chronic stress is believed to lead to an ongoing perturbation of the stress response systems like the ANS or HPA axis geared toward providing the organism with additional energy to adapt to stress. This chronic activation is believed to be associated with an imbalance in energy regulation and can by itself become a possible source of disease. Chronic stress as a possible source of ANS dysregulation and eventual physical or psychological disease has been around as a concept for a long time (e.g., Selye, 1936 ), and as a consequence, a multitude of studies have examined the link between chronic stress and ANS activity. As so often, the literature is a mixed bag, with some studies showing evidence for an increase in SNS and a decrease in PSNS activity as a consequence of chronic stress, with others observing a decrease in predominantly SNS activity, and yet others showing no effects (Fries et al., 2005 ; Hellhammer, Meinlschmidt, & Pruessner, 2018 ; McGirr et al., 2010 ; Vanitallie, 2002 ). Despite these inconsistencies, research tends to find that chronic stress can lead to enduring changes in ANS and other stress response systems. Putative models, like the allostatic load model and the theory of general adaptation syndrome, assume that the changes in the stress response systems associated with exposure to chronic stressors, rather than the stressors itself, are to blame for the health state of the individual.

Early Life Adversity

Early life adversity, such as childhood neglect, physical or sexual abuse, or exposure to conflict during critical development periods, appears to have particularly pervasive effects on health across the life span and is believed to precipitate or exacerbate internalizing problems (e.g., depression, anxiety), externalizing problems (e.g., aggression), cardiovascular disease, substance abuse, and other health problems (Dvir, Ford, Hill, & Frazier, 2014 ; Felitti et al., 1998 ).

The effects of early life adversity on health may be mediated by enduring alterations of the physiological stress systems, including the ANS (Shonkoff et al., 2012 ). Research has associated early life adversity with altered ANS function at baseline and under stress. For example, among studies examining baseline activity, early life adversity is associated with greater SNS activity (Esposito, Koss, Donzella, & Gunnar, 2016 ) and lower PSNS activity (Dale et al., 2017 ; Gray, Theall, Lipschutz, & Drury, 2017 ). Findings are more mixed for basal cardiovascular activity. Some studies associate early life adversity with greater cardiovascular activity (Dale et al., 2017 ), while others observe lower cardiovascular activity (Winzeler et al., 2016 ). Research on ANS reactivity and early life adversity is particularly heterogeneous. Individuals exposed to early life adversity have been shown to possess greater cardiovascular reactivity (Heim et al., 2000 ), greater SNS reactivity (Cărnuţă, Crişan, Vulturar, Opre, & Miu, 2015 ; Kuras et al., 2017 ; Lucas-Thompson & Granger, 2014 ), and greater PSNS reactivity (Skowron et al., 2011 ). Contrarily, other studies associate early life adversity with blunted cardiovascular reactivity (Lucas-Thompson & Granger, 2014 ; Voellmin et al., 2015 ), blunted SNS reactivity (Busso, McLaughlin, & Sheridan, 2017 ; McLaughlin et al., 2015 ; Mielock, Morris, & Rao, 2017 ), and blunted PSNS reactivity (Calkins, Graziano, Berdan, Keane, & Degnan, 2008 ). Interestingly, while several studies observe significant associations between SNS reactivity and early life adversity, the effect of early life adversity on PSNS reactivity is often nonsignificant (Busso et al., 2017 ; Cărnuţă et al., 2015 ; Dale et al., 2017 ; McLaughlin et al., 2015 ; Winzeler et al., 2016 ). Taken together, relations of early life adversity with ANS function are therefore mixed and are likely moderated by numerous factors such as sex (Gray et al., 2017 ), task (McLaughlin, Sheridan, Alves, & Mendes, 2014 ), type of adversity (Skowron et al., 2011 ), and genes (Allegrini, Evans, de Rooij, Greaves-Lord, & Huizink, 2017 ).

Classical Physiological Models in Stress Research

Selye’s general adaptation syndrome.

Hans Selye is often referred to as the grandfather of stress research, and his seminal work on the effects of acute and chronic stress on especially the adrenal glands is included in most contemporary psychology textbooks that address “stress.” In his book The Stress of Life (Selye, 1978 ), he describes how his clumsy handling of laboratory rats led to their frequent escape with subsequent chase and recapture. He later noticed that the rats who had temporarily escaped him had larger adrenal glands than those handled by his colleagues who had apparently not been exposed to the same (clumsy) treatment. This initial observation was followed by a systematic investigation into the causes and meaning of the change of the adrenal glands as a consequence of this special type of environmental stressor (i.e., him losing the rats). Selye ended up spending most of his life investigating the consequences of stress and realized that chronic stress can have profound consequences on health and disease. In the case of the handled rats, the increase in volume and weight of the adrenal glands had to do with the constant stimulation of the HPA axis and the subsequent need for a higher production of stress hormones, to which the glands responded by increasing their size and weight, to satisfy the high demand.

Selye’s work culminated in the formulation of the general adaptation syndrome (GAS), a theory which at its core contained the idea that there is a temporal process in the response to chronic stress. In the beginning, when the individual is first exposed to the (chronic) increase in demand, the organism is responding by increasing its ability to defend itself—its stress response systems (i.e., energy systems like the SNS and HPA) become chronically active to maximize the bodily defenses. This, according to Selye, will indeed enable the organism to better deal with the threat at hand, at the price of depleting its surplus resources. Should the period of chronic stress continue to tax the individual, eventually the organism is no longer able to increase its energy availability, and the reactivity of the systems declines even below normal activity. At this point, there is a mismatch between what the environment demands and what the individual can deliver, and the health of the individual is at risk. Selye was not specific as to what disease can occur, and he suggested that it depended on the individual characteristics of the organism as to what exactly happens. This is in line with the various physical and psychological consequences that stress can have—depression, burnout, ulcers, or heart disease were all possible consequences, according to Selye.

Selye’s theory is compelling because of its simplicity. It rings true that an overtaxed system eventually will break—the pitcher that goes to the well too often is broken at last. It is rather intuitive that we cannot expect our bodies to perform at 110% for prolonged periods of time without something eventually happening to us. At the same time, that is also the significant weakness of the model—it is blurry on the exact mechanisms, and by leaving the exact consequences undefined it becomes very difficult if not impossible to test empirically. To Selye’s credit, neuroscience at the time was not much advanced for many of the systems to be understood in detail, or the endocrine and neural mechanisms to be known yet. So his legacy certainly is to put the term “stress” on the agenda of physiologists, psychologists, and neuroscientists ever since.

Diathesis-Stress Models

The diathesis-stress model (Meehl, 1962 ) aims to address one of the shortcomings of the general adaptation syndrome theory, namely that chronic stress does not always precipitate disease. The diathesis-stress model is not so much one model, and there is no single individual that could be clearly associated with the numerous models that were generated over the years in the diathesis stress context (Ingram & Luxton, 2005 ). At the core, is a straightforward idea: A specific vulnerability exists in the individual that is unrelated with negative outcomes as long as there is no significant stress exposure; once the individual has to endure significant amounts of stress, disease is likely to occur. There have been numerous variations on the initial concept—strict threshold models that assume a constant vulnerability, various models that allow for changing vulnerabilities depending on external or internal circumstances, models that allow for an interaction between the type of stressor and the specific vulnerability, and models that consider static versus dynamic vulnerabilities (e.g., McKeever & Huff, 2003 ; Monroe & Hadjiyannakis, 2002 ; Monroe & Simons, 1991 ; Post, 1992 ; Zubin & Spring, 1977 ). Also similar to the general adaption syndrome theory, the empirical testability of the diathesis-stress model is limited—it can explain disease post hoc (“the person fell ill from depression because he or she was vulnerable to it”), but it is much harder to determine what exactly the factors are that define a specific vulnerability.

Allostatic Load Theory

Allostatic load theory is associated with, but also stands in contrast to, the “homeostasis” concept developed by Claude Bernard and elaborated on by Cannon ( 1929 ). Chronologically appearing after the work of Selye ( 1978 ), allostatic load theory focuses on the long-term cost of the individual to maintain homeostasis. At the core is the assumption that individuals depend on surplus energy (typically from endogenous energy stores in terms of adipose tissue in the long term, glucose and protein in the short term) for emergency responses to occur when experiencing stress. If demands for increased energy are prolonged, an organism would then be in danger of using up these surplus energy stores, and it is likely to react to the danger of depletion. Thus, to maintain the ability of emergency responses, especially during times of chronic demand, in response the organism might increase its energy uptake and storage by first initiating feelings of hunger, and secondly by engaging in mechanisms to increase the storage of energy (e.g., through glucocorticoid signaling) so that the anticipated chronic demand can better be dealt with. This concept has been called “allostasis” (McEwen, 1998 ; Sterling & Eyer, 1988 ), which literally means “stability through change.” Similar to Selye who followed in the footsteps of Cannon with homeostasis of physiological systems, allostasis was first described by Sterling and Eyer in 1988 , referring to the cardiovascular system and how it adjusts during resting and active states. From there, allostasis was then generalized to other systems, like the HPA axis (McEwen, 1998 ).

In contrast to homeostasis, allostasis changes physiological parameters so that homeostatic processes can continue. Thus, while homeostasis keeps “set points” and describes the processes to maintain these (such as body temperature), allostasis describes the modification of other parameters to keep these set points. For example, the increase in food intake in response to increased metabolism when exposed to a harsh environment would be the allostatic change that enables the homeostatic process of keeping the body temperature stable when the organism is out in the cold.

This can be further exemplified by looking at various examples in the context of various systems across the body. For example, to maintain necessary amounts of oxygen and nutrient supply to the muscles during exercise, catecholamines have to be released through the SNS to adjust heart rate and blood pressure. The release of catecholamines, and the subsequent increase in heart rate and blood pressure, is an allostatic process. Within the endocrine system, the release of glucocorticoids by the HPA axis, and the subsequent increase in food intake after exposure to a psychological or physical stressor, is an example for an allostatic process to keep energy levels stable, which itself is a homeostatic process. In a sense, allostasis and homeostasis are two sides of the same coin. While homeostasis focuses on the aspects that remain stable, allostasis focuses on the aspects that are changing for the system to remain stable.

Once the focus shifts from the systems that overall remain stable to the parameters that are changing to keep the system stable, it becomes apparent that “stability” might be a costly process: Depending on the demands, it might involve the “wearing out” of those parameters that undergo constant change to ensure this overall stability of the system. This is where the emphasis is with this theory: the concept of allostatic load. What is the price to pay for keeping the organism stable? Being looked into for several decades now, there is a realization that part of the metabolic changes with aging might in fact be allostatic changes (McEwen, 2002 ; Robertson & Watts, 2016 ). Metabolic syndrome, a condition that affects an increasing number of people in developed countries, describes a cluster of risk factors for physical disease, including abdominal obesity, elevated blood pressure, elevated glucose levels, high blood triglyceride levels, and others. It is associated with a reduced life expectancy, and increased risk for disease, mostly diabetes and atherosclerosis. Future research will have to provide further evidence to the idea that in many individuals, these metabolic changes occurring with aging might represent the body’s response to accumulated and chronic life stress.

Autonomic Space Model

Considering the association between SNS activity and PSNS activity may help resolve inconsistent relationships between autonomic function and health reported in the literature (Berntson & Cacioppo, 2004 ). Early researchers like Langley ( 1921 ) promoted the view that SNS and PSNS activity are reciprocally associated such that when one branch activates, the other deactivates. Autonomic space model (Berntson, Cacioppo, & Quigley, 1991 , 1993 ) argues that other modes of associations between the SNS and PSNS exist and have important implications for health and behavior as well. In addition to reciprocal associations, SNS and PSNS activity can change in the same direction (coactivity) or the PSNS and SNS can uncouple from one another. The mode of association between the PSNS and SNS can be represented as a position on a two-dimensional grid called autonomic space (Figure 22.2 ), with SNS activity on one dimension and PSNS activity on the other. A person’s position in autonomic space can be quantified at rest or during stress using pharmacological or noninvasive methods (Berntson, Cacioppo, Binkley, et al., 1994 ; Berntson, Cacioppo, & Quigley, 1994 ; Cacioppo et al., 1994 ).

Autonomic space is a two-dimensional grid representing the range of possible associations between PSNS activity and SNS activity in standardized units. Associations can vary from reciprocity (high PSNS activity and low SNS activity, or vice versa ), co-activity (co-activation or co- deactivation), or uncoupling (i.e. uncorrelated) changes in activity.

Position in autonomic space can vary between or within individuals and is predicted to impact health by affecting the response of target organs that are innervated by both the SNS and PSNS (e.g., heart rate [HR]). Autonomic space model predicts that compared to nonreciprocal modes, reciprocity broadens the response range of the target organ, accelerates the response, and increases directional stability of the response, so that the change goes in one direction rather than fluctuating back and forth. Reciprocal modes therefore facilitate greater reactivity of target organs (e.g., greater HR reactivity) while nonreciprocal modes, particularly coactivity, preserve the baseline state of the target organ, manifesting as blunted cardiovascular reactivity to stress.

The association between the SNS and PSNS may also correlate with health and behavior because different modes of SNS-PSNS coupling have distinct neurological correlates. A shift from one mode to another may therefore reflect the dominance or integrity of a particular neurological system. Reciprocity is largely dependent on baroreflex mechanisms in the brainstem, while nonreciprocal associations can occur when limbic brain regions such as amygdala and hypothalamus inhibit autonomic control centers in the brain stem. As Berntson and colleagues comment, limbic and anterior regions are implicated in emotion and appraisal (Berntson & Cacioppo, 2004 ; Berntson et al., 1991 ). Appraising a situation as threatening may therefore modulate the association between the SNS and PSNS. Consistent with this, classical conditioning experiments have observed coactivation during anticipation of electric shock in humans (Obrist, Wood, & Perez-Reyes, 1965 ) and rats (Iwata & LeDoux, 1988 ), potentially linking coactivation to certain types of psychological stress. Furthermore, coactivation occurs more often during psychological stress, while physical stressors more often induce reciprocity (Berntson, Cacioppo, Binkley, et al., 1994 ; Cacioppo et al., 1994 ).

The exact situational determinants and neurological mechanisms underlying autonomic space have yet to be specified. Nonetheless, position in autonomic space is expected to better discriminate between certain tasks (e.g., physical vs. psychological stress). They may also better predict physiological and psychological function than markers that do not discriminate between the SNS and PSNS (e.g., HR), or markers that reflect only PSNS activity or SNS activity.

Empirical Support and Current Status of Autonomic Space Model

Evidence of nonreciprocal PSNS-SNS coupling has existed for some time (Cannon, 1939 ; Gellhorn, Cortell, & Feldman, 1940 ; Koizumi, Terui, Kollai, & Brooks, 1982 ; Kollai & Koizumi, 1979 ). Berntson et al. ( 1993 ) review empirical data in humans demonstrating the existence of coactivity, reciprocity, and uncoupling. Subsequent research also shows that different patterns of PSNS-SNS coupling not only exist but have important functional implications. In a study of mental workload, Backs ( 1995 ) measured heart period, RSA, and Traube-Hering-Mayer waves (a SNS marker) while participants performed tasks with varying levels of physical and mental demand. As predicted by autonomic space model, nonreciprocal modes were associated with blunted heart period reactivity, supporting the notion that different modes of coupling differentially affect the physiology of target organs like the heart, which are innervated by both the PSNS and SNS. Also consistent with autonomic space theory, Backs ( 1995 ) found that position in autonomic space was a better predictor of mental workload than HR, demonstrating that autonomic space conveys unique and important information about function that is not conveyed by other autonomic markers. This is demonstrated in other studies as well. Using PEP and RSA as markers of the SNS and PSNS, respectively, Giuliano et al. ( 2017 ) found that position in autonomic space was a better marker of working memory than either SNS activity or PSNS activity alone. Adults exhibiting reciprocal activation showed better working memory capacity during mental challenge compared to coactivators. Similarly, preschoolers showing reciprocal activation (specifically PSNS deactivation and SNS activation) exhibited better emotional and attentional regulation during social challenge (Clark, Skowron, Giuliano, & Fisher, 2016 ). Reciprocal PSNS-SNS coupling, therefore, appears to correlate with abilities that could help individuals cope with challenging situations such as difficult working memory tasks and emotional and attentional regulation.

The relationship between the PSNS and SNS has been found to be a better predictor of stress-related outcomes than either considered alone. El-Sheikh et al. ( 2009 ) found that children exhibiting coactivity (either high RSA and SCR reactivity, or low RSA and SCR reactivity) developed more externalizing problems if they were exposed to marital conflict, while reciprocal activation appeared to reduce risk of externalizing problems in conflict-exposed children. Likewise, in toddlers, prenatal adversity predicted more aggression in children exhibiting coactivation, while toddlers exhibiting reciprocal activation showed less aggression (Suurland, van der Heijden, Huijbregts, van Goozen, & Swaab, 2017 ). Similarly, in adolescence, coactivation was also found to exacerbate the effect of early life adversity on aggression (Gordis, Feres, Olezeski, Rabkin, & Trickett, 2010 ). Adults showing coactivation have also shown worse aggression (Wagner & Abaied, 2015 ) and depression (Holterman, Murray-Close, & Breslend, 2016 ) following peer victimization compared to those with reciprocal activation. Taken together, these findings suggest that across development, PSNS-SNS coupling moderates the effects of various forms of adversity on different health outcomes. Nonreciprocal coupling is associated with greater vulnerability to stress-related mental health problems, like depression and externalizing problems, while reciprocal coupling indicates resilience against the harmful effects of stress.

In addition to stress-related mental health problems, coactivity may also indicate other stress-related problems like cardiovascular disease. Coactivation alters HR dynamics (Eickholt et al., 2018 ; Tulppo et al., 2005 ) and may predispose individuals to atrial fibrillation (Tan et al., 2008 ), a risk factor for heart attack and stroke (Odutayo et al., 2016 ). Hypothetically, situations that induce coactivity chronically may precipitate or exacerbate atrial fibrillation, placing individuals at greater risk of heart disease; however, this idea has yet to be explored empirically.

Although data implicate coactivity as a risk factor for disease, there may nonetheless be advantages associated with coactivity. During stress, coactivity is associated with increased secretory immune system function (Bosch, de Geus, Veerman, Hoogstraten, & Amerongen, 2003 ) and less negative affect (Miller, Kahle, Lopez, & Hastings, 2015 ). The adaptive function of coactivity should be further examined because it may help explain why and when coactivity occurs.

Strengths and Limitations of the Autonomic Space Model

The autonomic space model is among the first models to acknowledge nonreciprocal coupling between PSNS and SNS activity. A significant strength of this model is to highlight the functional significance of nonreciprocal coupling of SNS and PSNS activity (i.e., SNS-PSNS coactivation or uncoupled changes in activity). This model could also improve our capacity to predict health outcomes in individuals exposed to stress. Researching the relationship between health and the activity of a single autonomic branch has so far yielded inconsistent results. Many pathologies are sometimes associated with higher activity and other times lower activity of the same marker. The association between autonomic branches may yield a more consistent and reliable predictor of stress-related health problems than either branch alone, since the functional impact of one branch’s activity depends on the activity of the other branch.

On the other hand, the autonomic space model presents some limitations and opportunities for growth. The model excels at predicting important performance and health outcomes but falls short at explaining them. Although coactivity may predict worse stress-related health outcomes, the temporal dimension is unresolved—it is unclear whether coactivity causes, co-occurs, or results from adverse health outcomes. It is also unclear how different modes of coupling develop overtime. Some authors propose that passive cognitive challenge can evoke coactivity while active challenges evoke reciprocity (Berntson, Cacioppo, & Fieldstone, 1996 ; Bosch et al., 2003 ). This does not readily explain why the same task elicits coactivity in some individuals yet reciprocity in others (e.g., El-Sheikh et al., 2009 ). Finally, the autonomic space model only considers associations between the PSNS and SNS. Unlike other physiological models of stress (e.g., adaptive calibration model), it has yet to consider associations between the ANS and other stress systems such as the HPA axis. Neurological mechanisms underlying different modes of coupling are also vague. The developers of the autonomic space model suggest anterior brain regions, particularly those linked to emotion and attention, control the switch between reciprocity and coactivity (Berntson et al., 1991 ). Specifying these neurological mechanisms, and linking them to specific cognitive, physiological and behavioral processes, may help explain how reciprocity and coactivity develop over time, interact with other systems (e.g., the HPA axis), and contribute to stress-related health problems. Despite the limitations, the autonomic space model is a valuable contribution to stress research because it reveals the importance of investigating the associations between components of the ANS.

Neurovisceral Integration Theory

Neurovisceral integration theory (Smith, Thayer, Khalsa, & Lane, 2017 ; Thayer, Hansen, Saus-Rose, & Johnsen, 2009 ; Thayer & Lane, 2000 , 2009 ) considers the neurological and cognitive mechanisms underlying the association between health and autonomic function. According to neurovisceral integration theory (NIT), the SNS and PSNS are extensions of the central autonomic network (CAN), a system that regulates homeostasis, attention, and emotion. The CAN integrates diverse information about internal and external conditions, and selects biological and behavioral responses adaptive for the current context. Among the core assumptions of the CAN is that it connects higher order cortical regions (e.g., ventromedial prefrontal, anterior cingulate, insular cortex), midlevel regions (e.g., central amygdala, hypothalamus, periaqueductal gray), and brainstem regions (e.g., nucleus of the solitary tract, ventrolateral medulla, parabrachial nucleus) with the sensory and motor neurons of the ANS (Benarroch, 1993 ; Thayer & Lane, 2009 ). The bidirectional flow of information across the CAN forms an integrated representation of internal and external demands and coordinates emotion, attention, and visceral state to respond to these demands.

Internal and external demands change constantly. Health and well-being, therefore, require the CAN to rapidly and accurately detect changes in demands, select appropriate responses, and inhibit inappropriate ones. When the CAN malfunctions, individuals could thus become stuck in a state that no longer fits the current context. Stress-related health problems such as anxiety can arise when individuals become stuck in a defensive mode even when the context is no longer threatening (Brosschot, Gerin, & Thayer, 2006 ).

The CAN’s capacity to dynamically and efficiently integrate information depends significantly on the prefrontal cortex, which provides a more detailed representation of the broader context and enhances the salience of long-term goals (Smith et al., 2017 ). Among the brain structures forming the CAN, there is also a regulation hierarchy; for example, the prefrontal cortex inhibits subcortical divisions of the CAN such as the central amygdala. These subcortical regions respond to simpler, more immediate cues and promote a defensive mental and physiological state (e.g., fight-or-flight response). Insufficient prefrontal control can lead to overexcitation of the amygdala, prolonging the fight-or-flight response even when the context is no longer threatening. Adequate prefrontal control is therefore assumed to be important for preventing stress-related illness.

NIT asserts that higher RSA is an indicator of adequate prefrontal control over the CAN. Individuals with higher RSA should thus be less vulnerable to stress-related illness for several reasons. First, higher RSA indicates more prefrontal control, and subsequently better executive function, and control over attention and emotion. This capacity is likely to minimize adverse consequences of exposure to stressors by resolving stressful situations efficiently and preventing their occurrence in the future. Control over attention and emotion can further prevent overactivation of the SNS and HPA axis by preventing an exaggerated perception of threat, thereby limiting allostatic load. The prefrontal cortex also directly inhibits brain regions that activate the HPA axis and SNS stress response such as the central amygdala. This could help reduce allostatic load.

Empirical Support and Current Status of Neurovisceral Integration Theory

Consistent with NIT, studies suggest that individuals with higher RSA levels at rest experience less stress-related health problems. High basal RSA is also negatively correlated with several stress-related illnesses, including cardiovascular disease (Thayer & Lane, 2007 ), depression (Agelink, Boz, Ullrich, & Andrich, 2002 ), and anxiety (Dieleman et al., 2015 ). RSA also moderates the effects of adversity on health. Higher basal RSA appears to reduce the impact of early life adversity on internalizing problems (El-Sheikh, Harger, & Whitson, 2001 ; McLaughlin, Alves, & Sheridan, 2014 ), externalizing problems (El-Sheikh et al., 2001 ), aggression (Suurland, van der Heijden, Huijbregts, van Goozen, & Swaab, 2018 ), delinquency (Hinnant, Erath, & El-Sheikh, 2015 ), and substance use (Hinnant et al., 2015 ).

According to NIT, higher basal RSA predicts resilience to stress partly because higher RSA reflects greater prefrontal control over emotion and attention. In line with these predictions, numerous studies associate higher basal RSA levels with better regulation of attention (Suess, Porges, & Plude, 1994 ) and emotion (Appelhans & Luecken, 2006 ), reduced attention to threatening stimuli (Park, Bavel, Vasey, & Thayer, 2013 ), and better executive function (Holzman & Bridgett, 2017 ), all of which depend on prefrontal control (Heatherton, 2011 ). Neuroimaging studies associate higher RSA with greater prefrontal activity (Thayer, Åhs, Fredrikson, Sollers, & Wager, 2012 ) and greater functional connectivity between the medial prefrontal cortex and amygdala (Sakaki et al., 2016 ). Together these results support the notion that higher basal RSA indexes better prefrontal control over emotion and attention.

Prefrontal control, as indicated by high RSA, may also protect individuals from stress-related illness by inhibiting systems like the SNS or HPA axis that increase allostatic load. Consistent with this claim, women with early life adversity released less cortisol and pro-inflammatory cytokines during stress exposure if they also had high RSA levels (Tell, Mathews, Burr, & Janusek, 2018 ). Higher baseline RSA is also associated with lower cardiovascular reactivity to stress (Grossman, Watkins, Wilhelm, Manolakis, & Lown, 1996 ; Souza et al., 2009 ). RSA also tends to negatively correlate with SNS activity; however, as we discussed in the section on the autonomic space model, PSNS and SNS activation is not always reciprocal (Berntson et al., 1993 ). Sometimes the SNS and PSNS coactivate or uncouple. It is unclear, however, how these nonreciprocal modes of SNS-PSNS coupling fit within NIT or, in other words, whether the autonomic space model can complement NIT or is in conflict with it.

NIT further predicts that higher SNS activity indicates dysfunctional prefrontal control and greater susceptibility to stress-related illness. Consistent with this, in children with higher SNS reactivity, parental depression led to worse psychosocial adjustment (Abaied, 2016 ), and more internalizing and externalizing problems (Cummings, El-Sheikh, Kouros, & Keller, 2007 ). The relationship between health and SNS activity or reactivity may be more complicated than suggested by NIT, however. Some studies associate SNS hyperactivity with anxiety (Dieleman et al., 2015 ; Lambert et al., 2010 ; Schoorl, Rijn, Wied, Goozen, & Swaab, 2016 ) and depression (Ishitobi et al., 2010 ; Lambert et al., 2010 ). Contrarily, a few studies associate SNS hypoactivity with the same conditions: anxiety (Hoehn-Saric et al., 1989 ) and depression (Cubała & Landowski, 2014 ; Schwerdtfeger & Rosenkaimer, 2011 ). Similar to the SNS, stress-related problems have been associated with both hyperactivity and hypoactivity of the HPA axis (Boyce & Ellis, 2005 ). The relationship between blunted SNS/HPA axis activity and stress-related problems does not easily fit within the framework of NIT.

Strengths and Limitations of Neurovisceral Integration Theory

NIT reinforces the prognostic value of basal RSA as a predictor of stress-related illness. Individuals with higher RSA appear more resilient against stress-related illness. NIT also articulates neurocognitive processes such as emotional regulation that link high basal RSA with resilience. Furthermore, NIT provides a model of how different neural systems within the CAN interact to control autonomic function, cognition, emotion, and ultimately health. Understanding how chronic adversity and other factors interact to influence the CAN may help us better understand how stress-related illness develops over time. Furthermore, since the CAN consists of brain regions that regulate other stress systems such as the HPA axis, NIT may help us understand how the ANS interacts with these other systems to affect health; however, its predictions about the SNS and HPA axis may need updating to account for inconsistent associations between blunted activity/reactivity and stress-related illness. NIT has a few other limitations. While this theory accounts for the relationship between health and basal RSA, it does not clearly explain the relationship between health and vagal reactivity, or the reactivity of other physiological systems, for that matter. Furthermore, NIT predominantly focuses on RSA. The SNS may receive less attention in NIT because this theory considers reciprocal associations between the SNS and PSNS, and does not consider alternative possible associations, like coactivity, between the SNS and PSNS.

Polyvagal Theory

Polyvagal theory (PT) (Porges, 1995 , 1997 , 1998 , 2001 , 2003 , 2007 , 2009 ) makes predictions about stress-related illness by considering how different parts of the ANS emerged at different points in evolution. PT argues that the ANS consists of three phylogenetically, structurally, and functionally distinct components: the dorsal vagus, the SNS, and the ventral vagus. Prominently, PT argues that these systems evolved to cope with different situations and have different effects on health.

According to PT, the first system to evolve was the dorsal vagus (or unmyelinated vagus), which is a distinct branch of the PSNS originating from the dorsal motor nucleus. The dorsal vagus is a potent suppressor of heart rate and metabolism. In threatening situations, activation of the dorsal vagus allows organisms to avoid detection by predators and to conserve resources. This primitive stress response, often referred to as immobilization or freezing response, is adaptive for primitive organisms (e.g., reptiles), but it can be deadly for more recently evolved organisms like humans, who require a constant energy supply.

The next system to evolve was the SNS, which increases metabolism, counteracting the effects of the dorsal vagus. According to PT, moderate SNS activity inhibits the dorsal vagus, while robust SNS activation, along with activation of the HPA axis, facilitates the fight-or-flight response by mobilizing stored energy and promoting vigilance, aggression, and other defensive behaviors. While the fight-or-flight response is not as harmful as the immobilization response, consistent with allostatic load theory, PT predicts that chronic activation of the SNS or HPA axis damages organs over time. Vigilance, aggression, and other defensive behaviors are also maladaptive for social organisms such as humans, as these behaviors can alienate sources of social support while increasing potential sources of adversity.

The final component of the ANS, according to PT, and the most recent system to have evolved, is the ventral vagus (or myelinated vagus), which is a distinct branch of the PSNS originating from the nucleus ambiguus within the reticular formation. Like the dorsal vagus, the ventral vagus slows heart rate, but not as much or for as long as the dorsal vagus. Since the ventral vagus is myelinated, it exerts more rapid and precise control over heart rate than the dorsal vagus or SNS. Consequently, according to PT, RSA is a marker specifically of ventral vagal activity. PT argues that the ventral vagus evolved to meet the needs of more advanced social organisms and protects their health in four ways. (1) The ventral vagus promotes homeostasis. It supports vegetative functions conducive to growth and recovery, and it conveys information about visceral state back to the brain. (2) The ventral vagus limits allostatic load by inhibiting the SNS and HPA axis. Acute reductions in vagal tone are already sufficient to increase metabolism, so the organism can respond to certain challenges without activating the SNS and HPA axis. (3) The ventral vagus facilitates self-soothing and helps regulate emotion and attention. (4) Finally, the ventral vagus facilitates social engagement, by preventing defensive behaviors, and through anatomical and physiological connections with structures involved in communication. Together, the ventral vagus thus facilitates homeostasis, recovery from stress, minimizes allostatic load, and promotes cognition and behaviors that are known to protect individuals from stress such as emotional and attentional regulation, and social engagement.

Each of the components of the ANS, the ventral vagus, SNS/HPA axis, and dorsal vagus, supports different functions that are incompatible with each other; thus, they are activated at different times. PT predicts that these three systems activate in a hierarchical manner, consistent with the principle of Jacksonian dissolution (Jackson, 1958 ). Jackson’s principle states that evolutionarily more recent systems inhibit older ones. If the recent system is no longer sufficient, the next most recent system takes over, shifting the organism to a more primitive response. Applying Jackson’s principle, PT predicts that in safe environments, the ventral vagus inhibits the SNS and HPA axis, supporting social engagement and self-soothing. In response to moderate challenge, the ventral vagus may moderately withdraw to increase metabolism. In more threatening situations, the ventral vagus withdraws more completely, freeing the SNS and HPA axis, switching the organism from social engagement to a fight-or-flight response. If the fight-or-flight response is insufficient to deal with threat, as a last resort the SNS and HPA axis also withdraw, freeing the dorsal vagus to mount an immobilization (freezing) response. This allows organisms to respond to different levels of threat.

PT makes several predictions about stress-related health problems. High ventral vagal activity, as indexed by high levels of RSA, indicates the individual perceives safety and is socially engaged, a situation more likely to emerge in nonstressful environments. Since the ventral vagus promotes growth and recovery and prevents overactivation of the SNS and HPA axis, hypothetically, individuals with higher basal RSA should also be less susceptible to stress-related illness. Both PT and NIT associate higher basal RSA with better health outcomes and resilience against stress. PT further predicts that in addition to high basal RSA, healthy individuals should also exhibit brief decreases in RSA during acute stress. Failure to reduce RSA during stress (i.e., blunted RSA reactivity) is further predicted to correlate with poor health and developmental outcomes. Blunted RSA and SNS reactivity to stress may also indicate an immobilization response, particularly in the presence of life-threatening, traumatic events. Such a reactivity profile is likely to occur in conditions of extreme adversity and also predicts poor health outcomes since prolonged suppression of metabolism would be expected to damage the heart and brain.

Empirical Support and Current Status of Polyvagal Theory

Consistent with PT, basal RSA positively correlates with attention regulation (Suess et al., 1994 ), emotion regulation (Appelhans & Luecken, 2006 ), social engagement (Geisler, Kubiak, Siewert, & Weber, 2013 ), and prosocial behavior (Beauchaine et al., 2013 ). This is in line with the notion that the ventral vagus, as indexed by RSA, facilitates social engagement, emotional regulation, and attention regulation.

Also consistent with PT, research has found that RSA reliably decreases during challenge (Beauchaine, Gatzke-Kopp, & Mead, 2006 ), and moderate reduction in RSA during challenge is associated with better executive function (Marcovitch et al., 2010 ) and cognitive performance (Roos et al., 2018 ). The relationship between RSA reactivity and cognitive outcomes, however, appears to vary by context. Some studies find that high RSA reactivity predicts better cognitive outcomes in nonstressful environments, but worse outcomes in individuals living in chronically stressful environments (Giuliano, Roos, Farrar, & Skowron, 2018 ; Obradovic, Bush, Stamperdahl, Adler, & Boyce, 2010 ). PT does not readily explain why and how the environment would moderate the relationship between RSA reactivity and cognitive outcomes.

Both PT and NIT predict that individuals with higher basal RSA are less vulnerable to the harmful effects of stress. As mentioned in the section on NIT, ample research suggests that individuals with high RSA develop fewer health problems when exposed to adversity (El-Sheikh et al., 2009 ; Hinnant et al., 2015 ; McLaughlin, Alves, et al., 2014 ; Suurland et al., 2017 ). Studies also find that low basal RSA is associated with various stress-related illnesses such as cardiovascular disease (Thayer & Lane, 2007 ), depression (Agelink et al., 2002 ), and anxiety (Dieleman et al., 2015 ).

Like NIT, PT predicts that the relationship between higher basal RSA and better health outcomes is partly mediated by inhibition of the SNS and HPA axis. As mentioned in the section on NIT, this prediction is inconsistently supported. Some studies associate stress-related illness with greater SNS or HPA axis activity, while others studies associate stress-related illness with lower (not higher) SNS or HPA axis activity. Nonetheless, the relationship between SNS hypoactivity and poor health outcomes may still be consistent with PT. Hypothetically, SNS hypoactivity may indicate that the individual has shifted to the immobilization response, mediated by the dorsal vagus.

Strengths and Limitations of Polyvagal Theory

PT identifies processes such as social engagement and self-regulation that link higher RSA with better resilience against stress-related illness. Inhibition of the HPA axis and SNS may be another mechanism linking high vagal tone to better resilience; however, it is difficult to evaluate this claim given the inconsistent associations between SNS/HPA axis activity and stress-related disease reported in the literature. Nonetheless, PT may potentially explain why SNS activity and reactivity are inconsistently associated with stress-related problems. Individuals with higher SNS activity or reactivity are at increased risk of allostatic load, whereas blunted SNS activity may be a sign the individual has entered the immobilization phase.

PT, like all theories, has a number of limitations. First, the theory assumes inhibitory (i.e., reciprocal) relationships between the SNS and PSNS. Like NIT, PT should be expanded to accommodate coactivation of SNS and PSNS. Another limitation concerns predictions made about reactivity. Consistent with PT, some studies associate higher RSA reactivity to stress with better cognitive outcomes; however, other studies find that the relationship between reactivity and cognitive outcomes is moderated by context. PT does not clearly explain why context moderates effects of RSA reactivity; however, biological sensitivity to context theory does.

Biological Sensitivity to Context Theory

The relationship between autonomic function and health may vary between studies because the impact of autonomic function depends on the individual’s context. Biological sensitivity to context theory (BSC) (Boyce & Ellis, 2005 ; Ellis & Boyce, 2008 ) is an evolutionary developmental theory that emphasizes how the environment interacts with the reactivity of the physiological stress systems in the organism to determine health and developmental outcomes. An intuitive concept in BSC is that high reactivity per se is neither good nor bad. The relationship between reactivity and health depends on what the environment demands. Theories that existed before BSC, such as the diathesis-stress or allostatic load theory, predict that highly reactive individuals are more vulnerable to stress-related illness because they accumulate more allostatic load. As Boyce and Ellis ( 2005 ) review, while data certainly exist that associate greater reactivity with worse health and developmental outcomes, a large number of studies associate greater reactivity with better health and developmental outcomes. To explain these inconsistent findings, BSC proposes that whether a particular level of reactivity harms or promotes health depends on the individual’s context. Specifically, high reactivity exacerbates health problems in adverse environments but promotes positive health and developmental outcomes in supportive, nonstressful environments. In contrast, less reactive individuals may not fair as poorly in stressful environments, but they do not benefit as much from supportive environments, showing the same moderate outcomes regardless of the environment.

To explain the interaction between environment and physiological reactivity, BSC argues that low reactivity and high reactivity each are advantageous in different environments. In nonstressful environments, high reactivity maximizes long-term growth and survival by enhancing attention and engagement with positive sources of stimulation. In supportive environments, the physiological stress response systems are infrequently and briefly perturbed, preventing excess allostatic load. When stress becomes more frequent or intense, high reactivity leads to excess allostatic load. In moderately stressful conditions, low reactivity is therefore conducive to long-term growth and survival since it limits allostatic load. In highly threatening environments, low reactivity ceases to be advantageous, since activation of the physiological stress response systems is required to survive. High reactivity may be necessary to survive in the short term, but it comes at the expense of undermining long-term growth and survival.

Since high and low reactivity are adaptive in different environments, BSC proposes that humans evolved to shift their reactivity toward a level optimal for the individual’s environment. Boyce and Ellis (Boyce & Ellis, 2005 ; Ellis & Boyce, 2008 ) predict a U-shaped relationship between increasing levels of adversity and physiological reactivity. Individuals exposed to extremely supportive or extremely stressful environments are predicted to develop higher reactivity, while those exposed to moderately stressful environments develop low reactivity. This process is believed to occur gradually early in development. Consequently, individuals may therefore exhibit a level of reactivity that is no longer adaptive for their current context, if their individual environmental context changes after a critical development period.

Empirical Support and Current Status of Biological Sensitivity to Context Theory

An early test of BSC (Ellis, Essex, & Boyce, 2005 ) observed the expected U-shaped relationship between adversity and reactivity. High SNS reactivity tended to occur among children exposed to extremely low or extremely high adversity; low SNS reactivity was common in environments that were not particularly stressful or supportive. It is nonetheless worth noting that many individuals exposed to extreme adversity early in life, such as Romanian orphans, exhibit blunted (not greater) SNS reactivity (McLaughlin et al., 2015 ); thus, the relationship between adversity and ANS reactivity may be more complex than the U-shaped relationship initially proposed by BSC.

Ample empirical evidence supports BSC’s prediction that adversity and autonomic reactivity interact to determine health outcomes. Consistent with BSC, studies associate greater reactivity with worse health outcomes in adverse environments, but better outcomes in supportive environments. In terms of cardiovascular reactivity, Cook et al. ( 2012 ) found that greater cardiovascular reactivity predicted worse interpersonal competence and anger regulation for adolescents experiencing maltreatment, but better interpersonal competence and anger regulation for adolescents in more supportive environments.

Using RSA reactivity as a marker of PSNS reactivity, Conradt and colleagues ( 2016 ) found that higher RSA reactivity at 1 month of age predicted more internalizing and externalizing problems at 3 years of age—but only for children with high levels of caregiver stress. Likewise, in preschoolers, Obradovic and colleagues ( 2010 ) examined several outcomes, including externalizing behaviors, prosocial behavior, and social engagement. High RSA reactivity predicted worse outcomes in children living in stressful environments, but better outcomes in children living in nonstressful condition. Contexts also moderate the effects of SNS reactivity. For instance, El-Sheikh et al. ( 2007 ) found that for girls (but not boys), the combination of high early life adversity and high SCR reactivity increased risk of internalizing and externalizing problems.

Contrary to predictions made by BSC, numerous studies also suggest the opposite association between reactivity and stress-related illness. For example, higher PSNS reactivity to stress appeared to reduce rather than exacerbate the impact of childhood adversity on children’s internalizing pathology (McLaughlin, Alves, et al., 2014 ). Also contrary to BSC, higher SNS reactivity reduced rather than exacerbated the impact of maternal depression on children’s externalizing pathology (Waters et al., 2016 ). Interestingly, a large number of studies examining the interaction between early life adversity and autonomic reactivity observe sex differences, which are not clearly explained by BSC theory (El-Sheikh et al., 2007 ; Gray et al., 2017 ; Lorber, Erlanger, & Slep, 2013 ; Sijtsema, Roon, Groot, & Riese, 2015 ).

Strengths and Limitations of Biological Sensitivity to Context Theory

BSC speaks to how autonomic function might more accurately predict health when the individual’s context is also taken into consideration. BSC is one of the few theories that attempt to explain why the relationship between health and autonomic function varies between studies; thus, it could also explain why the relationship between autonomic function and early life adversity varies between studies.

BSC nonetheless has a few limitations. Extreme adversity is not always associated with heightened stress reactivity as predicted by BSC. Furthermore, some studies observe interactions between adversity and reactivity that go against BSC. Sometimes the expected interaction is observed in one sex but not the other. Furthermore, BSC focuses on general physiological reactivity and does not make specific predictions about individual stress systems. This is problematic, since as autonomic space theory reveals, PSNS and SNS activity can change independently of one another. It is unclear how to classify these individuals within BSC theory. From the perspective of polyvagal theory, the PSNS, SNS, and HPA axis response to stress differentially impacts health; thus, it may be unreasonable to predict that individuals with high SNS reactivity will have the same health outcomes as individuals with high PSNS reactivity.

New Developments

Adaptive calibration model.

A new theory, the adaptive calibration model of stress responsivity (ACM) (Del Giudice, Ellis, & Shirtcliff, 2011 ), aims to explain individual differences in the physiological stress systems, the HPA axis, SNS, and PSNS. To explain how stress systems develop over time and impact health, ACM expands on biological sensitivity to context theory (BSC), incorporating concepts from polyvagal theory (PT), allostatic load theory, and other models in stress research in addition to concepts from evolutionary biology (e.g., life history theory). According to the ACM, the stress response systems evolved to serve three key functions: (1) to help survive acute stressors by implementing allostasis, (2) filter and encode information about threats and opportunities in the environment, and based on this information, (3) affect physiology and behavior in a way that guides development toward a phenotype that is optimal for the given environment. Here, “optimal” means to maximize reproductive fitness. Consequently, alterations in stress system function can lead to characteristics that may be undesirable, but over the course of human evolution, increased the likelihood of passing one’s genes on to the next generation.

The ACM also provides a taxonomy that can be used to describe individual differences in stress system function (baseline activity and stress reactivity). As summarized in Table 22.1 , there are four patterns of responsivity. Each pattern emerges in a particular environment and predicts specific health and developmental outcomes. Type I, the sensitive type, is similar to the sensitive phenotype described in BSC and develops in very low levels of early life adversity. Sensitive individuals are more susceptible to stress-related illness if they encounter adversity but exhibit better health and developmental outcomes in nonstressful environments. Consistent with PT, the sensitive type, which shows higher PSNS activity and reactivity, is expected to show better social engagement and emotional and attentional regulation in supportive environments. Type II, the buffered type, develops in conditions that are not particularly safe or adverse. When buffered individuals encounter adversity, they are less susceptible to stress-related illness, but they are also less susceptible to positive environmental influences. Type III, the vigilant type, develops in more stressful conditions and is characterized by a robust and persistent fight-or-flight response. These individuals are more susceptible to stress-related illness but are more likely to survive harsh conditions, at least to the point where they reproduce. Finally, type IV, the unemotional type, emerges in extremely harsh conditions and is characterized by blunted activity and reactivity of the PSNS, SNS, and HPA axis. The unemotional type is expected to show high rates of antisocial behavior and other problems due to a reduced sensitivity to social feedback. Importantly, different types are not discrete categories but are continuous with each other. Individuals thus can transition from one type to another depending on their cumulative exposure to early life adversity at critical periods in development such as prenatal development, early childhood, puberty, and potentially other periods.

Empirical Support and Current Status of the Adaptive Calibration Model

The ACM is a new theory, so empirical support thus far is limited. Nonetheless, a few studies support the basic predictions of ACM. Del Giudice, Hinnant, Ellis and El-Sheikh ( 2011 ) examined children exposed to varying levels of early life adversity and measured SCR and RSA basal activity and stress reactivity (no markers of the HPA axis were included). Using finite mixture modeling, the authors reduced the variance in SCR and RSA activity and reactivity into the four patterns predicted by the ACM. Pattern was related to early life adversity as predicted by the ACM. More recently, a study of men (Ellis, Oldehinkel, & Nederhof, 2016 ) measured PSNS, SNS, and HPA axis markers at rest and during stress. Again, the four-pattern classification was validated, and pattern associated with early life adversity in the expected direction. For the most part, pattern was also associated with the predicted behavioral and developmental outcomes. For instance, as expected, the unemotional type was associated with the highest levels of aggression and rule breaking.

While the ACM predicts four patterns of responsivity, additional patterns might exist. In a large sample of adolescents, Quas et al. ( 2014 ) found six distinct responsivity patterns. While the first four corresponded to the patterns predicted by ACM, two patterns were new. In a separate study, Kolacz et al. ( 2016 ) found three types (sensitive, buffered, and vigilant) in addition to a novel type. Kolacz et al. ( 2016 ) did not observe the unemotional type, potentially because they did not sufficiently sample individuals with extreme levels of early life adversity.

Strengths and Limitations of the Adaptive Calibration Model

Since the ACM integrates multiple perspectives covered by other theories (BSC, PT, allostatic load), the theory has multiple strengths. Like PT, the ACM acknowledges that reactivity and basal activity predict distinct outcomes. Like BSC, the ACM aims to account for heterogeneous relationships between autonomic function and chronic stress, and autonomic function and health. The ACM provides insights into how individual differences in stress system function develop over time depending on genes and exposure to early life adversity. Since the relationship between early life adversity and stress reactivity is nonlinear, it may partly explain why effects of early life adversity on stress system physiology vary between studies. The ACM improves upon BSC by making specific predictions about PSNS, SNS, and HPA axis reactivity. For instance, both the sensitive and vigilant type show higher reactivity, but the sensitive type shows predominantly higher PSNS reactivity, whereas the SNS shows predominantly higher SNS reactivity; consequently, sensitive and vigilant types are associated with distinct ecological antecedents and distinct health and developmental outcomes.

ACM nonetheless has several limitations and opportunities for growth. First, ACM is a complex model, making it difficult to falsify. Low, moderate, high, and extreme exposure to early life adversity are expected to have different effects on stress function. Since there is no standard operational definition of early life adversity, it is difficult to delineate low, moderate, high, and extreme adversity, particularly when a wide range of events and experiences can be called “adverse.” A similar argument can be made regarding reactivity and baseline activity—there is no standardized definition of low, moderate, and high reactivity or activity. This limitation could apply to any theory about ANS function; however, it is particularly relevant to the ACM since it posits nonlinear associations between reactivity, adversity, and health. The absence of quantitative definitions for low, moderate, and high reactivity/activity makes the theory more difficult to falsify. Despite these limitations, the ACM is a promising new model that encourages researchers to consider relations between the SNS, PSNS, and HPA axis and other neuroendocrine systems as well.

Changes in Physiology as a Result of Interaction With Other Systems—Empirical Findings

Recently, our group has begun to systematically examine the interaction between both the HPA axis and ANS on the psychological, physiological, and endocrine level during an acute stress test. To this end, we looked at the cross-correlation between the SNS and HPA axis stress responses (Engert et al., 2011 ) and how behavioral variables depend on the ratio of HPA reactivity to autonomic reactivity (Ali & Pruessner, 2012 ). Further, we combined the dexamethasone suppression test with the Trier Social Stress Test (TSST) to study the effects of stress on the ANS in the absence of a reactive HPA axis. This study (Andrews et al., 2012 ) was the first attempt to systematically investigate the effect of manipulating these stress systems, and thus deserves a somewhat more detailed description: Here, we exposed 30 healthy young men to a psychosocial stressor and measured salivary cortisol, a hormone of the HPA axis, in addition to salivary alpha-amylase, heart rate, blood pressure, and subjective stress. As the main experimental manipulation, half of the subjects received a standard dose of dexamethasone (DEX; 2 mg) the night before testing, resulting in elevated negative feedback at the level of the pituitary and a central low-cortisol state since DEX cannot cross the blood–brain barrier (de Kloet et al., 1974 , 1975 ), resulting in increased corticotropin-releasing hormone (CRH), but suppresses subsequent secretion of peripheral HPA axis hormones, adrenocorticotropin and cortisol. This can be compared to a state where the HPA axis is dysfunctional and unable to respond to stress, as discussed for states like burnout and chronic fatigue syndrome. As a result of this manipulation, subjects who received DEX demonstrated a higher increase in subjective stress post TSST, and a significantly higher heart rate throughout the protocol, when compared to the placebo group. This suggested an active compensation between the HPA axis and ANS, where SNS activity may be elevated, or PSNS activity may be diminished, in the presence of a suppressed HPA axis response.

Although we were the first group to combine an acute psychosocial stressor with DEX to investigate this cross-talk, others have also reported such an association, and a number of hypotheses have been proposed to explain the increased SNS activity following dexamethasone administration. First, the dexamethasone-induced low-cortisol state in the brain could have elevated heart rate via a CRH surge (due to the lack of negative feedback), by way of a periventricular nucleus and locus coeruleus connection (Yamaguchi & Okada, 2009 ). Also, Chrousos and Gold ( 1992 ) found that norepinephrine potentiates the release of CRH, creating a feedforward mechanism between the systems; thus, a central ANS mechanism could have been initiated to augment the HPA axis response, a mechanism also discussed by Suzuki et al. ( 2003 ). Consequently, the increased cardiovascular activity found in a population where cortisol output of the HPA axis is suppressed may be due to these factors individually and/or in combination (Andrews et al., 2012 ). Since the regulation of the ANS and HPA axis overlaps at several points in the brain (Ulrich-Lai & Herman, 2009 ), predominantly in the hypothalamus, it can be speculated that this is an active compensatory mechanism, such that the absence of the peripheral HPA response may up-regulate SNS activity or decrease PSNS activity, compensating for the lack of a stress response in one system with altered activity in the other, to keep the organism in an equilibrium, and allow allostasis.

This can be interpreted to have demonstrated a potential pathway for the development of cardiovascular disease, metabolic syndrome, and diabetes (Sabbah, Watt, Sheiham, & Tsakos, 2008 ; Seeman et al., 2001 ; Selye, 1970 ). This further points to a potential disease mechanism where either a blunted HPA axis activity or an increased cardiovascular reactivity might lead to these types of disease.

We also investigated (Andrews & Pruessner, 2013 ) suppressing the ANS (SNS) by using propranolol (PROP) in combination with the TSST. When administering subjects PROP 1 hour before the TSST, thereby preventing a SNS response, we observed signs of a compensatory increase in HPA axis activity in response to stress (Andrews & Pruessner, 2013 ). As expected, cardiovascular activation was strongly suppressed in the PROP group. Heart rate, salivary alpha-amylase, and systolic blood pressure levels all showed very small or no increase in response to stress, in the PROP group. In contrast, subjective stress and diastolic blood pressure were not different between the two groups. The main result that indicated significant cross-talk between the HPA axis and SNS was observed for cortisol levels, which were significantly higher in the experimental group. The finding of higher HPA axis activity after SNS suppression has also been reported by a number of other laboratories (Benschop et al., 1996 ; Kizildere et al., 2003 ; Maheu et al., 2005 ; Oei et al., 2010 ; Simeckova et al., 2000 ), suggesting that the absence of SNS response leads to an increase in HPA axis activity, compensating for the lack of a stress response with an increase in another stress response system, to keep the organism in an equilibrium. These results are quite intriguing, as one could have expected a lower cortisol response in the absence of a physiological stress response; after all, no physiological arousal is signaling to the brain a state of stress, as would be expected from past research on emotion and emotion processing (e.g., Dutton & Aron, 1974 ). The fact that SNS suppression augments the cortisol stress responses strongly suggests that at a central level the lack of a physiological response is answered by a stronger activation of the HPA axis.

This mechanism that results in higher cortisol responses to stress has potential psychopathological effects as well, since central hyperactivity of the HPA axis (i.e., increased CRH secretion) is associated with depression and mood disorders. Some of the most prominent theories on depression suggest that it is the central effect of CRH that is associated with depressive symptomatology and mood dysfunction, through the effects of CRH in core limbic structures related to mood and anxiety, for example, the amygdala and the prefrontal cortex (Binder & Nemeroff, 2010 ; Hauger et al., 2009 ; Nemeroff, 1996 , 1998 ). This is in line with the proposed neuroanatomical mechanisms to explain the compensatory effect between the HPA axis and ANS as well. First, there is the possibility of an increase in epinephrine production due to propranolol’s blocking noradrenergic binding to beta 2-adrenergic receptors. Epinephrine could then in turn increase CRH release from the hypothalamus, with subsequent increase in cortisol (Viru et al., 2007 )—this represents a central mechanism. Second, there is also the possibility of a direct inhibitory effect of SNS activation on the adrenal cortex. In cases where the SNS system is inhibited, a disinhibition of the HPA axis could result (Viru et al., 2007 ). This represents a compensatory mechanism at the level of the adrenal cortex. These two mechanisms could further complement each other, making the HPA/SNS interaction more potent. While the exact routes of action still await further empirical confirmation, the available evidence points to a negative interaction between the SNS and HPA after they have been triggered by central nervous system components when threat is detected. Taken together, these preliminary pharmacological manipulations point toward mechanisms by which the wear and tear on the stress systems can lead to cardiovascular disease and metabolic syndrome with aging. Especially when combined with a sedentary lifestyle and physical inactivity, increased food consumption, insulin resistance, abdominal obesity, and hypertension could potentially follow from these effects.

As we have seen over the course of this chapter, how the ANS functions at rest and in response to stressors has important implications for stress-related illness. Although research findings are mixed, evidence suggests that autonomic activity and reactivity may mediate and moderate the effects of stress on health and developmental outcomes. Specifically, for accepted markers of the PSNS like RSA, the evidence consistently points to better health with higher levels of basal activity on this particular variable. A diverse range of psychophysiological models attempt to explain how the ANS contributes to stress-related health outcomes. These models vary in key elements of the ANS, how these elements are measured, and whether lack of or excessive activity/reactivity might be a sign of impaired health or constitute a health risk.

Future Directions

It is challenging to integrate and evaluate psychophysiological models of stress since research findings vary considerably between studies, providing conflicting information about the relationship between ANS function and health outcomes. Mixed research findings could partly arise from the considerable variation in how researchers measure ANS function, and how those measures are interpreted. Developing and consistently implementing a clear set of methodological standards specific for stress research may therefore help resolve inconsistent results. Mixed findings also potentially suggest that relationships between ANS function and health outcomes are moderated by various external factors and internal factors. Some of the psychophysiological models discussed here, such as biological sensitivity to context theory, provide insight into potential factors that moderate the relationship between autonomic function and health.

Future research should continue to determine why the relationship between autonomic function and health outcomes varies. Examining the interplay between the PSNS, SNS, and other stress response systems, such as the HPA axis, will be an important avenue for future research. Autonomic space model, neurovisceral integration theory, polyvagal theory, and the adaptive calibration model all provide testable hypotheses about how the PSNS, SNS, and other stress systems like HPA axis interact with each other to affect health and well-being. Future research should test these hypotheses and expand current models to include new systems such as the enteric nervous system. Novel methodological approaches should also be considered, like the use of innovative statistical methods such as finite mixture modeling to determine how different patterns of activity or reactivity across multiple stress systems are associated with different health and developmental outcomes. Pharmacological manipulation of the stress response systems such as the propanol and dexamethasone experiments discussed earlier could help introduce systematic experimental manipulation into the field, and help researchers better understand the interaction of the various physiological systems at play in health and disease.

Abaied, J. L. ( 2016 ). Skin conductance level reactivity as a moderator of the link between parent depressive symptoms and psychosocial adjustment in emerging adults. Journal of Social and Personal Relationships , 33 (4), 534–556. doi:10.1177/0265407515583170 10.1177/0265407515583170

Google Scholar

Agelink, M. W. , Boz, C. , Ullrich, H. , & Andrich, J. ( 2002 ). Relationship between major depression and heart rate variability. Clinical consequences and implications for antidepressive treatment. Psychiatry Research , 113 , 139–149. doi:10.1016/S0165-1781(02)00225-1 10.1016/S0165-1781(02)00225-1

Ali, N. , & Pruessner, J. C. ( 2012 ). The salivary alpha amylase over cortisol ratio as a marker to assess dysregulations of the stress systems. Physiology & Behavior , 106 (1), 65–72. doi:10.1016/j.physbeh.2011.10.003 10.1016/j.physbeh.2011.10.003

Allegrini, A. G. , Evans, B. E. , de Rooij, S. , Greaves-Lord, K. , & Huizink, A. C. ( 2017 ). Gene × environment contributions to autonomic stress reactivity in youth. Development and Psychopathology , 31 , 1–15. doi:10.1017/S095457941700181X 10.1017/S095457941700181X

Allen, J. , Chambers, A. S. , & Towers, D. N. ( 2007 ). The many metrics of cardiac chronotropy: A pragmatic primer and a brief comparison of metrics. Biological Psychology , 74 (2), 243–262. doi:10.1016/j.biopsycho.2006.08.005 10.1016/j.biopsycho.2006.08.005

Andrews, J. , D’Aguiar, C. , & Pruessner, J. C. ( 2012 ). The combined dexamethasone/TSST paradigm—a new method for psychoneuroendocrinology. PLOS ONE , 7 (6), e38994. doi:10.1371/journal.pone.0038994 10.1371/journal.pone.0038994

Andrews, J. , & Pruessner, J. C. ( 2013 ). The combined propranolol/TSST paradigm—a new method for psychoneuroendocrinology. PLOS ONE , 8 (2), e57567. doi:10.1371/journal.pone.0057567 10.1371/journal.pone.0057567

Appelhans, B. M. , & Luecken, L. J. ( 2006 ). Heart rate variability as an index of regulated emotional responding. Review of General Psychology , 10 (3), 229. doi:10.1037/1089-2680.10.3.229 10.1037/1089-2680.10.3.229

Backs, R. W. ( 1995 ). Going beyond heart rate: Autonomic space and cardiovascular assessment of mental workload. The International Journal of Aviation Psychology , 5 (1), 25–48. doi:10.1207/s15327108ijap0501_3 10.1207/s15327108ijap0501_3

Beauchaine, T. P. , Gatzke-Kopp, L. , & Mead, H. K. ( 2006 ). Polyvagal theory and developmental psychopathology: Emotion dysregulation and conduct problems from preschool to adolescence. Biological Psychology , 74 (2), 174–184. doi:10.1016/j.biopsycho.2005.08.008 10.1016/j.biopsycho.2005.08.008

Beauchaine, T. P. , Gatzke-Kopp, L. , Neuhaus, E. , Chipman, J. , Reid, J. M. , & Webster-Stratton, C. ( 2013 ). Sympathetic- and parasympathetic-linked cardiac function and prediction of externalizing behavior, emotion regulation, and prosocial behavior among preschoolers treated for ADHD. Journal of Consulting and Clinical Psychology , 81 (3), 481. doi:10.1037/a0032302 10.1037/a0032302

Benarroch, E. E. ( 1993 ). The central autonomic network—Functional-organization, dysfunction, and perspective. Mayo Clinic Proceedings , 68 (10), 988–1001. doi:10.1016/j.ijpsycho.2015.08.004 10.1016/j.ijpsycho.2015.08.004

Benedek, M. , & Kaernbach, C. ( 2010 ). A continuous measure of phasic electrodermal activity. Journal of Neuroscience Methods , 190 (1), 80–91. doi:10.1016/j.jneumeth.2010.04.028 10.1016/j.jneumeth.2010.04.028

Benschop, R. J. , Jacobs, R. , Sommer, B. , Schurmeyer, T. H. , Raab, J. R. , Schmidt, R. E. , & Schedlowski, M. ( 1996 ). Modulation of the immunologic response to acute stress in humans by beta-blockade or benzodiazepines. FASEB Journal , 10 (4), 517–524. doi:10.1096/fasebj.10.4.8647351 10.1096/fasebj.10.4.8647351

Berntson, G. G. , & Cacioppo, J. T. ( 2004 ). Heart rate variability: Stress and psychiatric conditions. In M. Malik & A. J. Camm (Eds.), Dynamic electrocardiography . Austin, TX: Futura Publishing.

Google Preview

Berntson, G. G. , Cacioppo, J. T. , Binkley, P. F. , Uchino, B. N. , Quigley, K. S. , & Fieldstone, A. ( 1994 ). Autonomic cardiac control. III. Psychological stress and cardiac response in autonomic space as revealed by pharmacological blockades. Psychophysiology , 31 (6), 599–608. doi:10.1111/j.1469–8986.1994.tb02352.x 10.1111/j.1469–8986.1994.tb02352.x

Berntson, G. G. , Cacioppo, J. T. , & Fieldstone, A. ( 1996 ). Illusions, arithmetic, and the bidirectional modulation of vagal control of the heart. Biological Psychology , 44 (1), 1–17. doi:10.1016/S0301-0511(96)05197-6 10.1016/S0301-0511(96)05197-6

Berntson, G. G. , Cacioppo, J. T. , & Grossman, P. ( 2007 ). Whither vagal tone. Biological Psychology , 74 (2), 295–300. doi:10.1016/j.biopsycho.2006.08.006 10.1016/j.biopsycho.2006.08.006

Berntson, G. G. , Cacioppo, J. T. , & Quigley, K. S. ( 1991 ). Autonomic determinism: The modes of autonomic control, the doctrine of autonomic space, and the laws of autonomic constraint. Psychological Review , 98 (4), 459–487. doi:10.1037/0033-295X.98.4.459 10.1037/0033-295X.98.4.459

Berntson, G. G. , Cacioppo, J. T. , & Quigley, K. S. ( 1993 ). Cardiac psychophysiology and autonomic space in humans: Empirical perspectives and conceptual implications. Psychological Bulletin , 114 (2), 296–322. doi:10.1037/0033-2909.114.2.296 10.1037/0033-2909.114.2.296

Berntson, G. G. , Cacioppo, J. T. , & Quigley, K. S. ( 1994 ). Autonomic cardiac control. I. Estimation and validation from pharmacological blockades. Psychophysiology , 31 (6), 572–585. doi:10.1111/j.1469–8986.1994.tb02350.x 10.1111/j.1469–8986.1994.tb02350.x

Berntson, G. G. , Lozano, D. L. , & Chen, Y. J. ( 2005 ). Filter properties of root mean square successive difference (RMSSD) for heart rate. Psychophysiology , 42 (2), 246–252. doi:10.1111/j.1469–8986.2005.00277.x 10.1111/j.1469–8986.2005.00277.x

Bigger Jr., J. T. , Fleiss, J. L. , Steinman, R. C. , Rolnitzky, L. M. , Kleiger, R. E. , & Rottman, J. N. ( 1992 ). Frequency domain measures of heart period variability and mortality after myocardial infarction. Circulation , 85 (1), 164–171. doi:10.1161/circ.85.1.1728446 10.1161/circ.85.1.1728446

Binder, E. B. , & Nemeroff, C. B. ( 2010 ). The CRF system, stress, depression and anxiety-insights from human genetic studies. Molecular Psychiatry , 15 (6), 574–588. doi:10.1038/mp.2009.141 10.1038/mp.2009.141

Blechert, J. , Michael, T. , Grossman, P. , Lajtman, M. , & Wilhelm, F. H. ( 2007 ). Autonomic and respiratory characteristics of posttraumatic stress disorder and panic disorder. Psychosomatic Medicine , 69 (9), 935–943. doi:10.1097/PSY.0b013e31815a8f6b 10.1097/PSY.0b013e31815a8f6b

Bosch, J. A. , de Geus, E. J. C. , Carroll, D. , Goedhart, A. D. , Anane, L. A. , van Zanten, J. J. , … Edwards, K. M. ( 2009 ). A general enhancement of autonomic and cortisol responses during social evaluative threat. Psychosomatic Medicine , 71 (8), 877–885. doi:10.1097/PSY.0b013e3181baef05 10.1097/PSY.0b013e3181baef05

Bosch, J. A. , de Geus, E. J. C. , Veerman, E. C. I. , Hoogstraten, J. , & Amerongen, A. V. ( 2003 ). Innate secretory immunity in response to laboratory stressors that evoke distinct patterns of cardiac autonomic activity. Psychosomatic Medicine , 65 (2), 245–258. doi:10.1097/01.PSY.0000058376.50240.2D 10.1097/01.PSY.0000058376.50240.2D

Bosch, J. A. , Veerman, E. C. I. , de Geus, E. J. , & Proctor, G. B. ( 2011 ). Alpha-amylase as a reliable and convenient measure of sympathetic activity: Don’t start salivating just yet ! Psychoneuroendocrinology , 36 (4), 449–453. doi:10.1016/j.psyneuen.2010.12.019 10.1016/j.psyneuen.2010.12.019

Boyce, T. W. & Ellis, B. J. ( 2005 ). Biological sensitivity to context: I. An evolutionary-developmental theory of the origins and functions of stress reactivity. Development and Psychopathology , 17 , 271–301. doi:10.1017/S0954579405050145 10.1017/S0954579405050145

Boyce, T. W. , Quas, J. , Alkon, A. , Smider, N. A. , Essex, M. J. , Kupfer, D. J. , & MacArthur Assessment Battery Working Group of the MacArthur Foundation Research Network on Psychopathology and Development. ( 2001 ). Autonomic reactivity and psychopathology in middle childhood. The British Journal of Psychiatry , 179 (2), 144–150. doi:10.1192/bjp.179.2.144 10.1192/bjp.179.2.144

Boycsein, W. ( 2012 ). Electrodermal activity . New York, NY: Springer Science+Business Media.

Brindle, R. C. , Ginty, A. T. & Conklin, S. M. ( 2013 ). Is the association between depression and blunted cardiovascular stress reactions mediated by perceptions of stress? International Journal of Psychophysiology , 90 , 66–72. doi:10.1016/j.ijpsycho.2013.06.003 10.1016/j.ijpsycho.2013.06.003

Brosschot, J. F. , Gerin, W. , & Thayer, J. F. ( 2006 ). The perseverative cognition hypothesis: A review of worry, prolonged stress-related physiological activation, and health. Journal of Psychosomatic Research , 60 (2), 113–124. doi:10.1016/j.jpsychores.2005.06.074 10.1016/j.jpsychores.2005.06.074

Busso, D. S. , McLaughlin, K. A. , & Sheridan, M. A. ( 2017 ). Dimensions of adversity, physiological reactivity, and externalizing psychopathology in adolescence: Deprivation and threat. Psychosomatic Medicine , 79 (2), 162–171. doi:10.1097/PSY.0000000000000369 10.1097/PSY.0000000000000369

Cacioppo, J. T. , Berntson, G. G. , Binkley, P. F. , Quigley, K. S. , Uchino, B. N. , & Fieldstone, A. ( 1994 ). Autonomic cardiac control. II. Noninvasive indices and basal response as revealed by autonomic blockades. Psychophysiology , 31 (6), 586–598. doi:10.1111/j.1469–8986.1994.tb02351.x 10.1111/j.1469–8986.1994.tb02351.x

Calkins, S. D. , Graziano, P. A. , Berdan, L. E. , Keane, S. P. , & Degnan, K. A. ( 2008 ). Predicting cardiac vagal regulation in early childhood from maternal–child relationship quality during toddlerhood. Developmental Psychobiology , 50 (8), 751–766. doi:10.1002/dev.20344 10.1002/dev.20344

Camm, A. J. , Malik, M. , Bigger, J. T. , Breithardt, G. , Cerutti, S. , Cohen, R. J. , Coumel, P. , Fallen, E. L. , Kennedy, H. L. , Kleiger, R. E. , Lombardi, F. , Malliani, A. , Moss, A. J. , Rottman, J. N. , Schmidt, G. , Schwartz, P. J. & … Singer, D. H. ( 1996 ). Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. European Heart Journal , 17 , 354–381. doi:10.1093/oxfordjournals.eurheartj.a014868. 10.1093/oxfordjournals.eurheartj.a014868

Cannon, W. B. ( 1928 ). The mechanism of emotional disturbance of bodily functions. New England Journal of Medicine , 198 , 877–884. doi:10.1056/Nejm192806141981701 10.1056/Nejm192806141981701

Cannon, W. B. ( 1929 ). Organization for physiological homeostasis. Physiological Reviews , 9(3) , 399–431. doi:10.1152/physrev.1929.9.3.399 10.1152/physrev.1929.9.3.399

Cannon, W. B. ( 1939 ). The wisdom of the body . New York, NY: Norton.

Carabotti, M. , Scirocco, A. , Maselli, M. A. , & Severi, C. ( 2015 ). The gut-brain axis: Interactions between enteric microbiota, central and enteric nervous systems. Annals of Gastroenterology , 28 (2), 203–209. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367209/

Cărnuţă, M. , Crişan, L. G. , Vulturar, R. , Opre, A. , & Miu, A. C. ( 2015 ). Emotional non-acceptance links early life stress and blunted cortisol reactivity to social threat. Psychoneuroendocrinology , 51 , 176–187. doi:10.1016/j.psyneuen.2014.09.026 10.1016/j.psyneuen.2014.09.026

Carroll, D. , Ginty, A. T. , Painter, R. C. , Roseboom, T. J. , Phillips, A. C. , & de Rooij, S. R. ( 2012 ). Systolic blood pressure reactions to acute stress are associated with future hypertension status in the Dutch Famine Birth Cohort Study. International Journal of Psychophysiology , 85 (2), 270–273. doi:10.1016/j.ijpsycho.2012.04.001 10.1016/j.ijpsycho.2012.04.001

Chapleau, M. W. , & Sabharwal, R. ( 2011 ). Methods of assessing vagus nerve activity and reflexes. Heart Failure Reviews , 16 (2), 109–127. doi:10.1007/s10741-010-9174-6 10.1007/s10741-010-9174-6

Chatterton, R. T. , Vogelsong, K. M. , Lu, Y. C. , Ellman, A. B. , & Hudgens, G. A. ( 1996 ). Salivary alpha-amylase as a measure of endogenous adrenergic activity. Clinical Physiology , 16 (4), 433–448. doi:10.1111/j.1475-097X.1996.tb00731.x 10.1111/j.1475-097X.1996.tb00731.x

Chrousos, G. P. , & Gold, P. W. ( 1992 ). The concepts of stress and stress system disorders. Overview of physical and behavioral homeostasis. JAMA , 267 (9), 1244–1252. doi:10.1001/jama.1992.03480090092034 10.1001/jama.1992.03480090092034

Chumaeva, N. , Hintsanen, M. , Ravaja, N. , Puttonen, S. , Heponiemi, T. , Pulkki-Raback, L. , … Keltikangas-Jarvinen, L. ( 2009 ). Interactive effect of long-term mental stress and cardiac stress reactivity on carotid intima-media thickness: The Cardiovascular Risk in Young Finns study. Stress , 12 (4), 283–293. doi:10.1080/10253890802372406 10.1080/10253890802372406

Clark, C. , Skowron, E. A. , Giuliano, R. J. , & Fisher, P. A. ( 2016 ). Intersections between cardiac physiology, emotion regulation and interpersonal warmth in preschoolers: Implications for drug abuse prevention from translational neuroscience. Drug and Alcohol Dependence , 163 , S60–S69. doi:10.1016/j.drugalcdep.2016.01.033 10.1016/j.drugalcdep.2016.01.033

Conradt, E. , Beauchaine, T. , Abar, B. , Lagasse, L. , Shankaran, S. , Bada, H. , … Lester, B. ( 2016 ). Early caregiving stress exposure moderates the relation between respiratory sinus arrhythmia reactivity at 1 month and biobehavioral outcomes at age 3. Psychophysiology , 53 (1), 83–96. doi:10.1111/psyp.12569 10.1111/psyp.12569

Cook, E. C. , Chaplin, T. M. , Sinha, R. , Tebes, J. K. , & Mayes, L. C. ( 2012 ). The stress response and adolescents’ adjustment: The impact of child maltreatment. Journal of Youth and Adolescence , 41 (8), 1067–1077. doi:10.1007/s10964-012-9746-y 10.1007/s10964-012-9746-y

Cubała, W. , & Landowski, J. ( 2014 ). Low baseline salivary alpha-amylase in drug-naïve patients with short-illness-duration first episode major depressive disorder. Journal of Affective Disorders , 157 , 14–17. doi:10.1016/j.jad.2013.12.043 10.1016/j.jad.2013.12.043

Cummings, M. E. , El-Sheikh, M. , Kouros, C. D. , & Keller, P. S. ( 2007 ). Children’s skin conductance reactivity as a mechanism of risk in the context of parental depressive symptoms. Journal of Child Psychology and Psychiatry , 48 (5), 436–445. doi:10.1111/j.1469–7610.2006.01713.x 10.1111/j.1469–7610.2006.01713.x

Dale, L. P. , Shaikh, S. K. , Fasciano, L. C. , Watorek, V. D. , Heilman, K. J. , & Porges, S. W. ( 2017 ). College females with maltreatment histories have atypical autonomic regulation and poor psychological wellbeing. Psychological Trauma: Theory, Research, Practice, and Policy , 10 (4), 427–434. doi:10.1037/tra0000342 10.1037/tra0000342

Davis, M. , Suveg, C. , Whitehead, M. , Jones, A. , & Shaffer, A. ( 2016 ). Preschoolers’ psychophysiological responses to mood induction tasks moderate the intergenerational transmission of internalizing problems. Biological Psychology , 117 , 159–169. doi:10.1016/j.biopsycho.2016.03.015 10.1016/j.biopsycho.2016.03.015

Dawson, M. E. , Schell, A. M. , & Filion, D. L. ( 2007 ). The electrodermal system. In J. T. Cacioppo , L. G. Tassinary , & G. G. Berntson, G. G. (Eds.), Handbook of pPsychophysiology (pp. 159–181). Cambridge, UK: Cambridge University Press.

de Kloet, E. R. , van der Vies, J. , & de Wied, D. ( 1974 ). The site of the suppressive action of dexamethasone on pituitary-adrenal activity. Endocrinology , 94 (1), 61–73. doi:10.1210/endo-94-1-61 10.1210/endo-94-1-61

de Kloet, R. , Wallach, G. , & McEwen, B. S. ( 1975 ). Differences in corticosterone and dexamethasone binding to rat brain and pituitary. Endocrinology , 96 (3), 598–609. doi:10.1210/endo-96-3-598 10.1210/endo-96-3-598

Del Giudice, M. , Ellis, B. , & Shirtcliff, E. ( 2011 ). The adaptive calibration model of stress responsivity. Neuroscience & Biobehavioral Reviews , 35 (7), 1562–1592. doi:10.1016/j.neubiorev.2010.11.007 10.1016/j.neubiorev.2010.11.007

Del Giudice, M. , Hinnant, B. J. , Ellis, B. J. , & El-Sheikh, M. ( 2011 ). Adaptive patterns of stress responsivity: A preliminary investigation. Developmental Psychology , 48 (3), 775–790. doi:10.1037/a0026519 10.1037/a0026519

Dickerson, S. S. , & Kemeny, M. E. ( 2004 ). Acute stressors and cortisol responses: a theoretical integration and synthesis of laboratory research. Psychological Bulletin , 130 (3), 355-391. doi:10.1037/0033-2909.130.3.355 10.1037/0033-2909.130.3.355

Dieleman, G. C. , Huizink, A. C. , Tulen, J. , Utens, E. , Creemers, H. E. , van der Ende, J. , & Verhulst, F. C. ( 2015 ). Alterations in HPA-axis and autonomic nervous system functioning in childhood anxiety disorders point to a chronic stress hypothesis. Psychoneuroendocrinology , 51 , 135–150. doi:10.1016/j.psyneuen.2014.09.002 10.1016/j.psyneuen.2014.09.002

Dimsdale, J. E. , & Moss, J. ( 1980 ). Plasma catecholamines in stress and exercise. JAMA , 243 (4), 340–342. doi:10.1001/jama.1980.03300300018017 10.1001/jama.1980.03300300018017

Dutton, D. G. , & Aron, A. P. ( 1974 ). Some evidence for heightened sexual attraction under conditions of high anxiety. Journal of Personality and Social Psychology , 30 (4), 510–517. doi:10.1037/h0037031 10.1037/h0037031

Dvir, Y. , Ford, J. D. , Hill, M. , & Frazier, J. A. ( 2014 ). Childhood maltreatment, emotional dysregulation, and psychiatric comorbidities. Harvard Review of Psychiatry , 22 (3), 149–161. doi:10.1097/HRP.0000000000000014 10.1097/HRP.0000000000000014

Eckberg, D. L. ( 1983 ). Human sinus arrhythmia as an index of vagal cardiac outflow. Journal of Applied Physiology , 54 (4), 961–966. doi:10.1152/jappl.1983.54.4.961 10.1152/jappl.1983.54.4.961

Eickholt, C. , Jungen, C. , Drexel, T. , Alken, F. , Kuklik, P. , Muehlsteff, J. , Makimoto, H. , Hoffmann, B. , Kelm, M. , Ziegler, D. , Kloecker, N. , Willems, S. & … Meyer, C. ( 2018 ). Sympathetic and parasympathetic coactivation induces perturbed heart rate dynamics in patients with paroxysmal atrial fibrillation. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research , 24 , 2164–2172. doi:10.12659/MSM.905209 10.12659/MSM.905209

El-Sheikh, M. , Harger, J. , & Whitson, S. M. ( 2001 ). Exposure to interparental conflict and children’s adjustment and physical health: The moderating role of vagal tone. Child Development , 72(6), 1617–1636. doi:10.1111/1467-8624.00369 10.1111/1467-8624.00369

El-Sheikh, M. , Keller, P. S. , & Erath, S. A. ( 2007 ). Marital conflict and risk for child maladjustment over time: Skin conductance level reactivity as a vulnerability factor. Journal of Abnormal Child Psychology , 35 (5), 715–727. doi:10.1007/s10802-007-9127-2 10.1007/s10802-007-9127-2

El-Sheikh, M. , Kouros, C. D. , Erath, S. , Cummings, E. M. , Keller, P. , Staton, L. , … Collins, W. A. ( 2009 ). Marital conflict and children’s externalizing behavior: Interactions between parasympathetic and sympathetic nervous system activity. Monographs of the Society for Research in Child Development , 74 (1), vii–79. doi:10.1111/j.1540–5834.2009.00501.x 10.1111/j.1540–5834.2009.00501.x

Elliott, W. J. ( 2007 ). Systemic hypertension. Current Problems in Cardiology , 32 (4), 201–259. doi:10.1016/j.cpcardiol.2007.01.002 10.1016/j.cpcardiol.2007.01.002

Ellis, B. J. , & Boyce, T. W. ( 2008 ). Biological sensitivity to context. Current Directions in Psychological Science , 17 (3), 183–187. doi:10.1111/j.1467–8721.2008.00571.x 10.1111/j.1467–8721.2008.00571.x

Ellis, B. J. , Essex, M. J. , & Boyce, W. T. ( 2005 ). Biological sensitivity to context: II. Empirical explorations of an evolutionary developmental theory. Development and Psychopathology , 17 (2), 303–328. doi:10.1017/S0954579405050157 10.1017/S0954579405050157

Ellis, B. J. , Oldehinkel, A. J. , & Nederhof, E. ( 2016 ). The adaptive calibration model of stress responsivity: An empirical test in the Tracking Adolescents and Individual Lives Survey study. Development and Psychopathology , 29 (3), 1–21. doi:10.1017/S0954579416000985 10.1017/S0954579416000985

Engert, V. , Vogel, S. , Efanov, S. I. , Duchesne, A. , Corbo, V. , Ali, N. , & Pruessner, J. C. ( 2011 ). Investigation into the cross-correlation of salivary cortisol and alpha-amylase responses to psychological stress. Psychoneuroendocrinology , 36 (9), 1294–1302. doi:10.1016/j.psyneuen.2011.02.018 10.1016/j.psyneuen.2011.02.018

Esposito, E. A. , Koss, K. J. , Donzella, B. , & Gunnar, M. R. ( 2016 ). Early deprivation and autonomic nervous system functioning in post-institutionalized children. Developmental Psychobiology , 58 (3), 328–340. doi:10.1002/dev.21373 10.1002/dev.21373

Everson, S. A. , Lynch, J. W. , Kaplan, G. A. , Lakka, T. A. , Sivenius, J. , & Salonen, J. T. ( 2001 ). Stress-induced blood pressure reactivity and incident stroke in middle-aged men. Stroke , 32 (6), 1263–1270. https://www.ncbi.nlm.nih.gov/pubmed/11387485

Faraco, G. , & Iadecola, C. ( 2013 ). Hypertension : A harbinger of stroke and dementia. Hypertension , 62 (5), 810–817. doi:10.1161/HYPERTENSIONAHA.113.01063 10.1161/HYPERTENSIONAHA.113.01063

Felitti, V. J. , Anda, R. F. , Nordenberg, D. , Williamson, D. F. , Spitz, A. M. , Edwards, V. , … Marks, J. S. ( 1998 ). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. American Journal of Preventative Medicine , 14 (4), 245–258. doi:10.1016/S0749-3797(98)00017-8 10.1016/S0749-3797(98)00017-8

Flaa, A. , Eide, I. K. , Kjeldsen, S. E. , & Rostrup, M. ( 2008 ). Sympathoadrenal stress reactivity is a predictor of future blood pressure: An 18-year follow-up study. Hypertension , 52 (2), 336–341. doi:10.1161/Hypertensionaha.108.111625 10.1161/Hypertensionaha.108.111625

Fries, E. , Hesse, J. , Hellhammer, J. , & Hellhammer, D. H. ( 2005 ). A new view on hypocortisolism. Psychoneuroendocrinology , 30 (10), 1010–1016. doi:10.1016/j.psyneuen.2005.04.006 10.1016/j.psyneuen.2005.04.006

Furness, J. B. , Callaghan, B. P. , Rivera, L. R. , & Cho, H. J. ( 2014 ). The enteric nervous system and gastrointestinal innervation: Integrated local and central control. Advances in Experimental Medicine and Biology , 817 , 39–71. doi:10.1007/978-1-4939-0897-4_3 10.1007/978-1-4939-0897-4_3

Geisler, F. , Kubiak, T. , Siewert, K. , & Weber, H. ( 2013 ). Cardiac vagal tone is associated with social engagement and self-regulation. Biological Psychology , 93 (2), 279–286. doi:10.1016/j.biopsycho.2013.02.013 10.1016/j.biopsycho.2013.02.013

Gellhorn, E. , Cortell, R. , & Feldman, J. ( 1940 ). The autonomic basis of emotion. Science , 92 , 288–289. doi:10.1126/science.92.2387.288 10.1126/science.92.2387.288

Gianaros, P. J. , Bleil, M. E. , Muldoon, M. F. , Jennings, R. J. , Sutton-Tyrrell, K. , McCaffery, J. M. , & Manuck, S. B. ( 2002 ). Is cardiovascular reactivity associated with atherosclerosis among hypertensives? Hypertension , 40 (5), 742–747. doi:10.1161/01.HYP.0000035707.57492.EB 10.1161/01.HYP.0000035707.57492.EB

Gianaros, P. J. , Salomon, K. , Zhou, F. , Owens, J. F. , Edmundowicz, D. , Kuller, L. H. , & Matthews, K. A. ( 2005 ). A greater reduction in high-frequency heart rate variability to a psychological stressor is associated with subclinical coronary and aortic calcification in postmenopausal women. Psychosomatic Medicine , 67 (4), 553–560. doi:10.1097/01.psy.0000170335.92770.7a 10.1097/01.psy.0000170335.92770.7a

Ginty, A. T. , Kraynak, T. E. , Fisher, J. P. , & Gianaros, P. J. ( 2017 ). Cardiovascular and autonomic reactivity to psychological stress: Neurophysiological substrates and links to cardiovascular disease. Autonomic Neuroscience , 207 , 2–9. doi:10.1016/j.autneu.2017.03.003 10.1016/j.autneu.2017.03.003

Giuliano, R. J. , Gatzke-Kopp, L. M. , Roos, L. E. , & Skowron, E. A. ( 2017 ). Resting sympathetic arousal moderates the association between parasympathetic reactivity and working memory performance in adults reporting high levels of life stress. Psychophysiology , 54 (8), 1195–1208. doi:10.1111/psyp.12872 10.1111/psyp.12872

Giuliano, R. J. , Roos, L. E. , Farrar, J. D. , & Skowron, E. A. ( 2018 ). Cumulative risk exposure moderates the association between parasympathetic reactivity and inhibitory control in preschool-age children. Developmental Psychobiology , 60 (3), 324–332. doi:10.1002/dev.21608 10.1002/dev.21608

Goldstein, D. S. , & Kopin, I. J. ( 2008 ). Adrenomedullary, adrenocortical, and sympathoneural responses to stressors: A meta-analysis. Endocrine Regulations , 42 (4), 111–119. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/18999898

Gordis, E. B. , Feres, N. , Olezeski, C. L. , Rabkin, A. N. , & Trickett, P. K. ( 2010 ). Skin conductance reactivity and respiratory sinus arrhythmia Among maltreated and comparison youth: Relations with aggressive behavior. Journal of Pediatric Psychology , 35 (5), 547–558. doi:10.1093/jpepsy/jsp113 10.1093/jpepsy/jsp113

Gray, S. A. O. , Theall, K. , Lipschutz, R. , & Drury, S. ( 2017 ). Sex differences in the contribution of respiratory sinus arrhythmia and trauma to children’s psychopathology. Journal of Psychopathology and Behavioral Assessment , 39 (1), 67–78. doi:10.1007/s10862-016-9568-4 10.1007/s10862-016-9568-4

Greenwood, J. P. , Stoker, J. B. , & Mary, D. A. ( 1999 ). Single-unit sympathetic discharge: Quantitative assessment in human hypertensive disease. Circulation , 100 (12), 1305–1310. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/10491375

Grossman, P. , & Taylor, E. W. ( 2007 ). Toward understanding respiratory sinus arrhythmia: Relations to cardiac vagal tone, evolution and biobehavioral functions. Biological Psychology , 74 (2), 263–285. doi:10.1016/j.biopsycho.2005.11.014 10.1016/j.biopsycho.2005.11.014

Grossman, P. , Watkins, L. L. , Wilhelm, F. H. , Manolakis, D. , & Lown, B. ( 1996 ). Cardiac vagal control and dynamic responses to psychological stress among patients with coronary artery disease. The American Journal of Cardiology , 78 (12), 1424–1427. doi:10.1016/S0002-9149(97)89295-8 10.1016/S0002-9149(97)89295-8

Hamilton, J. L. , & Alloy, L. B. ( 2016 ). Atypical reactivity of heart rate variability to stress and depression across development: Systematic review of the literature and directions for future research. Clinical Psychology Review , 50 , 67–79. doi:10.1016/j.cpr.2016.09.003 10.1016/j.cpr.2016.09.003

Hare, D. L. , Toukhsati, S. R. , Johansson, P. , & Jaarsma, T. ( 2014 ). Depression and cardiovascular disease: A clinical review. European Heart Journal , 35 (21), 1365–1372. doi:10.1093/eurheartj/eht462 10.1093/eurheartj/eht462

Hauger, R. L. , Risbrough, V. , Oakley, R. H. , Olivares-Reyes, J. A. , & Dautzenberg, F. M. ( 2009 ). Role of CRF receptor signaling in stress vulnerability, anxiety, and depression. Annals of the New York Academy of Sciences , 1179 , 120–143. doi:10.1111/j.1749–6632.2009.05011.x 10.1111/j.1749–6632.2009.05011.x

Hastings, P. D. , Nuselovici, J. N. , Utendale, W. T. , Coutya, J. , McShane, K. E. , & Sullivan, C. ( 2008 ). Applying the polyvagal theory to children’s emotion regulation: Social context, socialization, and adjustment. Biological Psychology , 79 (3), 299–306. doi:10.1016/j.biopsycho.2008.07.005 10.1016/j.biopsycho.2008.07.005

Heatherton, T. F. ( 2011 ). Neuroscience of self and self-regulation. Annual Review of Psychology , 62 , 363–390. doi:10.1146/annurev.psych.121208.131616 10.1146/annurev.psych.121208.131616

Heim, C. , Newport, J. D. , Heit, S. , Graham, Y. P. , Wilcox, M. , Bonsall, R. , … Nemeroff, C. B. ( 2000 ). Pituitary-adrenal and autonomic responses to stress in women after sexual and physical abuse in childhood. JAMA , 284 (5), 592–597. doi:10.1001/jama.284.5.592 10.1001/jama.284.5.592

Hellhammer, D. , Meinlschmidt, G. , Pruessner, J. C. ( 2018 ). Conceptual endophenotypes: A strategy to advance the impact of psychoneuroendocrinology in precision medicine. Psychoneuroendocrinology , 89 , 147–160. doi:10.1016/j.psyneuen.2017.12.009. 10.1016/j.psyneuen.2017.12.009

Heponiemi, T. , Elovainio, M. , Pulkki, L. , Puttonen, S. , Raitakari, O. , & Keltikangas-Jarvinen, L. ( 2007 ). Cardiac autonomic reactivity and recovery in predicting carotid atherosclerosis: The cardiovascular risk in young Finns study. Health Psychology , 26 (1), 13–21. doi:10.1037/0278-6133.26.1.13 10.1037/0278-6133.26.1.13

Het, S. , Vocks, S. , Wolf, J. M. , Hammelstein, P. , Herpertz, S. , & Wolf, O. T. ( 2015 ). Blunted neuroendocrine stress reactivity in young women with eating disorders. Journal of Psychosomatic Research , 78 (3), 260–267. doi:10.1016/j.jpsychores.2014.11.001 10.1016/j.jpsychores.2014.11.001

Hinnant, B. J. , Erath, S. A. , & El-Sheikh, M. ( 2015 ). Harsh parenting, parasympathetic activity, and development of delinquency and substance use. Journal of Abnormal Psychology , 124 (1), 137–151. doi:10.1037/abn0000026 10.1037/abn0000026

Hoehn-Saric, R. , McLeod, D. R. , & Zimmerli, W. D. ( 1989 ). Somatic manifestations in women with generalized anxiety disorder. Psychophysiological responses to psychological stress. Archives of General Psychiatry , 46 (12), 1113–1119. doi:10.1001/archpsyc.1989.01810120055009 10.1001/archpsyc.1989.01810120055009

Holterman, L. , Murray-Close, D. K. , & Breslend, N. L. ( 2016 ). Relational victimization and depressive symptoms: The role of autonomic nervous system reactivity in emerging adults. International Journal of Psychophysiology , 110 , 119–127. doi:10.1016/j.ijpsycho.2016.11.003 10.1016/j.ijpsycho.2016.11.003

Holzman, J. B. , & Bridgett, D. J. ( 2017 ). Heart rate variability indices as bio-markers of top-down self-regulatory mechanisms: A meta-analytic review. Neuroscience & Biobehavioral Reviews , 74 , 233–255. doi:10.1016/j.neubiorev.2016.12.032 10.1016/j.neubiorev.2016.12.032

Houtveen, J. H. , Groot, P. F. C. , & De Geus, E. J. C. ( 2005 ). Effects of variation in posture and respiration on RSA and pre-ejection period. Psychophysiology , 42 (6), 713–719. doi:10.3109/13651501.2010.500737 10.3109/13651501.2010.500737

Hu, M. X. , Lamers, F. , Hiles, S. A. , Penninx, B. , & de Geus, E. ( 2016 ). Basal autonomic activity, stress reactivity, and increases in metabolic syndrome components over time. Psychoneuroendocrinology , 71 , 119–126. doi:10.1016/j.psyneuen.2016.05.018 10.1016/j.psyneuen.2016.05.018

Huikuri, H. V. , Makikallio, T. , Airaksinen, K. E. , Mitrani, R. , Castellanos, A. , & Myerburg, R. J. ( 1999 ). Measurement of heart rate variability: A clinical tool or a research toy? Journal of the American College of Cardiology , 34 (7), 1878–1883. doi:10.1016/S0735-1097(99)00468-4 10.1016/S0735-1097(99)00468-4

Ingram, R. E. , & Luxton, D. D. ( 2005 ). Vulnerability-stress models. In B. L. Hankin & J. R. Z. Abela (Eds.), Development of psychopathology: A vulnerability-stress perspective (pp. 32–46). Thousand Oaks, CA: Sage.

Ishitobi, Y. , Akiyoshi, J. , Tanaka, Y. , Ando, T. , Okamoto, S. , Kanehisa, M. , Kohno, K. , Ninomiya, T. , Maruyama, Y. , Tsuru, J. , Kawano, A. , Hanada, H. , Isogawa, K. & … Kodama, K. ( 2010 ). Elevated salivary α-amylase and cortisol levels in unremitted and remitted depressed patients. International Journal of Psychiatry in Clinical Practice , 14 , 268–273. doi:10.3109/13651501.2010.500737 10.3109/13651501.2010.500737

Iwata, J. , & LeDoux, J. E. ( 1988 ). Dissociation of associative and nonassociative concomitants of classical fear conditioning in the freely behaving rat. Behavioral Neuroscience , 102 (1), 66–76. doi:10.1037/0735-7044.102.1.66 10.1037/0735-7044.102.1.66

Jackson, J. H. ( 1958 ). Evolution and dissolution of the nervous system. In J. Taylor (Ed.), Selected writings of John Hughlings Jackson (pp. 45–118). London, UK: Stapes Press.

Juster, R. P. , Perna, A. , Marin, M. F. , Sindi, S. , & Lupien, S. J. ( 2012 ). Timing is everything: Anticipatory stress dynamics among cortisol and blood pressure reactivity and recovery in healthy adults. Stress , 15 (6), 569–577. doi:10.3109/10253890.2012.661494 10.3109/10253890.2012.661494

Kamen, P. W. , Krum, H. , & Tonkin, A. M. ( 1996 ). Poincare plot of heart rate variability allows quantitative display of parasympathetic nervous activity in humans. Clinical Science , 91 (2), 201–208. doi:10.1042/cs0910201 10.1042/cs0910201

Kamen, P. W. , & Tonkin, A. M. ( 1995 ). Application of the Poincare plot to heart-rate-variability—A new measure of functional status in heart-failure. Australian and New Zealand Journal of Medicine , 25 (1), 18–26. doi:10.1111/j.1445–5994.1995.tb00573.x 10.1111/j.1445–5994.1995.tb00573.x

Kibler, J. L. , & Ma, M. ( 2004 ). Depressive symptoms and cardiovascular reactivity to laboratory behavioral stress. International Journal of Behavioral Medicine , 11 (2), 81–87. doi:10.1207/s15327558ijbm1102_3 10.1207/s15327558ijbm1102_3

Kirschbaum, C. , Pirke, K. M. , & Hellhammer, D. H. ( 1993 ). The Trier Social Stress Test—A tool for investigating psychobiological stress responses in a laboratory setting. Neuropsychobiology , 28(1–2) , 76–81. doi:10.1159/000119004 10.1159/000119004

Kizildere, S. , Gluck, T. , Zietz, B. , Scholmerich, J. , & Straub, R. H. ( 2003 ). During a corticotropin-releasing hormone test in healthy subjects, administration of a beta-adrenergic antagonist induced secretion of cortisol and dehydroepiandrosterone sulfate and inhibited secretion of ACTH. European Journal of Endocrinology , 148 (1), 45–53. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/12534357

Koizumi, K. , Terui, N. , Kollai, M. , & Brooks, C. M. ( 1982 ). Functional significance of coactivation of vagal and sympathetic cardiac nerves. Proceedings of the National Academy of Sciences , 79 (6), 2116–2120. doi:10.1073/pnas.79.6.2116 10.1073/pnas.79.6.2116

Kolacz, J. , Holochwost, S. J. , Gariépy, J. , & Mills-Koonce, R. W. ( 2016 ). Patterns of joint parasympathetic, sympathetic, and adrenocortical activity and their associations with temperament in early childhood. Developmental Psychobiology , 58 (8), 990–1001. doi:10.1002/dev.21429 10.1002/dev.21429

Kollai, M. , & Koizumi, K. ( 1979 ). Reciprocal and non-reciprocal action of the vagal and sympathetic nerves innervating the heart. Journal of the Autonomic Nervous System , 1 (1), 33–52. doi:10.1016/0165-1838(79)90004-3 10.1016/0165-1838(79)90004-3

Koo-Loeb, J. H. , Pedersen, C. , & Girdler, S. S. ( 1998 ). Blunted cardiovascular and catecholamine stress reactivity in women with bulimia nervosa. Psychiatry Research , 80 (1), 13–27. doi:10.1016/S0165-1781(98)00057-2 10.1016/S0165-1781(98)00057-2

Kuras, Y. I. , McInnis, C. M. , Thoma, M. V. , Chen, X. , Hanlin, L. , Gianferante, D. , & Rohleder, N. ( 2017 ). Increased alpha-amylase response to an acute psychosocial stress challenge in healthy adults with childhood adversity. Developmental Psychobiology , 59 (1), 91–98. doi:10.1002/dev.21470 10.1002/dev.21470

Lambert, E. , Dawood, T. , Straznicky, N. , Sari, C. , Schlaich, M. , Esler, M. , & Lambert, G. ( 2010 ). Association between the sympathetic firing pattern and anxiety level in patients with the metabolic syndrome and elevated blood pressure. Journal of Hypertension , 28 (3), 543–550. doi:10.1097/HJH.0b013e3283350ea4 10.1097/HJH.0b013e3283350ea4

Langley, J. N. ( 1921 ). The autonomic nervous system . Cambridge, UK: Heffler & Sons.

Lazarus, R. S. , & Folkman, S. ( 1984 ). Stress, appraisal, and coping . New York, NY: Springer.

Lewis, G. F. , Furman, S. A. , McCool, M. F. , & Porges, S. W. ( 2012 ). Statistical strategies to quantify respiratory sinus arrhythmia: Are commonly used metrics equivalent? Biological Psychology , 89 (2), 349–362. doi:10.1016/j.biopsycho.2011.11.009 10.1016/j.biopsycho.2011.11.009

Light, K. C. , Kothandapani, R. V. , & Allen, M. T. ( 1998 ). Enhanced cardiovascular and catecholamine responses in women with depressive symptoms. International Journal of Psychophysiology , 28 (2), 157–166. doi:10.1016/S0167-8760(97)00093-7 10.1016/S0167-8760(97)00093-7

Lorber, M. F. , Erlanger, A. C. , & Slep, A. M. ( 2013 ). Biological sensitivity to context in couples: Why partner aggression hurts some more than others. Journal of Consulting and Clinical Psychology , 81 (1), 166–176. doi:10.1037/a0030973 10.1037/a0030973

Lucas-Thompson, R. G. , & Granger, D. A. ( 2014 ). Parent–child relationship quality moderates the link between marital conflict and adolescents’ physiological responses to social evaluative threat. Journal of Family Psychology , 28 (4), 538–548. doi:10.1037/a0037328 10.1037/a0037328

Maheu, F. S. , Joober, R. , & Lupien, S. J. ( 2005 ). Declarative memory after stress in humans: differential involvement of the beta-adrenergic and corticosteroid systems. The Journal of Clinical Endocrinology & Metabolism, 90(3), 1697–1704. doi:10.1210/jc.2004–0009 10.1210/jc.2004–0009

Marcovitch, S. , Leigh, J. , Calkins, S. D. , Leerks, E. M. , O’Brien, M. , & Blankson, N. A. ( 2010 ). Moderate vagal withdrawal in 3.5-year-old children is associated with optimal performance on executive function tasks. Developmental Psychobiology , 52 (6), 603–608. doi:10.1002/dev.20462 10.1002/dev.20462

Mastorakos, G. , Pavlatou, M. , Diamanti-Kandarakis, E. , & Chrousos, G. P. ( 2005 ). Exercise and the stress system. Hormones (Athens) , 4 (2), 73–89. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/16613809

Mason, J.W. ( 1968 ). The scope of psychoendocrine research. Psychosomatic Medicine, 30(5), 565-575.

McEwen, B. S. ( 1998 ). Stress, adaptation, and disease. Allostasis and allostatic load. Annals of the New York Academy of Sciences , 840 , 33–44. doi:10.1111/j.1749–6632.1998.tb09546.x 10.1111/j.1749–6632.1998.tb09546.x

McEwen, B. S. ( 2002 ). Sex, stress and the hippocampus: allostasis, allostatic load and the aging process. Neurobiology of Aging , 23 (5), 921–939. doi:10.1016/S0197-4580(02)00027-1 10.1016/S0197-4580(02)00027-1

McFall, M. E. , Murburg, M. M. , Ko, G. N. , & Veith, R. C. ( 1990 ). Autonomic responses to stress in Vietnam combat veterans with posttraumatic-stress-disorder. Biological Psychiatry , 27 (10), 1165–1175. doi:10.1016/0006-3223(90)90053-5 10.1016/0006-3223(90)90053-5

McGirr, A. , Diaconu, G. , Berlim, M. T. , Pruessner, J. C. , Sablé, R. , Cabot, S. , & Turecki, G. ( 2010 ). Dysregulation of the sympathetic nervous system, hypothalamic–pituitary–adrenal axis and executive function in individuals at risk for suicide. Journal of Psychiatry & Neuroscience , 35 (6), 399–408.

McKeever, V. M. , & Huff, M. E. ( 2003 ). A diathesis-stress model of posttraumatic stress disorder: Ecological, biological, and residual stress pathways. Review of General Psychology , 7 (3), 237–250.

McLaughlin, K. A. , Alves, S. , & Sheridan, M. A. ( 2014 ). Vagal regulation and internalizing psychopathology among adolescents exposed to childhood adversity. Developmental Psychobiology , 56 (5), 1036–1051. doi:10.1002/dev.21187 10.1002/dev.21187

McLaughlin, K. A. , Sheridan, M. A. , Alves, S. , & Mendes, W. ( 2014 ). Child maltreatment and autonomic nervous system reactivity: Identifying dysregulated stress reactivity patterns by using the biopsychosocial model of challenge and threat. Psychosomatic Medicine , 76 (7), 538–546. doi:10.1097/PSY.0000000000000098 10.1097/PSY.0000000000000098

McLaughlin, K. A. , Sheridan, M. A. , Tibu, F. , Fox, N. A. , Zeanah, C. H. , & Nelson, C. A. ( 2015 ). Causal effects of the early caregiving environment on development of stress response systems in children. Proceedings of the National Academy of Sciences , 112 (18), 5637–5642. doi:10.1073/pnas.1423363112 10.1073/pnas.1423363112

Meehl, P. E. ( 1962 ). Schizotaxia, schizotypy, schizophrenia. American Psychologist , 17 , 827–838 Schizophrenia (pp. 21–46). Abingdon, UK: Routledge . doi:10.1037/h0041029 10.1037/h0041029

Messerli-Burgy, N. , Engesser, C. , Lemmenmeier, E. , Steptoe, A. , & Laederach-Hofmann, K. ( 2010 ). Cardiovascular stress reactivity and recovery in bulimia nervosa and binge eating disorder. International Journal of Psychophysiology , 78 (2), 163–168. doi:10.1016/j.ijpsycho.2010.07.005 10.1016/j.ijpsycho.2010.07.005

Mielock, A. S. , Morris, M. C. , & Rao, U. ( 2017 ). Patterns of cortisol and alpha-amylase reactivity to psychosocial stress in maltreated women. Journal of Affective Disorders , 209 , 46–52. doi:10.1016/j.jad.2016.11.009 10.1016/j.jad.2016.11.009

Miller, J. G. , Kahle, S. , Lopez, M. , & Hastings, P. D. ( 2015 ). Compassionate love buffers stress-reactive mothers from fight-or-flight parenting. Developmental Psychology , 51 (1), 36–43. doi:10.1037/a0038236 10.1037/a0038236

Mills, P. J. , & Dimsdale, J. E. ( 1992 ). Sympathetic nervous system responses to psychosocial stressors. In T. J. R. Turner , A. Sherwood , & K. C. Light (Eds.), Individual differences in cCardiovascular rResponse to sStress . New York, NY: Plenum Press.

Monroe, S. M. , & Hadjiyannakis, H. ( 2002 ). The social environment and depression: Focusing on severe life stress. In I. H. Gotlib & C. L. Hammen (Eds.), Handbook of depression (pp. 314–340). New York, NY: Guilford Press.

Monroe, S. M. , & Simons, A. D. ( 1991 ). Diathesis-stress theories in the context of life-stress research: Implications for the depressive disorders. Psychological Bulletin , 110 , 406–425.

Nagy, T. , van Lien, R. , Willemsen, G. , Proctor, G. , Efting, M. , Fulop, M. , … Bosch, J. A. ( 2015 ). A fluid response: Alpha-amylase reactions to acute laboratory stress are related to sample timing and saliva flow rate. Biological Psychology , 109 , 111–119. doi:10.1016/j.biopsycho.2015.04.012 10.1016/j.biopsycho.2015.04.012

Nater, U. M. , La Marca, R. , Florin, L. , Moses, A. , Langhans, W. , Koller, M. M. , & Ehlert, U. ( 2006 ). Stress-induced changes in human salivary alpha-amylase activity: Associations with adrenergic activity. Psychoneuroendocrinology , 31 (1), 49–58. doi:10.1016/j.psyneuen.2005.05.010 10.1016/j.psyneuen.2005.05.010

Nater, U. M. , & Rohleder, N. ( 2009 ). Salivary alpha-amylase as a non-invasive biomarker for the sympathetic nervous system: Current state of research. Psychoneuroendocrinology , 34 (4), 486–496. doi:10.1016/j.psyneuen.2009.01.014 10.1016/j.psyneuen.2009.01.014

Nemeroff, C. B. ( 1996 ). The corticotropin-releasing factor (CRF) hypothesis of depression: New findings and new directions. Molecular Psychiatry , 1 (4), 336–342. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/9118360

Nemeroff, C. B. ( 1998 ). Psychopharmacology of affective disorders in the 21st century. Biological Psychiatry , 44 (7), 517–525. doi:10.1016/S0006-3223(98)00068-7 10.1016/S0006-3223(98)00068-7

Newlin, D. B. , & Levenson, R. W. ( 1979 ). Pre-ejection period: Measuring beta-adrenergic influences upon the heart. Psychophysiology , 16 (6), 546–552. doi:10.1111/j.1469–8986.1979.tb01519.x 10.1111/j.1469–8986.1979.tb01519.x

Obradovic, J. , Bush, N. R. , Stamperdahl, J. , Adler, N. E. , & Boyce, W. T. ( 2010 ). Biological sensitivity to context: The interactive effects of stress reactivity and family adversity on socioemotional behavior and school readiness. Child Development , 81 (1), 270–289. doi:10.1111/j.1467–8624.2009.01394.x 10.1111/j.1467–8624.2009.01394.x

Obrist, P. A. , Wood, D. M. , & Perez-Reyes, M. ( 1965 ). Heart rate during conditioning in humans: Effects of UCS intensity, vagal blockade, and adrenergic block of vasomotor activity. Journal of Experimental Psychology , 70 (1), 32–42. doi:10.1037/h0022033 10.1037/h0022033

Odemuyiwa, O. , Malik, M. , Farrell, T. , Bashir, Y. , Poloniecki, J. , & Camm, J. ( 1991 ). Comparison of the predictive characteristics of heart rate variability index and left ventricular ejection fraction for all-cause mortality, arrhythmic events and sudden death after acute myocardial infarction. American Journal of Cardiology , 68 (5), 434–439. doi:10.1016/0002-9149(91)90774-F 10.1016/0002-9149(91)90774-F

Odutayo, A. , Wong, C. X. , Hsiao, A. J. , Hopewell, S. , Altman, D. G. , & Emdin, C. A. ( 2016 ). Atrial fibrillation and risks of cardiovascular disease, renal disease, and death: Systematic review and meta-analysis. British Medical Journal , 354 , i4482. doi:10.1136/bmj.i4482 10.1136/bmj.i4482

Oei, N. Y. , Tollenaar, M. S. , Elzinga, B. M. , & Spinhoven, P. ( 2010 ). Propranolol reduces emotional distraction in working memory: A partial mediating role of propranolol-induced cortisol increases? Neurobiology of Learning and Memory , 93 (3), 388–395. doi:10.1016/j.nlm.2009.12.005 10.1016/j.nlm.2009.12.005

Park, G. , Van Bavel, J. J. , Vasey, M. W. , & Thayer, J. F. ( 2013 ). Cardiac vagal tone predicts attentional engagement to and disengagement from fearful faces. Emotion , 13 (4), 645–656. doi:10.1037/a0032971 10.1037/a0032971

Penttila, J. , Helminen, A. , Jartti, T. , Kuusela, T. , Huikuri, H. V. , Tulppo, M. P. , … Scheinin, H. ( 2001 ). Time domain, geometrical and frequency domain analysis of cardiac vagal outflow: Effects of various respiratory patterns. Clinical Physiology , 21 (3), 365–376. doi:10.1046/j.1365–2281.2001.00337.x 10.1046/j.1365–2281.2001.00337.x

Peters, M. L. , Godaert, G. L. , Ballieux, R. E. , van Vliet, M. , Willemsen, J. J. , Sweep, F. C. , & Heijnen, C. J. ( 1998 ). Cardiovascular and endocrine responses to experimental stress: Effects of mental effort and controllability. Psychoneuroendocrinology , 23 (1), 1–17. doi:10.1016/S0306-4530(97)00082-6 10.1016/S0306-4530(97)00082-6

Petrakova, L. , Doering, B. K. , Vits, S. , Engler, H. , Rief, W. , Schedlowski, M. , & Grigoleit, J. S. ( 2015 ). Psychosocial stress increases salivary alpha-amylase activity independently from plasma noradrenaline levels. PLoS One , 10 (8), e0134561. doi:10.1371/journal.pone.0134561 10.1371/journal.pone.0134561

Pine, D. S. , Wasserman, G. , Coplan, J. , Staghezza-Jaramillo, B. , Davies, M. , Fried, J. E. , … Shaffer, D. ( 1996 ). Cardiac profile and disruptive behavior in boys at risk for delinquency. Psychosomatic Medicine , 58 (4), 342–353. doi:10.1097/00006842-199607000-00007 10.1097/00006842-199607000-00007

Pitzalis, M. V. , Mastropasqua, F. , Massari, F. , Forleo, C. , DiMaggio, M. , Passantino, A. , … Rizzon, P. ( 1996 ). Short- and long-term reproducibility of time and frequency domain heart rate variability measurements in normal subjects. Cardiovascular Research , 32 (2), 226–233. doi:10.1016/0008-6363(96)00086-7 10.1016/0008-6363(96)00086-7

Porges, S. W. ( 1995 ). Orienting in a defensive world: Mammalian modifications of our evolutionary heritage: A polyvagal theory. Psychophysiology , 32 (4), 301–318. doi:10.1111/j.1469–8986.1995.tb01213.x 10.1111/j.1469–8986.1995.tb01213.x

Porges, S. W. ( 1997 ). Emotion: An evolutionary by-product of the neural regulation of the autonomic nervous system. Annals of the New York Academy of Sciences , 807 , 62–77. doi:10.1111/j.1749–6632.1997.tb51913.x 10.1111/j.1749–6632.1997.tb51913.x

Porges, S. W. ( 1998 ). Love: An emergent property of the mammalian autonomic nervous system. Psychoneuroendocrinology , 23 (8), 837–861. doi:10.1016/S0306-4530(98)00057-2 10.1016/S0306-4530(98)00057-2

Porges, S. W. ( 2001 ). The polyvagal theory: Phylogenetic substrates of a social nervous system. International Journal of Psychophysiology , 42 (2), 123–146. doi:10.1016/S0167-8760(01)00162-3 10.1016/S0167-8760(01)00162-3

Porges, S. W. ( 2003 ). The polyvagal theory: Phylogenetic contributions to social behavior. Physiology & Behavior , 79 (3), 503–513. doi:10.1016/S0031-9384(03)00156-2 10.1016/S0031-9384(03)00156-2

Porges, S. W. ( 2007 ). The polyvagal perspective. Biological Psychology , 74 (2), 116–143. doi:10.1016/j.biopsycho.2006.06.009 10.1016/j.biopsycho.2006.06.009

Porges, S. W. ( 2009 ). The polyvagal theory: New insights into adaptive reactions of the autonomic nervous system. Cleveland Clinic Journal of Medicine , 76 (Suppl 2), S86–S90. doi:10.3949/ccjm.76.s2.17 10.3949/ccjm.76.s2.17

Post, R. M. ( 1992 ). Transduction of psychosocial stress into the neurobiology of recurrent affective disorder. American Journal of Psychiatry , 149 , 999–1010. doi:10.1176/ajp.149.8.999 10.1176/ajp.149.8.999

Quas, J. , Yim, I. , Oberlander, T. , Nordstokke, D. , Essex, M. , Armstrong, J. , … Boyce, W. ( 2014 ). The symphonic structure of childhood stress reactivity: Patterns of sympathetic, parasympathetic, and adrenocortical responses to psychological challenge. Development and Psychopathology , 26 (4), 963–982. doi:10.1017/S0954579414000480 10.1017/S0954579414000480

Reyes del Paso, G. A. , Langewitz, W. , Mulder, L. J. M. , Van Roon, A. , & Duschek, S. ( 2013 ). The utility of low frequency heart rate variability as an index of sympathetic cardiac tone: A review with emphasis on a reanalysis of previous studies. Psychophysiology , 50 (5), 477–487. doi:10.1111/psyp.12027 10.1111/psyp.12027

Robertson, T. , & Watts, E. ( 2016 ). The importance of age, sex and place in understanding socioeconomic inequalities in allostatic load: Evidence from the Scottish Health Survey (2008-2011). BMC Public Health , 16 , 126. doi:10.1186/s12889-016-2796-4 10.1186/s12889-016-2796-4

Roos, L. E. , Beauchamp, K. G. , Giuliano, R. , Zalewski, M. , Kim, H. K. , & Fisher, P. A. ( 2018 ). Children’s biological responsivity to acute stress predicts concurrent cognitive performance. Stress , 21 (4), 347–354. doi:10.1080/10253890.2018.1458087 10.1080/10253890.2018.1458087

Sabbah, W. , Watt, R. G. , Sheiham, A. , & Tsakos, G. ( 2008 ). Effects of allostatic load on the social gradient in ischaemic heart disease and periodontal disease: Evidence from the Third National Health and Nutrition Examination Survey. Journal of Epidemiology and Community Health , 62 (5), 415–420. doi:10.1136/jech.2007.064188 10.1136/jech.2007.064188

Sakaki, M. , Yoo, H. J. , Nga, L. , Lee, T. H. , Thayer, J. F. , & Mather, M. ( 2016 ). Heart rate variability is associated with amygdala functional connectivity with MPFC across younger and older adults. Neuroimage , 139 , 44–52. doi:10.1016/j.neuroimage.2016.05.076 10.1016/j.neuroimage.2016.05.076

Salomon, K. , Bylsma, L. M. , White, K. E. , Panaite, V. , & Rottenberg, J. ( 2013 ). Is blunted cardiovascular reactivity in depression mood-state dependent? A comparison of major depressive disorder remitted depression and healthy controls. International Journal of Psychophysiology , 90 (1), 50–57. doi:10.1016/j.ijpsycho.2013.05.018 10.1016/j.ijpsycho.2013.05.018

Salomon, K. , Clift, A. , Karlsdottir, M. , & Rottenberg, J. ( 2009 ). Major depressive disorder is associated with attenuated cardiovascular reactivity and impaired recovery among those free of cardiovascular disease. Health Psychology , 28 (2), 157–165. doi:10.1037/a0013001 10.1037/a0013001

Sassi, R. , Cerutti, S. , Lombardi, F. , Malik, M. , Huikuri, H. V. , Peng, C. K. , Schmidt, G. & Yamamoto, Y. ( 2015 ). Advances in heart rate variability signal analysis: Joint position statement by the e-Cardiology ESC Working Group and the European Heart Rhythm Association co-endorsed by the Asia Pacific Heart Rhythm Society. Europace , 17 (9), 1341–1353. doi:10.1093/europace/euv015 10.1093/europace/euv015

Schoorl, J. , Rijn, S. , Wied, M. , Goozen, S. H. M. , & Swaab, H. ( 2016 ). Variability in emotional/behavioral problems in boys with oppositional defiant disorder or conduct disorder: The role of arousal. European Child & Adolescent Psychiatry , 25 (8), 821–830. doi:10.1007/s00787-015-0790-5 10.1007/s00787-015-0790-5

Schwerdtfeger, A. , & Rosenkaimer, A.-K. ( 2011 ). Depressive symptoms and attenuated physiological reactivity to laboratory stressors. Biological Psychology , 87 (3), 430–438. doi:10.1016/j.biopsycho.2011.05.009 10.1016/j.biopsycho.2011.05.009

Seeman, T. E. , McEwen, B. S. , Rowe, J. W. , & Singer, B. H. ( 2001 ). Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging. Proceedings of the National Academy of Sciences , 98 (8), 4770–4775.

Selye, H. ( 1936 ). A syndrome produced by diverse nocuous agents. Nature , 138 , 32.

Selye, H. ( 1970 ). Stress and aging. Journal of the American Geriatrics Society , 18 , 669-680. doi:10.1111/j.1532-5415.1970.tb02813.x 10.1111/j.1532-5415.1970.tb02813.x

Selye, H. ( 1978 ). The stress of life . New York, NY: McGraw-Hill Education.

Shaffer, F. , & Ginsberg, J. P. ( 2017 ). An overview of heart rate variability metrics and norms. Frontiers in Public Health , 5 , 258. doi:10.3389/fpubh.2017.00258 10.3389/fpubh.2017.00258

Sharpley, C. F. ( 2002 ). Heart rate reactivity and variability as psychophysiological links between stress, anxiety, depression, and cardiovascular disease: Implications for health psychology Interventions. Australian Psychologist , 37 (1), 56–62. doi:10.1080/00050060210001706686 10.1080/00050060210001706686

Sherwood, A. , Allen, M. T. , Fahrenberg, J. , Kelsey, R. M. , Lovallo, W. R. , & Vandoornen, L. J. P. ( 1990 ). Methodological guidelines for impedance cardiography. Psychophysiology , 27 (1), 1–23. doi:10.1111/j.1469–8986.1990.tb02171.x 10.1111/j.1469–8986.1990.tb02171.x

Sherwood, A. , Hill, L. K. , Blumenthal, J. A. , Adams, K. F. , Paine, N. J. , Koch, G. G. , … Hinderliter, A. L. ( 2017 ). Blood pressure reactivity to psychological stress is associated with clinical outcomes in patients with heart failure. American Heart Journal , 191 , 82–90. doi:10.1016/j.ahj.2017.07.003 10.1016/j.ahj.2017.07.003

Shields, R. W. ( 1993 ). Functional anatomy of the autonomic nervous system. Journal of Clinical Neurophysiology , 10 (1), 2–13. doi:10.1097/00004691-199301000-00002 10.1097/00004691-199301000-00002

Shinba, T. ( 2014 ). Altered autonomic activity and reactivity in depression revealed by heart-rate variability measurement during rest and task conditions. Psychiatry and Clinical Neurosciences , 68 (3), 225–233. doi:10.1111/pcn.12123 10.1111/pcn.12123

Shonkoff, J. P. , Garner, A. S. , The Committee on Psychosocial Aspects of Child and Family Health, Committee on Early Childhood, Adoption, and Dependent Care & Section on Developmental and Behavioral Pediatrics . ( 2012 ). The lifelong effects of early childhood adversity and toxic stress. Pediatrics , 129 (1), E232–E246. doi:10.1542/peds.2011–2663 10.1542/peds.2011–2663

Sijtsema, J. J. , Roon, A. M. , Groot, P. F. C. , & Riese, H. ( 2015 ). Early life adversities and adolescent antisocial behavior: The role of cardiac autonomic nervous system reactivity in the TRAILS study. Biological Psychology , 110 , 24–33. doi:10.1016/j.biopsycho.2015.06.012 10.1016/j.biopsycho.2015.06.012

Simeckova, M. , Jansky, L. , Lesna, I. I. , Vybiral, S. , & Sramek, P. ( 2000 ). Role of beta adrenoceptors in metabolic and cardiovascular responses of cold exposed humans. Journal of Thermal Biology , 25 (6), 437–442. doi:10.1016/S0306-4565(00)00007-3 10.1016/S0306-4565(00)00007-3

Singh, K. , & Shen, B. J. ( 2013 ). Abdominal obesity and chronic stress interact to predict blunted cardiovascular reactivity. International Journal of Psychophysiology , 90 (1), 73–79. doi:10.1016/j.ijpsycho.2013.03.010 10.1016/j.ijpsycho.2013.03.010

Skowron, E. A. , Loken, E. , Gatzke-Kopp, L. M. , Cipriano-Essel, E. A. , Woehrle, P. L. , Epps, J. J. , Gowda, A. , & Ammerman, R. T. ( 2011 ). Mapping cardiac physiology and parenting processes in maltreating mother–child dyads. Journal of Family Psychology , 25 (5), 663–674. doi:10.1037/a0024528 10.1037/a0024528

Smeijers, L. , Szabó, B. M. , van Dammen, L. , Wonnink, W. , Jakobs, B. S. , Bosch, J. A. , & Kop, W. J. ( 2015 ). Emotional, neurohormonal, and hemodynamic responses to mental stress in Tako-Tsubo cardiomyopathy. The American Journal of Cardiology , 115 (11), 1580–1586. doi:10.1016/j.amjcard.2015.02.064 10.1016/j.amjcard.2015.02.064

Smith, R. , Thayer, J. F. , Khalsa, S. S. , & Lane, R. D. ( 2017 ). The hierarchical basis of neurovisceral integration. Neuroscience & Biobehavioral Reviews , 75 , 274–296. doi:10.1016/j.neubiorev.2017.02.003 10.1016/j.neubiorev.2017.02.003

Snoek, H. , Goozen, S. , Matthy, W. , Buitelaar, J. , & Engeland, H. ( 2004 ). Stress responsivity in children with externalizing behavior disorders. Development and Psychopathology , 16 (2), 389–406. doi:10.1017/S0954579404044578 10.1017/S0954579404044578

Souza, G. G. L. , Mendonça-de-Souza, A. C. F. , Barros, E. M. , Coutinho, E. F. S. , Oliveira, L. , Mendlowicz, M. V. , … Volchan, E. ( 2009 ). Resilience and vagal tone predict cardiac recovery from acute social stress. Stress , 10 (4), 368–374. doi:10.1080/10253890701419886 10.1080/10253890701419886

Stanford, S. C. , Mikhail, G. , Salmon, P. , Gettins, D. , Zielinski, S. , & Pepper, J. R. ( 1997 ). Psychological stress does not affect plasma catecholamines in subjects with cardiovascular disorder. Pharmacology Biochemistry and Behavior , 58 (4), 1167–1174. doi:10.1016/S0091-3057(97)00335-3 10.1016/S0091-3057(97)00335-3

Sterling, P. , & Eyer, J. ( 1988 ). Allostasis: A new paradigm to explain arousal pathology. In S. Fisher & J. Reason (Eds.), Handbook of life stress, cognition and health (pp. 629–649). New York, NY: John Wiley & Sons.

Suess, P. E. , Porges, S. W. , & Plude, D. J. ( 1994 ). Cardiac vagal tone and sustained attention in school-age children. Psychophysiology , 31 (1), 17–22. doi:10.1111/j.1469–8986.1994.tb01020.x 10.1111/j.1469–8986.1994.tb01020.x

Suurland, J. , van der Heijden, K. B. , Huijbregts, S. C. J. , van Goozen, S. H. M. , & Swaab, H. ( 2017 ). Interaction between prenatal risk and infant parasympathetic and sympathetic stress reactivity predicts early aggression. Biological Psychology , 128 , 98–104. doi:10.1016/j.biopsycho.2017.07.005 10.1016/j.biopsycho.2017.07.005

Suurland, J. , van der Heijden, K. B. , Huijbregts, S. C. J. , van Goozen, S. H. M. , & Swaab, H. ( 2018 ). Infant parasympathetic and sympathetic activity during baseline, stress and recovery: Interactions with prenatal adversity predict physical aggression in toddlerhood. Journal of Abnormal Child Psychology , 46 (4), 755–768. doi:10.1007/s10802-017-0337-y 10.1007/s10802-017-0337-y

Suzuki, T. , Nakamura, Y. , Moriya, T. , Sasano, H. ( 2003 ). Effects of steroid hormones on vascular functions. Microscopy research and technique, 60. 76–84.

Tan, A. Y. , Zhou, S. M. , Ogawa, M. , Song, J. , Chu, M. , Li, H. M. , … Chen, P. S. ( 2008 ). Neural mechanisms of paroxysmal atrial fibrillation and paroxysmal atrial tachycardia in ambulatory canines. Circulation , 118 (9), 916–925. doi:10.1161/Circulationaha.108.776203 10.1161/Circulationaha.108.776203

Taylor, C. B. ( 2010 ). Depression, heart rate related variables and cardiovascular disease. International Journal of Psychophysiology , 78 (1), 80–88. doi:10.1016/j.ijpsycho.2010.04.006 10.1016/j.ijpsycho.2010.04.006

Tell, D. , Mathews, H. L. , Burr, R. L. , & Janusek, L. ( 2018 ). During stress, heart rate variability moderates the impact of childhood adversity in women with breast cancer. Stress , 21 (2), 1–9. doi:10.1080/10253890.2018.1424132 10.1080/10253890.2018.1424132

Thayer, J. F. , Åhs, F. , Fredrikson, M. , Sollers, J. J. , & Wager, T. D. ( 2012 ). A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health. Neuroscience & Biobehavioral Reviews , 36 (2), 747–756. doi:10.1016/j.neubiorev.2011.11.009 10.1016/j.neubiorev.2011.11.009

Thayer, J. F. , Hansen, A. L. , Saus-Rose, E. , & Johnsen, B. ( 2009 ). Heart rate variability, prefrontal neural function, and cognitive performance: The neurovisceral integration perspective on self-regulation, adaptation, and health. Annals of Behavioral Medicine , 37 (2), 141–153. doi:10.1007/s12160-009-9101-z 10.1007/s12160-009-9101-z

Thayer, J. F. , & Lane, R. D. ( 2000 ). A model of neurovisceral integration in emotion regulation and dysregulation. Journal of Affective Disorders , 61 (3), 201–216. doi:10.1016/S0165-0327(00)00338-4 10.1016/S0165-0327(00)00338-4

Thayer, J. F. , & Lane, R. D. ( 2007 ). The role of vagal function in the risk for cardiovascular disease and mortality. Biological Psychology , 74 (2), 224–242. doi:10.1016/j.biopsycho.2005.11.013 10.1016/j.biopsycho.2005.11.013

Thayer, J. F. , & Lane, R. D. ( 2009 ). Claude Bernard and the heart–brain connection: Further elaboration of a model of neurovisceral integration. Neuroscience & Biobehavioral Reviews , 33 (2), 81–88. doi:10.1016/j.neubiorev.2008.08.004 10.1016/j.neubiorev.2008.08.004

Thoma, M. V. , Kirschbaum, C. , Wolf, J. M. , & Rohleder, N. ( 2012 ). Acute stress responses in salivary alpha-amylase predict increases of plasma norepinephrine. Biological Psychology , 91 (3), 342–348. doi:10.1016/j.biopsycho.2012.07.008 10.1016/j.biopsycho.2012.07.008

Tulppo, M. P. , Kiviniemi, A. M. , Hautala, A. J. , Kallio, M. , Seppanen, T. , Makikallio, T. H. , & Huikuri, H. V. ( 2005 ). Physiological background of the loss of fractal heart rate dynamics. Circulation , 112 (3), 314–319. doi:10.1161/Circulationaha.104.523712 10.1161/Circulationaha.104.523712

Tulppo, M. P. , Makikallio, T. H. , Takala, T. E. S. , Seppanen, T. , & Huikuri, H. V. ( 1996 ). Quantitative beat-to-beat analysis of heart rate dynamics during exercise. American Journal of Physiology-Heart and Circulatory Physiology , 271 (1), H244–H252. doi:10.1152/ajpheart.1996.271.1.H244 10.1152/ajpheart.1996.271.1.H244

Ulrich-Lai, Y. M. , & Herman, J. P. ( 2009 ). Neural regulation of endocrine and autonomic stress responses. Nature Reviews Neuroscience , 10 (6), 397–409. doi:10.1038/nrn2647 10.1038/nrn2647

van Stegeren, A. , Rohleder, N. , Everaerd, W. , & Wolf, O. T. ( 2006 ). Salivary alpha amylase as marker for adrenergic activity during stress: Effect of betablockade. Psychoneuroendocrinology , 31 (1), 137–141. doi:10.1016/j.psyneuen.2005.05.012 10.1016/j.psyneuen.2005.05.012

Vanitallie, T. B. ( 2002 ). Stress: A risk factor for serious illness. Metabolism-Clinical and Experimental , 51 (6), 40–45. doi:10.1053/meta.2002.33191 10.1053/meta.2002.33191

Viru, A. , Viru, M. , Karelson, K. , Janson, T. , Siim, K. , Fischer, K. , & Hackney, A. C. ( 2007 ). Adrenergic effects on adrenocortical cortisol response to incremental exercise to exhaustion. European Journal of Applied Physiology , 100 (2), 241–245. doi:10.1007/s00421-007-0416-9 10.1007/s00421-007-0416-9

Voellmin, A. , Winzeler, K. , Hug, E. , Wilhelm, F. H. , Schaefer, V. , Gaab, J. , La Marca, R. , Pruessner, J. C. & Bader, K. ( 2015 ). Blunted endocrine and cardiovascular reactivity in young healthy women reporting a history of childhood adversity. Psychoneuroendocrinology , 51 , 58–67. doi:10.1016/j.psyneuen.2014.09.008 10.1016/j.psyneuen.2014.09.008

Wagner, C. R. , & Abaied, J. L. ( 2015 ). Relational victimization and proactive versus reactive relational aggression: The moderating effects of respiratory sinus arrhythmia and skin conductance. Aggressive Behavior , 41 (6), 566–579. doi:10.1002/ab.21596 10.1002/ab.21596

Warner, H. R. , & Cox, A. ( 1962 ). A mathematical model of heart rate control by sympathetic and vagus efferent information. Journal of Applied Physiology , 17 , 349–355. doi:10.1152/jappl.1962.17.2.349 10.1152/jappl.1962.17.2.349

Waters, S. F. , Boyce, T. W. , Eskenazi, B. , & Alkon, A. ( 2016 ). The impact of maternal depression and overcrowded housing on associations between autonomic nervous system reactivity and externalizing behavior problems in vulnerable Latino children. Psychophysiology , 53 (1), 97–104. doi:10.1111/psyp.12539 10.1111/psyp.12539

Wehrwein, E. A. , Orer, H. S. , & Barman, S. M. ( 2016 ). Overview of the anatomy, physiology, and pharmacology of the autonomic nervous system. Comprehensive Physiology , 6 (3), 1239–1278. doi:10.1002/cphy.c150037 10.1002/cphy.c150037

Winzeler, K. , Voellmin, A. , Hug, E. , Kirmse, U. , Helmig, S. , Princip, M. , … Wilhelm, F. H. ( 2016 ). Adverse childhood experiences and autonomic regulation in response to acute stress: the role of the sympathetic and parasympathetic nervous systems. Anxiety, Stress, & Coping , 30 (2), 145–154. doi:10.1080/10615806.2016.1238076 10.1080/10615806.2016.1238076

Yamaguchi, N. , & Okada, S. ( 2009 ). Cyclooxygenase-1 and -2 in spinally projecting neurons are involved in CRF-induced sympathetic activation. Auton Neuroscience, 151(2), 82–89. doi:10.1016/j.autneu.2009.06.009 10.1016/j.autneu.2009.06.009

Yoo, B. B. , & Mazmanian, S. K. ( 2017 ). The enteric network: Interactions between the immune and nervous systems of the gut. Immunity , 46 (6), 910–926. doi:10.1016/j.immuni.2017.05.011 10.1016/j.immuni.2017.05.011

Zubin, J. , & Spring, B. ( 1977 ). Vulnerability: A new view of schizophrenia. Journal of Abnormal Psychology , 86 (2), 103–126. doi:10.1037/0021-843X.86.2.103 10.1037/0021-843X.86.2.103

About Oxford Academic
Publish journals with us
University press partners
What we publish
New features
Open access
Institutional account management
Rights and permissions
Get help with access
Accessibility
Advertising
Media enquiries
Oxford University Press
Oxford Languages
University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

Copyright © 2024 Oxford University Press
Cookie settings
Cookie policy
Privacy policy
Legal notice

This Feature Is Available To Subscribers Only

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression

Affiliations Department of Psychology, University of Gothenburg, Gothenburg, Sweden, Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden

Affiliation Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden

Affiliations Department of Psychology, University of Gothenburg, Gothenburg, Sweden, Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden, Department of Psychology, Education and Sport Science, Linneaus University, Kalmar, Sweden

* E-mail: [email protected]

Affiliations Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden, Center for Ethics, Law, and Mental Health (CELAM), University of Gothenburg, Gothenburg, Sweden, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

Ali Al Nima,
Patricia Rosenberg,
Trevor Archer,
Danilo Garcia

Published: September 9, 2013
https://doi.org/10.1371/journal.pone.0073265
Reader Comments

23 Sep 2013: Nima AA, Rosenberg P, Archer T, Garcia D (2013) Correction: Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression. PLOS ONE 8(9): 10.1371/annotation/49e2c5c8-e8a8-4011-80fc-02c6724b2acc. https://doi.org/10.1371/annotation/49e2c5c8-e8a8-4011-80fc-02c6724b2acc View correction

Mediation analysis investigates whether a variable (i.e., mediator) changes in regard to an independent variable, in turn, affecting a dependent variable. Moderation analysis, on the other hand, investigates whether the statistical interaction between independent variables predict a dependent variable. Although this difference between these two types of analysis is explicit in current literature, there is still confusion with regard to the mediating and moderating effects of different variables on depression. The purpose of this study was to assess the mediating and moderating effects of anxiety, stress, positive affect, and negative affect on depression.

Two hundred and two university students (males = 93, females = 113) completed questionnaires assessing anxiety, stress, self-esteem, positive and negative affect, and depression. Mediation and moderation analyses were conducted using techniques based on standard multiple regression and hierarchical regression analyses.

Main Findings

The results indicated that (i) anxiety partially mediated the effects of both stress and self-esteem upon depression, (ii) that stress partially mediated the effects of anxiety and positive affect upon depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect, and between positive affect and negative affect upon depression.

The study highlights different research questions that can be investigated depending on whether researchers decide to use the same variables as mediators and/or moderators.

Citation: Nima AA, Rosenberg P, Archer T, Garcia D (2013) Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression. PLoS ONE 8(9): e73265. https://doi.org/10.1371/journal.pone.0073265

Editor: Ben J. Harrison, The University of Melbourne, Australia

Received: February 21, 2013; Accepted: July 22, 2013; Published: September 9, 2013

Copyright: © 2013 Nima et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The authors have no support or funding to report.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Mediation refers to the covariance relationships among three variables: an independent variable (1), an assumed mediating variable (2), and a dependent variable (3). Mediation analysis investigates whether the mediating variable accounts for a significant amount of the shared variance between the independent and the dependent variables–the mediator changes in regard to the independent variable, in turn, affecting the dependent one [1] , [2] . On the other hand, moderation refers to the examination of the statistical interaction between independent variables in predicting a dependent variable [1] , [3] . In contrast to the mediator, the moderator is not expected to be correlated with both the independent and the dependent variable–Baron and Kenny [1] actually recommend that it is best if the moderator is not correlated with the independent variable and if the moderator is relatively stable, like a demographic variable (e.g., gender, socio-economic status) or a personality trait (e.g., affectivity).

Although both types of analysis lead to different conclusions [3] and the distinction between statistical procedures is part of the current literature [2] , there is still confusion about the use of moderation and mediation analyses using data pertaining to the prediction of depression. There are, for example, contradictions among studies that investigate mediating and moderating effects of anxiety, stress, self-esteem, and affect on depression. Depression, anxiety and stress are suggested to influence individuals' social relations and activities, work, and studies, as well as compromising decision-making and coping strategies [4] , [5] , [6] . Successfully coping with anxiety, depressiveness, and stressful situations may contribute to high levels of self-esteem and self-confidence, in addition increasing well-being, and psychological and physical health [6] . Thus, it is important to disentangle how these variables are related to each other. However, while some researchers perform mediation analysis with some of the variables mentioned here, other researchers conduct moderation analysis with the same variables. Seldom are both moderation and mediation performed on the same dataset. Before disentangling mediation and moderation effects on depression in the current literature, we briefly present the methodology behind the analysis performed in this study.

Mediation and moderation

Baron and Kenny [1] postulated several criteria for the analysis of a mediating effect: a significant correlation between the independent and the dependent variable, the independent variable must be significantly associated with the mediator, the mediator predicts the dependent variable even when the independent variable is controlled for, and the correlation between the independent and the dependent variable must be eliminated or reduced when the mediator is controlled for. All the criteria is then tested using the Sobel test which shows whether indirect effects are significant or not [1] , [7] . A complete mediating effect occurs when the correlation between the independent and the dependent variable are eliminated when the mediator is controlled for [8] . Analyses of mediation can, for example, help researchers to move beyond answering if high levels of stress lead to high levels of depression. With mediation analysis researchers might instead answer how stress is related to depression.

In contrast to mediation, moderation investigates the unique conditions under which two variables are related [3] . The third variable here, the moderator, is not an intermediate variable in the causal sequence from the independent to the dependent variable. For the analysis of moderation effects, the relation between the independent and dependent variable must be different at different levels of the moderator [3] . Moderators are included in the statistical analysis as an interaction term [1] . When analyzing moderating effects the variables should first be centered (i.e., calculating the mean to become 0 and the standard deviation to become 1) in order to avoid problems with multi-colinearity [8] . Moderating effects can be calculated using multiple hierarchical linear regressions whereby main effects are presented in the first step and interactions in the second step [1] . Analysis of moderation, for example, helps researchers to answer when or under which conditions stress is related to depression.

Mediation and moderation effects on depression

Cognitive vulnerability models suggest that maladaptive self-schema mirroring helplessness and low self-esteem explain the development and maintenance of depression (for a review see [9] ). These cognitive vulnerability factors become activated by negative life events or negative moods [10] and are suggested to interact with environmental stressors to increase risk for depression and other emotional disorders [11] , [10] . In this line of thinking, the experience of stress, low self-esteem, and negative emotions can cause depression, but also be used to explain how (i.e., mediation) and under which conditions (i.e., moderation) specific variables influence depression.

Using mediational analyses to investigate how cognitive therapy intervations reduced depression, researchers have showed that the intervention reduced anxiety, which in turn was responsible for 91% of the reduction in depression [12] . In the same study, reductions in depression, by the intervention, accounted only for 6% of the reduction in anxiety. Thus, anxiety seems to affect depression more than depression affects anxiety and, together with stress, is both a cause of and a powerful mediator influencing depression (See also [13] ). Indeed, there are positive relationships between depression, anxiety and stress in different cultures [14] . Moreover, while some studies show that stress (independent variable) increases anxiety (mediator), which in turn increased depression (dependent variable) [14] , other studies show that stress (moderator) interacts with maladaptive self-schemata (dependent variable) to increase depression (independent variable) [15] , [16] .

The present study

In order to illustrate how mediation and moderation can be used to address different research questions we first focus our attention to anxiety and stress as mediators of different variables that earlier have been shown to be related to depression. Secondly, we use all variables to find which of these variables moderate the effects on depression.

The specific aims of the present study were:

To investigate if anxiety mediated the effect of stress, self-esteem, and affect on depression.
To investigate if stress mediated the effects of anxiety, self-esteem, and affect on depression.
To examine moderation effects between anxiety, stress, self-esteem, and affect on depression.

Ethics statement

This research protocol was approved by the Ethics Committee of the University of Gothenburg and written informed consent was obtained from all the study participants.

Participants

The present study was based upon a sample of 206 participants (males = 93, females = 113). All the participants were first year students in different disciplines at two universities in South Sweden. The mean age for the male students was 25.93 years ( SD = 6.66), and 25.30 years ( SD = 5.83) for the female students.

In total, 206 questionnaires were distributed to the students. Together 202 questionnaires were responded to leaving a total dropout of 1.94%. This dropout concerned three sections that the participants chose not to respond to at all, and one section that was completed incorrectly. None of these four questionnaires was included in the analyses.

Instruments

Hospital anxiety and depression scale [17] ..

The Swedish translation of this instrument [18] was used to measure anxiety and depression. The instrument consists of 14 statements (7 of which measure depression and 7 measure anxiety) to which participants are asked to respond grade of agreement on a Likert scale (0 to 3). The utility, reliability and validity of the instrument has been shown in multiple studies (e.g., [19] ).

Perceived Stress Scale [20] .

The Swedish version [21] of this instrument was used to measures individuals' experience of stress. The instrument consist of 14 statements to which participants rate on a Likert scale (0 = never , 4 = very often ). High values indicate that the individual expresses a high degree of stress.

Rosenberg's Self-Esteem Scale [22] .

The Rosenberg's Self-Esteem Scale (Swedish version by Lindwall [23] ) consists of 10 statements focusing on general feelings toward the self. Participants are asked to report grade of agreement in a four-point Likert scale (1 = agree not at all, 4 = agree completely ). This is the most widely used instrument for estimation of self-esteem with high levels of reliability and validity (e.g., [24] , [25] ).

Positive Affect and Negative Affect Schedule [26] .

This is a widely applied instrument for measuring individuals' self-reported mood and feelings. The Swedish version has been used among participants of different ages and occupations (e.g., [27] , [28] , [29] ). The instrument consists of 20 adjectives, 10 positive affect (e.g., proud, strong) and 10 negative affect (e.g., afraid, irritable). The adjectives are rated on a five-point Likert scale (1 = not at all , 5 = very much ). The instrument is a reliable, valid, and effective self-report instrument for estimating these two important and independent aspects of mood [26] .

Questionnaires were distributed to the participants on several different locations within the university, including the library and lecture halls. Participants were asked to complete the questionnaire after being informed about the purpose and duration (10–15 minutes) of the study. Participants were also ensured complete anonymity and informed that they could end their participation whenever they liked.

Correlational analysis

Depression showed positive, significant relationships with anxiety, stress and negative affect. Table 1 presents the correlation coefficients, mean values and standard deviations ( sd ), as well as Cronbach ' s α for all the variables in the study.

PPT PowerPoint slide
PNG larger image
TIFF original image

https://doi.org/10.1371/journal.pone.0073265.t001

Mediation analysis

Regression analyses were performed in order to investigate if anxiety mediated the effect of stress, self-esteem, and affect on depression (aim 1). The first regression showed that stress ( B = .03, 95% CI [.02,.05], β = .36, t = 4.32, p <.001), self-esteem ( B = −.03, 95% CI [−.05, −.01], β = −.24, t = −3.20, p <.001), and positive affect ( B = −.02, 95% CI [−.05, −.01], β = −.19, t = −2.93, p = .004) had each an unique effect on depression. Surprisingly, negative affect did not predict depression ( p = 0.77) and was therefore removed from the mediation model, thus not included in further analysis.

The second regression tested whether stress, self-esteem and positive affect uniquely predicted the mediator (i.e., anxiety). Stress was found to be positively associated ( B = .21, 95% CI [.15,.27], β = .47, t = 7.35, p <.001), whereas self-esteem was negatively associated ( B = −.29, 95% CI [−.38, −.21], β = −.42, t = −6.48, p <.001) to anxiety. Positive affect, however, was not associated to anxiety ( p = .50) and was therefore removed from further analysis.

A hierarchical regression analysis using depression as the outcome variable was performed using stress and self-esteem as predictors in the first step, and anxiety as predictor in the second step. This analysis allows the examination of whether stress and self-esteem predict depression and if this relation is weaken in the presence of anxiety as the mediator. The result indicated that, in the first step, both stress ( B = .04, 95% CI [.03,.05], β = .45, t = 6.43, p <.001) and self-esteem ( B = .04, 95% CI [.03,.05], β = .45, t = 6.43, p <.001) predicted depression. When anxiety (i.e., the mediator) was controlled for predictability was reduced somewhat but was still significant for stress ( B = .03, 95% CI [.02,.04], β = .33, t = 4.29, p <.001) and for self-esteem ( B = −.03, 95% CI [−.05, −.01], β = −.20, t = −2.62, p = .009). Anxiety, as a mediator, predicted depression even when both stress and self-esteem were controlled for ( B = .05, 95% CI [.02,.08], β = .26, t = 3.17, p = .002). Anxiety improved the prediction of depression over-and-above the independent variables (i.e., stress and self-esteem) (Δ R 2 = .03, F (1, 198) = 10.06, p = .002). See Table 2 for the details.

https://doi.org/10.1371/journal.pone.0073265.t002

A Sobel test was conducted to test the mediating criteria and to assess whether indirect effects were significant or not. The result showed that the complete pathway from stress (independent variable) to anxiety (mediator) to depression (dependent variable) was significant ( z = 2.89, p = .003). The complete pathway from self-esteem (independent variable) to anxiety (mediator) to depression (dependent variable) was also significant ( z = 2.82, p = .004). Thus, indicating that anxiety partially mediates the effects of both stress and self-esteem on depression. This result may indicate also that both stress and self-esteem contribute directly to explain the variation in depression and indirectly via experienced level of anxiety (see Figure 1 ).

Changes in Beta weights when the mediator is present are highlighted in red.

https://doi.org/10.1371/journal.pone.0073265.g001

For the second aim, regression analyses were performed in order to test if stress mediated the effect of anxiety, self-esteem, and affect on depression. The first regression showed that anxiety ( B = .07, 95% CI [.04,.10], β = .37, t = 4.57, p <.001), self-esteem ( B = −.02, 95% CI [−.05, −.01], β = −.18, t = −2.23, p = .03), and positive affect ( B = −.03, 95% CI [−.04, −.02], β = −.27, t = −4.35, p <.001) predicted depression independently of each other. Negative affect did not predict depression ( p = 0.74) and was therefore removed from further analysis.

The second regression investigated if anxiety, self-esteem and positive affect uniquely predicted the mediator (i.e., stress). Stress was positively associated to anxiety ( B = 1.01, 95% CI [.75, 1.30], β = .46, t = 7.35, p <.001), negatively associated to self-esteem ( B = −.30, 95% CI [−.50, −.01], β = −.19, t = −2.90, p = .004), and a negatively associated to positive affect ( B = −.33, 95% CI [−.46, −.20], β = −.27, t = −5.02, p <.001).

A hierarchical regression analysis using depression as the outcome and anxiety, self-esteem, and positive affect as the predictors in the first step, and stress as the predictor in the second step, allowed the examination of whether anxiety, self-esteem and positive affect predicted depression and if this association would weaken when stress (i.e., the mediator) was present. In the first step of the regression anxiety ( B = .07, 95% CI [.05,.10], β = .38, t = 5.31, p = .02), self-esteem ( B = −.03, 95% CI [−.05, −.01], β = −.18, t = −2.41, p = .02), and positive affect ( B = −.03, 95% CI [−.04, −.02], β = −.27, t = −4.36, p <.001) significantly explained depression. When stress (i.e., the mediator) was controlled for, predictability was reduced somewhat but was still significant for anxiety ( B = .05, 95% CI [.02,.08], β = .05, t = 4.29, p <.001) and for positive affect ( B = −.02, 95% CI [−.04, −.01], β = −.20, t = −3.16, p = .002), whereas self-esteem did not reach significance ( p < = .08). In the second step, the mediator (i.e., stress) predicted depression even when anxiety, self-esteem, and positive affect were controlled for ( B = .02, 95% CI [.08,.04], β = .25, t = 3.07, p = .002). Stress improved the prediction of depression over-and-above the independent variables (i.e., anxiety, self-esteem and positive affect) (Δ R 2 = .02, F (1, 197) = 9.40, p = .002). See Table 3 for the details.

https://doi.org/10.1371/journal.pone.0073265.t003

Furthermore, the Sobel test indicated that the complete pathways from the independent variables (anxiety: z = 2.81, p = .004; self-esteem: z = 2.05, p = .04; positive affect: z = 2.58, p <.01) to the mediator (i.e., stress), to the outcome (i.e., depression) were significant. These specific results might be explained on the basis that stress partially mediated the effects of both anxiety and positive affect on depression while stress completely mediated the effects of self-esteem on depression. In other words, anxiety and positive affect contributed directly to explain the variation in depression and indirectly via the experienced level of stress. Self-esteem contributed only indirectly via the experienced level of stress to explain the variation in depression. In other words, stress effects on depression originate from “its own power” and explained more of the variation in depression than self-esteem (see Figure 2 ).

https://doi.org/10.1371/journal.pone.0073265.g002

Moderation analysis

Multiple linear regression analyses were used in order to examine moderation effects between anxiety, stress, self-esteem and affect on depression. The analysis indicated that about 52% of the variation in the dependent variable (i.e., depression) could be explained by the main effects and the interaction effects ( R 2 = .55, adjusted R 2 = .51, F (55, 186) = 14.87, p <.001). When the variables (dependent and independent) were standardized, both the standardized regression coefficients beta (β) and the unstandardized regression coefficients beta (B) became the same value with regard to the main effects. Three of the main effects were significant and contributed uniquely to high levels of depression: anxiety ( B = .26, t = 3.12, p = .002), stress ( B = .25, t = 2.86, p = .005), and self-esteem ( B = −.17, t = −2.17, p = .03). The main effect of positive affect was also significant and contributed to low levels of depression ( B = −.16, t = −2.027, p = .02) (see Figure 3 ). Furthermore, the results indicated that two moderator effects were significant. These were the interaction between stress and negative affect ( B = −.28, β = −.39, t = −2.36, p = .02) (see Figure 4 ) and the interaction between positive affect and negative affect ( B = −.21, β = −.29, t = −2.30, p = .02) ( Figure 5 ).

https://doi.org/10.1371/journal.pone.0073265.g003

Low stress and low negative affect leads to lower levels of depression compared to high stress and high negative affect.

https://doi.org/10.1371/journal.pone.0073265.g004

High positive affect and low negative affect lead to lower levels of depression compared to low positive affect and high negative affect.

https://doi.org/10.1371/journal.pone.0073265.g005

The results in the present study show that (i) anxiety partially mediated the effects of both stress and self-esteem on depression, (ii) that stress partially mediated the effects of anxiety and positive affect on depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect, and positive affect and negative affect on depression.

Mediating effects

The study suggests that anxiety contributes directly to explaining the variance in depression while stress and self-esteem might contribute directly to explaining the variance in depression and indirectly by increasing feelings of anxiety. Indeed, individuals who experience stress over a long period of time are susceptible to increased anxiety and depression [30] , [31] and previous research shows that high self-esteem seems to buffer against anxiety and depression [32] , [33] . The study also showed that stress partially mediated the effects of both anxiety and positive affect on depression and that stress completely mediated the effects of self-esteem on depression. Anxiety and positive affect contributed directly to explain the variation in depression and indirectly to the experienced level of stress. Self-esteem contributed only indirectly via the experienced level of stress to explain the variation in depression, i.e. stress affects depression on the basis of ‘its own power’ and explains much more of the variation in depressive experiences than self-esteem. In general, individuals who experience low anxiety and frequently experience positive affect seem to experience low stress, which might reduce their levels of depression. Academic stress, for instance, may increase the risk for experiencing depression among students [34] . Although self-esteem did not emerged as an important variable here, under circumstances in which difficulties in life become chronic, some researchers suggest that low self-esteem facilitates the experience of stress [35] .

Moderator effects/interaction effects

The present study showed that the interaction between stress and negative affect and between positive and negative affect influenced self-reported depression symptoms. Moderation effects between stress and negative affect imply that the students experiencing low levels of stress and low negative affect reported lower levels of depression than those who experience high levels of stress and high negative affect. This result confirms earlier findings that underline the strong positive association between negative affect and both stress and depression [36] , [37] . Nevertheless, negative affect by itself did not predicted depression. In this regard, it is important to point out that the absence of positive emotions is a better predictor of morbidity than the presence of negative emotions [38] , [39] . A modification to this statement, as illustrated by the results discussed next, could be that the presence of negative emotions in conjunction with the absence of positive emotions increases morbidity.

The moderating effects between positive and negative affect on the experience of depression imply that the students experiencing high levels of positive affect and low levels of negative affect reported lower levels of depression than those who experience low levels of positive affect and high levels of negative affect. This result fits previous observations indicating that different combinations of these affect dimensions are related to different measures of physical and mental health and well-being, such as, blood pressure, depression, quality of sleep, anxiety, life satisfaction, psychological well-being, and self-regulation [40] – [51] .

Limitations

The result indicated a relatively low mean value for depression ( M = 3.69), perhaps because the studied population was university students. These might limit the generalization power of the results and might also explain why negative affect, commonly associated to depression, was not related to depression in the present study. Moreover, there is a potential influence of single source/single method variance on the findings, especially given the high correlation between all the variables under examination.

Conclusions

The present study highlights different results that could be arrived depending on whether researchers decide to use variables as mediators or moderators. For example, when using meditational analyses, anxiety and stress seem to be important factors that explain how the different variables used here influence depression–increases in anxiety and stress by any other factor seem to lead to increases in depression. In contrast, when moderation analyses were used, the interaction of stress and affect predicted depression and the interaction of both affectivity dimensions (i.e., positive and negative affect) also predicted depression–stress might increase depression under the condition that the individual is high in negative affectivity, in turn, negative affectivity might increase depression under the condition that the individual experiences low positive affectivity.

Acknowledgments

The authors would like to thank the reviewers for their openness and suggestions, which significantly improved the article.

Author Contributions

Conceived and designed the experiments: AAN TA. Performed the experiments: AAN. Analyzed the data: AAN DG. Contributed reagents/materials/analysis tools: AAN TA DG. Wrote the paper: AAN PR TA DG.

View Article
Google Scholar
3. MacKinnon DP, Luecken LJ (2008) How and for Whom? Mediation and Moderation in Health Psychology. Health Psychol 27 (2 Suppl.): s99–s102.
4. Aaroe R (2006) Vinn över din depression [Defeat depression]. Stockholm: Liber.
5. Agerberg M (1998) Ut ur mörkret [Out from the Darkness]. Stockholm: Nordstedt.
6. Gilbert P (2005) Hantera din depression [Cope with your Depression]. Stockholm: Bokförlaget Prisma.
8. Tabachnick BG, Fidell LS (2007) Using Multivariate Statistics, Fifth Edition. Boston: Pearson Education, Inc.
10. Beck AT (1967) Depression: Causes and treatment. Philadelphia: University of Pennsylvania Press.
21. Eskin M, Parr D (1996) Introducing a Swedish version of an instrument measuring mental stress. Stockholm: Psykologiska institutionen Stockholms Universitet.
22. Rosenberg M (1965) Society and the Adolescent Self-Image. Princeton, NJ: Princeton University Press.
23. Lindwall M (2011) Självkänsla – Bortom populärpsykologi & enkla sanningar [Self-Esteem – Beyond Popular Psychology and Simple Truths]. Lund:Studentlitteratur.
25. Blascovich J, Tomaka J (1991) Measures of self-esteem. In: Robinson JP, Shaver PR, Wrightsman LS (Red.) Measures of personality and social psychological attitudes San Diego: Academic Press. 161–194.
30. Eysenck M (Ed.) (2000) Psychology: an integrated approach. New York: Oxford University Press.
31. Lazarus RS, Folkman S (1984) Stress, Appraisal, and Coping. New York: Springer.
32. Johnson M (2003) Självkänsla och anpassning [Self-esteem and Adaptation]. Lund: Studentlitteratur.
33. Cullberg Weston M (2005) Ditt inre centrum – Om självkänsla, självbild och konturen av ditt själv [Your Inner Centre – About Self-esteem, Self-image and the Contours of Yourself]. Stockholm: Natur och Kultur.
34. Lindén M (1997) Studentens livssituation. Frihet, sårbarhet, kris och utveckling [Students' Life Situation. Freedom, Vulnerability, Crisis and Development]. Uppsala: Studenthälsan.
35. Williams S (1995) Press utan stress ger maximal prestation [Pressure without Stress gives Maximal Performance]. Malmö: Richters förlag.
37. Garcia D, Kerekes N, Andersson-Arntén A–C, Archer T (2012) Temperament, Character, and Adolescents' Depressive Symptoms: Focusing on Affect. Depress Res Treat. DOI:10.1155/2012/925372.
40. Garcia D, Ghiabi B, Moradi S, Siddiqui A, Archer T (2013) The Happy Personality: A Tale of Two Philosophies. In Morris EF, Jackson M-A editors. Psychology of Personality. New York: Nova Science Publishers. 41–59.
41. Schütz E, Nima AA, Sailer U, Andersson-Arntén A–C, Archer T, Garcia D (2013) The affective profiles in the USA: Happiness, depression, life satisfaction, and happiness-increasing strategies. In press.
43. Garcia D, Nima AA, Archer T (2013) Temperament and Character's Relationship to Subjective Well- Being in Salvadorian Adolescents and Young Adults. In press.
44. Garcia D (2013) La vie en Rose: High Levels of Well-Being and Events Inside and Outside Autobiographical Memory. J Happiness Stud. DOI: 10.1007/s10902-013-9443-x.
48. Adrianson L, Djumaludin A, Neila R, Archer T (2013) Cultural influences upon health, affect, self-esteem and impulsiveness: An Indonesian-Swedish comparison. Int J Res Stud Psychol. DOI: 10.5861/ijrsp.2013.228.

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Chapter 16. Stress, Health, and Coping

16.2 Stress and Coping

Jennifer Walinga

Learning Objectives

Define coping and adaptation.
Understand the various conceptualizations of stress as stimulus, response, and transactional process.
Understand the role of cognition and physiology in coping with stress.
Recognize emotion-focused and problem-focused coping strategies.
Understand the relationships and interactions between health, stress, and coping.

In order to understand how people learn to cope with stress, it is important to first reflect on the different conceptualizations of stress and how the coping research has emerged alongside distinct approaches to stress. Stress has been viewed as a response , a stimulus, and a transaction . How an individual conceptualizes stress determines his or her response, adaptation, or coping strategies.

Stress As a Response

Stress as a response model, initially introduced by Hans Selye (1956), describes stress as a physiological response pattern and was captured within his general adaptation syndrome (GAS) model (Figure 16.3). This model describes stress as a dependent variable and includes three concepts :

Stress is a defensive mechanism.
Stress follows the three stages of alarm, resistance, and exhaustion.
If the stress is prolonged or severe, it could result in diseases of adaptation or even death.

Later, in The Stress Concept: Past, Present and Future (1983), Selye introduced the idea that the stress response could result in positive or negative outcomes based on cognitive interpretations of the physical symptoms or physiological experience (Figure 16.3, “The General Adaptation to Stress Model “) . In this way, stress could be experienced as eustress (positive) or dystress (negative). However, Selye always considered stress to be a physiologically based construct or response. Gradually, other researchers expanded the thinking on stress to include and involve psychological concepts earlier in the stress model.

The response model of stress incorporates coping within the model itself. The idea of adaptation or coping is inherent to the GAS model at both the alarm and resistance stages. When confronted with a negative stimulus, the alarm response initiates the sympathetic nervous system to combat or avoid the stressor (i.e., increased heart rate, temperature, adrenaline, and glucose levels). The resistance response then initiates physiological systems with a fight or flight reaction to the stressor, returning the system to homeostasis, reducing harm, or more generally accommodating the stressor, which can lead to adaptive diseases such as sleep deprivation, mental illness, hypertension, or heart disease. Thus, along with the early conceptualization of stress as a physiological response, early research on coping was also born. As early as 1932, Walter Cannon described the notion of self-regulation in his work The Wisdom of the Body.

Stress As a Stimulus

The theory of stress as a stimulus was introduced in the 1960s, and viewed stress as a significant life event or change that demands response, adjustment, or adaptation. Holmes and Rahe (1967) created the Social Readjustment Rating Scale (SRRS) consisting of 42 life events scored according to the estimated degree of adjustment they would each demand of the person experiencing them (e.g., marriage, divorce, relocation, change or loss of job, loss of loved one). Holmes and Rahe theorized that stress was an independent variable in the health-stress-coping equation — the cause of an experience rather than the experience itself. While some correlations emerged between SRRS scores and illness (Rahe, Mahan, & Arthur, 1970; Johnson & Sarason, 1979), there were problems with the stress as stimulus theory. The stress as stimulus theory assumes:

Change is inherently stressful.
Life events demand the same levels of adjustment across the population.
There is a common threshold of adjustment beyond which illness will result.

Rahe and Holmes initially viewed the human subject as a passive recipient of stress, one who played no role in determining the degree, intensity, or valence of the stressor. Later, Rahe introduced the concept of interpretation into his research (Rahe & Arthur, 1978), suggesting that a change or life event could be interpreted as a positive or negative experience based on cognitive and emotional factors. However, the stress as stimulus model still ignored important variables such as prior learning, environment, support networks, personality, and life experience.

Stress As a Transaction

In attempting to explain stress as more of a dynamic process, Richard Lazarus developed the transactional theory of stress and coping (TTSC) (Lazarus, 1966; Lazarus & Folkman, 1984), which presents stress as a product of a transaction between a person (including multiple systems: cognitive, physiological, affective, psychological, neurological) and his or her complex environment . Stress as a transaction was introduced with the most impact when Dr. Susan Kobasa first used the concept of hardiness (Kobasa, 1979). Hardiness refers to a pattern of personality characteristics that distinguishes people who remain healthy under life stress compared with those who develop health problems. In the late 1970s, the concept of hardiness was further developed by Salvatore Maddi, Kobasa, and their graduate students at the University of Chicago (Kobasa, 1982; Kobasa & Maddi, 1981; Kobasa, Maddi, & Kahn, 1982; Kobasa, Maddi, Puccetti, & Zola, 1985; Maddi & Kobasa, 1984). Hardiness has some notable similarities with other personality constructs in psychology, including locus of control (Rotter, 1966), sense of coherence (Antonovsky, 1987), self-efficacy (Bandura, 1997), and dispositional optimism (Scheier & Carver, 1985), all of which will be discussed in the next section. Researchers introduced multiple variables to the stress-as-transaction model, expanding and categorizing various factors to account for the complex systems involved in experiencing a stressor (Werner, 1993). The nature of stress was described in multiple ways: acute, episodic or intermittent, and chronic. Different types of stressors emerged, such as event, situation, cue, and condition, which then fell into categories based on locus of control, predictability, tone, impact, and duration. Figure 16.4 illustrates theories of stress as a response, stimulus, and transaction.

In his book Psychological Stress and the Coping Process (1966), Lazarus presented an elegant integration of previous research on stress, health, and coping that placed a person’s appraisal of a stressor at the centre of the stress experience. How an individual appraises a stressor determines how he or she copes with or responds to the stressor. Whether or not a stressor is experienced as discomforting is influenced by a variety of personal and contextual factors including capacities, skills and abilities, constraints, resources, and norms (Mechanic, 1978). Lazarus and Folkman (1984) unpacked the concept of interpretation further in their model of stress appraisal, which includes primary, secondary, and reappraisal components (see Figure 16.5, “ The Transactional Theory of Stress and Coping”). Primary appraisal involves determining whether the stressor poses a threat . Secondary appraisal involves the individual’s evaluation of the resources or coping strategies at his or her disposal for addressing any perceived threats . The process of reappraisal is ongoing and involves continually reappraising both the nature of the stressor and the resources available for responding to the stressor .

Coping with Stress

There are many ways that people strive to cope with stressors and feelings of stress in their lives. A host of literature, both popular and academic, extols the practice of stress management and whole industries are devoted to it. Many techniques are available to help individuals cope with the stresses that life brings. Some of the techniques listed in Figure 16.6, “Stress Management Techniques,” induce a lower than usual stress level temporarily to compensate the biological tissues involved; others face the stressor at a higher level of abstraction. Stress management techniques are more general and range from cognitive (mindfulness, cognitive therapy, meditation) to physical (yoga, art, natural medicine, deep breathing) to environmental (spa visits, music, pets, nature).

Stress coping , as described by researchers such as Lazarus and Folkman, implies a more specific process of cognitive appraisal to determine whether an individual believes he or she has the resources to respond effectively to the challenges of a stressor or change (Folkman & Lazarus, 1988; Lazarus & Folkman, 1987). The appraisal literature explains the response or coping process in terms of problem-focused coping or emotion-focused coping (Folkman & Lazarus, 1980; Lazarus & Folkman, 1984), also referred to as active and passive coping styles (Jex, Bliese, Buzzell, & Primeau, 2001). As well, approach and avoidance-style measures of coping exist involving assertiveness or withdrawal (Anshel, 1996; Anshel & Weinberg, 1999; Roth & Cohen, 1986). When faced with a challenge, an individual primarily appraises the challenge as either threatening or non-threatening, and secondarily in terms of whether he or she has the resources to respond to or cope with the challenge effectively. If the individual does not believe he or she has the capacity to respond to the challenge or feels a lack of control, he or she is most likely to turn to an emotion-focused coping response such as wishful thinking (e.g., I wish that I could change what is happening or how I feel), distancing (e.g., I’ll try to forget the whole thing), or emphasizing the positive (e.g., I’ll just look for the silver lining) (Lazarus & Folkman, 1987). If the person has the resources to manage the challenge, he or she will usually develop a problem-focused coping response such as analysis (e.g., I try to analyze the problem in order to understand it better; I’m making a plan of action and following it). It is theorized and empirically demonstrated that a person’s secondary appraisal then determines coping strategies (Lazarus & Folkman, 1987). Coping strategies vary from positive thinking to denial (see Figure 16.7, “COPE Inventory”) and are measured and tested using a variety of instruments and scales such as the COPE inventory (Carver, Scheier, & Weintraub, 1989).

Research Focus: Stress and Playing Soccer

Walinga (2008), in her work with a university soccer team that was undergoing several stressful changes in addition to the usual performance stressors, recently elaborated upon the appraisal model by suggesting that reappraisal more specifically involves a reiteration of the primary-secondary appraisal process. Once a person determines that a stressor is indeed a threat, and secondarily appraises resources as lacking, he or she then primarily appraises the secondary appraisal. In other words, the person determines whether having a lack of resources indeed poses some sort of threat. If lack of resources is deemed not to be a threat, the person is much more likely to generate creative solutions to the initial stressor and therefore cope effectively. But if a lack of resources is deemed to be a threat, then the person tends to focus on finding resources rather than addressing the initial stressor, and arrives at ineffective control-focused coping strategies.

In the case of the university soccer players, some initial stressors were identified as “a particularly challenging or sizable opponent,” “rainy conditions,” “the cold,” “not connecting with the coach,” or “negative attitudes on the field.” Typical emotion- or control-focused coping strategies included “working harder” and “sucking it up,” as well as avoidance or passivity. One player who struggled with her opponent’s size felt that she had little control over the fact that her opponent was taller and thus “beat her to the header balls.” She explained how she would “just kinda fade away when we play that team…get passive and just fade into the background.” Her coping response signified a withdrawal subscale on the emotion-focused coping scale, and when asked about her degree of satisfaction with her chosen path of response, she replied that she was “unhappy but could see no other alternative.” However, generally the team and several of the key leaders expressed alternative coping strategies not accounted for in the transactional theory of stress and coping. While several members of the team had a negative secondary appraisal, believing themselves to be lacking in the resources required to deal with the changes that occurred to the team, during the interviews it became apparent that such powerlessness did not, as was expected, lead only to emotion-focused coping, such as defensiveness, blame, or withdrawal; an acknowledged lack of control often resulted in an ability to move on and solve the challenges of change effectively.

Many of the team members believed “hitting rock bottom” accounted for their successful transformation, acting as a sort of “trigger” or “restart” and enabling them to gain greater clarity about their goals, as well as strategies for achieving these goals. Rather than focusing on increasing control or controlling the barrier or threat itself, the tolerant individual accepts the barrier as reality and accepts the lack of control as a reality. This person can now attend to and identify the challenges that the barrier poses to attaining her goals. For instance, the goalkeeper focused not on regretting or blaming herself for a missed save, or even trying harder next time, but instead focused on the challenges that a difficult shot posed for her and how she might resolve an unexpected spin on the ball. When faced with rainy conditions, the tolerant player focused not on denying or pushing through the rain, but on the problems the rain creates for her and how to resolve the resulting lack of ball control or slippery field conditions:

“I guess the spin on the ball was out of my control, but I had total control in terms of adjusting to it.”
“I was not in control of what my opponent did with the ball or could have done to ensure that I did not win the ball, but I was in control of making sure I did not dive into the tackle, I held my check up so we could get numbers back and avoid a counterattack.”
“I went forward when I probably shouldn’t have and I left our defenders outnumbered in the back, so I made sure I won the ball so that we would not be faced with a 3-on-2.”
“Despite my fatigue, I decided to make better decisions on when to commit myself and made sure I communicated when I needed help so that my opponent wouldn’t get a breakaway.”
“The lights in my eyes were beyond my control, but I could control my focus on the ball and my positioning.”
“I was not in control of the fact that they were fast; I was in control of my positioning and my decision making.”

By extending the theory of stress and coping, it is hypothesized here that when an individual perceives that he or she is lacking in resources to manage a threat, the perceived lack of control, and not necessarily anxiety, becomes the new challenge and focal point. If the person deems the perceived lack of control to be threatening or problematic for any reason, this would hypothetically cause him or her to fixate on increasing resources for managing the threat (control-focused coping), and impede any kind of response to the particular threats the challenge itself generates. If, on the other hand, the person accepts the lack of control, deeming the lack of resources to be a benign reality, he or she would be able to move the focus to the problems this threat creates and consider options for resolution and goal achievement (problem-focused coping). Control-focused coping seems to be a more generalizable construct for explaining an individual’s inability to focus on the problem at hand. The readiness model proposes that the appraisal process continues to cycle through the primary and secondary phases to determine an individual’s coping response (i.e., primary appraisal = Is it a threat?; secondary appraisal = Do I have the resources to change or control the threat?; if not, we find ourselves back at primary appraisal = Is my lack of control a threat?), and it is this cyclical process of appraisal that offers leverage for facilitating effective coping.

Related concepts to stress coping include locus of control (Rotter, 1966), sense of coherence (Antonovsky, 1987), self-efficacy (Bandura, 1997), and stress-related growth (Scheier & Carver, 1985). Rotter posited that a person with an internal locus of control believes that their achievements and outcomes are determined by their own decisions and efforts. If they do not succeed, they believe it is due to their own lack of effort. Whereas, a person with an external locus of control believes that achievements and outcomes are determined by fate, luck, or other . If the person does not succeed, he or she believes it is due to external forces outside of the person’s control. Aaron Antonovsky (1987) defined sense of coherence as:

a global orientation that expresses the extent to which one has a pervasive, enduring though dynamic feeling of confidence that (1) the stimuli deriving from one’s internal and external environments in the course of living are structured, predictable and explicable; (2) the resources are available to one to meet the demands posed by these stimuli; and (3) these demands are challenges, worthy of investment and engagement (pg. 19).

Self-efficacy is often confused with self-confidence, but in fact confidence is merely one of the many factors that make up a strong sense of self-efficacy. Albert Bandura (1997) defined self-efficacy as the extent or strength of one’s belief in one’s own ability to complete tasks and reach goals . Self-confidence is a trait measure (a quality that is built over time) whereas self-efficacy is a state measure (a capacity experienced at a specific point in time and concerning a specific task). Stress-related growth or thriving is a dispositional response to stress that enables the individual to see opportunities for growth as opposed to threat or debilitation . Spreitzer and colleagues (2005) offered a preliminary definition of thriving as a “psychological state in which individuals experience both a sense of vitality and a sense of learning at work” (p. 538). Carver (1998) described thriving as being “better off after adversity” (p. 247). There are many examples of individuals surpassing previous performances when faced with particularly stressful scenarios, showing increased growth and strength in the face of adversity.

Coping and Health

The capacity for thriving, resilience, or stress-related growth has been associated with improved health outcomes. For example, building on Carver’s work on dispositional optimism and thriving, Shepperd, Maroto, and Pbert (1996) found, in their longitudinal study of cardiac patients, that optimism predicts success in making health changes associated with lower risk of cardiac disease. Optimism was significantly and directly correlated with improved health outcomes, including lower levels of saturated fat, body fat, and global coronary risk, and positively associated with success in increasing aerobic capacity. Billings and colleagues (2000) showed that coping affected positive and negative affect among men who were caregiving for AIDS patients. Social support coping predicted increases in positive affect, which in turn were related to fewer physical symptoms. Avoidant coping, however, was related to increases in negative affect, which were related to more physical symptoms.

Research Focus: Coping with Melanoma

Perhaps the most dramatic of stress coping interventions studies was conducted by Fawzy and his colleagues (Fawzy, Cousins, Fawzy, Kemeny, & Morton, 1990; Fawzy, Kemeny, et al., 1990; Fawzy, et al., 1993; Fawzy & Fawzy, 1994), who did specific coping skills interventions with melanoma patients. During a six-week structured program, participants experienced multiple program components including health education, psychological support, problem-solving, and stress management training. In the short term, the experimental subjects were more likely to use active behaviour coping than the controls, and also had more positive affect. Differences in immune functioning were evident between the two groups at the six-month assessment. Specifically, experimental subjects had a greater percentage of large granular lymphocytes, more NK cells, and better NK cytotoxicity. While coping strategies were not directly associated with immune cell changes, they were correlated with affect, which in turn was associated with immune functioning. The studies supported the hypothesis that effects of coping on biomedical outcomes may be mediated through affect. At a five-year follow-up, a third of the control group had died, compared with less than 10% of the experimental group. Longer survival was associated with more active coping at baseline.

Key Takeaways

Stress has been conceived of in different ways: as a response, as a stimulus, and as a transaction.
Stress as response treats stress as the physiological dependent variable.
Stress as stimulus treats stress as a life event or change that acts as an independent variable.
Stress as transaction considers the myriad personal, social, and environmental factors that come into play in determining the nature, degree, and impact of the stress experience.
There are a variety of stress management techniques deriving from a multitude of theoretical derivations and philosophies.
Coping with stress can be a trait or state-based process — an inherent quality or ability or a learned skill or capacity.
How people appraise a stressor determines how they will attempt to cope with the stressor.
Appraisal hinges on multiple human, social, and environmental factors.
Concepts related to coping include optimism, thriving, hardiness, locus of control, and self-efficacy, all qualities and capacities that can influence the coping strategies an individual chooses to apply to a stressor.

Exercises and Critical Thinking

Reflect on a recent emotionally or physiologically impactful stressor that you perceived to be threatening or negative. What social, environmental, and personal factors contributed to your appraisal of the stressor? Referencing the list of coping items on the COPE inventory, what types of coping strategies did you apply?
Imagine a stressful situation that you believe you coped with positively. Can you identify some coping strategies you used? Can you determine whether you were able to grow through the experience? What factors facilitated a positive outcome for you?
What are some major life events you have experienced? Can you identify differences in how you appraised these events? How you coped with these events?

Anshel, M.H. (1996). Coping styles among adolescent competitive athletes. The Journal of Social Psychology, 136, 311-323.

Anshel, M.H. & Weinberg, R.T. (1999). Re-examining coping among basketball referees following stressful events: Implications for coping interventions. Journal of Sport Behavior, 22, 144-161.

Antonovsky, A. (1987). Unraveling the mystery of health: How people manage stress and stay well . San Francisco: Jossey Bass.

Bandura, A. (1997 ). Self-efficacy: The exercise of control. New York: Freeman.

Billings, D. W., Folkman, S., Acree, M., & Moskowitz, J. T. (2000). Coping and physical health during caregiving: The roles of positive and negative affect. Journal of Personality and Social Psychology, 79 , 131–142.

Carver, C. S. (1998). Resilience and thriving: Issues, models, and linkages. Journal of Social Issues, 54 , 245–266.

Carver, C. S., Scheier, M. F., & Weintraub, J. K. (1989). Assessing coping strategies: A theoretically based approach . Journal of Personality and Social Psychology, 56 , 267–283.

Cannon, W. B. (1932). The Wisdom of the Body. New York: W.W. Norton.

Fawzy, F., & Fawzy, N. (1994). Psychoeducational interventions and health outcomes. In R. Glaser and J. K. Kiecolt-Glaser (Eds.). Handbook of human stress and immunity (pp. 365–402). San Diego: Academic Press.

Fawzy, F. I., Fawzy, N. W., Hyun, C., Elashoff, R., Guthrie, D., Fahey, J. L., & Moron, D. L. (1993). Malignant melanoma: Effects on early structured psychiatric intervention, coping, and affective state on recurrence and survival six years later. Archives of General Psychiatry, 50 , 681–689.

Fawzy, F. I., Cousins, N., Fawzy, N. W., Kemeny, M., & Morton, D. I. (1990). A structured psychiatric intervention for cancer patients: I. Changes over time in methods of coping and affective disturbance. Archives of General Psychiatry, 47 , 720–725.

Fawzy, F. I., Kemeny, M., Fawzy, N. W., Elashoff, R., Morton, D., Cousins, N., & Fahey, J. L. (1990). A structured psychiatric intervention for cancer patients: II. Changes over time in immunological measures. Archives of General Psychiatry, 47 , 729–235.

Folkman, S. & Lazarus, R.S. (1980). An analysis of coping in a middle-aged community sample. Journal of Health & Social Behavior, 21 (3), 219-239.

Folkman, S., Lazarus, R. S. (1988). Coping as a mediator of emotion. Journal of Personal and Social Psycholog,. 54, 466-75.

Holmes, T., & Rahe, R. (1967). The Social Reajustment Rating Scale. Journal of Psychosomatic Research, 12, (4), p. 213–233.

Jex, S.M., Bliese, P.D., Buzzell, S., & Primeau. J. (2001). The impact of self-efficacy on stressor–strain relations: Coping style as an explanatory mechanism. Journal of Applied Psychology 86 (3), 401.

Johnson , J. H., & Sarason , I. G. (1979). Moderator variables in life stress research. In I. Sarason & C. Spielberger (Eds.), Stress an d anxiety, 6, 151–167.

Kobasa, S. C. (1979). Stressful life events, personality, and health – Inquiry into hardiness. Journal of Personality and Social Psychology, 37 (1), 1–11.

Kobasa, S. C. (1982). The hardy personality: Toward a social psychology of stress and health. In G. Sanders & J. Suls (Eds), social Psychology of Health and Illness (p. 3-32). Hillsdale, NJ: Erlbaum.

Kobasa, S. C., Maddi, S. R., & Courington, S. (1981). Personality and constitution as mediators in the stress-illness relationship. Journal of Health and Social Behavior 22 (4), 368–378.

Kobasa, S. C., Maddi, S. R., & Kahn, S. (1982). Hardiness and health: A prospective study. Journal of Personality and Social Psychology 42 (1), 168–177.

Kobasa, S. C., Maddi, S. R., Puccetti, M. C., & Zola, M. A. (1985). Effectiveness of hardiness, exercise and social support as resources against illness. Journal of Psychosomatic Research 29 (5), 525–533.

Lazarus, R. S. (1966). Psychological stress and the coping process. New York, NY: McGraw-Hill.

Lazarus, R. S. (1999). Stress and emotion: A new synthesis. New York: Springer.

Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping . New York: Springer.

Lazarus, R. S., & Folkman, S. (1987). Transactional theory and research on emotions and coping. European Journal of Personality, 1, 141–169 .

Maddi, S. R., & Kobasa, S. C. (1984). The hardy executive: Health under stress . Homewood, IL: Dow Jones-Irwin.

Mechanic, D. (1978). Students under stress: A study in the social psychology of adaptation . Madison: University of Wisconsin Press.

Rahe, R. H., & Arthur, R. J. (1978). Life change and illness studies: Past history and future directions. Journal of Human Stress, 4, 3–15.

Rahe R. H., Mahan J. L., & Arthur R. J. (1970). Prediction of near-future health change from subjects’ preceding life changes. Journal of Psychosomatic Research, 14 (4), 401–6.

Roth, S., & Cohen, L.J. (1986). Approach, avoidance, and coping with stress. American Psychologist, 41 , 813-819.

Rotter, J. B. (1966) Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs, 80 Sanders, G.S. & Suls, J. (Eds.), Social psychology of health and illness (pp. 1–25).

Scheier, M. F., & Carver, C. S. (1985). Optimism, coping, and health – Assessment and implications of generalized outcome expectancies. Health Psychology, 4 (3), 219–247.

Selye, H. (1956). The stress of life . New York: McGraw Hill.

Selye, H. (1983). The concept of stress: Past, present and future. In C.L. Cooper (Ed.). Stress research: Issues for the eighties. New York: John Wiley.

Shepperd, J. A., Maroto, J. J., & Pbert , L. A. (1996). Dispositional optimism as a predictor of health changes among cardiac patients. Journal of Research in Personality 30 , 517–534.

Spreitzer, G., Sutcliffe, K., Dutton, J., Sonenshein, S. & Grant, A. (2005). A socially embedded model of thriving at work. Organization Science 16 (5): 537-549.

Walinga, J. (2008). Change Readiness: The Roles of Appraisal, Focus, and Perceived Control. Journal of Applied Behavioral Science, 44 (3), 315–347.

Werner, E.E. (1993). Risk, resilience, and recovery: Perspectives from the Kauai longitudinal study. Development and Psychopathology, 5 , 503-515.

Image Attributions

Figure 16.3: A diagram of the General Adaptation syndrome model by David G. Myers (http://commons.wikimedia.org/wiki/File:General_Adaptation_Syndrome.jpg) used under the CC-BY 3.0 (http://creativecommons.org/licenses/by/3.0/deed.en).

Figure 16.4: by J. Walinga.

Figure 16.5: by J. Walinga.

Figure 16.6: by J. Walinga.

Figure 16.7: Adapted by J. Walinga from Carver, Scheier, & Weintraub, 1989.

Long Descriptions

[Return to Figure 16.6] Figure 16.7 long description: COPE Inventory scale of coping techniques

positive reinterpretation and growth
mental disengagement
focus on and venting of emotions
use of instrumental social support
active coping
religious coping
behavioural disengagement
use of emotional social support
substance use
suppression of competing activities

[Return to Figure 16.7]

Introduction to Psychology - 1st Canadian Edition Copyright © 2014 by Jennifer Walinga is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Share This Book

Foundations
Write Paper

Search form

Experiments
Anthropology
Self-Esteem
Social Anxiety
Psychology >

Psychological Theories of Stress

The psychological theories of stress gradually evolved from the Theory of Emotion (James-Lange), The Emergency Theory (Cannon-Bard), and to the Theory of Emotion (Schachter-Singer).

This article is a part of the guide:

Stress and Cognitive Appraisal
General Adaptation Syndrome
Three Different Kinds of Stress
Coping Mechanisms
How does Stress Affect Performance?

Browse Full Outline

1 What is Stress?
2.1 Physiological Stress Response
2.2 Nature of Emotions
3.1 James-Lange Theory of Emotion
3.2 Cannon-Bard Theory of Emotion
3.3 Schachter-Singer Theory of Emotion
3.4 Stress and Cognitive Appraisal
4.1 Social Support
4.2 Gender and Culture
5.1 Theories of Coping
5.2 Stress Management
5.3 Stress Therapies
5.4 How does Stress Affect Performance?
6.1 Knowing Your Stressors
7.1 Stress and Cancer
7.2 Warning Signs - Burnout
7.3 Stress in Children
8 Two-Factor Theory of Motivation

Because stress is one of the most interesting and mysterious subjects we have since the beginning of time, its study is not only limited to what happens to the body during a stressful situation, but also to what occurs in the psyche of an individual. In this article, we will discuss the different psychological theories of stress proposed by James & Lange, Cannon & Brad, and Schachter & Singer.

James-Lange: Theory of Emotion

In 1884 and in 1885, theorists William James and Carl Lange might have separately proposed their respective theories on the correlation of stress and emotion, but they had a unified idea on this relationship - emotions do not immediately succeed the perception of the stressor or the stressful event; they become present after the body’s response to the stress. For instance, when you see a growling dog, your heart starts to race, your breath begins to go faster, then your eyes become wide open. According to James and Lange, the feeling of fear or any other emotion only begins after you experience these bodily changes. This means that the emotional behavior is not possible to occur unless it is connected to one’s brain.

See the full article: The James-Lange Theory of Emotion

Cannon-Bard: The Emergency Theory

This theory is quite the opposite of what James and Lange proposed. According to theorist Walter Cannon, emotion in response to stress can actually occur even when the bodily changes are not present. Cannon said that the visceral or internal physiologic response of one’s body is more slowly recognized by the brain as compared with its function to release emotional response. He attempted to prove his theory by means of creating the so-called “decorticated cats”, wherein the neural connections of the body are separated from the cortex in the brain of the cats. When faced with a stressful response, the decorticated cats showed emotional behavior which meant feelings of aggression and rage. This emotion was then manifested by bodily changes such as baring of teeth, growling and erect hair.

To further enhance Cannon’s theory, theorist Philip Bard expanded the ideals of Cannon by arguing that a lower brain stem structure called the thalamus is important in the production of emotional responses. According to Bard, the emotional response is released first, and then sent as signals by the thalamus to the brain cortex for the interpretation alongside with the sending of signals to the sympathetic nervous system or SNS to begin the physiologic response to stress. Therefore, this theory argues that emotional response to stress is not a product of the physiologic response; rather, they occur simultaneously.

See the full article: Cannon-Bard Theory of Emotion

The Schachter-Singer Theory

Theorists Stanley Schachter and Jerome Singer argued that the appropriate identification of the emotion requires both cognitive activity and emotional arousal in order to experience an emotion. Attribution, or the process wherein the brain can identify the stress stimulus producing an emotion is also proposed by Schachter and Singer . The theory explains that we become aware of the reason behind the emotional response, and when we the reason is not obvious, we start to look for environmental clues for the proper interpretation of the emotion to occur.

Psychology 101
Flags and Countries
Capitals and Countries

Sarah Mae Sincero (Aug 25, 2012). Psychological Theories of Stress. Retrieved Apr 23, 2024 from Explorable.com: https://explorable.com/psychological-theories-of-stress

You Are Allowed To Copy The Text

The text in this article is licensed under the Creative Commons-License Attribution 4.0 International (CC BY 4.0) .

This means you're free to copy, share and adapt any parts (or all) of the text in the article, as long as you give appropriate credit and provide a link/reference to this page.

That is it. You don't need our permission to copy the article; just include a link/reference back to this page. You can use it freely (with some kind of link), and we're also okay with people reprinting in publications like books, blogs, newsletters, course-material, papers, wikipedia and presentations (with clear attribution).

Lazarus and Cognitive Appraisal

Want to stay up to date? Follow us!

Save this course for later.

Don't have time for it all now? No problem, save it as a course and come back to it later.

Footer bottom

Subscribe to our RSS Feed
Like us on Facebook
Follow us on Twitter

Bipolar Disorder
Therapy Center
When To See a Therapist
Types of Therapy
Best Online Therapy
Best Couples Therapy
Best Family Therapy
Managing Stress
Sleep and Dreaming
Understanding Emotions
Self-Improvement
Healthy Relationships
Student Resources
Personality Types
Guided Meditations
Verywell Mind Insights
2023 Verywell Mind 25
Mental Health in the Classroom
Editorial Process
Meet Our Review Board
Crisis Support

How to Write a Great Hypothesis

Hypothesis Definition, Format, Examples, and Tips

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk, "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.

Verywell / Alex Dos Diaz

The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis.

Operationalization

Hypothesis Types

Hypotheses examples.

Collecting Data

A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process.

Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

At a Glance

A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

Forming a question
Performing background research
Creating a hypothesis
Designing an experiment
Collecting data
Analyzing the results
Drawing conclusions
Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. At this point, researchers then begin to develop a testable hypothesis.

Unless you are creating an exploratory study, your hypothesis should always explain what you expect to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore numerous factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment do not support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk adage that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

Is your hypothesis based on your research on a topic?
Can your hypothesis be tested?
Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the journal articles you read . Many authors will suggest questions that still need to be explored.

How to Formulate a Good Hypothesis

To form a hypothesis, you should take these steps:

Collect as many observations about a topic or problem as you can.
Evaluate these observations and look for possible causes of the problem.
Create a list of possible explanations that you might want to explore.
After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method , falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that if something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

The Importance of Operational Definitions

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.

Replicability

One of the basic principles of any type of scientific research is that the results must be replicable.

Replication means repeating an experiment in the same way to produce the same results. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. For example, how would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.

Hypothesis Checklist

Does your hypothesis focus on something that you can actually test?
Does your hypothesis include both an independent and dependent variable?
Can you manipulate the variables?
Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

Simple hypothesis : This type of hypothesis suggests there is a relationship between one independent variable and one dependent variable.
Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative population sample and then generalizes the findings to the larger group.
Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the dependent variable if you change the independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

"Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
"Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."
"Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."
"Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."

Examples of a complex hypothesis include:

"People with high-sugar diets and sedentary activity levels are more likely to develop depression."
"Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

"There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
"There is no difference in scores on a memory recall task between children and adults."
"There is no difference in aggression levels between children who play first-person shooter games and those who do not."

Examples of an alternative hypothesis:

"People who take St. John's wort supplements will have less anxiety than those who do not."
"Adults will perform better on a memory task than children."
"Children who play first-person shooter games will show higher levels of aggression than children who do not."

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as case studies , naturalistic observations , and surveys are often used when conducting an experiment is difficult or impossible. These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a correlational study can examine how the variables are related. This research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually cause another to change.

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Thompson WH, Skau S. On the scope of scientific hypotheses . R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607

Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:]. Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z

Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004

Nosek BA, Errington TM. What is replication ? PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691

Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies . Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Diathesis–Stress Model

Oliver Sussman

Neuroscience Researcher

Harvard University Undergraduate

Oliver Sussman is an undergraduate at Harvard University studying neuroscience within the interdisciplinary Mind, Brain, and Behavior program.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

On This Page:

The Diathesis-Stress Model suggests that psychological disorders arise from the interaction of an underlying vulnerability (diathesis) and external stressors. An individual may have a predisposition to a disorder, but it’s the combination of this vulnerability and adverse life events that triggers its manifestation.

What is Diathesis?

The term “diathesis” comes from the Greek word for disposition (“diathesis”). In the context of the diathesis-stress model, this disposition is a factor that makes it more likely that an individual will develop a disorder following a stressful life event.

A diathesis can be a biological factor, like abnormal variations in one or more genes. But other sorts of factors, even if not genetically hard-wired, can also be considered diatheses so long as they form early on and are stable across a person’s life.

For example, traumatic early life experiences, such as the loss of a parent, can act as longstanding predispositions to a psychological disorder. In addition, personality traits like high neuroticism are sometimes also referred to as diatheses.

Finally, diatheses can be situational factors — like living in a low-income household or having a parent with mental illness (Theodore, 2020).

Some of these factors might matter more for some psychological disorders compared to others (for example, a particular genetic variation might increase one’s risk of developing depression but not schizophrenia).

It’s important to note that not all diatheses are created equal. For example, some genetic variations only slightly increase an individual’s risk of a mental disorder, while others increase one’s risk substantially.

As a result, in the diathesis-stress model, different diatheses give rise to different responses to stress.

To conceptualize this, consider the “cup analogy.” Imagine several cups filled with different amounts of marbles; when water is poured into those cups, the cups with more marbles will overflow more easily.

Diatheses are like marbles, and stress is like water: the greater the diathesis, the less stress is needed to cause “overflow” (i.e., give rise to mental illness) (Theodore, 2020).

Diathesis-Stress Model

The diathesis-stress model is a concept in psychiatry and psychopathology that offers a theory of how psychological disorders emerge.

It intervenes in the debate about “ nature vs. nurture ” in psychopathology — whether disorders are predominantly caused by innate biological factors (“nature”) or by social and situational factors (“nurture”) — by providing an account of how both might coincide in giving rise to a disorder.

According to the diathesis-stress model, the emergence of a psychological disorder requires first the existence of a diathesis, or an innate predisposition to that disorder in an individual, and second, stress, or a set of challenging life circumstances that trigger the disorder’s development.

Furthermore, individuals with greater innate predispositions to a disorder may require less stress to trigger that disorder, and vice versa.

In this way, the diathesis-stress model explains how psychological disorders might be related to both nature and nurture and how those two components might interact with one another (Broerman, 2017).

The diathesis-stress model is a modern development of a longstanding debate about the causes of mental illness. This debate began as early as ancient Greece and Rome when theories included imbalances in bodily fluids and interactions with the devil.

Later, this evolved into the “nature vs. nurture” debate. By the late 20th century, it became clear that nature interacted with nurture to produce disorder, and the diathesis-stress model came to the forefront (Theodore, 2020).

The model has been useful in explaining why some individuals with biological dispositions to mental illness do not develop a disorder and why some individuals living through stressful life circumstances nonetheless remain psychologically healthy.

It has also opened the door to research into protective factors: positive elements that counteract the effects of diathesis and stress to prevent the onset of a disorder.

Finally, it has proven particularly useful in the context of specific disorders, such as schizophrenia and depression.

Diathesis and Stress Interactions

According to the diathesis-stress model, diatheses interact with stress to bring about mental illness. In this context, “stress” is an umbrella term encompassing any life event that disrupts an individual’s psychological equilibrium — their normal, healthy regulation of thoughts and emotions.

In the diathesis-stress model, these challenging life events are thought to interact with individuals’ innate dispositions to bring psychological disorders to the surface.

Stress comes in many different forms. It may be a single traumatic event, like the death of a close relative or friend. But stress can also be an ongoing, sustained challenge in one’s life, like a chronic illness or an abusive relationship.

It can even be more mundane, the sorts of things we usually mean when we talk about “stress” — like anxiety from work or school (Theodore, 2020).

These events or situations can profoundly impact individual psychology and interact with diatheses to foment mental illness.

The role of stress in the diathesis-stress model is nuanced. For one, some life circumstances may constitute both a diathesis and stress. For instance, a child with a parent who suffers from mental illness may be genetically predisposed to that illness and may also undergo stress as a result of her parent’s condition (Theodore, 2020).

Second, the timing of stress within an individual’s lifespan may be important; certain disorders are thought to have “windows of vulnerability” during which they are more likely to be brought about by stressful life events (Lokuge, 2011)

Moreover, positive life circumstances, called protective factors, may counteract stress, which decrease the likelihood that a disorder will emerge in response to stress.

Finally, different stresses are thought to play different roles across mental disorders — in other words, a particular form of stressful life event may play an especially pronounced role in depression, or schizophrenia, etc. These last two points will be explored in the sections below.

Protective Factors

Just as negative elements in one’s life make the onset of a psychological disorder more likely, there can also be positive elements that make the onset of a disorder less likely. These positive elements are called protective factors.

Protective factors help explain why some people who have both significant diatheses and stresses nonetheless remain psychologically healthy — in these cases, protective factors prevent a disorder from coming to the surface (Theodore, 2020).

Protective factors can be conditions, meaning beneficial life circumstances that protect against mental illness. They can also be attributes: traits or behaviors of an individual that make them more resilient against psychological disorders (“Protective Factors”).

Conditions that act as protective factors include strong parental and social support and assistance from psychotherapists or counselors. Attributes that act as protective factors include social and emotional competence and the use of healthy coping strategies and stress management techniques (Theodore, 2020).

By itself, the diathesis-stress model does not necessarily include protective factors in its assessment of the causes of psychological disorders.

As a result, the model has been updated in recent years to accommodate protective factors. This updated model is sometimes called the stress-vulnerability-protective factors model (Theodore, 2020).

The diathesis-stress model has proven useful in illuminating the causes of specific psychological disorders. One area where the model has had considerable success is schizophrenia, a disease with both genetic and environmental causes.

Schizophrenia

While schizophrenia has a strong genetic component, some individuals with genetic susceptibilities to the disorder nonetheless remain healthy.

As a result, the view currently held by many psychiatrists is that schizophrenia requires a genetic predisposition in combination with stress later on in life, which then triggers the emergence of the disorder.

Some researchers have also put forth a neural diathesis-stress model of schizophrenia, in which they attempt to explain how brain changes resulting from diatheses and stresses give rise to the disorder (Jones and Fernyhough, 2007).

Thus, the diathesis-stress model does well to explain the origins of schizophrenia and has even been supported by evidence from neuroscience.

The diathesis-stress model has also been used to explain the origins of depression. Similarly to schizophrenia, genetic risk factors for depression have been identified, but not all people with those risk factors go on to develop the disorder.

According to the diathesis-stress model of depression, stressful life events interact with genetic predispositions to bring about depressive symptoms.

This model of depression has been validated by research — a study found there to be an interaction effect between genetic risk factors for depression and scores on an inventory of stressful life events in predicting depressive symptoms (Colodro-Conde et al., 2018).

The model has also proven useful in explaining suicidal behavior. Early models of suicidal behavior tended to focus exclusively on stress, which failed to account for why some individuals exposed to extreme stress nonetheless refrain from engaging in suicidal behavior.

Since suicidal behavior likely also relies on an interaction between genetic and early childhood dispositions with stress later in life, researchers have suggested that efforts to treat and prevent suicidal behavior should utilize a diathesis-stress model (van Heeringen, 2012).

Different psychological disorders have different causes. Some may rely more strongly on hard-wired predispositions, while others may respond more to stressful events later in life.

Nevertheless, the diathesis-stress model has been shown to have wide applicability across many areas of psychiatry.

It offers a powerful explanation of how nature and nurture might come together to give rise to mental illness, a much-needed advancement over earlier theories that took one or the other to be completely determinative.

Broerman, R. (2017). Diathesis-Stress Model. In V. Zeigler-Hill & T. K. Shackelford (Eds.), Encyclopedia of Personality and Individual Differences (pp. 1–3). Springer International Publishing. https://doi.org/10.1007/978-3-319-28099-8_891-1

Colodro-Conde, L., Couvy-Duchesne, B., Zhu, G., Coventry, W. L., Byrne, E. M., Gordon, S., Wright, M. J., Montgomery, G. W., Madden, P. a. F., Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Ripke, S., Eaves, L. J., Heath, A. C., Wray, N. R., Medland, S. E., & Martin, N. G. (2018). A direct test of the diathesis-stress model for depression. Molecular Psychiatry, 23(7), 1590–1596. https://doi.org/10.1038/mp.2017.130

DIATHESIS | Meaning & Definition for UK English | Lexico.com. (n.d.). Lexico Dictionaries | English. Retrieved February 23, 2022, from https://www.lexico.com/definition/diathesis

Jones, S. R., & Fernyhough, C. (2007). A new look at the neural diathesis–stress model of schizophrenia: The primacy of social-evaluative and uncontrollable situations. Schizophrenia Bulletin, 33(5), 1171–1177. https://doi.org/10.1093/schbul/sbl058

Lokuge, S., Frey, B. N., Foster, J. A., Soares, C. N., & Steiner, M. (2011). Depression in women: Windows of vulnerability and new insights into the link between estrogen and serotonin. The Journal of Clinical Psychiatry, 72(11), e1563-1569. https://doi.org/10.4088/JCP.11com07089

Protective Factors to Promote Well-Being and Prevent Child Abuse & Neglect—Child Welfare Information Gateway. (n.d.). Retrieved February 23, 2022, from https://www.childwelfare.gov/topics/preventing/promoting/protectfactors/

Theodore. (2020, April). Diathesis-Stress Model (Definition + Examples). Retrieved from https://practicalpie.com/diathesis-stress-model/.

van Heeringen, K. (2012). Stress–Diathesis Model of Suicidal Behavior. In Y. Dwivedi (Ed.), The Neurobiological Basis of Suicide. CRC Press/Taylor & Francis. http://www.ncbi.nlm.nih.gov/books/NBK107203/

Walker, E. F., & Diforio, D. (1997). Schizophrenia: a neural diathesis-stress model . Psychological review, 104(4), 667.

How Stress Impacts Daily Life and What We Can Do About It

Stress, anxiety, and overwhelm disrupt our daily lives but we can find balance..

Posted April 21, 2024 | Reviewed by Jessica Schrader

What Is Stress?
Find a therapist to overcome stress
An honest assessment can help us to identify places where our daily lives are negatively impacted by stress.
How we function on a daily basis provides valuable insight into how we are handling stress and anxiety.
Envisioning what ideal daily functioning would look like can help us formulate a plan for stress reduction.

Anxiety and stress are disruptors. They get in the way of our ability to live our lives and to successfully fulfill our daily obligations and responsibilities. Worse, they take us out of present moments of joy, contentment, and peace and replace them with future thoughts, suppositions, and inaccurate conclusions. When we are overcome with worry, our minds attach to “what if” rather than to “what is.” This type of thinking serves to distract us, disturb our daily lives, and rob us of a sense of stability and equilibrium.

In psychological terms, daily functioning and activities of daily living are essentially the things we would ideally and healthily be able to accomplish on a daily basis when we are unimpeded by worry, stress, or overwhelm. However, when stress and worry get in the way, we can find it difficult to complete even the most necessary and basic tasks. This is due not to laziness or lack of accountability but, rather, to the feeling of paralysis and fatigue that can come with overwhelming worry and stress. Some areas of daily functioning that can be negatively affected by anxiety include:

Personal hygiene and self-care.
Fulfillment of work duties and obligations.
Fulfillment of family/ parenting / caregiving duties.
Attention to financial responsibilities/household obligations.
Attention to physical well-being/health/exercise/sleep/ diet .
Ability to engage in pleasurable activities/hobbies/interests/rest and relaxation.

When any of all of these areas of daily living are impacted by anxiety, we narrow our lives and experiences and, in a sense, live incompletely, as certain elements of our daily lives fall by the wayside. We focus inordinately on our worries, which obscures these other important parts of our lives.

This begs the question of what we can do when we recognize that our daily functioning is being negatively affected by worry and anxiety.

Honestly assess what is happening in our lives (work, family, personal relationships, physical health, financial strain, etc.). Paying attention to the specific elements that are causing us to stress and worry is an integral step in formulating a plan for reducing the negative impact of overwhelm.
Envision what restored daily functioning might look like. Think about how we would like our lives to look if we were at optimal functioning. Perhaps this means we would have time to spend with our families, to exercise and engage in personal interests, and to leave work “at the door” when we leave the office. Having a sense of what restored functioning would look like can help us to think pragmatically about how to implement positive changes.
Identify areas where we need support. If, for instance, we are struggling with how many hours we are working, we may consider using a personal day, speaking to a supervisor, or thinking about how to implement stronger boundaries with our jobs. When we look honestly at how much time and energy are devoted to different areas of our lives, we can acknowledge where help is needed.
Implement a plan for stress reduction. As a new therapist, I routinely saw upwards of 30 clients a week, often seeing eight or nine consecutively without a break. I reached a point where I had to make a change, as it became clear that this type of schedule was unsustainable and was disrupting my daily functioning. My plan started small: begin scheduling a break in the middle of the day to eat lunch and take a break. From there, I worked to reduce my caseload to a more manageable number. It was only through an honest self-assessment of my stress level that I was able to envision how my life could be bettered by making changes to reduce my susceptibility to burnout .

When we are able to adequately reduce anxiety, stress, and overwhelm, our daily functioning reaches a level of restoration in which we are able to fulfill obligations, be present in our experiences, and devote time and energy to the things we want to do without undue focus on worries, stressors, or future potentialities. Signs of restored daily functioning might include:

More time to devote to interests, hobbies, and self-care.
Reduced time focusing on work-related worries and anxiety.
Stronger boundaries with work communication and working after-hours.
Better focus on personal hygiene, physical activity, and physical well-being.
More balance between work, family, and self.
Less focus and fixation on future scenarios (“what-ifs”) and more attention to the present moment (“what is").

Phil Lane, MSW, LCSW, is a psychotherapist in private practice and the author of the book, Understanding and Coping with Illness Anxiety.

Find a Therapist
Find a Treatment Center
Find a Psychiatrist
Find a Support Group
Find Teletherapy
United States
Brooklyn, NY
Chicago, IL
Houston, TX
Los Angeles, CA
New York, NY
Portland, OR
San Diego, CA
San Francisco, CA
Seattle, WA
Washington, DC
Asperger's
Bipolar Disorder
Chronic Pain
Eating Disorders
Passive Aggression
Personality
Goal Setting
Positive Psychology
Stopping Smoking
Low Sexual Desire
Relationships
Child Development
Therapy Center NEW
Diagnosis Dictionary
Types of Therapy

Understanding what emotional intelligence looks like and the steps needed to improve it could light a path to a more emotionally adept world.

Coronavirus Disease 2019
Affective Forecasting
Neuroscience

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

Advanced Search
Journal List
HHS Author Manuscripts
PMC10159010

How Does Yoga Reduce Stress? A Clinical Trial Testing Psychological Mechanisms

Crystal l. park.

1 Department of Psychological Sciences, University of Connecticut

Lucy Finkelstein-Fox

Shane j. sacco.

2 Department of Allied Health Sciences, University of Connecticut

Tosca D. Braun

3 Warren Alpert Medical School of Brown University

4 Department of Psychiatry, Massachusetts General Hospital

Yoga interventions can reduce stress, but the mechanisms remain largely unidentified. Understanding how yoga works is essential to optimizing interventions. The present study tested five potential psychosocial mechanisms (increased mindfulness, interoceptive awareness, spiritual well-being, self-compassion, and self-control) that have been proposed to explain yoga’s impact on stress.

Forty-two participants (62% female; 64% White) in a yoga program for stress reduction completed surveys at baseline (T1), mid-intervention (T2), and post-intervention (12 weeks; T3). We measured both perceived global stress and stress reactivity. Changes were assessed with paired t-tests; associations between changes in mechanisms were tested in residual change models.

Only stress reactivity decreased, on average, from T1 to T3. Except for self-compassion, all psychosocial mechanisms increased from T1 to T3, with minimal changes from T2 to T3. Except for self-control, increases in each mechanism were strongly associated with decreases in both measures of stress between T1 and T2 and decreases in perceived global stress from T1 to T3 (all p ’s<.05)

Conclusions:

Increased psychosocial resources are associated with stress reduction. Yoga interventions targeting these resources may show stronger stress reduction effects. Future research should test these linkages more rigorously using active comparison groups and larger samples.

Stress is a commonly-experienced aversive state purported to impact the course of disease and illness at a systemic level ( Cohen, Edmondson, & Kronish, 2015 ; Muscatell & Eisenberger, 2012 ). Indeed, many health conditions have been shown to directly relate to or be exacerbated by stress (e.g., migraine, gastrointestinal problems, hypertension), and even health conditions that are not overtly related to stress often have close linkages ( Muscatell & Eisenberger, 2012 ). For example, acute pain severity is highly influenced by perceived stress ( Wieland et al., 2017 ; Woda, Picard, & Dutheil, 2016 ). In addition, stress itself is widely considered to constitute a problematic health condition ( Goyal et al., 2014 ).

Stress is one of the most commonly studied outcomes of yoga practice ( Domingues, 2018 ) and yoga interventions targeting stress reduction have generally demonstrated favorable findings ( Chong, Tsunaka, Tsang, Chan, & Cheung, 2011 ; Pascoe & Bauer, 2015 ; Pascoe, Thompson, & Ski, 2017 ). Indeed, randomized controlled trials (RCTs) of yoga conducted across varied samples, including healthy stressed individuals, employees, students, pregnant women, people in treatment for cancer, and people with hypertension, arthritis, headaches, and asthma, have demonstrated significant reductions in self-reported stress (see Pascoe & Bauer, 2015 , for a review).

Importantly, self-reported stress can reflect either global perceptions of psychological pressure in one’s life (e.g., feeling overwhelmed, unable to keep up) or physiological arousal that leaves one overly-reactive to provocations (e.g., feeling agitated, intolerant, touchy). While related, these aspects of stress are distinct in terms of individuals’ experience ( Oken, Chamine, & Wakeland, 2015 ; Flett, Nepon, Hewitt, & Fitzgerald, 2016 ). consequences ( Adam & Epel, 2007 ; Crawford & Henry, 2003 ), and treatment approaches ( Chiesa & Seretti, 2009 ; Iglesias et al., 2012 ; Lindsay, Young, Smyth, Brown, & Creswell, 2018 ). Yoga research has generally focused on the former (e.g., Chong et al., 2011 ), but people tend to find both aspects of stress aversive and troubling ( Aldwin, 2007 ; Cohen, Kamarck, & Mermelstein 1983 ; Lovibond & Lovibond, 1994). Thus, assessing the impact of yoga on both aspects of stress may be useful, given that yoga’s effects on each aspect is distinct and might act through different mechanisms of change. For example, stress reactivity may be impacted more strongly by physical posture and breathwork than would psychological perceived stress. In turn, elements of yoga that target cognitive-affective aspects of stress appraisals, such as mindfulness, self-compassion, and meditation, may exert stronger direct effects on psychological stress than on stress reactivity. However, these differences remain purely speculative in the absence of empirical research and merit formal tests.

Indeed, despite the considerable amount of research on yoga and stress, we know little about how yoga reduces stress. Until recently, researchers focused primarily on testing yoga’s efficacy for improving health status across a variety of health problems and conditions, with little emphasis on cognitive-behavioral mechanisms of change. As efficacy is increasingly demonstrated in clinical trials research, understanding how yoga produces salutary effects is emerging as an important next step toward optimizing interventions offered to the public. To date, surprisingly few studies have focused on identifying the mechanisms through which yoga reduces stress ( Riley & Park, 2015 ), and of those, most lacked adequate sample sizes, time frames, and theoretical bases. However, multiple theoretical perspectives have been advanced regarding the psychological mechanisms that might underlie yoga’s effects on stress ( Gard, Noggle, Park, Vago, & Wilson, 2014 ; Kinser et al., 2012 ; Streeter et al., 2012 ). Among the most promising are increased mindfulness, interoceptive awareness, self-compassion, self-control, and spiritual well-being.

First, myriad studies have shown that yoga practice is positively related to mindfulness. Several studies have tested whether mindfulness mediates yoga’s effects on outcomes such as post-traumatic stress (PTS) symptoms, with mixed effects (e.g., Mehling et al., 2018 ; Dick et al., 2014 ), but we were not able to locate studies that specifically examined mindfulness as a mechanism of yoga’s effects on stress per se. Interoceptive awareness, the representation of the body’s internal states, has been suggested as a related potential mechanism of action for body-based mindfulness interventions, particularly those with a strong physical basis such as yoga ( Mehling et al., 2011 ). Improving awareness of one’s internal states may provide opportunities to engage in mind-body skills that allow yoga practitioners to consciously intervene in their own stress reduction. One clinical trial of war veterans with PTSD found that interoceptive awareness, along with mindfulness, corresponded with reductions in symptoms in an integrated exercise program that included some elements of yoga (Neukirch, Reid, & Shires, 2018). Again, we were unable to find any formal tests of interoceptive awareness as a mechanism of change that may predict stress reduction in a yoga intervention.

Improvement in self-compassion, or mindful self-kindness, has also been suggested to be a mechanism by which yoga reduces stress ( Braun et al., 2016 ; Neff & Germer, 2012 ). Self-compassion involves being caring and compassionate towards oneself in the face of hardship or perceived inadequacy ( Neff, 2003 ). Acting with kindness towards oneself is associated with less stress reactivity and better coping skills ( Allen & Leary, 2010 ). We located one study that tested self-compassion as a mediator of yoga’s effects on stress, a longitudinal study of 33 young adults in a four-month residential yoga intervention program; increases in self-compassion were associated with reductions in perceived stress ( Gard et al., 2012 ).

Self-control and spiritual well-being have also been theoretically and empirically linked to yoga practice ( Gard et al., 2014 ; Gerbarg & Brown, 2015 ), but we were unable to find any studies directly testing mechanistic linkages to stress. Self-control, the capacity to consciously alter or override one’s incipient responses, especially to bring them into line with one’s goals or standards, is related to lower stress levels ( Tangney et al., 2004 ; Park et al., 2016 ) and several studies have suggested that yoga can increase self-control (e.g., Park et al., 2017 ; Ramadoss & Bose, 2010 ). Copious empirical evidence links higher spiritual well-being with lower levels of stress (e.g., Park & Slattery, 2013 ), and several studies have demonstrated that yoga is associated with positive aspects of spirituality ( Büssing, Hedtstück, Khalsa, Ostermann, & Heusser, 2012 ; Gaiswinkler & Unterrainer, 2016 ). Thus, while not directly tested to date, these pathways—self-control and spiritual well-being—may indeed explain yoga’s effects on stress.

The present study set out to examine these five potential mechanisms of change (mindfulness, interoceptive awareness, spiritual well-being, self-compassion, and self-control) that may be associated with the effects of a 12-week yoga intervention and subsequent stress reduction. We elected to use an intervention based on Kripalu yoga, a practice that is relatively high in body awareness, acceptance/self-compassion, breathwork, mental and emotional awareness, and active postures compared to other yoga types ( Park et al., 2018 ). Based on previous literature, we hypothesized that: 1) all five psychosocial mechanisms, as well as indicators of two different aspects of stress, would significantly improve over the course of the intervention; 2) changes in psychosocial mechanisms from pre- to mid-treatment would be associated with changes in both indicators of stress from pre- to mid-and pre- to post-treatment.

Participants and procedures

The current study comprises a secondary analysis of a parent study assessing the effects of yoga on dietary change, which will be reported elsewhere (Masked for review, under review). Recruitment from two sites in the Northeastern US – an urban medical school in MA and a rural public university in CT – began in April 2015 and final assessments were completed in October 2016. Recruitment ads for a stress reduction program were posted via public transit and direct mail and online advertisements. Study candidates completed a web survey and phone screen, and for those remaining eligible, an in-person screening appointment where they provided written informed consent. Final eligibility was then confirmed following completion of the Mini International Neuropsychiatric Interview (MINI; Sheehan et al., 1998 ), the Eating Disorders module from the DSM-IV Structured Clinical Interview (SCID; First, Spitzer, Gibbon, & Williams, 1995 ), and a BMI assessment. Participants were required to be between 23–67 years of age and to be seeking stress reduction.

Exclusion criteria, based on the parent study, encompassed an exercise regimen of more than 180 minutes per week (based on Haskell et al., 2007 ), consumption of 5 or more servings of fruits and vegetables, current diagnosis of psychiatric illness or prior eating disorder diagnosis as determined by the MINI or SCID eating disorders module, significant prior meditation or yoga experience (defined as ≥12 classes in last 3 years or more than 20 classes in lifetime), medications that altered appetite, and medical conditions that would limit the ability to exercise or do yoga. Following screening, 117 volunteers provided informed consent, of whom 84 were randomized. Participant flow is shown in Figure 1 .

An external file that holds a picture, illustration, etc.
Object name is nihms-1891283-f0001.jpg

Participant Flow (CONSORT diagram)

Participants were randomized with equal allocation ratio into one of three home practice groups for the program duration: “low practice” (10 min./day six days per week), “medium practice” (40 min./day three days per week, and 10 min./day three days a week), and “high practice” (40 min./day six days per week). The parent study was conservatively powered on an N of 135 participants to detect significant differences in change between home practice groups. In light of the present study’s focus on covariance between stress and potential mechanisms over the course of the yoga program, the analyses reported here were collapsed across randomization groups to preserve statistical power.

Following initial baseline assessment (T1), this study included two additional assessment points: at 8 weeks (T2; mid-treatment), and at 12 weeks (T3; post-treatment). Participants were remunerated up to $100 for completing study assessments and received the yoga program for free. The study protocol was approved by both sites’ Institutional Review Boards (IRBs) and monitored by Westat. The protocol is registered in Clinicaltrials.gov ( {"type":"clinical-trial","attrs":{"text":"NCT02098018","term_id":"NCT02098018"}} NCT02098018 ).

Yoga intervention

The Kripalu yoga intervention integrated yoga practice with yoga philosophy pertinent to self- and affect-regulation to decrease physiological arousal and enhance well-being. Participants learned how to monitor and modulate mental, emotional, and physiological responses moment-to-moment through in-class experiential exercises and prescribed home yoga practice. The intervention was 12 weeks in length and consisted of two consecutive segments. The first segment was a manualized eight-week intervention designed to serve as an introduction to mindful yoga that was initially created and piloted by the Kripalu Center for Yoga. The intervention was slightly modified for use with a high-stress population. Each of the eight once-weekly, two-hour sessions included 100–115 minutes of yoga practice (meditation, breathing exercises, postures, relaxation) and 25–30 min. of theory/philosophy. The second segment began at the ninth week, comprised four weeks of 90-minute, once-weekly sessions of yoga practice (no didactic content), and concluded at 12 weeks. Participants who completed nine or more sessions from the first and/or second segment of the yoga intervention were considered to have received the full “dose” of the intervention and were categorized as compliant to the study protocol. Treatment compliance had no bearing on the analyses reported here; all participants who completed post-treatment assessments were retained for analyses (see Data Analysis section).

Psychological Stress and Stress Reactivity were assessed, respectively, with a measure tapping into global psychological appraisals of one’s life as overwhelmingly stressful (the Perceived Stress Scale; PSS; Cohen & Williamson, 1988 ) and a measure tapping descriptions of oneself as stress-reactive (stress subscale of the Depression Anxiety Stress Scale; DASS-21; Lovibond & Lovibond, 1995 ). The PSS contains 10 items, rated from 0 ( Never ) to 3 ( Very Often ); higher sum scores indicate higher levels of overall perceived stress. The PSS has good reliability and validity ( Cohen & Williamson, 1988 ). The PSS is designed to measure subjective perceptions of stress depending on changes in environmental stressors and coping resources ( Cohen & Williamson, 1988 ); thus, no standardized clinical cut-offs exist for this measure. Within the present study, alphas for the PSS were .90, .93, and .91, at T1, T2, and T3, respectively. The DASS-21 stress subscale consists of 7 of the 21 items of the DASS-21 scale and assesses stress in terms of stress reactivity and arousal (e.g., “touchy”, “agitated”, “difficult to relax”). Items are rated from 0 ( did not apply to me at all ) to 3 ( applied to me very much, or most of the time ); higher sum scores indicate higher levels of stress. Clinical cut-offs for stress scores on the DASS were developed by authors, including: normal (0–14) mild (15–18), moderate (19–25), severe (26–33), and extremely severe (34+) ( Lovibond & Lovibond, 1995 ). The DASS subscales have good reliability and validity ( Lovibond & Lovibond, 1995 ). Within the present study, alphas for the DASS stress subscale were .83, .85, and .88, at T1, T2, and T3, respectively.

Mindfulness was assessed with the 24-item Five-Facet Mindfulness Questionnaire, short form (FFMQ-SF; Bohlmeijer, ten Klooster, Fledderus, Veehof, & Baer, 2011 ), a revision of the original 39-item FFMQ ( Baer, Smith, Hopkins, Krietemeyer, & Toney, 2006 ). The FFMQ taps into five domains of mindfulness (acting with awareness, describing, observing, non-reacting, non-judging) and produces a global score. Item responses range from 1 ( Never or Very Rarely True ) to 5 ( Very Often or Always True ); higher average scores indicate greater mindfulness. The FFMQ global score has demonstrated good validity and reliability ( Bohlmeijer et al., 2011 ). In the present study, alphas were .88, .89, and .90, at T1, T2, and T3, respectively.

Interoceptive awareness was assessed with the 32-item Multi-dimensional Assessment of Interoceptive Awareness Scale (MAIA; Mehling et al., 2012 ). Item responses range from 1 ( Never ) to 5 ( Always ). Higher scores indicate more interoceptive awareness. The MAIA’s global domain, used in the present study, sums eight subscales (noticing, not distracting, not worrying, attention regulation, emotional awareness, self-regulation, body listening, and trusting). The MAIA global scale demonstrates good internal consistency ( Mehling et al., 2012 ). In the present study, alpha was .93, .94, and .93 at T1, T2, and T3, respectively.

Spiritual well-being was assessed with the 12-item Functional Assessment of Chronic Illness Therapy - Spiritual Well-Being (FACIT-Sp; Peterman, Fitchett, Brady, Hernandez, & Cella, 2002 ). Item responses range from 0 ( Not at all ) to 4 ( Very much ), with higher sum scores indicating greater spiritual well-being. The FACIT-Sp generates subscales for meaning, peace, and faith and an overall score, the latter of which was used in the present study. The validation study indicated good internal consistency for the overall scale ( Peterman et al., 2002 ). Within the present study, alphas were .83, .86, and .88, at T1, T2, and T3, respectively.

Self-compassion was assessed with the 12-item Self-Compassion Scale, Short Form (SCS-SF; Raes, Pommier, Neff, & Van Gucht, 2011 ), a revision of the original 26-item SCS ( Neff, 2003 ). Item responses range from 1 ( Almost Never ) to 5 ( Almost Always ), with higher scores indicating greater self-compassion. The SCS generates six subscales (self-kindness, self-judgment, common humanity, isolation, mindfulness, over-identification) and a global score, the latter used in the present study. The SCS-SF demonstrated good internal consistency for the global scale in the validation study ( Raes et al., 2011 ). Within the present study, alphas were .89, .87, and .82, at T1, T2, and T3, respectively.

Self-control was assessed with the 10-item Brief Self-Control Scale (BSCS; Tangey et al., 2004). Items are rated from 1 ( Not at all like me ) to 5 ( Very much like me ) and summed; higher scores indicate higher self-control. The BSCS produces two subscales and an overall score, the latter reported here. The BSCS has demonstrated adequate reliability and validity (Tangey et al., 2004). Within the present study, alphas were .78, .86, and .88, at T1, T2, and T3, respectively.

Recruitment and retention

At study start, a total of 84 participants attended at least one intervention session and elected to proceed with study participation. Those who did not complete T3 assessments ( n =42) evidenced no significant variance on baseline demographics or study variables relative to intervention completers ( n =42; p ’s>.11). Information on attendance and study attrition and completion rates are detailed in Figure 1 .

Data Analysis

Descriptive statistics were conducted to describe demographics and study variables at all timepoints; when available, clinical cut-offs were used to interpret magnitude of study variables. Paired t-tests were conducted to determine if study variables differed between T1 and T2, T2 and T3, and T1 and T3; effect sizes were calculated using Cohen’s d to describe standardized magnitudes of change between time-points. Study variables were inter-correlated using Pearson’s r to determine if any meaningful relationships existed at T1. Research site (i.e., rural vs. urban) and cohort (i.e., time of year that the intervention was completed) were also examined as potential covariates to study variable at T1 by conducting a series of ANOVAs. Correlational analyses were carried out to test primary mechanism of change hypotheses. For each mechanism and stress measure, standardized residuals were obtained by regressing observed endpoints on baseline scores (e.g., T2 PSS scores were regressed on T1 PSS scores). Standardized residuals of mechanisms and stress measures were correlated using Pearson’s r ; correlations were compared between stress measures using Z-tests. Standardized residuals of mechanisms were also inter-correlated using Pearson’s r to determine if any meaningful relationships existed between mechanisms of change. Missing data within those who completed T3 assessments was negligible (1 to 2 missing values, <=5 for few variables), and thus list-wise deletion was utilized. Alpha for two-sided tests was set to .05. All analyses were conducted in IBM SPSS Statistics for Windows, Version 26.0.

Descriptive Information

Descriptive statistics and change in all study variables is outlined in Table 1 .

Participant Characteristics and Estimated Differences between Timepoints.

Note. Bolded values indicate p<.05

Demographics.

Participants who completed the intervention were predominantly female (61.9%; n =26), were an average age of 41.0 years old (SD=14.2), and had an average baseline BMI of 25.2 (overweight; SD=4.9). A majority of participants were White (64.3%; n =27), with fewer being Asian (11.9%; n =5), biracial (11.9%; n=5), or reporting another (4.8%; n =2) or no race (7.1%; n =3). Few participants were Hispanic/Latino (9.5%; n =4). Over half of participants had a graduate degree (50.0%; n =21) or a 4-year undergraduate degree (33.3%; n=14), and fewer had a 2-year undergraduate degree (11.9%; n =5), some college completion (2.4%; n =1), or a high school diploma (2.4%; n =1). Most participants were either currently married (47.6%; n =20) or never married (40.5%; n =17); few participants were divorced (7.1%; n =3) or separated (2.4%; n =1).

As measured by the DASS, stress reactivity was mild to moderate at T1, and remained similar between T1 and T2, and T2 and T3. However, decreases in stress reactivity were moderate from T1 to T3. Psychological stress as measured by the PSS declined over timepoints, but these small effect sizes were not statistically significant.

Mechanisms.

Mindfulness was similar at T1 and T2, increased slightly between T2 and T3, and between T1 and T3. Interoceptive awareness greatly increased from T1 to T2 and remained similar between T2 and T3; increases between T1 and T3 were large, and similar to the observed increases between T1 and T2. Spiritual well-being increased with only small effect sizes from T1 to T2 and remained similar between T2 and T3; increases between T1 and T3 were moderate. Self-compassion remained statistically unchanged at T1, T2, and T3. Self-control also remained similar at T1, T2, and T3, with a small statistically significant increase from T1 to T3.

Differences in study variables by research site and cohort.

Regarding differences in study variables between research site and cohort, only baseline self-control differed by research site, in that the rural site (M=46.5, SD=8.5) reported significantly greater self-control than the urban site (M=39.6, SD=5.7), F (1,39)=8.5, p =.006. No study variables differed by cohort.

Cross-Sectional Correlations among Mechanisms and Stress at Baseline

Inter-correlation of mechanisms with stress..

Stress reactivity and psychological stress (as measured by DASS-21 and PSS, respectively) were strongly correlated at T1 ( r =0.72, p <.001). Higher psychological stress was related to lower levels of most psychosocial mechanisms: mindfulness ( r =−0.59, p <.001), spiritual well-being ( r =−0.47, p =.002), self-compassion ( r =−0.63, p <.001), and self-control ( r =−0.45, p =.004), but was not significantly related to interoceptive awareness ( p =.24). Associations with stress reactivity were similar for mindfulness ( r =−0.42, p =.007), self-compassion ( r =−0.47, p =.002), and self-control ( r =−0.33, p =.04), but stress reactivity was not significantly related to interoceptive awareness or spiritual well-being at T1 ( p ’s>.10).

Intercorrelation of mechanisms

Mindfulness was positively associated with spiritual well-being ( r =0.58, p <.001), self-compassion ( r =0.77, p <.001), and self-control at T1 ( r =0.50, p =.001). Spiritual well-being was also positively associated with self-compassion ( r =0.54, p <.001) and self-control ( r =0.38, p =.02). Self-compassion was positively correlated with self-control ( r =0.43, p =.005). Interoceptive awareness was only marginally positively related to self-compassion ( r =0.31, p =.052). No other relationships were statistically significant ( p ’s>.14).

Intercorrelation of Residual Change in Mechanisms and Stress

Intercorrelation of changes in mechanisms..

As shown in Table 2 , many inter-correlations between residual changes in mechanisms from T1 to T2 were noted: increases in self-compassion were associated with increases in mindfulness, interoceptive awareness, and spiritual well-being. Increases in spiritual well-being also correlated with increases in self-control. Increases in mindfulness and interoceptive awareness were marginally associated ( p =.053).

Inter-correlations between Residual Changes in Psychosocial Mechanisms from T1 to T2

Bolded values indicate p<.05.

Intercorrelation of changes in stress

As shown in Table 3 , decreases in psychological stress were strongly associated with decreases in stress reactivity from T1 to T2, T2 to T3, and T1 to T3. Decreases in psychological stress from T1 to T3 were also strongly associated with decreases in stress reactivity from T2 to T3, and vice versa, decreases in stress reactivity from T1 to T3 were strongly associated with decreases in psychological stress from T2 to T3. Residual changes in neither stress measures from T1 to T2 associated with changes in the other from T2 to T3 or T1 to T3.

Inter-correlations between Residual Changes in Stress

Bolded values indicate p<.05

Intercorrelation of changes in mechanisms with changes in stress.

As shown in Table 4 , residual increases from T1 to T2 in all psychosocial mechanisms except self-control were significantly associated with residual decreases in both stress reactivity and global psychological stress from T1 to T2. The correlation between T1-T2 residual change in spiritual well-being and T1-T2 change in stress was greater for psychological stress than stress reactivity. Residual changes in mechanisms from T1 to T2 were not associated with residual changes in stress reactivity or psychological stress from T2 to T3. For psychological stress, associations between T1 to T2 changes in mechanisms and T1 to T3 changes in stress followed the same pattern of statistical significance as did correlations with T1 to T2 changes in psychological stress (i.e., all residual change scores were significantly associated, excepting self-control). In contrast, only T1 to T2 change in self-compassion was significantly associated with T1 to T3 change in stress reactivity. The correlation between T1-T2 residual change in mindfulness and T1-T3 change in stress was greater for psychological stress than stress reactivity.

Associations between Post-Intervention Changes in Psychological Stress (PSS) and Stress Reactivity (DASS) and Changes in Proposed Mechanisms

These results advance yoga intervention research by providing essential information on psychological mechanisms through which yoga practice may reduce perceived stress. Most importantly, we demonstrate the usefulness of examining psychosocial mechanisms of change in a clinical trial and provide potentially fruitful direction for future research to build on the current evidence base regarding yoga and stress.

First, while stress reactivity and psychological stress are fairly strongly related, we found different patterns of yoga’s effects on these two outcomes. Although both aspects of stress declined across the intervention timepoints, only the reduction in stress reactivity was statistically significant across the entire sample. Yet, generally, we found stronger associations of within-person changes in psychosocial resources with perceived psychological stress than with stress reactivity, suggesting that cognitive/emotional aspects of stress may be most directly linked to the proposed “active ingredients” of yoga intervention.

Such differential findings may also be related to the type of yoga that we tested. Kripalu yoga emphasizes a self-compassionate stance toward stressful experience, such that participants are encouraged to non-judgmentally attend to and accept stressful experience while using breathwork and posture to regulate the effects of stress on well-being ( Faulds, 2005 ). Future research might compare different yoga interventions that are optimized more for reactivity or psychological stress to determine differential effects. For example, an intervention encouraging participants to direct attention away from stressful experience or reappraise perceptions of events as stressful might have stronger effects on perceptions of psychological than physiological stress. These findings also suggest that researchers should be more explicit about the type of stress that they are intent on studying and may have implications for future review articles, which might find differential effects for yoga on different dimensions of stress.

Second, all of the psychological resources included here increased over the course of the intervention, as we would expect based on previous research (e.g., Gard et al., 2012 ; DiGreeson et al, 2011 ; Dick et al., 2014 ; Mehling et al., 2018 ; Park et al., 2018 ; Bussing et al., 2012 ). The exception to this general trend was self-compassion, which did not significantly increase over the course of the intervention, in contrast to prior yoga studies (e.g., Gard et al., 2012 ). All of these increases became larger—and several only then large enough to be statistically significant at T3, suggesting that length of practice has a meaningful influence on steady change in psychological resources. In the present study, interoceptive awareness demonstrated by far the largest effect size from pre- to post-intervention (d = 0.98); in contrast, mindfulness, self-compassion, and self-control all demonstrated only small effect sizes (ds = 0.28, 0.28, 0.29). Future studies will benefit from examining change in these same proposed psychosocial mechanisms following different types of yoga (e.g., Bikram, pranayama), since it is likely that different practices will have very different effects on psychosocial mechanisms and change in perceived stress and stress reactivity ( Park, Finkelstein-Fox, Groessl, Lee, & Elwy, 2020 ). It may also be the case that change in psychological responses to stress (i.e., mindfulness, self-compassion, self-control) after a longer periods of regular yoga practice than what was necessitated by the present study, whereas attention to internal states (i.e., interoceptive awareness) changes more quickly. It will be very interesting for future research to examine change in mindfulness, self-compassion, and self-control after several months of regular yoga practice, particularly among a non-clinical sample of novice practitioners like the one included here.

Of note, the results reported here suggest that most of the hypothesized mechanisms demonstrated patterns of change concurrent with, rather than prior to, changes in stress. This finding highlights an important distinction between Kripalu yoga’s utility as a stress management resource vs. standalone clinical intervention. Even a single session of yoga practice has demonstrated significant pre-post effects on positive and negative affective experience ( Park et al., 2020 ), and regular, repeated yoga practice has been associated with positive stress-related outcomes ( Gard et al., 2014 ; Greenberg et al., 2018 ). In contrast to talk-based cognitive behavioral therapies that provide explicit discussion of disordered emotion regulation abilities ( Hofmann, Sawyer, Fang, & Asnaani, 2012 ), mechanisms of yoga interventions such as Kripalu may act much more quickly upon perceptions of acute stress by directing non-judgmental attention toward physical experience, and thus require different methods of assessing change in real time (e.g., ecological momentary assessment, measurement of affective states pre- and post- practice). Future research on yoga interventions will benefit from creative measurement individual variation in cognitions, affect, and stress reactivity.

Third, all of the proposed mechanisms, with the exception of self-control, demonstrated substantial associations with both aspects of stress by T2 and continued to show statistically significant associations only with psychological stress by T3. Changes in self-compassion continued to correlate with change in both aspects of stress by T3. Importantly, the strength of covariation between mechanisms and both psychological stress and stress reactivity was similar. This is with exception to the association between residual change in spiritual well-being and mindfulness from T1 to T2 and change in stress from T1 to T2 and T1 to T3, respectively, which was much stronger for psychological stress than for stress reactivity. This finding supports the possibility that spiritual well-being and mindfulness may more strongly act upon psychological stress within a temporal pathway, in contrast to more simultaneous covariation demonstrated with stress reactivity.

Finally, by examining the intercorrelations between changes in multiple mechanisms over time, we also highlight the extent to which various psychosocial resources covary during the course of a mindful yoga intervention; for example, results suggest that self-compassion and mindfulness may change at a similar rate, whereas changes in mindfulness and self-control or spiritual well-being may follow different patterns of change across a 12-week yoga intervention. These preliminary findings may have implications for the design of larger clinical trials targeting psychosocial mechanisms of change in stress; it will be particularly interesting for future studies to test the covariance between distinct correlated variables such as self-compassion and interoceptive awareness over multiple timepoints to parse apart causal or lagged associations between these constructs.

Limitations of our study must be acknowledged. We do not have a control group against which we could compare our findings, although it would be valuable to determine the extent to which stress and psychosocial resources changed over time independently of the yoga intervention. The strongest design would be an active comparison arm that controlled for nonspecific effects, but even an assessment-only group would allow ruling out temporal or seasonal effects ( Park et al., 2014 ). Our study was also underpowered to detect longitudinal effects of smaller magnitude due to a high non-completion rate and participant scheduling difficulties; it is likely that a larger sample would have elucidated more reliable changes in both stress and psychological resources and provided more generalizable findings. Our measures were all self-report and thus liable to all the biases inherent in self-report measures ( Paulhus & Vazire, 2007 ). Further, our set of psychological resources, while broad, likely leaves out other important psychological resources that may be important mechanisms of yoga’s effects on stress. In addition, we tested only one type of yoga; different types of yoga may have different effects on stress and resources. Further, our findings were associative and causal inferences cannot be directly made.

Although these many limitations render our findings suggestive rather than conclusive, they provide direction for subsequent research aimed at better understanding how yoga exerts salutary effects on stress. Future research should examine each of the potential mechanisms identified in the present study, as all five showed significant increases over time and four demonstrated significant roles within the hypothesized pathways linking yoga and stress. Clinical trials to test these pathways should be fully powered and include a strong comparison condition to verify them. Testing different types of yoga with different emphases may further illuminate which aspects of yoga exert stronger effects on specific psychological resources.

These results may have clinical implications for yoga therapists as well as other healthcare providers aiming to reduce stress. Given the different patterns demonstrated in our data, therapists treating stress-related complaints might consider the different kinds of impact that psychological resources have on global psychological stress and reactivity, which have the potential to inform treatment planning and even intervention optimization for highly stressed populations.

Our results suggest that Kripalu yoga may have beneficial effects for positive psychological resources such as interoceptive awareness, mindfulness, spiritual well-being, and self-compassion, all of which may have temporal effects on within-person change in perceived stress over time. Further, experiences of stress reactivity appear to decline significantly over the course of a mindful yoga intervention, suggesting that Kripalu yoga may be especially beneficial for individuals experiencing marked arousal and overreactions to stress exposure. Given increasing evidence of yoga’s effects on stress, future research may build on these results to better understand the specific pathways through which different aspects and types of yoga can reduce different types of stress, ultimately leading the way to personalized yoga interventions for stress reduction.

NIH NCCIH (grant 1R34AT007197)

Adam TC, & Epel ES (2007). Stress, eating and the reward system . Physiology & Behavior , 91 , 449–458. [ PubMed ] [ Google Scholar ]
Aldwin CM (2007). Stress, coping and development . New York, NY: Guilford. [ Google Scholar ]
Allen AB, & Leary MR (2010). Self-Compassion, stress, and coping . Social and Personality Psychology Compass , 4 , 107–118. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Baer RA, Smith GT, Hopkins J, Krietemeyer J, & Toney L (2006). Using self-report assessment methods to explore facets of mindfulness . Assessment , 13 , 27–45. [ PubMed ] [ Google Scholar ]
Bohlmeijer E, ten Klooster PM, Fledderus M, Veehof M, & Baer R (2011). Psychometric properties of the Five-Facet Mindfulness Questionnaire in depressed adults and development of a short form . Assessment , 18 , 308–320. [ PubMed ] [ Google Scholar ]
Braun TD, Park CL, Gorin AA, Garivaltis H, Noggle JJ, & Conboy LA (2016) Group-based yogic weight loss with Ayurveda-inspired components: A pilot investigation of female yoga practitioners and novices . International Journal of Yoga Therapy , 26 , 55–72. [ PubMed ] [ Google Scholar ]
Büssing A, Hedtstück A, Khalsa SBS, Ostermann T, & Heusser P (2012). Development of specific aspects of spirituality during a 6-month intensive yoga practice . Evidence-Based Complementary and Alternative Medicine, 2012 . [ Google Scholar ]
Chiesa A, & Serretti A (2009). Mindfulness-based stress reduction for stress management in healthy people: A review and meta-analysis . The Journal of Alternative and Complementary Medicine , 15 , 593–600. [ PubMed ] [ Google Scholar ]
Chong CSM, Tsunaka M, Tsang HW, Chan EP, & Cheung WM (2011). Effects of yoga on stress management in healthy adults: A systematic review . Alternative Therapies in Health and Medicine , 17 , 32–38. [ PubMed ] [ Google Scholar ]
Cohen BE, Edmondson D, & Kronish IM (2015). State of the art review: Depression, stress, anxiety, and cardiovascular disease . American Journal of Hypertension , 28 , 1295–1302. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Cohen S, Kamarck T, Mermelstein R (1983). A global measure of perceived stress . Journal of Health and Social Behavior , 24 , 385–396. [ PubMed ] [ Google Scholar ]
Cohen S, Williamson G. (1988). Perceived stress in a probability sample of the United States. In Spacapan S & Oskam S (Eds.), The social psychology of health: Claremont symposium on applied social psychology . 31–67. Sage: Newbury Park, CA. [ Google Scholar ]
Crawford JR, & Henry JD (2003). The Depression Anxiety Stress Scales (DASS): Normative data and latent structure in a large non clinical sample . British Journal of Clinical Psychology , 42 , 111–131. [ PubMed ] [ Google Scholar ]
Dick AM, Niles BL, Street AE, DiMartino DM, & Mitchell KS (2014). Examining mechanisms of change in a yoga intervention for women: The influence of mindfulness, psychological flexibility, and emotion regulation on PTSD symptoms . Journal of Clinical Psychology , 70 , 1170–1182. [ PubMed ] [ Google Scholar ]
DiGreeson JM, Webber DM, Smoski MJ, Brantley JG, Ekblad AG, Suarez EC, & Wolever RQ (2011). Changes in spirituality partly explain health-related quality of life outcomes after Mindfulness-Based Stress Reduction . Journal of Behavioral Medicine , 34 , 508–518. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Domingues RB (2018). Modern postural yoga as a mental health promoting tool: A systematic review . Complementary Therapy and Clinical Practice , 31 , 248–255. [ PubMed ] [ Google Scholar ]
Faulds R (2005). Kripalu yoga: A guide to practice on and off the mat . New York, NY: Bantam Dell. [ Google Scholar ]
First MB, Spitzer R, Gibbon M, & Williams JB (1995). Structured clinical interview for DSM-IV Axis I disorders—Patient edition (SCID—I/P, version 2.0) . New York, NY: New York State Psychiatric Institute. [ Google Scholar ]
Flett GL, Nepon T, Hewitt PL, & Fitzgerald K (2016). Perfectionism, components of stress reactivity, and depressive symptoms . Journal of Psychopathology and Behavioral Assessment , 38 , 645–654. [ Google Scholar ]
Gaiswinkler L, & Unterrainer HF (2016). The relationship between yoga involvement, mindfulness and psychological well-being . Complementary Therapies in Medicine , 26 , 123–127. [ PubMed ] [ Google Scholar ]
Gard T, Brach N, Hölzel BK, Noggle JJ, Conboy LA, & Lazar SW (2012). Effects of a yoga-based intervention for young adults on quality of life and perceived stress: the potential mediating roles of mindfulness and self-compassion . The Journal of Positive Psychology , 7 , 165–175. [ Google Scholar ]
Gard T, Noggle JJ, Park CL, Vago DR, & Wilson A (2014) Potential self-regulatory mechanisms of yoga for psychological health . Frontiers in Human Neuroscience , 8 , 770. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Gerbarg PL, & Brown RP (2015). Yoga and neuronal pathways to enhance stress response, emotion regulation, bonding, and spirituality. In Horovitz EG & Elgelid S (Eds.), Yoga Therapy: Therapy and Practice (pp. 67–82). New York, NY: Routledge. [ Google Scholar ]
Greenberg J, Braun TD, Schneider ML, Finkelstein-Fox L, Conboy LA, Schifano ED, Park CL, & Lazar SW (2018). Is less more? A randomized comparison of home practice in a mind-body program . Behavior Research & Therapy , 111 , 52–56. doi: 10.1016/j.brat.2018.10.003 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
Goyal M, Singh S, Sibinga EM, Gould NF, Rowland-Seymour A, Sharma R, …Haythornthwaite JA (2014). Meditation programs for psychological stress and well-being: A systematic review and meta-analysis . JAMA Internal Medicine , 174 , 357–368. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Haskell WL, Lee I-M, Pate RR, Powell KE, Blair SN, Franklin BA, … Bauman A (2007). Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart Association . Medicine and Science in Sports and Exercise , 39 , 1423–1434. [ PubMed ] [ Google Scholar ]
Hofmann SG, Sawyer AT, Fang A, & Asnaani A (2012). Emotion dysregulation model of mood and anxiety disorders . Depression and Anxiety , 29 , 409–416. doi: 10.1002/da.21888 [ PubMed ] [ CrossRef ] [ Google Scholar ]
Iglesias SL, Azzara S, Argibay JC, Arnaiz ML, de Valle Carpineta M, Granchetti H, & Lagomarsino E (2012). Psychological and physiological response of students to different types of stress management programs . American Journal of Health Promotion , 26 , 149–158. [ PubMed ] [ Google Scholar ]
Kinser PA, Goehler LE, & Taylor AG (2012). How might yoga help depression? A neurobiological perspective . Explore , 8 , 118–126. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Lindsay EK, Young S, Smyth JM, Brown KW, & Creswell JD (2018). Acceptance lowers stress reactivity: Dismantling mindfulness training in a randomized controlled trial . Psychoneuroendocrinology , 87 , 63–73 [ PubMed ] [ Google Scholar ]
Lovibond PF, & Lovibond SH (1995). The structure of negative emotional states: comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories . Behavior Research and Therapy , 33 , 335–343. [ PubMed ] [ Google Scholar ]
Mehling WE, Price C, Daubenmier JJ, Acree M, Bartmess E, & Stewart A (2012). The Multidimensional Assessment of Interoceptive Awareness (MAIA) . PLoS One , 7 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
Mehling WE, Wrubel J, Daubenmier JJ, Price CJ, Kerr CE, Silow T, … & Stewart AL (2011). Body awareness: A phenomenological inquiry into the common ground of mind-body therapies . Philosophy, Ethics, and Humanities in Medicine , 6 , 6. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Mehling WE, Chesney MA, Metzler TJ, Goldstein LA, Maguen S, Geronimo C, … & Neylan TC (2018). A 12-week integrative exercise program improves self reported mindfulness and interoceptive awareness in war veterans with posttraumatic stress symptoms . Journal of Clinical Psychology , 74 , 554–565. [ PubMed ] [ Google Scholar ]
Muscatell KA, & Eisenberger NI (2012). A social neuroscience perspective on stress and health . Social and Personality Psychology Compass , 6 , 890–904. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Neff KD (2003). The development and validation of a scale to measure self-compassion . Self and Identity , 2 , 223–250. [ Google Scholar ]
Neff KD & Germer CK (2012). A pilot study and randomized controlled trial of mindful self-compassion program . Journal of Clinical Psychology , 69 , 28–44. [ PubMed ] [ Google Scholar ]
Neukirch N, Reid S, & Shires A (2019). Yoga for PTSD and the role of interoceptive awareness: A preliminary mixed-methods case series study . European Journal of Trauma & Dissociation , 3 , 7–15. [ Google Scholar ]
Oken BS, Chamine I, & Wakeland W (2015). A systems approach to stress, stressors and resilience in humans . Behavioural Brain Research , 282 , 144–154. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Park CL, Elwy AR, Maiya M, Sarkin AJ, Riley KE, Eisen SV, Gutierrez IA, .. Groessl EJ (2018). The Essential Properties of Yoga Questionnaire (EPYQ): Psychometric properties . International Journal of Yoga Therapy , 28 , 23–38. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Park CL, Finkelstein-Fox L, Groessl EJ, Lee SY, & Elwy AR (2020). Exploring how different types of yoga change psychological resources and emotional well-being across a single session . Complementary Therapies in Medicine , 49 , 102354. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Park CL, Groessl E, Maiya M, Sarkin A, Eisen S, Riley KE, & Elwy ER (2014). Comparison groups in yoga research: A systematic review and critical evaluation of the literature . Complementary Therapies in Medicine , 22 , 920–929. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Park CL, Riley KE, Braun TD, Jung JY, Suh HG, Pescatello LS, & Antoni MH (2017). Yoga and cognitive-behavioral interventions to reduce stress in incoming college students: A pilot study . Journal of Applied Biobehavioral Research , 22 , e12068. [ Google Scholar ]
Park CL, & Slattery JM (2013). Religion and emotional health and well-being. In Paloutzian RF & Park CL (Eds.), Handbook of the psychology of religion and spirituality , 2nd Edition (pp. 540–559). New York, NY: Guilford. [ Google Scholar ]
Park CL, Wright BEW, Pais J, & Ray DM (2016). Reciprocal relations between daily stressful events and ego depletion: A smartphone-based experience sampling study . Journal of Social and Clinical Psychology , 35 , 738–753. [ Google Scholar ]
Pascoe MC, & Bauer IE (2015). A systematic review of randomised control trials on the effects of yoga on stress measures and mood . Journal of Psychiatric Research ,, 68 , 270–282. [ PubMed ] [ Google Scholar ]
Pascoe MC, Thompson DR, & Ski CF (2017). Yoga, mindfulness-based stress reduction and stress-related physiological measures: A meta-analysis . Psychoneuroendocrinology , 86 , 152–168. [ PubMed ] [ Google Scholar ]
Paulhus DL, & Vazire S (2007). The self-report method. In Robins RW, Fraley RC, & Krueger R (Eds.), Handbook of research methods in personality psychology . 224–239. New York, NY: Guilford Press. [ Google Scholar ]
Peterman AH, Fitchett G, Brady MJ, Hernandez L, & Cella D (2002). Measuring spiritual well-being in people with cancer: The Functional Assessment of Chronic Illness Therapy--Spiritual Well-being Scale (FACIT-Sp) . Annals of Behavioral Medicine , 24 , 49–58. [ PubMed ] [ Google Scholar ]
Ramadoss R, & Bose B (2010). Transformative life skills: Pilot study of a yoga model for reduced stress and improving self-control in vulnerable youth . International Journal of Yoga Therapy , 20 , 73–78. [ Google Scholar ]
Raes F, Pommier E, Neff KD, & Van Gucht D (2011). Construction and factorial validation of a short form of the Self-Compassion Scale . Clinical Psycology and Psychotherapy , 18 , 250–255. [ PubMed ] [ Google Scholar ]
Riley KE, & Park CL (2015). How does yoga reduce stress? A systematic review of mechanisms of change and a guide to future inquiry . Health Psychology Review , 9 , 379–396. [ PubMed ] [ Google Scholar ]
Sheehan D, Lecrubier Y, Sheehan H, Amorim P, Janavs J, Weiller E, … Dunbar G (1998). The Mini-International Neuropsychiatric Interview (M.I.N.I.): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10 . Journal of Clinical Psychiatry , 59 , 22–23. [ PubMed ] [ Google Scholar ]
Streeter CC, Gerbarg PL, Saper RB, Ciraulo DA, & Brown RP (2012). Effects of yoga on the autonomic nervous system, gamma-aminobutyric-acid, and allostasis in epilepsy, depression, and post-traumatic stress disorder . Medical Hypotheses , 78 , 571–579. [ PubMed ] [ Google Scholar ]
Tangney JP, Baumeister RF, & Boone AL (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success . Journal of Personality , 72 , 271–324. [ PubMed ] [ Google Scholar ]
Wieland LS, Skoetz N, Pilkington K, Vempati R, D’Adamo CR, & Berman BM (2017). Yoga treatment for chronic non-specific low back pain . Cochrane Database of Systematic Reviews . [ PMC free article ] [ PubMed ] [ Google Scholar ]
Woda A, Picard P, & Dutheil F (2016). Dysfunctional stress responses in chronic pain . Psychoneuroendocrinology , 71 , 127–135. [ PubMed ] [ Google Scholar ]

IMAGES

PPT
Schematic illustration of the hypothesis of stress equivalence [25
Stress-induced activation of the inflammatory response. Psychosocial
How to Write a Hypothesis: The Ultimate Guide with Examples
Frontiers
Critical stress hypothesis (adapted from Barton et al., 1995; Jaeger et

VIDEO

The Soil's Secrets: A Microbial 'Stress Vaccine' Revolutionizing Mental Health
Fundamentals and Principles of Non-Destructive Testing
Alzheimer's Disease
CBASP Session 2 SOH and TH
Chronic Stress Triggers Inflammation, Affecting Overall Health #shorts #stress #healthjourney
Fluid Mechanics-Lecture-12_Turbulent Flow

COMMENTS

Stress hypothesis overload: 131 hypotheses exploring the role of stress in tradeoffs, transitions, and health
Table 1 contains an alphabetized and more in-depth description of each hypothesis, including definition; predictions; stage or transition; taxon specificity; proposed mediators - categorized as HPA/I axis (glucocorticoids; GCs), autonomic nervous system, or other; and if relevant, baseline or post-stress GCs; and any additional notes. Out of the 131 hypotheses, 111 include specific mention ...
PDF Theories of Stress and Its Relationship to Health
Stress-Response Theory. Selye (1976a) initially proposed a triadic model as . the basis for the stress-response pattern. The ele-ments included adrenal cortex hypertrophy, thy-micolymphatic (e.g., the thymus, the lymph nodes, and the spleen) atrophy, and gastrointesti-nal ulcers. These three, he reasoned, were closely
Stress and Coping Theory Across the Adult Lifespan
Summary. Stress is a broad and complex phenomenon characterized by environmental demands, internal psychological processes, and physical outcomes. The study of stress is multifaceted and commonly divided into three theoretical perspectives: social, psychological, and biological. The social stress perspective emphasizes how stressful life ...
Stress hypothesis overload: 131 hypotheses exploring the role of stress
Stress is ubiquitous and thus, not surprisingly, many hypotheses and models have been created to better study the role stress plays in life. Stress spans fields and is found in the literature of biology, psychology, psychophysiology, sociology, economics, and medicine, just to name a few. Stress, an …
Lazarus and Folkman's psychological stress and coping theory.
Psychological stress is a complex phenomenon and numerous theoretical models have attempted to explain its etiology. These theoretical explanations can be categorized according to their primary conceptualization of the stress experience: stress as an external stimulus; stress as a response; stress as an individual/environmental transaction. The transactional theory of stress and coping ...
Stress, coping, and depression: testing new hypotheses in a
This hypothesis suggests that, in the context of chronic stress, Blacks' engagement in UHBs may serve to buffer the deleterious consequences of stress on depression through the HPA pathway, leading to a lower prevalence of depression but a greater prevalence of physical health problems than would have otherwise occurred.
Hans Selye (1907-1982): Founder of the stress theory
The word 'stress' is used in physics to refer to the interaction between a force and the resistance to counter that force, and it was Hans Selye who first incorporated this term into the medical lexicon to describe the " nonspecific response of the body to any demand ". Selye, who is known as the 'father of stress research ...
Best practices for stress measurement: How to measure psychological
Epidemiological studies confirm that both experiencing a greater number of stressful events and reporting high perceived stress over long periods of time are associated with worse mental and physical health, and mortality (Epel et al., 2018).The association between greater stressor exposure and increased disease risk has been replicated with many different types of stressor exposures (e.g ...
22 Psychophysiological Models of Stress
Psychophysiological models have a long history within stress research of trying to explain the link between stress exposure and psychological and physiological disease. The current chapter tries to offer complementary perspectives on this issue.
Stress hypothesis overload: 131 hypotheses exploring the role of stress
The STRESS-NL database contains data that allow metaanalytical as well as proof-of-principle analyses, enabling human stress research to take new avenues in both explorative and hypothesis-driven ...
The evolution of the concept of stress and the framework of the stress
Therefore, we suggest the framework of the stress system should comprise five basic elements: stressful stimulus, stressor, stress, stress response, and stress effect ( Figure 1A ). In this framework, the stressful stimulus is the starting point, the effect is the end point, and stressor, stress, and stress response are cascades. Figure 1.
Anxiety, Affect, Self-Esteem, and Stress: Mediation and ...
Main Findings. The results indicated that (i) anxiety partially mediated the effects of both stress and self-esteem upon depression, (ii) that stress partially mediated the effects of anxiety and positive affect upon depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect ...
16.2 Stress and Coping
Figure 16.5 The Transactional Theory of Stress and Coping, by J. Walinga. Coping with Stress. There are many ways that people strive to cope with stressors and feelings of stress in their lives. A host of literature, both popular and academic, extols the practice of stress management and whole industries are devoted to it.
What Makes Stress "Good" or "Bad"?
Stress often has negative effects. But in the right amounts, stress can be good for us. A theory known as the "inverted-U" hypothesis attempts to explain how varying levels of stress influence us ...
PDF The Stress Hypothesis
The main aim of the present thesis was to investigate whether psychological stress could be involved in the induction of diabetes-related autoimmunity, as a step on the way in investigating whether psychological stress can cause Type 1 diabetes. A stress hypothesis was suggested and some initial support was found.
Psychological Theories of Stress
The psychological theories of stress gradually evolved from the Theory of Emotion (James-Lange), The Emergency Theory (Cannon-Bard), and to the Theory of Emotion (Schachter-Singer). Because stress is one of the most interesting and mysterious subjects we have since the beginning of time, its study is not only limited to what happens to the body ...
Hypothesis: Definition, Examples, and Types
A hypothesis is a tentative statement about the relationship between two or more variables. Explore examples and learn how to format your research hypothesis. ... For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a ...
A new buffering theory of social support and psychological stress
This stress moderation hypothesis has provided a fruitful situation for the advent of more complex models that investigate the relationships between stress, support, and illness. Hence, psychological models considering factors that are related to the buffering effect have attracted considerable attention in the last years [25, 26].
Diathesis-Stress Model In Psychology
Diatheses are like marbles, and stress is like water: the greater the diathesis, the less stress is needed to cause "overflow" (i.e., give rise to mental illness) (Theodore, 2020). Diathesis-Stress Model. The diathesis-stress model is a concept in psychiatry and psychopathology that offers a theory of how psychological disorders emerge.
Stress: Concepts, Theoretical Models and Nursing Interventions
Stress is a global phenomenon of modern lifestyles that has been found to adversely affect health and student learning, as well as many other aspects of life and work, and is therefore recognized ...
How to Write a Strong Hypothesis
Developing a hypothesis (with example) Step 1. Ask a question. Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project. Example: Research question.
How Stress Impacts Daily Life and What We Can Do About It
Implement a plan for stress reduction. As a new therapist, I routinely saw upwards of 30 clients a week, often seeing eight or nine consecutively without a break.
The Effects of Stress on Physical Activity and Exercise
The rebound hypothesis of stress and PA proposed by Griffin et al. posits that stress can result in a degraded PA response followed within days or weeks by a compensatory uptick in PA. Specifically, these researchers speculate that people may overdo healthy behaviors, such as exercise, to compensate for poor attention to health during the ...
Alternative oxidase alleviates mitochondrial oxidative stress ...
Thus, upregulated AOX under limited nitrate reduction may dissipate excessive reductants and thereby attenuate oxidative stress. Nevertheless, so far there is no firm evidence for this hypothesis due to the lack of experimental systems to analyze the direct relationship between nitrate reduction and AOX.
How Does Yoga Reduce Stress? A Clinical Trial Testing Psychological
Stress is a commonly-experienced aversive state purported to impact the course of disease and illness at a systemic level (Cohen, Edmondson, & Kronish, 2015; Muscatell & Eisenberger, 2012).Indeed, many health conditions have been shown to directly relate to or be exacerbated by stress (e.g., migraine, gastrointestinal problems, hypertension), and even health conditions that are not overtly ...

Article contents

What Is Stress?

Social Stress Perspective

Categories of Stressors

Life Events

Chronic Stressors

Table 1. Problems Considered as Chronic Stressors

Table 2. Questions From the DISE

Table 3. The TLEQ and Its Prevalence Among Adults in the United States

Social Stress and Health: Exposure Versus Vulnerability

Psychological Stress Perspective

Psychological Stress and Appraisal

Coping Processes

Stress Appraisal and Coping Across Adulthood

Biological Stress Perspective

Activation of the Sympathetic-Adrenal Medullary System and Hypothalamic-Pituitary-Adrenal Axis

Age, Exposure to Stressors, Hypothalamic-Pituitary-Adrenal Axis, and the Sympathetic-Adrenal Medullary System

Allostatic Load

Stress and Health: Integrating the Social, Psychological, and Biological Stress Perspectives

Further Reading

Related Articles

Stress hypothesis overload: 131 hypotheses exploring the role of stress in tradeoffs, transitions, and health

Publication types

22 Psychophysiological Models of Stress

Introduction

Autonomic Nervous System

Sympathetic Nervous System

Parasympathetic Nervous System

Enteric Nervous System

Markers of the Autonomic Nervous System

Blood Pressure

Heart Period Variability

High-Frequency Heart Period Variability or Respiratory Sinus Arrhythmia

The Various Ways of Calculating Heart Period Variability and the Lack of Consensus

Pre-Ejection Period

Skin Conductance Response

Plasma Norepinephrine and Epinephrine

Salivary Alpha-Amylase

Links With Stress and Stress-Related Disease

Chronic Stress

Early Life Adversity

Classical Physiological Models in Stress Research

Diathesis-Stress Models

Allostatic Load Theory

Autonomic Space Model

Empirical Support and Current Status of Autonomic Space Model

Strengths and Limitations of the Autonomic Space Model

Neurovisceral Integration Theory

Empirical Support and Current Status of Neurovisceral Integration Theory

Strengths and Limitations of Neurovisceral Integration Theory

Polyvagal Theory

Empirical Support and Current Status of Polyvagal Theory

Strengths and Limitations of Polyvagal Theory

Biological Sensitivity to Context Theory

Empirical Support and Current Status of Biological Sensitivity to Context Theory

Strengths and Limitations of Biological Sensitivity to Context Theory

New Developments

Empirical Support and Current Status of the Adaptive Calibration Model

Strengths and Limitations of the Adaptive Calibration Model

Changes in Physiology as a Result of Interaction With Other Systems—Empirical Findings

Future Directions

This Feature Is Available To Subscribers Only

Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression

Main Findings

Introduction

Mediation and moderation

Mediation and moderation effects on depression

The present study

Ethics statement

Participants

Instruments

Perceived Stress Scale [20] .

Rosenberg's Self-Esteem Scale [22] .

Positive Affect and Negative Affect Schedule [26] .

Correlational analysis

Mediation analysis

Moderation analysis

Mediating effects

Moderator effects/interaction effects

Limitations