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• Published: 10 May 2024

Adolescents’ trajectories of depression and anxiety symptoms prior to and during the COVID-19 pandemic and their association with healthy sleep patterns

• Serena Bauducco   ORCID: orcid.org/0000-0002-1485-8564 1 , 2 ,
• Lauren A. Gardner 3 ,
• Scarlett Smout 3 ,
• Katrina E. Champion 3 ,
• Cath Chapman 3 ,
• Amanda Gamble 4 ,
• Maree Teesson 3 ,
• Michael Gradisar 5 , 6 &
• Nicola C. Newton 3  

Scientific Reports volume  14 , Article number:  10764 ( 2024 ) Cite this article

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The COVID-19 pandemic has seen a rise in anxiety and depression among adolescents. This study aimed to investigate the longitudinal associations between sleep and mental health among a large sample of Australian adolescents and examine whether healthy sleep patterns were protective of mental health in the context of the COVID-19 pandemic. We used three waves of longitudinal control group data from the Health4Life cluster-randomized trial (N = 2781, baseline M age  = 12.6, SD =  0.51; 47% boys and 1.4% ‘prefer not to say’). Latent class growth analyses across the 2 years period identified four trajectories of depressive symptoms: low-stable (64.3%), average-increasing (19.2%), high-decreasing (7.1%), moderate-increasing (9.4%), and three anxiety symptom trajectories: low-stable (74.8%), average-increasing (11.6%), high-decreasing (13.6%). We compared the trajectories on sociodemographic and sleep characteristics. Adolescents in low-risk trajectories were more likely to be boys and to report shorter sleep latency and wake after sleep onset, longer sleep duration, less sleepiness, and earlier chronotype. Where mental health improved or worsened, sleep patterns changed in the same direction. The subgroups analyses uncovered two important findings: (1) the majority of adolescents in the sample maintained good mental health and sleep habits ( low-stable trajectories), (2) adolescents with worsening mental health also reported worsening sleep patterns and vice versa in the improving mental health trajectories. These distinct patterns of sleep and mental health would not be seen using mean-centred statistical approaches.

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Introduction.

Mental disorders are the leading cause of disability among young people aged up to 24 years worldwide, accounting for one quarter of all years lived with disability 1 . In Australia, mental disorders make up three of the five leading causes of burden of disease among those aged 12–24 years 2 and cost the economy approximately $200–220 billion yearly 3 . The COVID-19 pandemic has caused disruptions to all facets of adolescent development and exacerbated mental health issues such as depression, anxiety and self harm 4 , 5 , 6 , 7 . Examining modifiable factors that were protective of mental health throughout this global crisis can offer insights on targets for prevention and early intervention, especially since improving the mental health of young people is a critical public health priority 8 .

There is growing evidence that sleep is a key modifiable factor associated with mental health 9 , 10 , 11 , 12 , 13 , 14 . Human sleep is primarily under biological control, governed by the well-supported two-process model of sleep 15 , 16 . The first process is sleep homeostatis, whereby pressure to sleep builds across the waking day and evening and dissipates during sleep. As adolescents develop, their ability to build sleep pressure in the evening declines, resulting in increased alertness in the evening. This inevitably results in a delay in the onset of sleep (i.e., a longer sleep onset latency) 16 . The second process—the circadian rhythm—is a cycle of sleep and wake across the 24 h day, and is of particular relevance during adolescence. From about age 10 to 20 years, the timing of the circadian rhythm delays, resulting in a later onset of sleep in the evening, and a later rise time (when allowed to sleep-in) 16 . However, 5 out of 7 days of the week, adolescents are prevented from sleeping at their natural circadian times as they need to wake relatively early to prepare for, travel to, and attend school 17 . This inevitably results in a restriction of sleep across the school week (i.e., shortened total sleep time) and weekend catch-up, which leads to irregular sleep and pepetuates weekday sleep debt 17 .

Multiple studies have shown that poor sleep during paediatric development can increase the odds of developing anxiety and depression, with two mechanisms implicated 9 . First, the restriction of sleep (less total sleep time) has been shown to dampen positive mood and hinder one’s next-day emotion regulation 9 . Second, an extended sleep onset latency is proposed to create an ideal environment for repetitive negative thinking (i.e., worry and rumination), which has been linked to both depression and anxiety in young people. An extended sleep onset latency is common among later chronotypes, which may be a predisposing factor for the development of depression and anxiety symptoms 18 . Conversely, a healthy sleep profile (particularly short sleep onset latency—between 5 and 30 min 19 , sufficient total sleep time—between 8 and 10 h 20 , and less daytime sleepiness) is associated with increased mental resilience (i.e., lower symptoms of anxiety and depression) 21 , 22 . Therefore, sleep is an important risk-/protective factor for the development of mental ill-health.

During the COVID-19 pandemic, mental resilience was tested on a global scale, and many adolescents experienced heightened psychopathology 4 , 5 , 6 , 7 . Sleep was also impacted, potentially relating to heightened stress and restrictions on movement and closure of schools; however, evidence as to whether healthy sleep improved or worsened has been mixed 23 , 24 , 25 . Surprisingly, one longitudinal study found that the prevalence of depressive symptoms, anxiety symptoms and sleep problems was higher before, compared to during and after, the pandemic 26 . While studies focusing on average changes are informative, they might miss for whom changes occur. Did all adolescents experience worse sleep and mental health? Were adolescents with healthy sleep patterns more resilient? For example, later chronotype 26 , 27 , shorter sleep duration 27 and insomnia symptoms 28 were associated with higher risk for adolescents’ mental ill-health during the pandemic. Identifying subgroups of adolescents at lower risk for mental ill-health during the pandemic, and thoroughly examining protective sleep characteristics, can inform key targets for prevention and early interventions in this population. Previous studies, however, have examined changes across their entire samples, and have examined only a few interindividual differences in sleep patterns.

To address this gap, we utilised data from pre-pandemic (2019), and during the pandemic (in the latter half of 2020 and 2021) among a large sample of early- to mid-Australian adolescents 29 . Using a person-centred analysis, we examined whether adolescents who experienced lower and stable levels of anxiety and depression before and during the pandemic had healthier sleep patterns (i.e., shorter sleep onset latency and night-time awakenings, sufficient total sleep time, low levels of sleepiness, an earlier chronotype, and shorter catch-up sleep on weekends) compared to adolescents experiencing poor and worsening mental health symptoms.

Descriptive statistics

The analytical sample of the current study consisted of 2781 students (baseline Mage = 12.6, SD = 0.5; 47% boys and 1.4% ‘prefer not to say’). The largest group was from New South Wales (49.8%), followed by Western Australia (28.1%), and Queensland (22.2%). The average perceived socioeconomic status in the sample was 9.43 (range 0–13; SD = 1.85). The majority of adolescents were born in Australia (86.2%) or another English-speaking country (6.9%). In line with this, the majority reported speaking English at home (93.1%). Means and standard deviations of depressive and anxiety symptoms and sleep variables (sleepiness, weekday sleep duration, sleep onset latency [SOL], wake after sleep onset [WASO], and chronotype) are presented in Table  1 .

Changes in depressive and anxiety symptoms over time

Two separate latent growth curve models were estimated to examine whether and how adolescents’ depressive and anxiety symptoms changed over time, from early to mid-adolescence and throughout the pandemic. Both yielded a good model fit (see Table  2 ). The mean of the slope was positive and statistically significant for both depression and anxiety symptoms, which indicates that on average, participants reported increasing symptoms over time. The variances of the slope and the intercept were both statistically significant, which indicates that adolescents differed both in the level of depressive and anxiety symptoms at T1 and in how they changed from T1 to T3 (see Table  2 ). Therefore, we went on to explore subgroups of adolescents following different trajectories of depressive and anxiety symptoms.

Depressive symptoms subgroup trajectories

We used latent class growth analysis (LCGA) to identify subgroups of adolescents who followed different trajectories of depressive symptoms over time and found four different trajectories (see “ Supplementary material ”). The first class ( high-decreasing ) included 7.1% of the sample. Adolescents in this class reported high levels of depressive symptoms at T1 and average symptoms at T3, relative to the sample average scores. The second class ( average-increasing ) included 19.2% of the sample and started at average levels of depression before the pandemic and increased to moderate symptoms over time. The third class ( low-stable ) represented 64.3% of the sample, who were adolescents reporting low symptoms of depression at T1 and their symptoms remained stable over time. The final trajectory class ( moderate-increasing ) represented 9.4% of the sample. Adolescents in this class reported higher-than-average levels of depressive symptoms at T1 and showed a significant increase in their symptoms over time. The four trajectories and the estimated mean changes are shown in Fig.  1 . The four trajectories significantly differed in their symptoms levels at T1 [F(3,2777) = 1379.0, p  < 0.001], at T2[F(3,2276) = 537.63, p  < 0.001], and T3 [F(3,2091) = 2894.02, p  < 0.001]. Depressive symptoms means and SDs for each trajectory at each time point are presented in Table  3 .

Trajectories of depressive symptoms throughout the pandemic. Note . The dashed line is the average score for the whole sample at T1-T2-T3. Depressive symptom scores ranged from 0–18.

Anxiety symptoms trajectories

Analysis for anxiety symptoms yielded three different trajectories (see Supplementary material ). The first class ( high-decreasing ) included 13.6% of the sample. Adolescents in this trajectory showed a statistically significant decline in anxiety symptoms, but still well above the average for the whole sample. The second trajectory ( average-increasing ) included 11.6% of the sample and went from average to high symptoms from T1 to T3. The third trajectory ( low-stable ) included 74.8% of the sample and showed a slight but significant increase in anxiety symptoms over time, although still in the low range. The three trajectories and the estimated mean changes are shown in Fig.  2 . The three trajectories significantly differed in their symptoms levels at T1 [F(2,2641) = 2154.50, p  < 0.001], at T2[F(2,2182) = 979.60, p  < 0.001], and T3 [F(2,2031) = 1281.02, p  < 0.001]. Anxiety symptoms means and SDs for each trajectory at each time point are presented in Table  3 .

Trajectories of anxiety symptoms throughout the pandemic. Note . The dashed line is the average score for the whole sample at T1-T2-T3, Anxiety symptom scores ranged from 13–65.

Sleep and sociodemographic characteristics among adolescents by trajectories of depressive symptoms

Sex distribution was significantly different among adolescents with different trajectories of depressive symptoms, χ 2 (6) = 151.25, p  < 0.001. In the high-decreasing group, girls were the majority (58%) together with the largest proportion of adolescents answering “prefer not to say” for their sex at birth (4%). Girls were overrepresented in the low-increasing trajectory (67.7% vs. 30.6% boys) and in the average-increasing trajectory (67.8% vs. 30.7% boys). Boys represented the majority in the low-stable trajectory (75.7% vs. 54.5% girls). Some differences in cultural and linguistic diversity emerged, χ 2  = 12.0, p  = 0.007, with the high-decreasing trajectory having the highest proportion of adolescents with an immigrant background (18.9%), followed by the low-stable group (10.5%) and the average-increasing and moderate-increasing (8.3% and 8.4% respectively). Relative socioeconomic position did not differ among the trajectories χ 2  = 3.3, p  = 0.348.

Table 3 shows the comparisons for sleep characteristics for each of the depressive symptom trajectories. Adolescents in the low-stable trajectory of depressive symptoms reported significantly better sleep patterns at all time points, including the shortest SOL and WASO, the longest sleep duration, the lowest sleepiness, and the earliest chronotype. Adolescents in the high-decreasing trajectory of depressive symptoms showed the worst sleep patterns compared to the other groups at T1, but by T3 there were no significant differences from the low-stable group in WASO, sleep duration, and chronotype. Sleepiness and SOL were still high but no longer the highest compared to adolescents in the two increasing-symptoms trajectories. In fact, adolescents in the two increasing trajectories were better off at T1, but reported significantly longer SOL and WASO, shorter sleep duration, excessive daytime sleepiness (> 17) 30 and later chronotype by T3. Interestingly, SOL was problematic in all trajectories, as it was close to or above the clinical guidelines of 30 min required for sleep-onset insomnia 19 .

Sleep and sociodemographic characteristics among adolescents by trajectories of anxiety symptoms

Sex distribution was significantly different among adolescents in different trajectories of anxiety symptoms, χ 2 (4) = 181.26, p  < 0.001. In the high-decreasing trajectory, girls were the largest group (73.5%) together with the largest proportion of adolescents answering “prefer not to say” for their sex at birth (2.4%). Girls were also overrepresented in the average-increasing trajectory (72.3% vs. 26.5% boys) whereas boys were slightly overrepresented in the low-stable trajectory (54.4% vs. 44.4% girls). Adolescents differed in cultural and linguistic diversity, χ 2  = 9.11, p  = 0.011, with the average-increasing trajectory having the lowest proportion of adolescents with an immigrant background (8.4%), compared to the low-stable (10.2%) and the high-decreasing group (13%). Relative socioeconomic position did not differ among the trajectories χ 2  = 1.75, p  = 0.416.

Table 4 shows the comparisons for sleep characteristics for each of the anxiety symptom trajectories. Adolescents in the low-stable trajectory of anxiety symptoms reported significantly better sleep patterns at all time points compared to the other groups, including the shortest SOL and WASO, the longest sleep duration, the lowest sleepiness, and the earliest chronotype. Adolescents in the high-decreasing trajectory of anxiety symptoms showed the worst sleep patterns compared to the other groups at T1, but by T3 there was no significant difference in WASO compared to the low-stable group and their sleep duration was no longer the shortest. Yet, sleepiness was still above recommended levels (> 17) and chronotype significantly later than the low-stable trajectory. Adolescents in the average-increasing trajectories started with similar SOL, WASO, and chronotype as the low-stable trajectory, but already reported a significantly shorter sleep duration and more sleepiness. By the end of the study, they were worse off in all sleep parameters. As in the depressive symptom trajectories, SOL was problematic in all groups (i.e., ≥ 30 min).

The aim of this study was to explore whether healthy sleep patterns were protective of adolescent mental health throughout the COVID-19 pandemic.

In the present study, both depression and anxiety symptoms generally increased over time. While this trend is similar to pre-pandemic studies for depression, it is in the opposite direction for anxiety, whose symptoms have previously shown to decline from childhood throughout adolescence 31 . A recent meta-analysis of mental health changes throughout the pandemic shows a clear increase in depressive symptoms in children and adolescents, and a slight increase in anxiety symptoms, with girls generally showing worse mental health 6 . Similar to previous trajectory-studies examining depressive and anxiety symptoms 32 , 33 , in the present study, not all adolescents displayed increasing symptoms: the majority of adolescents reported stable-low symptoms of both anxiety and depression, and a small portion of adolescents showed improving mental health. Identifying modifiable protective factors reported by adolescents in these low and declining symptom trajectories is crucial for promoting mental health in this population. In this study, we examined sleep as a potential protective factor and found that adolescents in low-risk trajectories of anxiety and depression consistently reported the healthiest sleep patterns. These healthy sleep characteristics included: (1) longer weekly sleep duration, (2) earlier chronotype, (3) lower sleepiness, (4) shorter sleep latency and time awake during the night. Weekend catch-up was significantly shorter for the low-stable trajectory of depression but was not significantly different between the trajectories of anxiety. When looking at the divergent trajectories of increasing vs decreasing symptoms of anxiety and depression, some interesting differences emerged.

Among adolescents whose depressive symptoms improved over time, sleep duration no longer differed from the low-risk trajectory by the end of the study. Similarly, for adolescents whose anxiety symptoms improved over time, their sleep duration was no longer the shortest compared to increasing-symptom trajectories. This is not surprising, as studies examining the link between sleep duration and mental health have found a dose-response association that supports the positive association between the recommended 8–10 h of sleep for adolescents and emotional health 34 , 35 . Chronotype followed similar trends as sleep duration, as a later chronotype leads to later bedtimes during schooldays, shortening the sleep opportunity when wake-times are fixed 36 . In contrast, an early chronotype seems to be protective for adolescents’ mental health, in line with previous studies during the pandemic 26 , 27 . An interesting finding was that the chronotype of adolescents in the high-decreasing trajectory of depression was significantly later than the other trajectories at T1, but did not differ from adolescents in the low-risk trajectory by the end of the study. Conversely, chronotype became significantly later for adolescents in the two increasing trajectories of depressive symptoms. This suggests that the natural delay in sleep timing slowed for teenagers whose depressive symptoms improved, while it delayed further for adolescents with increasing symptoms. This finding is worth exploring further, as an earlier chronotype has been found to be protective for depression for several reasons, not only because it is linked to earlier bedtimes and longer sleep duration, but also because it better aligns with the environment (e.g., bright light exposure) and with social obligations (e.g., morning school times) 18 . One hypothesis may be that for some adolescents, the more unstructured nature of online classes could have prompted more irregular sleep routines, making room for a delay in bed- and wake-times (and a later sleep midpoint/chronotype). However, some adolescents were able to increase their sleep duration and maintain (rather than delay) their timing. In this study, we did not directly assess lockdown status, but a previous study found a general increase in sleep duration in this population, independent of lockdown measures 25 . This might also explain the relatively small difference in weekend catchup between trajectories. Future studies should further explore what may explain these variations in chronotype, including individual characteristics and contextual factors (e.g., self-control, parental rules about sleep).

In addition to sleep quantity, perceived sleep quality is an important aspect closely linked to mental wellbeing 22 . Experts agree that measures of sleep continuity are good indicators of sleep quality 19 . In particular, time taken to fall asleep as well as time awake at night are hypothesised as important mechanisms for both anxiety and depression, as they create an opportunity for worry at a time when more adaptive emotion regulation strategies might not be activated 12 . Although SOL was markedly long among all adolescents (> 30 min), it was consistently shorter in the low-risk trajectories of both anxiety and depression, and no longer the longest among decreasing-symptom trajectories. Time awake at night followed similar trends. Finally, we also examined daytime complaints in relation to depression and anxiety symptoms. In the present study, teenagers who belonged to improving mental health symptom trajectories no longer reported the highest sleepiness by the end of the study, compared to worsening mental health symptom trajectories. Feelings of tiredness have been previously found to be both cross-sectionally and longitudinally linked to anxiety and depression in adolescents 22 . All in all, these results show significantly better sleep quality and quantity and less daytime sleepiness among adolescents with better mental health across the pandemic years. Furthermore, the divergent trajectories of anxiety and depressive symptoms clearly show that sleep patterns followed closely.

Sleep and mental health are closely intertwined. The aim of this study was not to discern directionality, rather we aimed to use a person-oriented perspective to inform who is at risk for developing problems, and poor sleep characteristics were a common determinant among risk-trajectories for both anxiety and depressive symptoms. Some differences in sleep patterns existed from the start of the study—for example, adolescents in the average-increasing trajectory of depression already reported overall worse sleep health compared to the low-stable trajectory. For the average-increasing trajectory of anxiety, sleep duration and sleepiness were distinct from the low-risk adolescents. These differences in sleep patterns could help explain why the pandemic sparked an increase in mental health problems in these adolescents and can potentially aid in the identification of individuals in need of early interventions. In fact, a recent study found that stressful events were followed by an increase in sleep problems and later increases in anxiety symptoms within a few months among adolescents 37 . Nonetheless, it might still be difficult to identify these emerging risk-groups (average-increasing trajectories), as their sleep was significantly different from the low-stable trajectories but it was not yet problematic (e.g., sleep duration close to the recommended 8 h/night 20 ; see Tables  4 , 5 ). This supports the importance of promoting sleep health in the adolescent population in a universal manner, as some of the adolescents at-risk might easily be missed. Given that the link between sleep and mental health is ultimately bi-directional and can create a vicious cycle of poor emotional regulation and poor sleep quality and quantity 38 , breaking this cycle by targeting sleep is warranted and has shown promising benefits for mental health 9 . For example, sleep has shown significant improvements (sleep onset latency in particular) alongside symptoms of depression following bright light therapy, cognitive behavioural therapy for insomnia (CBT-I), school-based sleep interventions 9 , and later school-start times 39 . Two recent meta-analyses found evidence that improving sleep can lead to an improvement in both anxiety and depressive symptoms 40 , 41 . In addition, addressing sleep problems first can be advantageous because it is less stigmatized and easier to talk about compared to mental health 40 .

The present study has a number of strengths and limitations that need to be taken into account when interpreting the results. Mental health symptoms and sleep patterns were self-reported, which can be subject to error and common method bias. However, externally developed measures that have been validated in adolescents were used. Although objective sleep measures are encouraged in future studies, self-reported sleep has proven valid compared to actigraphy 42 , 43 . This is also a more feasible method when including a large sample of adolescents followed over time. The large and diverse sample, spanning three Australian states is a strength of the study, together with the longitudinal design, which enabled to capture changes throughout the pandemic. Despite the three waves of longitudinal data, the results of this study cannot discern whether sleep patterns or mental health precede one another. More frequent longitudinal sampling could have provided a clearer picture 44 . However, using sophisticated person-oriented analyses allowed to highlight that not all adolescents were impacted the same way during the COVID-19 pandemic. In fact, the majority of the sample coped well during this stressful time (low-stable trajectories) and these low-risk classes also reported the healthiest sleep patterns. In addition, although WASO and SOL decreased over time in the whole sample, when looking at subgroups the decrease occurred only among adolescents whose symptoms improved. These important results might have been missed if only average changes were examined.

To conclude, sleep and mental health go hand-in-hand for adolescents. During a stressful time such as the COVID-19 pandemic, good sleep health was distinctive of adolescents who maintained low and stable symptoms of anxiety and depression. Given the bidirectional nature of the link between sleep and mental health, promoting healthy sleep habits in adolescents is a promising modifiable factor to improve and maintain mental health. Adolescent mental health is a public health priority 8 , and this study provides empirical evidence that sleep health should be one central target for prevention and intervention.

Design and participants

This study utilises data from the “Health4Life” cluster randomised controlled trial, which aimed to evaluate the efficacy of an eHealth intervention targeting six modifiable risk factors among Australian adolescents (sleep, physical activity, diet, screen time, alcohol use and tobacco smoking). Baseline data were collected in 2019 (approximately July-November) using online self-report surveys among Year 7 students at 71 secondary schools across New South Wales (NSW), Queensland (QLD) and Western Australia (WA), with follow up surveys conducted in 2020 (approximately July-December) and 2021 (approximately July-December). To avoid contamination effects from the intervention, this study focuses on control group data. Only students with data on depressive and anxiety symptoms at baseline were included (Depressive symptom trajectories: N T1  = 2781, N T2  = 2280, N T3  = 2095; Anxiety symptom trajectories: N T1  = 2781, N T2  = 2267, N T3  = 2088). Participants provided written consent and parents provided passive, active written or active verbal consent, depending on the approved procedures for the school/region. The Health4Life trial was performed in accordance with relevant guidelines and regulations, it was registered with the Australian and New Zealand Clinical Trials registry (ACTRN12619000431123) and has ethical approval from ten relevant committees (University of Sydney HREC2018/882, NSW Department of Education SERAP 2019006, University of Queensland 2019000037, Curtin University HRE2019-0083 and several Catholic Diocese committees). The study protocol provides further details on recruitment and consent procedures 29 .

Sociodemographic characteristics

Sociodemographic factors included sex assigned at birth, age, cultural and linguistic diversity (CALD), and relative socioeconomic position. CALD was defined as per recommendations from a recent Australian review 45 to include participants who were born in a non-English speaking country and/or primarily speak a language other than English at home. Relative family affluence was identified using the Family Affluence Scale III (FASIII), which has demonstrated good test–retest reliability (r = 0.90) and strong correlation with parental report 46 . The FASIII generates a summed score across indicators of familial wealth (e.g., number of computers, number of bathrooms in home, etc.) as a proxy for familial socioeconomic status that children and adolescents might be better at reporting compared to parent or caregivers’ income and education.

Sleep patterns

Average sleep duration per night was measured using the validated Modified Sleep Habits Survey 42 , 43 . Students reported the time they usually: (1) went to bed (time—12 h format), (2) attempted sleep (time—12 h format), (3) took to fall asleep (duration—h, min), (4) were awake during the night (duration—h, min), and 5() woke up in the morning (time—12 h format) over the past week (separately for week nights and weekend nights). In the present study, we derived several sleep parameters, including sleep onset latency (SOL; i.e., time taken to fall asleep), wake after sleep onset (WASO; i.e., time awake during the night), total sleep time (TST; i.e., time between falling asleep and wake up in the morning, minus WASO) during schooldays, and chronotype. We calculated chronotype as the midpoint of sleep on free days (i.e., sleep onset time on weekends plus sleep duration on weekends, divided by 2). According to Roenneberg et al. 47 a correction needs to be made as many adolescents restrict their sleep on schooldays and attempt to catch up on weekends. Therefore, if the sleep duration on weekends is longer than on schooldays, sleep midpoint is calculated as sleep onset time (weekends) plus sleep duration (average schoolday-weekend) divided by 2. The midpoint of sleep is a good behavioural marker for circadian phase 47 . Finally, to examine irregular sleep patterns during weekdays and weekends, we calculated “weekend sleep-in” by subtracting wake-up time on weekends—wake-up time on weekdays 48 .

The Pediatric Daytime Sleepiness Scale was used to assess daytime sleepiness 30 . It has been validated in adolescents and includes eight items such as ‘ How often do you fall asleep or feel drowsy in class? ’ and ‘ How often do you have trouble getting out of bed in the morning? ’ with five response options from ‘ Never ’ (0) to ‘ Very often/ always ’ (4), with scores ranging from 0 to 32. The cutoff for excessive sleepiness is 14 for boys and 17 for girls 30 . The Cronbach’s alpha was acceptable (α = 0.72).

Past 7-day anxiety symptoms were assessed with the PROMIS Anxiety Paediatric (PROMIS-AP) scale, which has been validated among adolescents 49 . The 13-item scale asks participants to report frequency of symptoms including difficulty relaxing, and feelings of nervousness, worry, and fear, amongst others on a scale from ‘never’ (1) to ‘ almost always’ (5), the total ranging from 13–65 49 . The Cronbach’s alpha was 0.94.

Past 7-day depressive symptoms were measured using the modified Patient Health Questionnaire for Adolescents scale (PHQ-A) 50 . The 9-item scale asks participants to report how often they experienced symptoms such as “feeling down, depressed, irritable or hopeless”, sleep issues, tiredness, and changes in appetite, weight or behaviours on a scale from ‘not at all’ (0) to ‘nearly every day’ (3) 50 . The 9 th item (measuring thoughts of death and self-harm) was removed on request of the ethics board. In addition, 2 items were excluded from analyses because of their overlap with sleep, our variable of interest. Depression symptoms were analysed using a sum of the remaining six items, ranging from 0–18 (Cronbach’s alpha = 0.84).

Data analysis

We followed a two-step procedure to identify different mental health trajectories 51 . In Step 1, we estimated a latent curve growth model to examine how, on average, adolescents’ mental health symptoms changed over a 2 years period, and to examine whether there was a significant between-person variation in intercept (initial level) and slope (change over time) of depression and anxiety. In Step 2, we used latent class growth analysis (LCGA) to identify adolescents with different mental health trajectories. To determine the number of trajectories that best fit the data we looked for the lowest Bayesian Information Criterion (BIC), highest entropy (i.e., classification accuracy), non-significant Lo–Mendell–Rubin test (LMR; i.e., model fit improvement from n  − 1 to n classes), and the proportion of adolescents in each group trajectory (> 5%) 52 . When these indicators were contrasting, we chose the most parsimonious solution (i.e., fewer classes) 52 . We analyzed trajectories for depressive symptoms and anxiety separately. To validate the distinctiveness of the classes, we compared depression and anxiety symptom trajectories on symptom levels at each time point using ANOVAs. After establishing the different trajectories, we compared adolescents in each trajectory on sex distribution and sleep parameters across three time points using the BCH method in Mplus 53 . This method uses a weighted multiple group analysis, where the groups correspond to the latent classes, and therefore the classes established in the LCGA model are not affected in this second step (i.e., when analysing differences in sleep patterns) 53 . Data were analysed in SPSS (v. 26) and Mplus 54 . We handled missing data in Mplus using full information maximum likelihood (FIML). Depressive symptoms model: 4 missing data patterns, covariance coverage ranged between 0.67 and 1.00. Anxiety model: 4 missing data patterns, covariance coverage ranged between 0.67 and 1.00. The covariance coverage was well above the recommended 0.10 to reliably use FIML. Moreover, FIML is a superior method compared to mean imputation, listwise deletion or pairwise deletion, as it provides more reliable standard errors 55 .

Data availability

The data underlying this article cannot be shared publicly due to the agreement made with the individuals that participated in the study. The data will be shared on reasonable request to the corresponding author.

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Acknowledgements

The Health4Life study was led by researchers at the Matilda Centre at the University of Sydney, Curtin University, the University of Queensland, the University of Newcastle, Northwestern University, and UNSW Sydney: Teesson, M., Newton, N.C, Kay-Lambkin, F.J., Champion, K.E., Chapman, C., Thornton, L.K., Slade, T., Mills, K.L., Sunderland, M., Bauer, J.D., Parmenter, B.J., Spring, B., Lubans, D.R., Allsop, S.J., Hides, L., McBride, N.T., Barrett, E.L., Stapinski, L.A., Mewton, L., Birrell, L.E., & Quinn, C & Gardner, L.A.

Open access funding provided by Örebro University. The Health4Life study was funded by the Paul Ramsay Foundation and the Australian National Health and Medical Research Council via Fellowships (KC, APP1120641; MT, APP1078407; and NN, APP1166377) and via a Centre of Research Excellence in the Prevention and Early Intervention in Mental Illness and Substance Use (PREMISE; APP11349009). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors would like to acknowledge all the research staff who have worked across the study, as well as the schools, students and teachers who participated in this research. The research team also acknowledges the assistance of the New South Wales Department of Education (SERAP 2019006), the Catholic Education Diocese of Bathurst, the Catholic Schools Office Diocese of Maitland-Newcastle, Edmund Rice Education Australia, the Brisbane Catholic Education Committee (373), and Catholic Education Western Australia (RP2019/07) for access to their schools to conduct this research.

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L.A.G., K.E.C., M.G., and S.B. conceived the idea behind the study. S.B. analysed the data. K.E.C., L.A.G., N.C.N. and M.T. acquired the fundings and coordinated data collection. All authors contributed to the interpretation of the results, writing, and reviewing the final manuscript.

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Dr. Gradisar reports that he is the CEO of WINK Sleep Pty Ltd which provides professional training for the treatment of sleep disorders, and is employed by Sleep Cycle AB, a listed company whose app tracks sleep.

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Bauducco, S., Gardner, L.A., Smout, S. et al. Adolescents’ trajectories of depression and anxiety symptoms prior to and during the COVID-19 pandemic and their association with healthy sleep patterns. Sci Rep 14 , 10764 (2024). https://doi.org/10.1038/s41598-024-60974-y

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7 Depression Research Paper Topic Ideas

Nancy Schimelpfening, MS is the administrator for the non-profit depression support group Depression Sanctuary. Nancy has a lifetime of experience with depression, experiencing firsthand how devastating this illness can be.

Cara Lustik is a fact-checker and copywriter.

In psychology classes, it's common for students to write a depression research paper. Researching depression may be beneficial if you have a personal interest in this topic and want to learn more, or if you're simply passionate about this mental health issue. However, since depression is a very complex subject, it offers many possible topics to focus on, which may leave you wondering where to begin.

If this is how you feel, here are a few research titles about depression to help inspire your topic choice. You can use these suggestions as actual research titles about depression, or you can use them to lead you to other more in-depth topics that you can look into further for your depression research paper.

What Is Depression?

Everyone experiences times when they feel a little bit blue or sad. This is a normal part of being human. Depression, however, is a medical condition that is quite different from everyday moodiness.

Your depression research paper may explore the basics, or it might delve deeper into the  definition of clinical depression  or the  difference between clinical depression and sadness .

What Research Says About the Psychology of Depression

Studies suggest that there are biological, psychological, and social aspects to depression, giving you many different areas to consider for your research title about depression.

Types of Depression

There are several different types of depression  that are dependent on how an individual's depression symptoms manifest themselves. Depression symptoms may vary in severity or in what is causing them. For instance, major depressive disorder (MDD) may have no identifiable cause, while postpartum depression is typically linked to pregnancy and childbirth.

Depressive symptoms may also be part of an illness called bipolar disorder. This includes fluctuations between depressive episodes and a state of extreme elation called mania. Bipolar disorder is a topic that offers many research opportunities, from its definition and its causes to associated risks, symptoms, and treatment.

Causes of Depression

The possible causes of depression are many and not yet well understood. However, it most likely results from an interplay of genetic vulnerability  and environmental factors. Your depression research paper could explore one or more of these causes and reference the latest research on the topic.

For instance, how does an imbalance in brain chemistry or poor nutrition relate to depression? Is there a relationship between the stressful, busier lives of today's society and the rise of depression? How can grief or a major medical condition lead to overwhelming sadness and depression?

Who Is at Risk for Depression?

This is a good research question about depression as certain risk factors may make a person more prone to developing this mental health condition, such as a family history of depression, adverse childhood experiences, stress , illness, and gender . This is not a complete list of all risk factors, however, it's a good place to start.

The growing rate of depression in children, teenagers, and young adults is an interesting subtopic you can focus on as well. Whether you dive into the reasons behind the increase in rates of depression or discuss the treatment options that are safe for young people, there is a lot of research available in this area and many unanswered questions to consider.

Depression Signs and Symptoms

The signs of depression are those outward manifestations of the illness that a doctor can observe when they examine a patient. For example, a lack of emotional responsiveness is a visible sign. On the other hand, symptoms are subjective things about the illness that only the patient can observe, such as feelings of guilt or sadness.

An illness such as depression is often invisible to the outside observer. That is why it is very important for patients to make an accurate accounting of all of their symptoms so their doctor can diagnose them properly. In your depression research paper, you may explore these "invisible" symptoms of depression in adults or explore how depression symptoms can be different in children .

How Is Depression Diagnosed?

This is another good depression research topic because, in some ways, the diagnosis of depression is more of an art than a science. Doctors must generally rely upon the patient's set of symptoms and what they can observe about them during their examination to make a diagnosis. 

While there are certain  laboratory tests that can be performed to rule out other medical illnesses as a cause of depression, there is not yet a definitive test for depression itself.

If you'd like to pursue this topic, you may want to start with the Diagnostic and Statistical Manual of Mental Disorders (DSM). The fifth edition, known as DSM-5, offers a very detailed explanation that guides doctors to a diagnosis. You can also compare the current model of diagnosing depression to historical methods of diagnosis—how have these updates improved the way depression is treated?

Treatment Options for Depression

The first choice for depression treatment is generally an antidepressant medication. Selective serotonin reuptake inhibitors (SSRIs) are the most popular choice because they can be quite effective and tend to have fewer side effects than other types of antidepressants.

Psychotherapy, or talk therapy, is another effective and common choice. It is especially efficacious when combined with antidepressant therapy. Certain other treatments, such as electroconvulsive therapy (ECT) or vagus nerve stimulation (VNS), are most commonly used for patients who do not respond to more common forms of treatment.

Focusing on one of these treatments is an option for your depression research paper. Comparing and contrasting several different types of treatment can also make a good research title about depression.

A Word From Verywell

The topic of depression really can take you down many different roads. When making your final decision on which to pursue in your depression research paper, it's often helpful to start by listing a few areas that pique your interest.

From there, consider doing a little preliminary research. You may come across something that grabs your attention like a new study, a controversial topic you didn't know about, or something that hits a personal note. This will help you narrow your focus, giving you your final research title about depression.

Remes O, Mendes JF, Templeton P. Biological, psychological, and social determinants of depression: A review of recent literature . Brain Sci . 2021;11(12):1633. doi:10.3390/brainsci11121633

National Institute of Mental Health. Depression .

American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition . American Psychiatric Association.

National Institute of Mental Health. Mental health medications .

Ferri, F. F. (2019). Ferri's Clinical Advisor 2020 E-Book: 5 Books in 1 . Netherlands: Elsevier Health Sciences.

By Nancy Schimelpfening Nancy Schimelpfening, MS is the administrator for the non-profit depression support group Depression Sanctuary. Nancy has a lifetime of experience with depression, experiencing firsthand how devastating this illness can be.  

• Open access
• Published: 12 March 2022

The association of resilience with depression, anxiety, stress and physical activity during the COVID-19 pandemic

• Quyen G. To 1 , 2 ,
• Corneel Vandelanotte 1 ,
• Kathryn Cope 2 ,
• Saman Khalesi 1 , 2 ,
• Susan L. Williams 1 , 2 ,
• Stephanie J. Alley 1 , 2 ,
• Tanya L. Thwaite 1 , 2 ,
• Andrew S. Fenning 2 &
• Robert Stanton 1 , 2  

BMC Public Health volume  22 , Article number:  491 ( 2022 ) Cite this article

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COVID-19 has resulted in substantial global upheaval. Resilience is important in protecting wellbeing, however few studies have investigated changes in resilience over time, and associations between resilience with depression, anxiety, stress, and physical activity during the COVID-19 pandemic.

Online surveys were conducted to collect both longitudinal and cross-sectional data at three time points during 2020. Australian adults aged 18 years and over were invited to complete the online surveys. Measures include the six-item Brief Resilience Scale, the 21-item Depression, Anxiety and Stress Scale, and the Active Australia Survey which have eight items identifying the duration and frequency of walking, and moderate and vigorous physical activities (MVPA), over the past 7 days. General linear mixed models and general linear models were used in the analysis.

In the longitudinal sample, adjusted differences (aDif) in resilience scores did not significantly change over time (time 2 vs. time 1 [aDif = − 0.02, 95% CI = − 0.08, 0.03], and time 3 vs. time 1 [aDif = < 0.01, 95% CI = − 0.07, 0.06]). On average, those engaging in at least 150 min of MVPA per week (aDif = 0.10, 95% CI = 0.04, 0.16), and having depression (aDif = 0.40, 95% CI = 0.33), anxiety (aDif = 0.34, 95% CI = 0.26, 0.41), and stress scores (aDif = 0.30, 95% CI = 0.23, 0.37) within the normal range had significantly higher resilience scores. The association between resilience and physical activity was independent of depression, anxiety, and stress levels. All results were similar for the cross-sectional sample.

Conclusions

Resilience scores did not change significantly during the COVID-19 pandemic. However, there were significant associations between resilience with physical activity and psychological distress. This research helps inform future interventions to enhance or nurture resilience, particularly targeted at people identified as at risk of psychological distress.

Peer Review reports

Initially reported in November 2019, the novel coronavirus (COVID-19) has infected more than 244 million people worldwide, with more than 4.9 million deaths (25 October 2021) [ 1 ]. In addition to causing a global health emergency, there has been subsequent social and economic repercussions on the world’s population due to government-imposed restrictions to protect public health [ 2 ]. How people respond to a persistent stressor, such as the COVID-19 pandemic, may vary based on individual resilience levels [ 3 ], which can be defined as “the process involving an ability to withstand and cope with ongoing or repeated demands and maintain healthy functioning in different domains of life such as work and family”(p.637) [ 4 ]. Understanding resilience and how it changes across time may help in designing interventions that aim to minimise psychological distress.

Few studies have examined changes in resilience during the COVID-19 pandemic. Sturman (2020) compared levels of resilience in the United States prior to the declaration of a global pandemic (November and December 2019), to levels in the early stages of the pandemic (mid-April 2020), and found no significant change over time [ 5 ]. Similarly, Kim et al. (2020) found no significant differences in resilience of Israeli adults between the peak of the COVID-19 pandemic, when Government-enforced restrictions were imposed, and 2 months later when the restrictions had been lifted [ 6 ]. However, a USA study found that resilience in the third week of COVID-19 stay-at-home restrictions (April 2020) were lower compared to normative data collected before the pandemic [ 7 ]. Additionally, we could not identify any studies examining longitudinal changes in resilience in Australian adults.

Resilience is an important protective factor against psychological distress. A systematic review and meta-analysis found that older adults with higher resilience were less likely to have depressive symptoms [ 8 ]; however, no Australian studies were included. To our knowledge, only two studies of resilience and depression have been undertaken in Australia. One study among Iranian immigrants living in Australia found lower levels of resilience associated with higher levels of depression [ 9 ]. In contrast, another study found no significant associations between resilience and depression among homeless people in regional Australia [ 10 ]. The association between resilience and anxiety was also investigated in another study that found higher levels of resilience was associated with less anxiety among Australians aged 55–90 years [ 11 ]. Additionally, several pilot interventions that aimed to improve participants’ resilience through education workshops appeared to have positive effects in mitigating workplace stress among Australian nurses [ 12 , 13 , 14 ]. However, these previous studies are limited by their cross-sectional design or were not conducted among the general population. A more recent study of Australian parents reported loneliness as a significant contributor to stress during the pandemic, however high levels of social support were associated with both lower stress and anxiety [ 15 ]. Healthcare professionals are also predisposed to significant distress and anxiety, despite high levels of resilience, suggesting resilience alone is insufficient as a protective toll against poor mental health [ 16 ].

Physical activity is an important health behaviour that benefits both physical and mental health [ 17 ]. Studies conducted during the COVID-19 pandemic consistently show strong positive associations between resilience and physical activity levels [ 7 , 18 , 19 ]. One possible underlying mechanism for this association could be due to the positive effect of physical activity on mental health [ 20 ]. However, whether physical activity is associated with resilience, independent of mental health status, has not been investigated in these cross-sectional studies. Furthermore, to our knowledge, no Australian study of these relationships has been found.

Therefore, this study aims to investigate: 1) changes in the resilience level of Australian adults over time during the pandemic; and 2) associations between resilience with depression, anxiety, stress, and physical activity. Findings from this study contribute important insights into the role of resilience for physical activity behaviour and psychological distress among Australian adults during the pandemic.

Study design and participants

Online surveys were conducted to collect both longitudinal and cross-sectional data at three time points. The first survey was conducted early on during the COVID-19 pandemic from 9th to 19th April 2020; the second from 30th July to 16th August 2020; and the third between 1st and 25th December 2020. During the first time point, Australian state governments had adopted extraordinary measures to reduce the rates of infection including social distancing, lockdowns, and travel restrictions. During the second time point, all Australian states except Victoria had relaxed restrictions due to low case numbers of the infection. At the time of the third survey, most COVID-19 restrictions were lifted in all States and Territories as the rates of infection were largely under control [ 21 , 22 ].

At each survey, participants (including new participants recruited for survey 2) were asked if they would like to participate in future data collection opportunities. Those completing at least two surveys became part of a longitudinal cohort while those who elected to complete only one survey formed the cross-sectional cohort. The surveys were anonymous and hosted on the Qualtrics survey platform. Australian adults aged 18 years and over were invited to complete the surveys using paid Facebook advertising, social media (e.g., Twitter) and institutional sources including email lists. Online informed consent was provided by all participants after they had read the information sheet that outlined the nature of their participation, the risks and benefits of participation, and how the data would be used. Ethical approval was granted by Central Queensland University’s Human Research Ethics Committee (Approval number 22332).

Demographic characteristics included age (years), gender, years of schooling, weekly household income (< 1000 AUD, 1000 - < 2000 AUD, or ≥ 2000 AUD), and marital status (in a relationship or not). Chronic disease status (Yes/No) was identified using the question; “Have you ever been told by a doctor that you have any chronic health problems?”. These included one or a combination of heart disease, high blood pressure, stroke, cancer, depressive disorder, anxiety disorder, psychotic illness, bipolar disorder, diabetes, arthritis, chronic back/neck pain, asthma, COPD, and chronic kidney/renal diseases [ 23 ].

Resilience was assessed using the six-item Brief Resilience Scale (BRS). The BRS measures an individuals’ ability to bounce back from an adverse event and focuses on the ability to recover [ 24 ]. The BRS is a reliable measure of resilience, with Cronbach’s alpha ranging from 0.80 to 0.91 and a 1 month test-retest reliability (ICC) of 0.69 [ 24 ]. The BRS is comprised of six items with three positively worded items (1, 3, and 5) and negatively worded items (2, 4, and 6). For example, a positive item states “I tend to bounce back quickly after hard times” while a negative item states “I have a hard time making it through stressful events”. Responses were provided on a 5-point Likert scale with anchors at 1 (strongly disagree) and 5 (strongly agree). The scale was scored by reverse coding the negative items and then averaging the total score for the six items. Final scores range from 1.0–5.0 with a score of 3.0–4.3 considered a normal level of resilience [ 25 ].

Psychological distress was measured using the 21-item Depression, Anxiety and Stress Scale (DASS-21) [ 26 ]. The DASS-21 has shown acceptable construct validity and high reliability (Cronbach’s alphas were 0.88, 0.82 and 0.90 for depression, anxiety and stress respectively) in a non-clinical adult population [ 27 ]. Each domain has seven items scored on a 4-point Likert scale between 0 (did not apply to me at all) and 3 (applied to me very much, or most of the time). Example items were “I was aware of dryness of my mouth” or “I found myself getting agitated”. A score was calculated for each domain by adding the scores for the relevant items and multiplying by two. Standard cut-points were used to determine whether participants had symptom severity above normal for depression (≥10 points), anxiety (≥8 points), and stress (≥15 points) [ 26 ].

Physical activity was assessed using the Active Australia Survey (AAS), which comprises eight items identifying the duration and frequency of walking, and moderate and vigorous (MVPA) physical activities, over the past 7 days. For example, questions about walking are “In the last week, how many times have you walked continuously, for at least 10 minutes, for recreation, exercise or to get to or from places?” and “What do you estimate was the total time that you spent walking in this way in the last week?”. The AAS guidelines were used to calculate total physical activity by summing minutes of walking, minutes of moderate activity, and minutes of vigorous activity (multiplied by 2). Participants were then categorised as meeting the physical activity guidelines (≥150 min of moderate – vigorous (MVPA) per week) or not (< 150 min MVPA per week) [ 28 ]. The AAS criterion validity has been found to be acceptable for use in self-administered format, with correlations between self-reported physical activity and weekly pedometer steps, and accelerometry being 0.43 and 0.52 respectively [ 29 ].

Statistical analysis was undertaken using SAS software v9.4. Two datasets, longitudinal and repeated cross-sectional, were analysed separately. Participants completing at least two surveys were included in the longitudinal dataset. The repeated cross-sectional dataset excluded those in the longitudinal dataset and therefore included only those completing one survey. Descriptive statistics (mean, standard deviation, and percentages) were calculated and are presented for each time point. Changes in resilience scores were examined using general linear mixed models for the longitudinal data, and general linear models for cross-sectional data. In addition to bivariate analyses, estimated changes in resilience scores were also adjusted for age, gender, years of education, weekly household income, relationship status, and chronic disease status. Multiple comparison correction was applied using the simulation option in PROC GLIMMIX.

Associations between resilience scores with physical activity and depression, anxiety, and stress were also examined using general linear mixed models for the longitudinal data and general linear models for the cross-sectional data. Three models were run for both datasets. Model 1 included resilience scores, time and either physical activity, depression, anxiety, or stress. Model 2 included the additional covariates: age, gender, years of education, weekly household income, relationship status, and chronic disease status. To examine whether the observed associations were independent, physical activity, depression, anxiety, and stress were also included in Model 3 together with time and all other covariates.

Due to missing values for the household income variable being higher than 10%, analyses were conducted with and without household income as a covariate. As the results between these two analyses did not change the findings, only models including household income are presented. Crude and adjusted differences in resilience scores with 95% confidence intervals are reported. All p -values were two sided and considered significant if < 0.05.

Table  1 shows characteristics of the longitudinal sample. At baseline, the majority of respondents were women (68.7%) and in a relationship (64.6%), with almost half reporting a chronic disease (47.5%). On average, participants were 52.5 (SD = 14.3) years old and had about 16 (SD = 4.7) years of education. Most had scores within the normal range for depression (64.0%), anxiety (80.7%), and stress (72.9%). More than half met the physical activity guidelines (56.4%). Average resilience score was about 3.4 out of 5.0 and within the normal range (3.0–4.3). The characteristics of those in the cross-sectional sample were very similar (Table  2 ).

Table  3 shows changes in resilience scores over time. In the longitudinal sample, crude (Model 1) and adjusted differences (aDif) (Model 2) in resilience scores were not significant between time 2 vs. time 1 (aDif = − 0.02, 95% CI = − 0.08, 0.03), and time 3 vs. time 1 (aDif = < 0.01, 95% CI = − 0.07, 0.06). Similarly, in the cross-sectional sample, crude and adjusted differences in resilience scores were not significant between time 2 vs. time 1 (aDif = − 0.04, 95% CI = − 0.14, 0.07), and time 3 vs. time 1 (aDif = − 0.02, 95% CI = − 0.15, 0.11).

Table  4 shows associations between resilience scores with physical activity, depression, anxiety, and stress. On average, those engaging in at least 150 min of MVPA per week had a significantly higher resilience score (Model 2) in the longitudinal (aDif = 0.10, 95% CI = 0.04, 0.16) and cross-sectional samples (aDif = 0.19, 95% CI = 0.11, 0.27). Resilience scores were also significantly higher for those with depression scores in the normal range (longitudinal sample: aDif = 0.40, 95% CI = 0.33, 0.46; cross-sectional sample: aDif = 0.72, 95% CI = 0.64, 0.79), anxiety scores in the normal range (longitudinal sample: aDif = 0.34, 95% CI = 0.26, 0.41; cross-sectional sample: aDif = 0.68, 95% CI = 0.60, 0.77), and stress scores in the normal range (longitudinal sample: aDif = 0.30, 95% CI = 0.23, 0.37; cross-sectional sample: aDif = 0.71, 95% CI = 0.63, 0.80). Additionally, model 3 shows significant associations between resilience with physical activity, depression, anxiety, and stress, independently from one another. Specifically, resilience scores were, on average, higher for those engaging in at least 150 min MVPA per week (longitudinal sample: aDif = 0.07, 95% CI = 0.01, 0.13; cross-sectional sample: aDif = 0.15, 95% CI = 0.08, 0.21), having depression scores in the normal range (longitudinal sample: aDif = 0.30, 95% CI = 0.22, 0.37; cross-sectional sample: aDif = 0.45, 95% CI = 0.37, 0.53), anxiety scores in the normal range (longitudinal sample: aDif = 0.19, 95% CI = 0.11, 0.27; cross-sectional sample: aDif = 0.20, 95% CI = 0.10, 0.30), and stress scores in the normal range (longitudinal sample: aDif = 0.12, 95% CI = 0.04, 0.19; cross-sectional sample: aDif = 0.30, 95% CI = 0.20, 0.40).

This study aimed to investigate changes in resilience of Australian adults across three time points in 2020 during the COVID-19 pandemic, and the associations between resilience and physical activity, depression, anxiety, and stress. The findings show that resilience scores did not change significantly during the pandemic and that participants who engaged in at least 150 MVPA minutes per week, and with depression, anxiety, and stress scores within the normal range, had higher resilience scores. The findings were consistent between the longitudinal and cross-sectional datasets; however, the effects were larger in the cross-sectional data.

Given the extraordinary social circumstances brought about by Australian state governments to enforce movement restrictions in response to the COVID-19 pandemic, and the uncertainty as a result of the health and economic impact of the pandemic, resilience levels may have changed. However, the results from this study suggest that resilience levels largely remained stable during the pandemic, which is consistent with the results from a study in Israel [ 6 ]. This is likely due to the samples (both longitudinal and cross-sectional) including mostly Australian adults (about three quarters) with high or normal levels of resilience. Therefore, they may manage and adapt well to the impacts caused by the pandemic. Another factor may be that the Australian government was effective in responding to the pandemic (ranking 3rd among OECD countries) and providing Australians with financial support and mental health consultation via telehealth [ 30 ], and therefore helping to alleviate the impacts. It is less likely, but also possible, that levels of resilience may have decreased between pre-COVID-19 and our first survey. Unfortunately, pre-COVID-19 data are not available for comparison. However, one study comparing two cross-sectional samples in small towns in upstate New York found no significant difference in resilience between pre-COVID-19 (November and December 2019) and peak-COVID-19 (mid-April 2020) [ 5 ].

Our findings are consistent with previous studies that have found inverse associations between levels of resilience and psychological distress among patients with chronic diseases [ 31 , 32 , 33 ], and medical students [ 34 , 35 ]. This finding is also consistent with those from other studies conducted during the COVID-19 pandemic in the U.S [ 36 , 37 ] and Italy [ 38 ]. These associations were expected, as resilience reflects an individual’s ability to cope with life’s adversity, trauma, and threats; and therefore, plays a role as an adaptive defence system against psychological distress such as depression, anxiety, and stress [ 39 ]. Given their significant effects on resilience, depression, anxiety, and stress are important factors that should be considered in interventions to improve resilience level in adult populations.

Resilience was also found to be positively associated with physical activity levels in studies conducted during the COVID-19 pandemic, which is consistent with findings in the present study [ 7 , 18 , 19 ]. The positive effects of physical activity on resilience may occur through improving mental health and possible underlying mechanisms for this were discussed by Silverman et al. (2014) [ 20 ]. For example, physical activity could serve as a buffer against stress and stress-related disorders. Physical activity also has benefits on brain and hormonal stress-responsive systems that could improve mood and cognition [ 20 , 40 ]. In this study, we found that physical activity was associated with resilience, independent of depression, anxiety, and stress levels. Although the effect size of physical activity (adjusted difference of 0.07 points) was small compared to that of depression (0.30 points), anxiety (0.19 points), and stress (0.12 points). Given that physical activity has other benefits on both physical and mental health [ 17 ], it is still an important factor for consideration in interventions targeting resilience levels.

There are a number of strengths in this study. First, the sample size is large with participants from all states and territories in Australia. Second, to the best of our knowledge, this is the first longitudinal study to explore levels of resilience during the COVID-19 pandemic in Australia. However, the study has limitations. Participation in this study was voluntary with nearly half of the sample having at least one chronic health condition and therefore, the findings may not be generalisable to populations with different characteristics. The self-reported questionnaires are also subject to recall bias, despite being validated instruments. In addition, the first survey started when the pandemic had already begun; and no pre-COVID-19 data was available. Therefore, it is not possible to know whether (and how) resilience scores changed between the pre-COVID-19 period and the first survey.

For the future, the findings from this study helps inform interventions that aim to enhance or nurture resilience. In particular, health promotion strategies that screen for, then target people identified as being at risk of psychological distress, those with low levels of resilience, or those not meeting the physical activity guidelines may maximize the effects of the interventions. Primary health care providers, Government websites, not-for-profit, or other mental health services could provide rapid screening then direct people to appropriate care.

Resilience scores did not change significantly during the COVID-19 pandemic. Participants who met the physical activity guidelines, had depression, anxiety, and stress scores within the normal range, had higher resilience scores compared to those who were less active and those with more psychological distress. Maintaining healthy behaviours such as regular physical activity may buffer the adverse psychological effect of the pandemic and maintain mental health and wellbeing.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

the Active Australia Survey

The Brief Resilience Scale

the Depression, Anxiety, and Stress Scale

Moderate and Vigorous Physical Activity

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Quyen G. To, Corneel Vandelanotte, Saman Khalesi, Susan L. Williams, Stephanie J. Alley, Tanya L. Thwaite & Robert Stanton

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To, Q.G., Vandelanotte, C., Cope, K. et al. The association of resilience with depression, anxiety, stress and physical activity during the COVID-19 pandemic. BMC Public Health 22 , 491 (2022). https://doi.org/10.1186/s12889-022-12911-9

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Depression and Suicide Risk Screening: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

Affiliations.

• 1 Kaiser Permanente Evidence-based Practice Center, Kaiser Permanente Center for Health Research, Portland, Oregon.
• 2 Gillings School of Global Public Health, University of North Carolina School of Medicine, Chapel Hill.
• PMID: 37338873
• DOI: 10.1001/jama.2023.7787

Importance: Depression is common and associated with substantial burden. Suicide rates have increased over the past decade, and both suicide attempts and deaths have devastating effects on individuals and families.

Objective: To review the benefits and harms of screening and treatment for depression and suicide risk and the accuracy of instruments to detect these conditions among primary care patients.

Data sources: MEDLINE, PsychINFO, Cochrane library through September 7, 2022; references of existing reviews; ongoing surveillance for relevant literature through November 25, 2022.

Study selection: English-language studies of screening or treatment compared with control conditions, or test accuracy of screening instruments (for depression, instruments were selected a priori; for suicide risk, all were included). Existing systematic reviews were used for treatment and test accuracy for depression.

Data extraction and synthesis: One investigator abstracted data; a second checked accuracy. Two investigators independently rated study quality. Findings were synthesized qualitatively, including reporting of meta-analysis results from existing systematic reviews; meta-analyses were conducted on original research when evidence was sufficient.

Main outcomes and measures: Depression outcomes; suicidal ideation, attempts, and deaths; sensitivity and specificity of screening tools.

Results: For depression, 105 studies were included: 32 original studies (N=385 607) and 73 systematic reviews (including ≈2138 studies [N ≈ 9.8 million]). Depression screening interventions, many of which included additional components beyond screening, were associated with a lower prevalence of depression or clinically important depressive symptomatology after 6 to 12 months (pooled odds ratio, 0.60 [95% CI, 0.50-0.73]; reported in 8 randomized clinical trials [n=10 244]; I2 = 0%). Several instruments demonstrated adequate test accuracy (eg, for the 9-item Patient Health Questionnaire at a cutoff of 10 or greater, the pooled sensitivity was 0.85 [95% CI, 0.79-0.89] and specificity was 0.85 [95% CI, 0.82-0.88]; reported in 47 studies [n = 11 234]). A large body of evidence supported benefits of psychological and pharmacologic treatment of depression. A pooled estimate from trials used for US Food and Drug Administration approval suggested a very small increase in the absolute risk of a suicide attempt with second-generation antidepressants (odds ratio, 1.53 [95% CI, 1.09-2.15]; n = 40 857; 0.7% of antidepressant users had a suicide attempt vs 0.3% of placebo users; median follow-up, 8 weeks). Twenty-seven studies (n = 24 826) addressed suicide risk. One randomized clinical trial (n=443) of a suicide risk screening intervention found no difference in suicidal ideation after 2 weeks between primary care patients who were and were not screened for suicide risk. Three studies of suicide risk test accuracy were included; none included replication of any instrument. The included suicide prevention studies generally did not demonstrate an improvement over usual care, which typically included specialty mental health treatment.

Conclusions and relevance: Evidence supported depression screening in primary care settings, including during pregnancy and postpartum. There are numerous important gaps in the evidence for suicide risk screening in primary care settings.

Publication types

• Meta-Analysis
• Research Support, U.S. Gov't, P.H.S.
• Systematic Review
• Antidepressive Agents / therapeutic use
• Depression* / diagnosis
• Depression* / therapy
• Mass Screening* / adverse effects
• Mass Screening* / methods
• Meta-Analysis as Topic
• Psychotherapy
• Randomized Controlled Trials as Topic
• Risk Assessment
• Sensitivity and Specificity
• Suicide, Attempted / prevention & control
• United States
• Antidepressive Agents

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• Anxiety, Depression, and Post-Traumatic Stress Disorder Currently, many people experience anxiety, depression, and post-traumatic stress disorder that affect their general health.
• Relation Between the COVID-19 Pandemic and Depression The paper is to share an insight into the detrimental effects of the COVID-19 pandemic on the mental health of thousands of people and provide advice on how to reduce its impact.
• How Covid-19 Isolation Contributed to Depression and Adolescent Suicide The pandemic affected adolescents because of stringent isolation measures, which resulted in mental challenges such as depression and anxiety, hence suicidal thoughts.
• The Rise of Depression in the Era of the Internet Understanding how the Internet affects human lives is essential in ascertaining the reasons for the growing loneliness in the intrinsically connected world.
• Depression as It Relates to Obesity This paper will argue that there is a positive correlation between depression and obesity. The paper will make use of authoritative sources to reinforce this assertion.
• Literature Evaluation on the Depression Illness The evaluation considers the articles that study such medical illness as depression from different planes of its perception.
• Application of Analysis of Variance in the Analysis of HIV/AIDS-Related Depression Cases Analysis of variance (ANOVA) is a commonly used approach in the testing of the equality of various means using variance.
• Components of the Treatment of Depression The most effective ways of treating people with depression include pharmacotherapy, psychotherapy or a combination of both.
• What Are the Characteristics and Causes of Depression?
• Why Are Athletes Vulnerable to Depression?
• Why and How Adolescents Are Affected by Generalized Anxiety Disorder and Clinical Depression?
• Does Depression Assist Eating Disorders?
• What Should You Know About Depression?
• How Can Mother Nature Lower Depression and Anxiety?
• How Can Video Games Relieve Stress and Reduce Depression?
• When Does Teacher Support Reduce Depression in Students?
• Why Are Teenagers Affected by Depression?
• How Teens and Depression Today?
• Are Mental Health Issues Like Depression Related to Race?
• What Does Depression Mean?
• How Did the Depression Affect France?
• How Does Depression Stop?
• When Postpartum Depression Leads to Psychosis?
• How Do Medication and Therapy Combat Depression?
• What Are the Leading Causes of Depression?
• What About Drugs for Anxiety and Depression?
• What’s the Big Deal About Anxiety and Depression in Students?
• How Should Childhood Depression and Anxiety Be?
• How Do Gender Stereotypes Warp Our View of Depression?
• What Are the Signs of Teenage Depression?
• Are Testosterone Levels and Depression Risk Linked Based on Partnering and Parenting?
• How Psychology Helps People With Depression?
• How Should Childhood Depression and Anxiety Be Treated or Dealt With?
• Adult Depression Treatment in the United States This study characterizes the treatment of adult depression in the US. It is prompted by the findings of earlier studies, which discover the lack of efficient depression care.
• Homelessness and Depression Among Illiterate People There are various myths people have about homelessness and depression. For example, many people believe that only illiterate people can be homeless.
• Depression and Workplace Violence The purpose of this paper is to provide an in-depth analysis how can workplace violence and verbal aggression be reduced or dealt with by employees.
• Patients with Depression’ Care: Betty Case Betty, a 45 years old woman, is referred to a local clinic because of feeling depressed. She has a history of three divorces and thinks that she is tired of living the old way.
• Depression in Hispanic Culture There are different ways in which culture or ethnicity can impact the treatment of the development of mental health disorders.
• “Yoga for Depression” Article by The Minded Institute One can say that depression is both the biological and mental Black Death of modern humanity in terms of prevalence and negative impact on global health.
• Mitigating Postnatal Depression in New Mothers: A Recreational Program Plan Post-natal depression is a popular form of depression in women. This paper presents an activity plan for the use of leisure as a therapeutic response to post-natal depression.
• History and Treatment of Depression Depression is currently one of the most common medical conditions among the adult population in the US. The paper aims to investigate the history and treatment of depression.
• Effects of Music Therapy on Depressed Elderly People Music therapy has been shown to have positive effects among people, and thus the aim was to assess the validity of such claims using elderly people.
• Self-Esteem and Depression in Quantitative Research The topic that has been proposed for quantitative research pertains to the problem of the relationship between self-esteem and depression.
• Major Depression’ Symptoms and Treatment – Psychology A continuous sense of tiredness, unhappiness, and hopelessness are key signs of clinical or major depression. Such mood changes alter the daily life programs of an individual for sometimes.
• Women’s Mental Health Disorder: Major Depression The mental health disorder paper aims to explore major depression, its symptoms, assessment, and intervention strategies appropriate for women.
• Depression in Young Adults: Annotated Bibliography The purpose of this study was to discover sociodemographic and health traits related to depression sufferers’ usage of various mental health services.
• Depression in Middle-Aged African Women The research study investigates depression in middle-aged African women because the mental health of the population is a serious concern of the modern healthcare sector.
• Detecting Depression in Young Adults: Literature Review The paper shows a need for early identification of depression symptoms in primary care practice. PHQ-2 and PHQ-9 are useful tools for portraying symptoms.
• Predicting Barriers to Treatment for Depression Mental health issues such as depression and drug abuse are the most frequent among teenagers and young adults. In this age range, both disorders tend to co-occur.
• Early Diagnosis of Depression: Public Health Depression in young adults has become a significant health problem across the US. It causes persistent feelings of loss of interest in activities and sadness.
• Depression and Social Media in Scientific vs. Popular Articles The damage can come in the form of misinformation, which can result in an unjustified and unnecessary self-restriction of social media.
• Depression in Adolescence: Causes and Treatment Depression amongst young adults at the puberty stage comes in hand with several causes that one cannot imagine, and depression happens or is triggered by various reasons.
• Addressing Depression Among Native Youths The current paper aims to utilize a Medicine Wheel model and a social work paradigm to manage depression among Native American Indian youths.
• Psychological Assessments and Intervention Strategies for Depression The article presents two case studies highlighting the importance of psychological assessments and intervention strategies for individuals experiencing depression.
• The Impact of Postpartum Maternal Depression on Postnatal Attachment This paper examines the influence of postpartum maternal depression on postnatal infant attachment, discusses the adverse effects of depression on attachment.
• Marijuana Effects on Risk of Anxiety and Depression The current paper aims to find out whether medical cannabis can positively affect anxiety and depression and the process of their treatment.
• Cognitive Behavioral Therapy for Anxiety and Depression Cognitive behavioral therapy analyzes the unconscious processes influencing the normal functioning of the human body, causing different pathologies.
• Hypnotherapy as an Effective Method for Treating Depression This paper explores the use of hypnotherapy as a treatment for depression and highlights the advantages of hypnosis in addressing depressive symptoms.
• Depression and Anxiety: Mary’s Case Mary’s husband’s death precipitated her depression and anxiety diagnosis. She feels lonely and miserable as she struggles with her daily endeavors with limited emotional support.
• Postpartum Depression in Women and Men The focus of the paper is health problems that affect women after giving birth to a child, such as depression. The author proposes that men also experience postpartum depression.
• Repression and Depression in “The Yellow Wallpaper” by Charlotte Perkins Gilman In “The Yellow Wallpaper” by Charlotte Perkins Gilman, the author highlighted the connection between repression and depression.
• Men and Depression: Signs, Symptoms, Causes, and Treatment Depression in men and women has several incompatibilities as males suffer from health problems more often than women as they rarely express their emotions.
• Promotion of Change Regarding Adolescent Depression In the essay, the author describes the methods to evaluate the symptoms of a patient who has been referred for counseling with depression.
• Interventions to Cope With Depression Depression is characterized by sadness, anxiety, feelings of worthlessness, and helplessness. These feelings do not necessarily relate to life events.
• Bipolar Depression and Bipolar Mania Although all bipolar disorders are characterized by periods of extreme mood, the main difference between them is the severity of the condition itself.
• Post-Stroke Anxiety and Depression The purpose of the given study is to ascertain how cognitive behavior therapy affects individuals with post-stroke ischemia in terms of depression reduction.
• Depression and Anxiety Management The medical staff will investigate the treatment modalities currently being utilized for the large population of patients experiencing symptoms of anxiety and depression.
• Is depression a biological condition or a result of unrealistic expectations?
• Should employers be legally required to provide support to workers with depression?
• Do the media portrayals of depression accurately reflect people’s experiences?
• Social media contributes to depression rates by eliciting the feeling of loneliness.
• Should mental health screening be mandatory in schools?
• Should depression be reclassified as a neurological disorder?
• Antidepressants are an overused quick-fix solution to depression.
• Should non-pharmacological treatments for depression be prioritized?
• Should depression be considered a disability?
• The use of electroconvulsive therapy for depression should be banned.
• Impacts of Stress of Low Income on the Risk of Depression in Children Socioeconomic hardships lead to a decline in the quality of parenting and the development of psychological and behavioral problems in children.
• African American Children Suffering From Anxiety and Depression Depression and anxiety are common among African American children and adolescents, and they face significant barriers to receiving care and treatment.
• Depression: Diagnostics and Treatment Depression, when it remains unchecked, can cause detrimental effects to individuals, such as suicide, which will eventually equate to mental disorders.
• Psychedelics in Depression and Anxiety Treatment Mental illnesses have become an essential part of health in the last few decades, with sufficient attention being devoted to interventions that resolve them.
• Depression and Anxiety Among African-American Children Depression and anxiety are common among African-American children and adolescents, but they face significant barriers to receiving care and treatment due to their age and race.
• Why Are Physical Activities Treatments for Depression? In this paper, the connection between physical activities and depression will be analyzed, and the common counterargument will be discussed.
• Depression in the Older Population The paper discusses depression is an actual clinical disorder for older people with specific reasons related to their age.
• Nutrition and Depression: A Psychological Perspective When discussing nutrition in toddlers and certain behavioral patterns, one of the first standpoints to pay attention to is the humanistic perspective.
• Social Media and Depression in Adolescents: The Causative Link This paper explores how social media causes depression in adolescents during the social-emotional stage of life.
• Physical Activities as Treatment for Depression This paper will discuss what factors are improved via physical exercise and how they help with treating depression.
• Therapeutic Interventions for the Older Adult With Depression and Dementia The paper researches the therapeutic interventions which relevant for the older people with depression and dementia nowadays.
• Depression Among Patients With Psoriasis Considering psoriasis as the cause of the development of depressive disorders, many researchers assign a decisive role to the severe skin itching that accompanies psoriasis.
• Qi Gong Practices’ Effects on Depression Qi Gong is a set of physical and spiritual practices aimed at the balance of mind, body, and soul and the article demonstrates whether it is good or not at treating depression.
• The Effects of Forgiveness Therapy on Depression for Women The study analyzes the impact of forgiveness therapy on the emotional state of women who have experienced emotional abuse.
• Post-operative Breast Cancer Patients With Depression: Annotated Bibliography This paper is an annotated bibliography about risk reduction strategies at the point of care: Post-operative breast cancer patients who are experiencing depression.
• Depression and Anxiety in Older Generation Depression and anxiety represent severe mental disorders that require immediate and prolonged treatment for patients of different ages.
• Coping with Depression After Loss of Loved Ones This case is about a 60-year-old man of African American origin. He suffered from depression after his wife’s death, which made him feel lonely and isolated.
• Postpartum Depression Screening Program Evaluation In order to manage the depression of mothers who have just delivered, it is important to introduce a routine postpartum depression-screening program in all public hospitals.
• Is Creativity A Modern Panacea From Boredom and Depression? Communication, daily life, and working patterns become nothing but fixed mechanisms that are deprived of any additional thoughts and perspectives.
• Adolescent Males With Depression: Poly-Substance Abuse Depression is the most crucial aspect that makes young males indulge in poly-substance abuse. There are various ways in which male adolescents express their depression.
• The Health of the Elderly: Depression and Severe Emotional Disturbance This study is intended for males and females over the age of 50 years who are likely to suffer from depression and severe emotional disturbance.
• Suicidal Ideation & Depression in Elderly Living in Nursing Home vs. With Family This paper attempts to compare the incidence of suicidal ideation and depression among elderly individuals living in nursing homes and those living with family in the community.
• Major Depression: Symptoms and Treatment Major depression is known as clinical depression, which is characterized by several symptoms. There are biological, psychological, social, and evolutionary causes of depression.
• Health Disparity Advocacy: Clinical Depression in the U.S. Recent statistics show that approximately more than 10 million people suffer from severe depression each year in the U.S..
• Serum Neurotrophic Factors in Adolescent Depression by Pallavi et al. The research hypothesis of the article is to compare the serum concentration of neurotrophic factors in depression patients and healthy control.
• The Treatment of Anxiety and Depression The meta-analysis provides ample evidence, which indicates that CES is not only effective but also safe in the treatment of anxiety and depression.
• Depression Intervention Among Diabetes Patients The research examines the communication patterns used by depression care specialist nurses when communicating with patients suffering from diabetes.
• Postnatal Depression in New Mothers and Its Prevention Leisure activities keep new mothers suffering from postnatal depression busy and enable them to interact with other members of the society.
• Treatment of Major Depression The purpose of the paper is to identify the etiology and the treatment of major depression from a psychoanalytic and cognitive perspective.
• Edinburgh Depression Screen for Treating Depression Edinburgh Depression screen is also known as Edinburgh Postnatal Depression Scale which is used to screen pregnant and postnatal women for emotional distress.
• Depression Treatment Variants in the US There is a debate regarding the best formula for depression treatment whereby some argue for using drugs, whereas others are advocating for therapy.
• Depression in the Elderly: Treatment Options Professionals may recommend various treatment options, including the use of antidepressants, psychotherapy such as cognitive-behavioral therapy.
• Depression Treatments and Therapeutic Strategies This article examines the effectiveness of different depression treatments and reviews the therapeutic strategies, which can be helpful if the initial treatment fails.
• Depression and the Nervous System Depression is a broad condition that is associated with failures in many parts of the nervous system. It can be both the cause and the effect of this imbalance.
• Can physical exercise alone effectively treat depression?
• Art therapy as a complementary treatment for depression.
• Is there a link between perfectionism and depression?
• The influence of sleep patterns on depression treatment outcomes.
• Can exposure to nature and green spaces decrease depression rates in cities?
• The relationship between diet and depression symptoms.
• The potential benefits of psychedelic-assisted therapy in treating depression.
• The role of outdoor experiences in alleviating depression symptoms.
• The relationship between depression and physical health in older adults.
• The role of workplace culture in preventing employee depression.
• Depression: Types, Symptoms, Etiology & Management Depression differs from other disorders, connected with mood swings, and it may present a serious threat to the individual’s health condition.
• The Effect of Music Therapy on Depression One major finding of study is that music therapy alleviates depression among the elderly. Music therapy could alleviate depression.
• Post-Natal Depression as an Affective Disorder Postpartum or post-natal depression (PPD) is a serious issue that can potentially be destructive to both infant and mother.
• “Neighborhood Racial Discrimination and the Development of Major Depression” by Russell The study investigates how neighborhood racial discrimination influences this severe mental disorder among African American Women.
• Adolescent Depression and Physical Health Depression in adolescents and young people under 24 is a factor that affects their physical health negatively and requires intervention from various stakeholders.
• Family Support to a Veteran With Depression Even the strongest soldiers become vulnerable to multiple health risks and behavioral changes, and depression is one of the problems military families face.
• Alcohol and Depression Article by Churchill and Farrell The selected article for this discussion is “Alcohol and Depression: Evidence From the 2014 Health Survey for England” by Sefa Awaworyi Churchill and Lisa Farrell.
• Negative Effects of Depression in Adolescents on Their Physical Health Mental disorders affect sleep patterns, physical activity, digestive and cardiac system. The purpose of the paper to provide information about adverse impacts of depression on health.
• Elderly Depression: Symptoms, Consequences, Behavior, and Therapy The paper aims to identify symptoms, behavioral inclinations of older adults, consequences of depression, and treatment ways.
• Depression in Feminist Literature of the 1890s The aim of the work is to analyze the cause of female sickness, which is their inability to express themselves and the pitiful place of a female in the society of that time.
• Major Depression Disorder: Causes and Treatment Loss in weight and appetite are some of the symptoms that a patient diagnosed with Major Depression Disorder could manifest.
• Mood Disorders: Depression Concepts Description The essay describes the nature of depression, its causes, characteristics, consequences, and possible ways of treatment.
• Geriatric Depression Diagnostics Study Protocol The research question is: how does the implementation of the National Institute for Health and Care Excellence guidelines affect the accuracy of diagnosing of depression?
• Mental Health Association of Depression and Alzheimer’s in the Elderly Depression can be a part of Alzheimer’s disease. Elderly people may have episodes of depression, but these episodes cannot be always linked to Alzheimer’s disease.
• Protective Factors Against Youthful Depression Several iterations of multiple correlation, step-wise and hierarchical regression yielded inconclusive results about the antecedents of youthful depression.
• Depression and Other Antecedents of Obesity Defeating the inertia about taking up a regular programme of sports and exercise can be a challenging goal. Hence, more advocacy campaigns focus on doing something about obesity with a more prudent diet.
• Depression and Related Psychological Issues Depression as any mental disorder can be ascribed, regarding the use of psychoanalysis, to a person`s inability to control his destructive or sexual instincts or impulses.
• Television Habituation and Adolescent Depression The paper investigates the theory that there is a link between heavy TV viewing and adolescent depression and assess the strength of association.
• Physiological Psychology. Postpartum Depression Depression is a focal public health question. In the childbearing period, it is commoner in females than in males with a 2:1 ratio.
• Adolescent Depression: Modern Issues and Resources Teenagers encounter many challenging health-related issues; mental health conditions are one of them. This paper presents the aspects of depression in adolescents.
• Occupational Psychology: Depression Counselling The case involves a 28-year-old employee at Data Analytics Ltd. A traumatic event affected his mental health, causing depression and reduced performance.
• Psychotherapeutic Group: Treatment of Mild-To-Moderate Depression The aim of this manual is to provide direction and employ high-quality sources dedicated to mild-to-moderate depression and group therapy to justify the choices made for the group.
• “Depression and Ways of Coping With Stress” by Orzechowska et al. The study “Depression and Ways of Coping With Stress” by Orzechowska et al. aimed the solve an issue pertinent to nursing since depression can influence any patient.
• Effectiveness of Telenursing in Reducing Readmission, Depression, and Anxiety The project is dedicated to testing the effectiveness of telenursing in reducing readmission, depression, and anxiety, as well as improving general health outcomes.
• Nurses’ Interventions in Postnatal Depression Treatment This investigation evaluates the effect of nurses’ interventions on the level of women’s postnatal depression and their emotional state.
• Postpartum Depression: Evidence-Based Care Outcomes In this evidence-based study, the instances of potassium depression should be viewed as the key dependent variable that will have to be monitored in the course of the analysis.
• Postpartum Depression: Diagnosis and Treatment This paper aims to discuss the peculiarities of five one-hour classes on depression awareness, to implement this intervention among first-year mothers, and to evaluate its worth during the first year after giving birth.
• Postpartum Depression In First-time Mothers The most common mental health problem associated with childbirth remains postpartum depression, which can affect both sexes, and negatively influences the newborn child.
• The Diagnosis and Treatment of Postpartum Depression Postpartum depression has many explanations, but the usual way of referring to this disease is linked to psychological problems.
• What Is Postpartum Depression? Causes, Symptoms, and Treatment The prevalence of postpartum depression is quite high as one in seven new American mothers develops this health issue.
• Depression in Adolescence as a Contemporary Issue Depression in adolescents is not medically different from adult depression but is caused by developmental and social challenges young people encounter.
• Predictors of Postpartum Depression The phenomenon of postpartum depression affects the quality of women’s lives, as well as their self-esteem and relationships with their child.
• Depression and Self-Esteem: Research Problem Apart from descriptively studying the relationship between depression and self-esteem, a more practical approach can be used to check how interventions for enhancing self-esteem might affect depression.
• The Relationship Between Depression and Self-Esteem The topic which is proposed to be studied is the relationship between depression and self-esteem. Self-esteem can be defined as individual’s subjective evaluation of his or her worth.
• The Impact of Depression on Motherhood This work studies the impact of depression screening on prenatal and posts natal motherhood and effects on early interventions using a literature review.
• Depression in Female Cancer Patients and Survivors Depression is often associated with fatigue and sleep disturbances that prevent females from thinking positively and focusing on the treatment and its outcomes.
• Depression in Cardiac or Diabetic Patients The paper develops a framework through which risk factors associated with the development of MDD among adult patients with heart disease or diabetes can be easily identified.
• The Geriatric Population’s Depression This paper discusses how does the implementation of National Institute for Health and Care guidelines affect the accuracy of diagnosing of depression in the geriatric population.
• Problem of Depression: Recognition and Management Depression is a major health concern, which is relatively prevalent in the modern world. Indeed, in the US, 6.7 % of adults experienced an episode of the Major Depressive Disorder in 2015.
• Health and Care Excellence in Depression Management The introduction of the National Institute for Health and Care Excellence guidelines can affect the accuracy of diagnosing and quality of managing depression.
• Impact of COVID-19 on Depression and Suicide Rates among Adolescents and Young People The purpose of this paper is to explore the influence of coronavirus on these tragic numbers.
• Mild Depression: Psychotherapy or Pharmacotherapy The research question in this paper is: in psychiatric patients with mild depression, what is the effect of psychotherapy on health compared with pharmacotherapy?
• Postpartum Bipolar Disorder and Depression The results of the Mood Disorder Questionnaire screening of a postpartum patient suggest a bipolar disorder caused by hormonal issues and a major depressive episode.
• Bipolar Disorder or Manic Depression Bipolar disorder is a mental illness characterized by unusual mood changes that shift from manic to depressive extremes. In the medical field, it`s called manic depression.
• The Improvement of Depression Management The present paper summarizes the context analysis that was prepared for a change project aimed at the improvement of depression management.
• Depression Management in US National Guidelines The project offers the VEGA medical center to implement the guidelines for depression management developed by the National Institute for Health and Care Excellence.
• Women’s Health and Major Depression Symptoms The client’s complaints refer to sleep problems, frequent mood swings (she gets sad a lot), and the desire to stay away from social interactions.
• Predictors of Postpartum Depression: Who Is at Risk? The article “Predictors of Postpartum Depression” by Katon, Russo, and Gavin focuses on the identification of risk factors related to postnatal depression.
• Depression and Its Treatment: Racial and Ethnic Disparities The racial and ethnic disparities in depression treatment can be used for the development of quality improvement initiatives aimed at the advancement of patient outcomes.
• Lamotrigine for Bipolar Depression Management Lamotrigine sold as Lamictal is considered an effective medication helping to reduce some symptoms that significantly affect epileptic and bipolar patients’ quality of life.
• Citalopram, Methylphenidate in Geriatric Depression Citalopram typically ranges among 10-20 antidepressants for its cost-effectiveness and positive effect on patients being even more effective than reboxetine and paroxetine.
• Depression and Self-Esteem Relationship Self-esteem can be defined as an “individual’s subjective evaluation of his or her worth as a person”; it does not necessarily describe one’s real talents.
• Postpartum Depression: Methods for the Prevention Postpartum depression is a pressing clinical problem that affects new mothers, infants, and other family members. The prevalence of postpartum depression ranges between 13 and 19 percent.
• Anxiety and Depression Among Females with Cancer The study investigated the prevalence of and the potential factors of risk for anxiety and/or depression among females with early breast cancer during the first 5 years.
• Post-Partum Depression and Perinatal Dyadic Psychotherapy Post-partum depression affects more than ten percent of young mothers, and a method Perinatal Dyadic Psychotherapy is widely used to reduce anxiety.
• VEGA Medical Center: Detection of Depression Practice guidelines for the psychiatric evaluation of adults, and they can be employed to solve the meso-level problem of the VEGA medical center and its nurses.
• The Postnatal (Postpartum) Depression’ Concept Postnatal or postpartum depression (PPD) is a subtype of depression which is experienced by women within the first half a year after giving birth.
• Depression in Obstetrics and Gynecology: Research This essay analyzes a clinical research article “Improving care for depression in obstetrics and gynecology: A randomized controlled trial” by Melville et al.
• Postpartum Depression, Prevention and Treatment Postpartum depression is a common psychiatric condition in women of the childbearing age. They are most likely to develop the disease within a year after childbirth.
• Smoking Cessation and Depression Problem The aim of the study is to scrutinize the issues inherent in the process of smoking cessation and align them with the occurrence of depression in an extensive sample of individuals.
• The Efficacy of Medication in Depression’ Treatment This paper attempts to provide a substantial material for the participation in an argument concerning the clinical effectiveness of antidepressant medications.
• Depression and Cognitive Psychotherapy Approaches Cognitive psychotherapy offers various techniques to cope with emotional problems. This paper discusses the most effective cognitive approaches.
• Treatment of Depression in Lesbians The aim of this paper is to review a case study of 45 years old lesbian woman who seeks treatment for depression and to discuss the biophysical, psychological, sociocultural, health system.
• Women’s Health: Predictors of Postpartum Depression The article written by Katon, Russo, and Gavin is focused on women’s health. It discusses predictors of postpartum depression (PPD), including sociodemographic and clinic risk factors.
• Depression Treatment and Management Treatment could be started only after patient is checked whether he has an allergy to the prescribed pills or not. If he is not allergic, he should also maintain clinical tests for depression.
• Depression and Thyroid Issues in Young Woman Young people are busy at studies or at work and do not pay much attention to primary symptoms unless they influence the quality of life.
• Counseling Depression: Ethical Aspects This paper explores the ethical aspects required to work with a widower who diminished passion for food, secluding himself in the house, portraying signs of depression.
• Postpartum Depression as Serious Mental Health Problem The research study aimed to evaluate the effectiveness of a two-step behavioral and educational intervention on the symptoms of postpartum depression in young mothers.
• European Alliances, Wars, Dictatorships and Depression The decades leading to World War I had unusual alignments. The European nations were still scrambling for Asia, Africa and parts of undeveloped Europe.
• Women’s Health: Depression as a Psychological Factor Women who identify themselves as lesbian are likely to experience depression. Biophysical, psychological, sociocultural, behavioral, and health system factors should be taken into consideration.
• Childhood Obesity and Depression Intervention The main intervention to combat depressive moods in adolescents should be linked to improving the psychological health of young people in cooperation with schools.
• Postnatal Depression Prevalence and Effects The paper analyzes the prevalence and risk factors of Postnatal (Postpartum) Depression as well as investigates the effect on the newborns whose mothers suffer from this condition.
• Depression in Older Adults Depression is one of the most common mental illnesses in the world. Evidence-based holistic intervention would provide more effective treatment for elderly patients with depression.
• Placebo and Treatments for Depression Natural alternative treatments for depression actually work better than the biochemical alternatives like antidepressants.
• Care for Depression in Obstetrics and Gynecology This work analyzes the article developed by Melville et al. in which discusses the theme of depression in obstetrics and gynecology and improving care for it.
• Depression Screening in Primary Care Screening for depression in patients suffering from long term conditions (LTCs) or persistent health problems of the body, could largely be erroneous.
• Clinical Depression Treatment: Issues and Solvings The paper describes and justifies the design selected for research on depression treatment. It also identifies ethical issues and proposes ways of addressing them.
• Depression in Older Persons – Psychology This article presents the research findings of a study conducted in Iran to assess how effective integrative and instrumental therapies are in the management of depression in older persons.
• Depression in the Elderly – Psychology This paper discusses how a person would know whether a relative had clinical depression or was sad due to specific changes or losses in life.
• Postnatal Depression: Prevalence of Postnatal Depression in Bahrain The study was aimed at estimating the prevalence of postnatal depression among 237 Bahraini women who attended checkups in 20 clinical centres over a period of 2 months.

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StudyCorgi . "227 Depression Research Topics & Essay Titles + Examples." September 9, 2021. https://studycorgi.com/ideas/depression-essay-topics/.

StudyCorgi . 2021. "227 Depression Research Topics & Essay Titles + Examples." September 9, 2021. https://studycorgi.com/ideas/depression-essay-topics/.

These essay examples and topics on Depression were carefully selected by the StudyCorgi editorial team. They meet our highest standards in terms of grammar, punctuation, style, and fact accuracy. Please ensure you properly reference the materials if you’re using them to write your assignment.

This essay topic collection was updated on January 22, 2024 .

Depression and Anxiety Are on the Rise Globally

A new study shows we’re experiencing a mental health crisis. what’s going on.

Posted November 1, 2021 | Reviewed by Davia Sills

• What Is Anxiety?
• Find counselling to overcome anxiety
• The overall rates of depression and anxiety have gone up during the COVID pandemic, with more women being impacted than men.
• Some reasons include women taking on more household responsibilities during COVID and the gender pay gap increasing during this difficult time.
• Providing easier access to mental health care and reducing stigma may encourage people to seek help when they need it.

I recently came across a study published in The Lancet that startled me. The findings on depression and anxiety disorder were grim, and no surprise, COVID-19 was the big culprit.

But COVID wasn’t the whole story, as I will explain. I also have some (hopefully) helpful advice to impart regarding mental illness, and I’ll get to that as well.

First, a quick recap of the study’s key findings.

Key Points From the Global Study

Published in the online version of The Lancet on October 8, 2021, and co-authored by dozens of researchers worldwide, the study looked at the prevalence and burden of depressive and anxiety disorders in 204 countries and territories during 2020, when the pandemic was at its worst. The study authors also discussed historical data on global depression and anxiety prevalence, providing context from the pre-pandemic period.

Study highlights include:

• Among both genders, the prevalence of anxiety disorder went up 25.6 percent worldwide during the pandemic. For depressive disorder, the prevalence increased by 27.6 percent.
• The prevalence increase for both disorders was significantly higher for women versus men. Depression prevalence increased 29.8 percent for women versus 24 percent for men. Anxiety prevalence increased 27.9 percent for women versus 21.7 percent for men. Note: In the pre-pandemic world, the prevalence rates for both disorders were already significantly higher for women than men.
• There was a clear correlation between the severity of the pandemic outbreak and the prevalence increases of the two disorders. For example, the countries and regions hardest hit by COVID showed the highest increases of depression and anxiety among the populace.
• Maybe most interesting, prevalence rates for men and women both before and during COVID were progressively higher for each age group. For example, men and women aged 20-39 had the highest rates, which were significantly higher than the rates of depression and anxiety for men and women aged 40-49. Men and women aged 40-49 have higher rates than those aged 50-59, and so on up to 90 years old.

The Realities Behind the Numbers

The researchers discussed possible social and economic reasons why women experienced greater increases of depressive and anxiety disorders during the pandemic. In some cases, these disparities existed long before COVID.

Possible explanations included:

• Worldwide, women tended to take on a greater share of household responsibilities during COVID due to school closings, caring for sick family members, and the like.
• Women tend to be more financially disadvantaged than men due to lower incomes, less savings, and less secure employment. This reality predates COVID.
• Rates of domestic violence rose during the pandemic, which disproportionately affects women more than men.

As for why younger adults are seeing higher prevalence rates of both disorders than older adults, the researchers point to several possible factors. First, widespread school and college disruptions affected the young far more. Second, younger workers were much more likely to lose their jobs than older workers. And third, the social isolation brought on by COVID hit young people a lot harder than older people.

What This Means, and Some Advice

First point: Research has shown that girls and young women may be especially affected by seeing so-called perfect bodies and perfect lives every day on their social media accounts. This omnipresent influence likely does more harm than we realize regarding body image and self-worth and would logically lead to higher rates of depression and anxiety.

Several studies in the last decade have also shown that the more time young people of both genders spend on social media each day, the higher their risk of having mental health problems, including anxiety and depression.

Second point: Another reason young people 25 and under were so hard hit by depressive and anxiety disorders during COVID was because the human brain is still developing at that age. As such, the brain can be especially prone to things like social isolation, increased drug and alcohol use (both were common during COVID), and even domestic violence and poor nutrition . The brain is resilient and can catch up from certain deficits, but the harmful effects that occur during its development stage can linger for years.

Third point: The researchers discussed the alarming fact that rates of depressive and anxiety disorders have never gone down since accurate measuring began in 1990. Meaning prevalence has either stayed the same year-to-year or gone up, despite the fact that globally there are now more support services, mental health facilities, and other interventions available than ever before.

Here’s My Take

First, there is still far too much stigma around mental illnesses like depression and anxiety disorder, so even though the care has improved for these conditions, and it’s more available in many parts of the world, people still shy away from treatment because of the stigma. That is certainly the case in the U.S.

Second, it’s one thing to have the care available, but it’s another thing to have access to it. In the U.S., for example, people often don’t have insurance, so they can’t afford mental health care. Or they have insurance, but their plan doesn’t cover mental illness adequately, despite the mental health care parity push of the last decade-plus. Another reason for lack of access is not having a mental health facility nearby, as frequently happens for people who live in rural areas.

Third, the increase in mental illness has gone hand in hand with the drug epidemic that has raged in the U.S. and other countries in the last 20 to 30 years. The one pushes the other upward in terms of prevalence, and vice versa. A person dealing with addiction as well as a co-occurring condition like depression or PTSD is very common in the addiction treatment field where I work.

Fourth point: One reason COVID has had such an outsized impact on our mental health is that so much of our maintenance mental health care slowed or came to a stop because of it. For example, it became more difficult to do things like getting refills on depression or anxiety medications, so compliance rates took a hit. No one wanted to venture out to the pharmacy for their meds! People on medication -assisted treatments with suboxone, methadone, and other helpful drugs suffered the same disruptions.

Same thing with our weekly or monthly therapy sessions. Some of this mental health care could be done remotely, but that didn’t work for a lot of people. Finally, there are all the other non-medical supports many people depend on, like yoga or meditation classes, gym workouts, or the run we do every Wednesday morning with our training partners. Many of these fell by the wayside because of COVID fears.

Fifth point: Here’s some advice. We’re still coming out of the COVID mess, but as of right now, in late October of 2021, the Delta variant finally seems to be ebbing for good here in the U.S. Still, the last year and seven months have been brutal on our mental health, so I urge you or a loved one to seek help if it’s needed.

Hopefully, you have some options for care. If you have a primary care physician, you can always start there. Make an appointment ASAP, and when it’s time for your visit, be honest about how you’re feeling. No need to spin or soft-pedal what’s going on. Ask about the next steps.

If you stopped seeing your therapist during COVID or weren’t seeing one to begin with, be determined to get an appointment on the calendar. Most mental health providers are seeing people in person again and will have safety protocols in place, so you’ll be fine. The risk of COVID infection is extremely low in these settings.

Another great option is a telehealth mental health visit. COVID changed this landscape for good, and you have many remote options now. Mental health professionals are offering telehealth sessions more than ever, in part because they’re getting reimbursed for them by health insurance payers at levels comparable to onsite visits. Take advantage of this newly opened window!

Lastly, if you’re really struggling with your alcohol or drug use or a suspected mental illness, and it’s affecting your life, it may be time to consider inpatient treatment. And you know what? It could end up being the most productive time you’ve ever spent.

If a friend or family can recommend a facility to you, that’s great, make the call. Otherwise, search by “inpatient mental health,” and you’ll likely find a few nearby places to check out. Again, this could be the smartest move you’ll ever make.

Santomauro, D.F., Mantilla Herrera, A.M., et al (2021). Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. The Lancet.

Viner, R.M. et al. (2019). Roles of cyberbullying, sleep, and physical activity in mediating the effects of social media use on mental health and wellbeing among young people in England. The Lancet.

Riehm, K.E. et al. (2019). Associations between time spent using social media and internalizing and externalizing problems among U.S. youth. JAMA Psychiatry.

Woods, H.C. et al. (2016). Social media use in adolescence is associated with poor sleep quality, anxiety, depression, and low self-esteem. Journal of Adolescence.

Lantie Jorandby, M.D. , is a board-certified psychiatrist with certification in Addiction Psychiatry and Addiction Medicine. She’s the Chief Medical Officer of Lakeview Health Addiction Treatment & Recovery in Jacksonville, Florida.

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Five research topics exploring the science of mental health.

Mental wellbeing is increasingly recognized as an essential aspect of our overall health. It supports our ability to handle challenges, build strong relationships, and live more fulfilling lives. The World Health Organization (WHO) emphasizes the importance of mental health by acknowledging it as a fundamental human right.

This Mental Health Awareness Week, we highlight the remarkable work of scientists driving open research that helps everyone achieve better mental health.

Here are five Research Topics that study themes including how we adapt to a changing world, the impact of loneliness on our wellbeing, and the connection between our diet and mental health.

All articles are openly available to view and download.

1 | Community Series in Mental Health Promotion and Protection, volume II

40.300 views | 16 articles

There is no health without mental health. Thus, this Research Topic collects ideas and research related to strategies that promote mental health across all disciplines. The goal is to raise awareness about mental health promotion and protection to ensure its incorporation in national mental health policies.

This topic is of relevance given the mental health crisis being experienced across the world right now. A reality that has prompted the WHO to declare that health is a state of complete physical, mental, and social wellbeing.

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2 | Dietary and Metabolic Approaches for Mental Health Conditions

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There is increased recognition that mental health disorders are, at least in part, a form of diet-related disease. For this reason, we focus attention on a Research Topic that examines the mechanistic interplay between dietary patterns and mental health conditions.

There is a clear consensus that the quality, quantity, and even timing of our human feeding patterns directly impact how brains function. But despite the epidemiological and mechanistic links between mental health and diet-related diseases, these two are often perceived as separate medical issues.

Even more urgent, public health messaging and clinical treatments for mental health conditions place relatively little emphasis on formulating nutrition to ease the underlying drivers of mental health conditions.

3 | Comparing Mental Health Cross-Culturally

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Although mental health has been widely discussed in later years, how mental health is perceived across different cultures remains to be examined. This Research Topic addresses this gap and deepens our knowledge of mental health by comparing positive and negative psychological constructs cross-culturally.

The definition and understanding of mental health remain to be refined, partially because of a lack of cross-cultural perspectives on mental health. Also, due to the rapid internationalization taking place in the world today, a culturally aware understanding of, and interventions for mental health problems are essential.

4 | Adaption to Change and Coping Strategies: New Resources for Mental Health

85.000 views | 29 articles

In this Research Topic, scientists study a wider range of variables involved in change and adaptation. They examine changes of any type or magnitude whenever the lack of adaptive response diminishes our development and well-being.

Today’s society is characterized by change, and sometimes, the constant changes are difficult to assimilate. This may be why feelings of frustration and defenselessness appear in the face of the impossibility of responding adequately to the requirements of a changing society.

Therefore, society must develop an updated notion of the processes inherent to changing developmental environments, personal skills, resources, and strategies. This know-how is crucial for achieving and maintaining balanced mental health.

5 | Mental Health Equity

29.900 views | 10 articles

The goal of this Research Topic is to move beyond a synthesis of what is already known about mental health in the context of health equity. Rather, the focus here is on transformative solutions, recommendations, and applied research that have real world implications on policy, practice, and future scholarship.

Attention in the field to upstream factors and the role of social and structural determinants of health in influencing health outcomes, combined with an influx of innovation –particularly the digitalization of healthcare—presents a unique opportunity to solve pressing issues in mental health through a health equity lens.

The topic is opportune because factors such as structural racism and climate change have disproportionately negatively impacted marginalized communities across the world, including Black, Indigenous, People of Color (BIPOC), LGBTQ+, people with disabilities, and transition-age youth and young adults. As a result, existing disparities in mental health have exacerbated.

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Biological, Psychological, and Social Determinants of Depression: A Review of Recent Literature

Olivia remes.

1 Institute for Manufacturing, University of Cambridge, Cambridge CB3 0FS, UK

João Francisco Mendes

2 NOVA Medical School, Universidade NOVA de Lisboa, 1099-085 Lisbon, Portugal; ku.ca.mac@94cfj

Peter Templeton

3 IfM Engage Limited, Institute for Manufacturing, University of Cambridge, Cambridge CB3 0FS, UK; ku.ca.mac@32twp

4 The William Templeton Foundation for Young People’s Mental Health (YPMH), Cambridge CB2 0AH, UK

Associated Data

Depression is one of the leading causes of disability, and, if left unmanaged, it can increase the risk for suicide. The evidence base on the determinants of depression is fragmented, which makes the interpretation of the results across studies difficult. The objective of this study is to conduct a thorough synthesis of the literature assessing the biological, psychological, and social determinants of depression in order to piece together the puzzle of the key factors that are related to this condition. Titles and abstracts published between 2017 and 2020 were identified in PubMed, as well as Medline, Scopus, and PsycInfo. Key words relating to biological, social, and psychological determinants as well as depression were applied to the databases, and the screening and data charting of the documents took place. We included 470 documents in this literature review. The findings showed that there are a plethora of risk and protective factors (relating to biological, psychological, and social determinants) that are related to depression; these determinants are interlinked and influence depression outcomes through a web of causation. In this paper, we describe and present the vast, fragmented, and complex literature related to this topic. This review may be used to guide practice, public health efforts, policy, and research related to mental health and, specifically, depression.

1. Introduction

Depression is one of the most common mental health issues, with an estimated prevalence of 5% among adults [ 1 , 2 ]. Symptoms may include anhedonia, feelings of worthlessness, concentration and sleep difficulties, and suicidal ideation. According to the World Health Organization, depression is a leading cause of disability; research shows that it is a burdensome condition with a negative impact on educational trajectories, work performance, and other areas of life [ 1 , 3 ]. Depression can start early in the lifecourse and, if it remains unmanaged, may increase the risk for substance abuse, chronic conditions, such as cardiovascular disease, and premature mortality [ 4 , 5 , 6 , 7 , 8 ].

Treatment for depression exists, such as pharmacotherapy, cognitive behavioural therapy, and other modalities. A meta-analysis of randomized, placebo-controlled trials of patients shows that 56–60% of people respond well to active treatment with antidepressants (selective serotonin reuptake inhibitors, tricyclic antidepressants) [ 9 ]. However, pharmacotherapy may be associated with problems, such as side-effects, relapse issues, a potential duration of weeks until the medication starts working, and possible limited efficacy in mild cases [ 10 , 11 , 12 , 13 , 14 ]. Psychotherapy is also available, but access barriers can make it difficult for a number of people to get the necessary help.

Studies on depression have increased significantly over the past few decades. However, the literature remains fragmented and the interpretation of heterogeneous findings across studies and between fields is difficult. The cross-pollination of ideas between disciplines, such as genetics, neurology, immunology, and psychology, is limited. Reviews on the determinants of depression have been conducted, but they either focus exclusively on a particular set of determinants (ex. genetic risk factors [ 15 ]) or population sub-group (ex. children and adolescents [ 16 ]) or focus on characteristics measured predominantly at the individual level (ex. focus on social support, history of depression [ 17 ]) without taking the wider context (ex. area-level variables) into account. An integrated approach paying attention to key determinants from the biological, psychological, and social spheres, as well as key themes, such as the lifecourse perspective, enables clinicians and public health authorities to develop tailored, person-centred approaches.

The primary aim of this literature review: to address the aforementioned challenges, we have synthesized recent research on the biological, psychological, and social determinants of depression and we have reviewed research from fields including genetics, immunology, neurology, psychology, public health, and epidemiology, among others.

The subsidiary aim: we have paid special attention to important themes, including the lifecourse perspective and interactions between determinants, to guide further efforts by public health and medical professionals.

This literature review can be used as an evidence base by those in public health and the clinical setting and can be used to inform targeted interventions.

2. Materials and Methods

We conducted a review of the literature on the biological, psychological, and social determinants of depression in the last 4 years. We decided to focus on these determinants after discussions with academics (from the Manchester Metropolitan University, University of Cardiff, University of Colorado, Boulder, University of Cork, University of Leuven, University of Texas), charity representatives, and people with lived experience at workshops held by the University of Cambridge in 2020. In several aspects, we attempted to conduct this review according to PRISMA guidelines [ 18 ].

The inclusion and exclusion criteria are the following:

• - We included documents, such as primary studies, literature reviews, systematic reviews, meta-analyses, reports, and commentaries on the determinants of depression. The determinants refer to variables that appear to be linked to the development of depression, such as physiological factors (e.g., the nervous system, genetics), but also factors that are further away or more distal to the condition. Determinants may be risk or protective factors, and individual- or wider-area-level variables.
• - We focused on major depressive disorder, treatment-resistant depression, dysthymia, depressive symptoms, poststroke depression, perinatal depression, as well as depressive-like behaviour (common in animal studies), among others.
• - We included papers regardless of the measurement methods of depression.
• - We included papers that focused on human and/or rodent research.
• - This review focused on articles written in the English language.
• - Documents published between 2017–2020 were captured to provide an understanding of the latest research on this topic.
• - Studies that assessed depression as a comorbidity or secondary to another disorder.
• - Studies that did not focus on rodent and/or human research.
• - Studies that focused on the treatment of depression. We made this decision, because this is an in-depth topic that would warrant a separate stand-alone review.
• Next, we searched PubMed (2017–2020) using keywords related to depression and determinants. Appendix A contains the search strategy used. We also conducted focused searches in Medline, Scopus, and PsycInfo (2017–2020).
• Once the documents were identified through the databases, the inclusion and exclusion criteria were applied to the titles and abstracts. Screening of documents was conducted by O.R., and a subsample was screened by J.M.; any discrepancies were resolved through a communication process.
• The full texts of documents were retrieved, and the inclusion and exclusion criteria were again applied. A subsample of documents underwent double screening by two authors (O.R., J.M.); again, any discrepancies were resolved through communication.
• a. A data charting form was created to capture the data elements of interest, including the authors, titles, determinants (biological, psychological, social), and the type of depression assessed by the research (e.g., major depression, depressive symptoms, depressive behaviour).
• b. The data charting form was piloted on a subset of documents, and refinements to it were made. The data charting form was created with the data elements described above and tested in 20 studies to determine whether refinements in the wording or language were needed.
• c. Data charting was conducted on the documents.
• d. Narrative analysis was conducted on the data charting table to identify key themes. When a particular finding was noted more than once, it was logged as a potential theme, with a review of these notes yielding key themes that appeared on multiple occasions. When key themes were identified, one researcher (O.R.) reviewed each document pertaining to that theme and derived concepts (key determinants and related outcomes). This process (a subsample) was verified by a second author (J.M.), and the two authors resolved any discrepancies through communication. Key themes were also checked as to whether they were of major significance to public mental health and at the forefront of public health discourse according to consultations we held with stakeholders from the Manchester Metropolitan University, University of Cardiff, University of Colorado, Boulder, University of Cork, University of Leuven, University of Texas, charity representatives, and people with lived experience at workshops held by the University of Cambridge in 2020.

We condensed the extensive information gleaned through our review into short summaries (with key points boxes for ease of understanding and interpretation of the data).

Through the searches, 6335 documents, such as primary studies, literature reviews, systematic reviews, meta-analyses, reports, and commentaries, were identified. After applying the inclusion and exclusion criteria, 470 papers were included in this review ( Supplementary Table S1 ). We focused on aspects related to biological, psychological, and social determinants of depression (examples of determinants and related outcomes are provided under each of the following sections.

3.1. Biological Factors

The following aspects will be discussed in this section: physical health conditions; then specific biological factors, including genetics; the microbiome; inflammatory factors; stress and hypothalamic–pituitary–adrenal (HPA) axis dysfunction, and the kynurenine pathway. Finally, aspects related to cognition will also be discussed in the context of depression.

3.1.1. Physical Health Conditions

Studies on physical health conditions—key points:

• The presence of a physical health condition can increase the risk for depression
• Psychological evaluation in physically sick populations is needed
• There is large heterogeneity in study design and measurement; this makes the comparison of findings between and across studies difficult

A number of studies examined the links between the outcome of depression and physical health-related factors, such as bladder outlet obstruction, cerebral atrophy, cataract, stroke, epilepsy, body mass index and obesity, diabetes, urinary tract infection, forms of cancer, inflammatory bowel disorder, glaucoma, acne, urea accumulation, cerebral small vessel disease, traumatic brain injury, and disability in multiple sclerosis [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 ]. For example, bladder outlet obstruction has been linked to inflammation and depressive behaviour in rodent research [ 24 ]. The presence of head and neck cancer also seemed to be related to an increased risk for depressive disorder [ 45 ]. Gestational diabetes mellitus has been linked to depressive symptoms in the postpartum period (but no association has been found with depression in the third pregnancy trimester) [ 50 ], and a plethora of other such examples of relationships between depression and physical conditions exist. As such, the assessment of psychopathology and the provision of support are necessary in individuals of ill health [ 45 ]. Despite the large evidence base on physical health-related factors, differences in study methodology and design, the lack of standardization when it comes to the measurement of various physical health conditions and depression, and heterogeneity in the study populations makes it difficult to compare studies [ 50 ].

The next subsections discuss specific biological factors, including genetics; the microbiome; inflammatory factors; stress and hypothalamic–pituitary–adrenal (HPA) axis dysfunction, and the kynurenine pathway; and aspects related to cognition.

3.1.2. Genetics

Studies on genetics—key points:

There were associations between genetic factors and depression; for example:

• The brain-derived neurotrophic factor (BDNF) plays an important role in depression
• Links exist between major histocompatibility complex region genes, as well as various gene polymorphisms and depression
• Single nucleotide polymorphisms (SNPs) of genes involved in the tryptophan catabolites pathway are of interest in relation to depression

A number of genetic-related factors, genomic regions, polymorphisms, and other related aspects have been examined with respect to depression [ 61 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 ]. The influence of BDNF in relation to depression has been amply studied [ 117 , 118 , 141 , 142 , 143 ]. Research has shown associations between depression and BDNF (as well as candidate SNPs of the BDNF gene, polymorphisms of the BDNF gene, and the interaction of these polymorphisms with other determinants, such as stress) [ 129 , 144 , 145 ]. Specific findings have been reported: for example, a study reported a link between the BDNF rs6265 allele (A) and major depressive disorder [ 117 ].

Other research focused on major histocompatibility complex region genes, endocannabinoid receptor gene polymorphisms, as well as tissue-specific genes and gene co-expression networks and their links to depression [ 99 , 110 , 112 ]. The SNPs of genes involved in the tryptophan catabolites pathway have also been of interest when studying the pathogenesis of depression.

The results from genetics studies are compelling; however, the findings remain mixed. One study indicated no support for depression candidate gene findings [ 122 ]. Another study found no association between specific polymorphisms and major depressive disorder [ 132 ]. As such, further research using larger samples is needed to corroborate the statistically significant associations reported in the literature.

3.1.3. Microbiome

Studies on the microbiome—key points:

• The gut bacteria and the brain communicate via both direct and indirect pathways called the gut-microbiota-brain axis (the bidirectional communication networks between the central nervous system and the gastrointestinal tract; this axis plays an important role in maintaining homeostasis).
• A disordered microbiome can lead to inflammation, which can then lead to depression
• There are possible links between the gut microbiome, host liver metabolism, brain inflammation, and depression

The common themes of this review have focused on the microbiome/microbiota or gut metabolome [ 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 ], the microbiota-gut-brain axis, and related factors [ 152 , 162 , 163 , 164 , 165 , 166 , 167 ]. When there is an imbalance in the intestinal bacteria, this can interfere with emotional regulation and contribute to harmful inflammatory processes and mood disorders [ 148 , 151 , 153 , 155 , 157 ]. Rodent research has shown that there may be a bidirectional association between the gut microbiota and depression: a disordered gut microbiota can play a role in the onset of this mental health problem, but, at the same time, the existence of stress and depression may also lead to a lower level of richness and diversity in the microbiome [ 158 ].

Research has also attempted to disentangle the links between the gut microbiome, host liver metabolism, brain inflammation, and depression, as well as the role of the ratio of lactobacillus to clostridium [ 152 ]. The literature has also examined the links between medication, such as antibiotics, and mood and behaviour, with the findings showing that antibiotics may be related to depression [ 159 , 168 ]. The links between the microbiome and depression are complex, and further studies are needed to determine the underpinning causal mechanisms.

3.1.4. Inflammation

Studies on inflammation—key points:

• Pro-inflammatory cytokines are linked to depression
• Pro-inflammatory cytokines, such as the tumour necrosis factor (TNF)-alpha, may play an important role
• Different methods of measurement are used, making the comparison of findings across studies difficult

Inflammation has been a theme in this literature review [ 60 , 161 , 164 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 ]. The findings show that raised levels of inflammation (because of factors such as pro-inflammatory cytokines) have been associated with depression [ 60 , 161 , 174 , 175 , 178 ]. For example, pro-inflammatory cytokines, such as tumour necrosis factor (TNF)-alpha, have been linked to depression [ 185 ]. Various determinants, such as early life stress, have also been linked to systemic inflammation, and this can increase the risk for depression [ 186 ].

Nevertheless, not everyone with elevated inflammation develops depression; therefore, this is just one route out of many linked to pathogenesis. Despite the compelling evidence reported with respect to inflammation, it is difficult to compare the findings across studies because of different methods used to assess depression and its risk factors.

3.1.5. Stress and HPA Axis Dysfunction

Studies on stress and HPA axis dysfunction—key points:

• Stress is linked to the release of proinflammatory factors
• The dysregulation of the HPA axis is linked to depression
• Determinants are interlinked in a complex web of causation

Stress was studied in various forms in rodent populations and humans [ 144 , 145 , 155 , 174 , 176 , 180 , 185 , 186 , 187 , 188 , 189 , 190 , 191 , 192 , 193 , 194 , 195 , 196 , 197 , 198 , 199 , 200 , 201 , 202 , 203 , 204 , 205 , 206 , 207 , 208 , 209 , 210 , 211 ].

Although this section has some overlap with others (as is to be expected because all of these determinants and body systems are interlinked), a number of studies have focused on the impact of stress on mental health. Stress has been mentioned in the literature as a risk factor of poor mental health and has emerged as an important determinant of depression. The effects of this variable are wide-ranging, and a short discussion is warranted.

Stress has been linked to the release of inflammatory factors, as well as the development of depression [ 204 ]. When the stress is high or lasts for a long period of time, this may negatively impact the brain. Chronic stress can impact the dendrites and synapses of various neurons, and may be implicated in the pathway leading to major depressive disorder [ 114 ]. As a review by Uchida et al. indicates, stress may be associated with the “dysregulation of neuronal and synaptic plasticity” [ 114 ]. Even in rodent studies, stress has a negative impact: chronic and unpredictable stress (and other forms of tension or stress) have been linked to unusual behaviour and depression symptoms [ 114 ].

The depression process and related brain changes, however, have also been linked to the hyperactivity or dysregulation of the HPA axis [ 127 , 130 , 131 , 182 , 212 ]. One review indicates that a potential underpinning mechanism of depression relates to “HPA axis abnormalities involved in chronic stress” [ 213 ]. There is a complex relationship between the HPA axis, glucocorticoid receptors, epigenetic mechanisms, and psychiatric sequelae [ 130 , 212 ].

In terms of the relationship between the HPA axis and stress and their influence on depression, the diathesis–stress model offers an explanation: it could be that early stress plays a role in the hyperactivation of the HPA axis, thus creating a predisposition “towards a maladaptive reaction to stress”. When this predisposition then meets an acute stressor, depression may ensue; thus, in line with the diathesis–stress model, a pre-existing vulnerability and stressor can create fertile ground for a mood disorder [ 213 ]. An integrated review by Dean and Keshavan [ 213 ] suggests that HPA axis hyperactivity is, in turn, related to other determinants, such as early deprivation and insecure early attachment; this again shows the complex web of causation between the different determinants.

3.1.6. Kynurenine Pathway

Studies on the kynurenine pathway—key points:

• The kynurenine pathway is linked to depression
• Indolamine 2,3-dioxegenase (IDO) polymorphisms are linked to postpartum depression

The kynurenine pathway was another theme that emerged in this review [ 120 , 178 , 181 , 184 , 214 , 215 , 216 , 217 , 218 , 219 , 220 , 221 ]. The kynurenine pathway has been implicated not only in general depressed mood (inflammation-induced depression) [ 184 , 214 , 219 ] but also postpartum depression [ 120 ]. When the kynurenine metabolism pathway is activated, this results in metabolites, which are neurotoxic.

A review by Jeon et al. notes a link between the impairment of the kynurenine pathway and inflammation-induced depression (triggered by treatment for various physical diseases, such as malignancy). The authors note that this could represent an important opportunity for immunopharmacology [ 214 ]. Another review by Danzer et al. suggests links between the inflammation-induced activation of indolamine 2,3-dioxegenase (the enzyme that converts tryptophan to kynurenine), the kynurenine metabolism pathway, and depression, and also remarks about the “opportunities for treatment of inflammation-induced depression” [ 184 ].

3.1.7. Cognition

Studies on cognition and the brain—key points:

• Cognitive decline and cognitive deficits are linked to increased depression risk
• Cognitive reserve is important in the disability/depression relationship
• Family history of cognitive impairment is linked to depression

A number of studies have focused on the theme of cognition and the brain. The results show that factors, such as low cognitive ability/function, cognitive vulnerability, cognitive impairment or deficits, subjective cognitive decline, regression of dendritic branching and hippocampal atrophy/death of hippocampal cells, impaired neuroplasticity, and neurogenesis-related aspects, have been linked to depression [ 131 , 212 , 222 , 223 , 224 , 225 , 226 , 227 , 228 , 229 , 230 , 231 , 232 , 233 , 234 , 235 , 236 , 237 , 238 , 239 ]. The cognitive reserve appears to act as a moderator and can magnify the impact of certain determinants on poor mental health. For example, in a study in which participants with multiple sclerosis also had low cognitive reserve, disability was shown to increase the risk for depression [ 63 ]. Cognitive deficits can be both causal and resultant in depression. A study on individuals attending outpatient stroke clinics showed that lower scores in cognition were related to depression; thus, cognitive impairment appears to be associated with depressive symptomatology [ 226 ]. Further, Halahakoon et al. [ 222 ] note a meta-analysis [ 240 ] that shows that a family history of cognitive impairment (in first degree relatives) is also linked to depression.

In addition to cognitive deficits, low-level cognitive ability [ 231 ] and cognitive vulnerability [ 232 ] have also been linked to depression. While cognitive impairment may be implicated in the pathogenesis of depressive symptoms [ 222 ], negative information processing biases are also important; according to the ‘cognitive neuropsychological’ model of depression, negative affective biases play a central part in the development of depression [ 222 , 241 ]. Nevertheless, the evidence on this topic is mixed and further work is needed to determine the underpinning mechanisms between these states.

3.2. Psychological Factors

Studies on psychological factors—key points:

• There are many affective risk factors linked to depression
• Determinants of depression include negative self-concept, sensitivity to rejection, neuroticism, rumination, negative emotionality, and others

A number of studies have been undertaken on the psychological factors linked to depression (including mastery, self-esteem, optimism, negative self-image, current or past mental health conditions, and various other aspects, including neuroticism, brooding, conflict, negative thinking, insight, cognitive fusion, emotional clarity, rumination, dysfunctional attitudes, interpretation bias, and attachment style) [ 66 , 128 , 140 , 205 , 210 , 228 , 235 , 242 , 243 , 244 , 245 , 246 , 247 , 248 , 249 , 250 , 251 , 252 , 253 , 254 , 255 , 256 , 257 , 258 , 259 , 260 , 261 , 262 , 263 , 264 , 265 , 266 , 267 , 268 , 269 , 270 , 271 , 272 , 273 , 274 , 275 , 276 , 277 , 278 , 279 , 280 , 281 , 282 , 283 , 284 , 285 , 286 , 287 , 288 , 289 , 290 ]. Determinants related to this condition include low self-esteem and shame, among other factors [ 269 , 270 , 275 , 278 ]. Several emotional states and traits, such as neuroticism [ 235 , 260 , 271 , 278 ], negative self-concept (with self-perceptions of worthlessness and uselessness), and negative interpretation or attention biases have been linked to depression [ 261 , 271 , 282 , 283 , 286 ]. Moreover, low emotional clarity has been associated with depression [ 267 ]. When it comes to the severity of the disorder, it appears that meta-emotions (“emotions that occur in response to other emotions (e.g., guilt about anger)” [ 268 ]) have a role to play in depression [ 268 ].

A determinant that has received much attention in mental health research concerns rumination. Rumination has been presented as a mediator but also as a risk factor for depression [ 57 , 210 , 259 ]. When studied as a risk factor, it appears that the relationship of rumination with depression is mediated by variables that include limited problem-solving ability and insufficient social support [ 259 ]. However, rumination also appears to act as a mediator: for example, this variable (particularly brooding rumination) lies on the causal pathway between poor attention control and depression [ 265 ]. This shows that determinants may present in several forms: as moderators or mediators, risk factors or outcomes, and this is why disentangling the relationships between the various factors linked to depression is a complex task.

The psychological determinants are commonly researched variables in the mental health literature. A wide range of factors have been linked to depression, such as the aforementioned determinants, but also: (low) optimism levels, maladaptive coping (such as avoidance), body image issues, and maladaptive perfectionism, among others [ 269 , 270 , 272 , 273 , 275 , 276 , 279 , 285 , 286 ]. Various mechanisms have been proposed to explain the way these determinants increase the risk for depression. One of the underpinning mechanisms linking the determinants and depression concerns coping. For example, positive fantasy engagement, cognitive biases, or personality dispositions may lead to emotion-focused coping, such as brooding, and subsequently increase the risk for depression [ 272 , 284 , 287 ]. Knowing the causal mechanisms linking the determinants to outcomes provides insight for the development of targeted interventions.

3.3. Social Determinants

Studies on social determinants—key points:

• Social determinants are the conditions in the environments where people are born, live, learn, work, play, etc.; these influence (mental) health [ 291 ]
• There are many social determinants linked to depression, such as sociodemographics, social support, adverse childhood experiences
• Determinants can be at the individual, social network, community, and societal levels

Studies also focused on the social determinants of (mental) health; these are the conditions in which people are born, live, learn, work, play, and age, and have a significant influence on wellbeing [ 291 ]. Factors such as age, social or socioeconomic status, social support, financial strain and deprivation, food insecurity, education, employment status, living arrangements, marital status, race, childhood conflict and bullying, violent crime exposure, abuse, discrimination, (self)-stigma, ethnicity and migrant status, working conditions, adverse or significant life events, illiteracy or health literacy, environmental events, job strain, and the built environment have been linked to depression, among others [ 52 , 133 , 235 , 236 , 239 , 252 , 269 , 280 , 292 , 293 , 294 , 295 , 296 , 297 , 298 , 299 , 300 , 301 , 302 , 303 , 304 , 305 , 306 , 307 , 308 , 309 , 310 , 311 , 312 , 313 , 314 , 315 , 316 , 317 , 318 , 319 , 320 , 321 , 322 , 323 , 324 , 325 , 326 , 327 , 328 , 329 , 330 , 331 , 332 , 333 , 334 , 335 , 336 , 337 , 338 , 339 , 340 , 341 , 342 , 343 , 344 , 345 , 346 , 347 , 348 , 349 , 350 , 351 , 352 , 353 , 354 , 355 , 356 , 357 , 358 , 359 , 360 , 361 , 362 , 363 , 364 , 365 , 366 , 367 , 368 , 369 , 370 , 371 ]. Social support and cohesion, as well as structural social capital, have also been identified as determinants [ 140 , 228 , 239 , 269 , 293 , 372 , 373 , 374 , 375 , 376 , 377 , 378 , 379 ]. In a study, part of the findings showed that low levels of education have been shown to be linked to post-stroke depression (but not severe or clinical depression outcomes) [ 299 ]. A study within a systematic review indicated that having only primary education was associated with a higher risk of depression compared to having secondary or higher education (although another study contrasted this finding) [ 296 ]. Various studies on socioeconomic status-related factors have been undertaken [ 239 , 297 ]; the research has shown that a low level of education is linked to depression [ 297 ]. Low income is also related to depressive disorders [ 312 ]. By contrast, high levels of education and income are protective [ 335 ].

A group of determinants touched upon by several studies included adverse childhood or early life experiences: ex. conflict with parents, early exposure to traumatic life events, bullying and childhood trauma were found to increase the risk of depression (ex. through pathways, such as inflammation, interaction effects, or cognitive biases) [ 161 , 182 , 258 , 358 , 362 , 380 ].

Gender-related factors were also found to play an important role with respect to mental health [ 235 , 381 , 382 , 383 , 384 , 385 ]. Gender inequalities can start early on in the lifecourse, and women were found to be twice as likely to have depression as men. Gender-related factors were linked to cognitive biases, resilience and vulnerabilities [ 362 , 384 ].

Determinants can impact mental health outcomes through underpinning mechanisms. For example, harmful determinants can influence the uptake of risk behaviours. Risk behaviours, such as sedentary behaviour, substance abuse and smoking/nicotine exposure, have been linked to depression [ 226 , 335 , 355 , 385 , 386 , 387 , 388 , 389 , 390 , 391 , 392 , 393 , 394 , 395 , 396 , 397 , 398 , 399 , 400 , 401 ]. Harmful determinants can also have an impact on diet. Indeed, dietary aspects and diet components (ex. vitamin D, folate, selenium intake, iron, vitamin B12, vitamin K, fiber intake, zinc) as well as diet-related inflammatory potential have been linked to depression outcomes [ 161 , 208 , 236 , 312 , 396 , 402 , 403 , 404 , 405 , 406 , 407 , 408 , 409 , 410 , 411 , 412 , 413 , 414 , 415 , 416 , 417 , 418 , 419 , 420 , 421 , 422 , 423 , 424 , 425 , 426 , 427 , 428 ]. A poor diet has been linked to depression through mechanisms such as inflammation [ 428 ].

Again, it is difficult to constrict diet to the ‘social determinants of health’ category as it also relates to inflammation (biological determinants) and could even stand alone as its own category. Nevertheless, all of these factors are interlinked and influence one another in a complex web of causation, as mentioned elsewhere in the paper.

Supplementary Figure S1 contains a representation of key determinants acting at various levels: the individual, social network, community, and societal levels. The determinants have an influence on risk behaviours, and this, in turn, can affect the mood (i.e., depression), body processes (ex. can increase inflammation), and may negatively influence brain structure and function.

3.4. Others

Studies on ‘other’ determinants—key points:

• A number of factors are related to depression
• These may not be as easily categorized as the other determinants in this paper

A number of factors arose in this review that were related to depression; it was difficult to place these under a specific heading above, so this ‘other’ category was created. A number of these could be sorted under the ‘social determinants of depression’ category. For example, being exposed to deprivation, hardship, or adversity may increase the risk for air pollution exposure and nighttime shift work, among others, and the latter determinants have been found to increase the risk for depression. Air pollution could also be regarded as an ecologic-level (environmental) determinant of mental health.

Nevertheless, we have decided to leave these factors in a separate category (because their categorization may not be as immediately clear-cut as others), and these factors include: low-level light [ 429 ], weight cycling [ 430 ], water contaminants [ 431 ], trade [ 432 ], air pollution [ 433 , 434 ], program-level variables (ex. feedback and learning experience) [ 435 ], TV viewing [ 436 ], falls [ 437 ], various other biological factors [ 116 , 136 , 141 , 151 , 164 , 182 , 363 , 364 , 438 , 439 , 440 , 441 , 442 , 443 , 444 , 445 , 446 , 447 , 448 , 449 , 450 , 451 , 452 , 453 , 454 , 455 , 456 , 457 , 458 , 459 , 460 , 461 , 462 , 463 , 464 , 465 , 466 , 467 , 468 , 469 ], mobile phone use [ 470 ], ultrasound chronic exposure [ 471 ], nighttime shift work [ 472 ], work accidents [ 473 ], therapy enrollment [ 226 ], and exposure to light at night [ 474 ].

4. Cross-Cutting Themes

4.1. lifecourse perspective.

Studies on the lifecourse perspective—key points:

• Early life has an importance on mental health
• Stress has been linked to depression
• In old age, the decline in social capital is important

Trajectories and life events are important when it comes to the lifecourse perspective. Research has touched on the influence of prenatal or early life stress on an individual’s mental health trajectory [ 164 , 199 , 475 ]. Severe stress that occurs in the form of early-life trauma has also been associated with depressive symptoms [ 362 , 380 ]. It may be that some individuals exposed to trauma develop thoughts of personal failure, which then serve as a catalyst of depression [ 380 ].

At the other end of the life trajectory—old age—specific determinants have been linked to an increased risk for depression. Older people are at a heightened risk of losing their social networks, and structural social capital has been identified as important in relation to depression in old age [ 293 ].

4.2. Gene–Environment Interactions

Studies on gene–environment interactions—key points:

• The environment and genetics interact to increase the risk of depression
• The etiology of depression is multifactorial
• Adolescence is a time of vulnerability

A number of studies have touched on gene–environment interactions [ 72 , 77 , 82 , 119 , 381 , 476 , 477 , 478 , 479 , 480 , 481 ]. The interactions between genetic factors and determinants, such as negative life events (ex. relationship and social difficulties, serious illness, unemployment and financial crises) and stressors (ex. death of spouse, minor violations of law, neighbourhood socioeconomic status) have been studied in relation to depression [ 82 , 135 , 298 , 449 , 481 ]. A study reported an interaction of significant life events with functional variation in the serotonin-transporter-linked polymorphic region (5-HTTLPR) allele type (in the context of multiple sclerosis) and linked this to depression [ 361 ], while another reported an interaction between stress and 5-HTTLPR in relation to depression [ 480 ]. Other research reported that the genetic variation of HPA-axis genes has moderating effects on the relationship between stressors and depression [ 198 ]. Another study showed that early-life stress interacts with gene variants to increase the risk for depression [ 77 ].

Adolescence is a time of vulnerability [ 111 , 480 ]. Perceived parental support has been found to interact with genes (GABRR1, GABRR2), and this appears to be associated with depressive symptoms in adolescence [ 480 ]. It is important to pay special attention to critical periods in the lifecourse so that adequate support is provided to those who are most vulnerable.

The etiology of depression is multifactorial, and it is worthwhile to examine the interaction between multiple factors, such as epigenetic, genetic, and environmental factors, in order to truly understand this mental health condition. Finally, taking into account critical periods of life when assessing gene–environment interactions is important for developing targeted interventions.

5. Discussion

Depression is one of the most common mental health conditions, and, if left untreated, it can increase the risk for substance abuse, anxiety disorders, and suicide. In the past 20 years, a large number of studies on the risk and protective factors of depression have been undertaken in various fields, such as genetics, neurology, immunology, and epidemiology. However, there are limitations associated with the extant evidence base. The previous syntheses on depression are limited in scope and focus exclusively on social or biological factors, population sub-groups, or examine depression as a comorbidity (rather than an independent disorder). The research on the determinants and causal pathways of depression is fragmentated and heterogeneous, and this has not helped to stimulate progress when it comes to the prevention and intervention of this condition—specifically unravelling the complexity of the determinants related to this condition and thus refining the prevention and intervention methods.

The scope of this paper was to bring together the heterogeneous, vast, and fragmented literature on depression and paint a picture of the key factors that contribute to this condition. The findings from this review show that there are important themes when it comes to the determinants of depression, such as: the microbiome, dysregulation of the HPA axis, inflammatory reactions, the kynurenine pathway, as well as psychological and social factors. It may be that physical factors are proximal determinants of depression, which, in turn, are acted on by more distal social factors, such as deprivation, environmental events, and social capital.

The Marmot Report [ 291 ], the World Health Organization [ 482 ], and Compton et al. [ 483 ] highlight that the most disadvantaged segments of society are suffering (the socioeconomic context is important), and this inequality in resources has translated to inequality in mental health outcomes [ 483 ]. To tackle the issue of egalitarianism and restore equality in the health between the groups, the social determinants need to be addressed [ 483 ]. A wide range of determinants of mental health have been identified in the literature: age, gender, ethnicity, family upbringing and early attachment patterns, social support, access to food, water and proper nutrition, and community factors. People spiral downwards because of individual- and societal-level circumstances; therefore, these circumstances along with the interactions between the determinants need to be considered.

Another important theme in the mental health literature is the lifecourse perspective. This shows that the timing of events has significance when it comes to mental health. Early life is a critical period during the lifespan at which cognitive processes develop. Exposure to harmful determinants, such as stress, during this period can place an individual on a trajectory of depression in adulthood or later life. When an individual is exposed to harmful determinants during critical periods and is also genetically predisposed to depression, the risk for the disorder can be compounded. This is why aspects such as the lifecourse perspective and gene–environment interactions need to be taken into account. Insight into this can also help to refine targeted interventions.

A number of interventions for depression have been developed or recommended, addressing, for example, the physical factors described here and lifestyle modifications. Interventions targeting various factors, such as education and socioeconomic status, are needed to help prevent and reduce the burden of depression. Further research on the efficacy of various interventions is needed. Additional studies are also needed on each of the themes described in this paper, for example: the biological factors related to postpartum depression [ 134 ], and further work is needed on depression outcomes, such as chronic, recurrent depression [ 452 ]. Previous literature has shown that chronic stress (associated with depression) is also linked to glucocorticoid receptor resistance, as well as problems with the regulation of the inflammatory response [ 484 ]. Further work is needed on this and the underpinning mechanisms between the determinants and outcomes. This review highlighted the myriad ways of measuring depression and its determinants [ 66 , 85 , 281 , 298 , 451 , 485 ]. Thus, the standardization of the measurements of the outcomes (ex. a gold standard for measuring depression) and determinants is essential; this can facilitate comparisons of findings across studies.

5.1. Strengths

This paper has important strengths. It brings together the wide literature on depression and helps to bridge disciplines in relation to one of the most common mental health problems. We identified, selected, and extracted data from studies, and provided concise summaries.

5.2. Limitations

The limitations of the review include missing potentially important studies; however, this is a weakness that cannot be avoided by literature reviews. Nevertheless, the aim of the review was not to identify each study that has been conducted on the risk and protective factors of depression (which a single review is unable to capture) but rather to gain insight into the breadth of literature on this topic, highlight key biological, psychological, and social determinants, and shed light on important themes, such as the lifecourse perspective and gene–environment interactions.

6. Conclusions

We have reviewed the determinants of depression and recognize that there are a multitude of risk and protective factors at the individual and wider ecologic levels. These determinants are interlinked and influence one another. We have attempted to describe the wide literature on this topic, and we have brought to light major factors that are of public mental health significance. This review may be used as an evidence base by those in public health, clinical practice, and research.

This paper discusses key areas in depression research; however, an exhaustive discussion of all the risk factors and determinants linked to depression and their mechanisms is not possible in one journal article—which, by its very nature, a single paper cannot do. We have brought to light overarching factors linked to depression and a workable conceptual framework that may guide clinical and public health practice; however, we encourage other researchers to continue to expand on this timely and relevant work—particularly as depression is a top priority on the policy agenda now.

Acknowledgments

Thank you to Isla Kuhn for the help with the Medline, Scopus, and PsycInfo database searches.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/brainsci11121633/s1 , Figure S1: Conceptual framework: Determinants of depression, Table S1: Data charting—A selection of determinants from the literature.

Appendix A.1. Search Strategy

Search: ((((((((((((((((“Gene-Environment Interaction”[Majr]) OR (“Genetics”[Mesh])) OR (“Genome-Wide Association Study”[Majr])) OR (“Microbiota”[Mesh] OR “Gastrointestinal Microbiome”[Mesh])) OR (“Neurogenic Inflammation”[Mesh])) OR (“genetic determinant”)) OR (“gut-brain-axis”)) OR (“Kynurenine”[Majr])) OR (“Cognition”[Mesh])) OR (“Neuronal Plasticity”[Majr])) OR (“Neurogenesis”[Mesh])) OR (“Genes”[Mesh])) OR (“Neurology”[Majr])) OR (“Social Determinants of Health”[Majr])) OR (“Glucocorticoids”[Mesh])) OR (“Tryptophan”[Mesh])) AND (“Depression”[Mesh] OR “Depressive Disorder”[Mesh]) Filters: from 2017—2020.

Ovid MEDLINE(R) and Epub Ahead of Print, In-Process, In-Data-Review & Other Non-Indexed Citations, Daily and Versions(R)

• exp *Depression/
• exp *Depressive Disorder/
• exp *”Social Determinants of Health”/
• exp *Tryptophan/
• exp *Glucocorticoids/
• exp *Neurology/
• exp *Genes/
• exp *Neurogenesis/
• exp *Neuronal Plasticity/
• exp *Kynurenine/
• exp *Genetics/
• exp *Neurogenic Inflammation/
• exp *Gastrointestinal Microbiome/
• exp *Genome-Wide Association Study/
• exp *Gene-Environment Interaction/
• exp *Depression/et [Etiology]
• exp *Depressive Disorder/et
• or/4-16   637368
• limit 22 to yr = “2017–Current”
• “cause* of depression”.mp.
• “cause* of depression”.ti.
• (cause adj3 (depression or depressive)).ti.
• (caus* adj3 (depression or depressive)).ti.

Appendix A.2. PsycInfo

(TITLE ( depression OR “ Depressive Disorder ”) AND TITLE (“ Social Determinants of Health ” OR tryptophan OR glucocorticoids OR neurology OR genes OR neurogenesis OR “ Neuronal Plasticity ” OR kynurenine OR genetics OR “ Neurogenic Inflammation ” OR “ Gastrointestinal Microbiome ” OR “ Genome-Wide Association Study ” OR “ Gene-Environment Interaction ” OR aetiology OR etiology )) OR TITLE ( cause* W/3 ( depression OR depressive )).

Author Contributions

O.R. was responsible for the design of the study and methodology undertaken. Despite P.T.’s involvement in YPMH, he had no role in the design of the study; P.T. was responsible for the conceptualization of the study. Validation was conducted by O.R. and J.F.M. Formal analysis (data charting) was undertaken by O.R. O.R. and P.T. were involved in the investigation, resource acquisition, and data presentation. The original draft preparation was undertaken by O.R. The writing was conducted by O.R., with review and editing by P.T. and J.F.M. Funding acquisition was undertaken by O.R. and P.T. All authors have read and agreed to the published version of the manuscript.

This research was funded by The William Templeton Foundation for Young People’s Mental Health, Cambridge Philosophical Society, and the Aviva Foundation.

Conflicts of Interest

The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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New guidelines for depression care emphasize patient-centered approach in Canada

by University of British Columbia

Psychiatrists and mental health professionals have a new standard for managing major depression, thanks to refreshed clinical guidelines published today by the Canadian Network for Mood and Anxiety Treatments (CANMAT).

The CANMAT guidelines are the most widely used clinical guidelines for depression in the world. The new version integrates the latest scientific evidence and advances in depression care since the previous guidelines were published in 2016. The update was led by researchers at the University of B.C. and the University of Toronto, alongside a national working group of more than 40 academic clinical experts and patient partners.

"These recommendations not only represent the evidence and broad consensus of leading experts in depression research and care, but, importantly, they also reflect the perspectives of patients with lived experience," says co-lead author Dr. Raymond Lam, professor of psychiatry at UBC and co-director of the Mood Disorders Centre at the Djavad Mowafaghian Centre for Brain Health.

"Our hope is that this update will empower clinicians with the latest recommendations that can help achieve better outcomes and improved quality of life for the millions of people affected by depression."

More than one in 10 Canadians will experience depression at some point in their lives, making it one of the largest public health burdens in Canada. However, it is estimated that only 20% of people receive adequate treatment.

The updated guidelines cover eight primary topic areas that map the patient care journey, from assessment and diagnosis through to the selection of treatments and strategies to prevent recurrence. The question-and-answer format is designed to be practical, accessible and easy for clinicians to use.

To develop the refreshed guidelines, the working group conducted a comprehensive literature review of new scientific evidence published since the previous 2016 guidelines. Drafts were revised based on review by patient partners, expert peer review and a defined expert consensus process.

The resulting recommendations are organized by lines of treatment based on the level of evidence supporting each therapy and factors such as safety, tolerability and feasibility. Guidance is provided to aid health care professionals in choosing the right treatment option with an emphasis on collaborative decision-making.

"Depression is a complex and highly individualized condition," says Dr. Lam. "The guidelines highlight the importance of collaborating with patients in care decisions and providing a personalized treatment approach that carefully considers a person's needs, preferences and treatment history."

The guidelines underline the strong evidence base for well-established first-line treatments, including a number of medications, as well as psychological treatments such as cognitive behavioral therapy , interpersonal therapy and behavioral activation. Based on recent evidence, a number of new psychological and pharmacological treatments were added to the list of treatment options.

"Notable additions to the new guidelines are a strong emphasis on patient participation in choosing treatment, applying outcome measures throughout care, and an overview of digital mental health tools in the management of depression," says co-lead author Dr. Sidney Kennedy, professor of psychiatry at the University of Toronto and director of the Centre for Depression and Suicide Studies at Unity Health Toronto.

The guidelines include further direction on how health care professionals can incorporate lifestyle interventions, such as exercise, nutrition and sleep hygiene. They also explore when neuromodulation treatments should be considered and what should be done when a patient doesn't respond to initial treatments or develops treatment-resistant depression.

"Many well-established psychological and behavioral interventions have accumulated more support for their efficacy across different delivery formats," says co-author Dr. Lena Quilty, associate professor of psychiatry at the University of Toronto and senior scientist at the Centre for Addiction and Mental Health.

"We are especially pleased to report on evidence for new interventions that target depression as well as commonly co-occurring challenges such as anxiety or disrupted cognitive processes. We hope that these additional alternatives provide more opportunities for integrated attention to these multi-faceted issues."

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New guidelines for depression care emphasize patient-centred approach

Psychiatrists and mental health professionals have a new standard for managing major depression, thanks to refreshed clinical guidelines published today by the Canadian Network for Mood and Anxiety Treatments (CANMAT).

The CANMAT guidelines are the most widely used clinical guidelines for depression in the world. The new version integrates the latest scientific evidence and advances in depression care since the previous guidelines were published in 2016. The update was led by researchers at the University of B.C. and the University of Toronto, alongside a national working group of more than 40 academic clinical experts and patient partners.

"These recommendations not only represent the evidence and broad consensus of leading experts in depression research and care, but, importantly, they also reflect the perspectives of patients with lived experience," says co-lead author Dr. Raymond Lam, professor of psychiatry at UBC and co-director of the Mood Disorders Centre at the Djavad Mowafaghian Centre for Brain Health. "Our hope is that this update will empower clinicians with the latest recommendations that can help achieve better outcomes and improved quality of life for the millions of people affected by depression."

More than one in 10 Canadians will experience depression at some point in their lives, making it one of the largest public health burdens in Canada. However, it is estimated that only 20 per cent of people receive adequate treatment.

The updated guidelines cover eight primary topic areas that map the patient care journey, from assessment and diagnosis through to the selection of treatments and strategies to prevent recurrence. The question-and-answer format is designed to be practical, accessible and easy for clinicians to use.

To develop the refreshed guidelines, the working group conducted a comprehensive literature review of new scientific evidence published since the previous 2016 guidelines. Drafts were revised based on review by patient partners, expert peer review and a defined expert consensus process.

The resulting recommendations are organized by lines of treatment based on the level of evidence supporting each therapy and factors such as safety, tolerability and feasibility. Guidance is provided to aid healthcare professionals in choosing the right treatment option with an emphasis on collaborative decision-making.

"Depression is a complex and highly individualized condition," says Dr. Lam. "The guidelines highlight the importance of collaborating with patients in care decisions and providing a personalized treatment approach that carefully considers a person's needs, preferences and treatment history."

The guidelines underline the strong evidence base for well-established first-line treatments, including a number of medications, as well as psychological treatments such as cognitive behavioural therapy, interpersonal therapy and behavioural activation. Based on recent evidence, a number of new psychological and pharmacological treatments were added to the list of treatment options.

"Notable additions to the new guidelines are a strong emphasis on patient participation in choosing treatment, applying outcome measures throughout care, and an overview of digital mental health tools in the management of depression," says co-lead author Dr. Sidney Kennedy, professor of psychiatry at the University of Toronto and director of the Centre for Depression and Suicide Studies at Unity Health Toronto.

The guidelines include further direction on how healthcare professionals can incorporate lifestyle interventions, such as exercise, nutrition and sleep hygiene. They also explore when neuromodulation treatments should be considered and what should be done when a patient doesn't respond to initial treatments or develops treatment-resistant depression.

"Many well-established psychological and behavioural interventions have accumulated more support for their efficacy across different delivery formats," says co-author Dr. Lena Quilty, associate professor of psychiatry at the University of Toronto and senior scientist at the Centre for Addiction and Mental Health. "We are especially pleased to report on evidence for new interventions that target depression as well as commonly co-occurring challenges such as anxiety or disrupted cognitive processes. We hope that these additional alternatives provide more opportunities for integrated attention to these multi-faceted issues."

CANMAT is a network of academic and clinical experts dedicated to improving clinical care for people with mood and anxiety disorders. The new depression guidelines were published today in The Canadian Journal of Psychiatry . The researchers will be releasing updated versions of the CANMAT Pocket Guide to Depression for clinicians and the CHOICE-D Patient and Family Guide to Depression Treatment.

• Mental Health Research
• Health Policy
• Today's Healthcare
• Patient Education and Counseling
• Mental Health
• Psychopathology
• Clinical depression
• Postpartum depression
• Bipolar disorder
• Seasonal affective disorder
• Psychologist

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Materials provided by University of British Columbia . Note: Content may be edited for style and length.

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• Raymond W. Lam, Sidney H. Kennedy, Camelia Adams, Anees Bahji, Serge Beaulieu, Venkat Bhat, Pierre Blier, Daniel M. Blumberger, Elisa Brietzke, Trisha Chakrabarty, André Do, Benicio N. Frey, Peter Giacobbe, David Gratzer, Sophie Grigoriadis, Jeffrey Habert, M. Ishrat Husain, Zahinoor Ismail, Alexander McGirr, Roger S. McIntyre, Erin E. Michalak, Daniel J. Müller, Sagar V. Parikh, Lena S. Quilty, Arun V. Ravindran, Nisha Ravindran, Johanne Renaud, Joshua D. Rosenblat, Zainab Samaan, Gayatri Saraf, Kathryn Schade, Ayal Schaffer, Mark Sinyor, Claudio N. Soares, Jennifer Swainson, Valerie H. Taylor, Smadar V. Tourjman, Rudolf Uher, Michael van Ameringen, Gustavo Vazquez, Simone Vigod, Daphne Voineskos, Lakshmi N. Yatham, Roumen V. Milev. Canadian Network for Mood and Anxiety Treatments (CANMAT) 2023 Update on Clinical Guidelines for Management of Major Depressive Disorder in Adults: Réseau canadien pour les traitements de l'humeur et de l'anxiété (CANMAT) 2023 Mise . The Canadian Journal of Psychiatry , 2024; DOI: 10.1177/07067437241245384

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Anxiety Disorders

What is anxiety.

Occasional anxiety is a normal part of life. Many people worry about things such as health, money, or family problems. But anxiety disorders involve more than temporary worry or fear. For people with an anxiety disorder, the anxiety does not go away and can get worse over time. The symptoms can interfere with daily activities such as job performance, schoolwork, and relationships.

There are several types of anxiety disorders, including generalized anxiety disorder, panic disorder, social anxiety disorder, and various phobia-related disorders.

What are the signs and symptoms of anxiety?

Generalized anxiety disorder.

Generalized anxiety disorder (GAD) usually involves a persistent feeling of anxiety or dread, which can interfere with daily life. It is not the same as occasionally worrying about things or experiencing anxiety due to stressful life events. People living with GAD experience frequent anxiety for months, if not years.

Symptoms of GAD include:

• Feeling restless, wound-up, or on-edge
• Being easily fatigued
• Having difficulty concentrating
• Being irritable
• Having headaches, muscle aches, stomachaches, or unexplained pains
• Difficulty controlling feelings of worry
• Having sleep problems, such as difficulty falling or staying asleep

Panic disorder

People with panic disorder have frequent and unexpected panic attacks. Panic attacks are sudden periods of intense fear, discomfort, or sense of losing control even when there is no clear danger or trigger. Not everyone who experiences a panic attack will develop panic disorder.

During a panic attack, a person may experience:

• Pounding or racing heart
• Trembling or tingling
• Feelings of impending doom
• Feelings of being out of control

People with panic disorder often worry about when the next attack will happen and actively try to prevent future attacks by avoiding places, situations, or behaviors they associate with panic attacks. Panic attacks can occur as frequently as several times a day or as rarely as a few times a year.

Social anxiety disorder

Social anxiety disorder is an intense, persistent fear of being watched and judged by others. For people with social anxiety disorder, the fear of social situations may feel so intense that it seems beyond their control. For some people, this fear may get in the way of going to work, attending school, or doing everyday things.

People with social anxiety disorder may experience:

• Blushing, sweating, or trembling
• Stomachaches
• Rigid body posture or speaking with an overly soft voice
• Difficulty making eye contact or being around people they don’t know
• Feelings of self-consciousness or fear that people will judge them negatively

Phobia-related disorders

A phobia is an intense fear of—or aversion to—specific objects or situations. Although it can be realistic to be anxious in some circumstances, the fear people with phobias feel is out of proportion to the actual danger caused by the situation or object.

People with a phobia:

• May have an irrational or excessive worry about encountering the feared object or situation
• Take active steps to avoid the feared object or situation
• Experience immediate intense anxiety upon encountering the feared object or situation
• Endure unavoidable objects and situations with intense anxiety

There are several types of phobias and phobia-related disorders:

Specific phobias (sometimes called simple phobias) : As the name suggests, people who have a specific phobia have an intense fear of, or feel intense anxiety about, specific types of objects or situations. Some examples of specific phobias include the fear of:

• Specific animals, such as spiders, dogs, or snakes
• Receiving injections

Social anxiety disorder (previously called social phobia) : People with social anxiety disorder have a general intense fear of, or anxiety toward, social or performance situations. They worry that actions or behaviors associated with their anxiety will be negatively evaluated by others, leading them to feel embarrassed. This worry often causes people with social anxiety to avoid social situations. Social anxiety disorder can manifest in a range of situations, such as within the workplace or the school environment.

Agoraphobia: People with agoraphobia have an intense fear of two or more of the following situations:

• Using public transportation
• Being in open spaces
• Being in enclosed spaces
• Standing in line or being in a crowd
• Being outside of the home alone

People with agoraphobia often avoid these situations, in part, because they think being able to leave might be difficult or impossible in the event they have panic-like reactions or other embarrassing symptoms. In the most severe form of agoraphobia, an individual can become housebound.

Separation anxiety disorder: Separation anxiety is often thought of as something that only children deal with. However, adults can also be diagnosed with separation anxiety disorder. People with separation anxiety disorder fear being away from the people they are close to. They often worry that something bad might happen to their loved ones while they are not together. This fear makes them avoid being alone or away from their loved ones. They may have bad dreams about being separated or feel unwell when separation is about to happen.

Selective mutism: A somewhat rare disorder associated with anxiety is selective mutism. Selective mutism occurs when people fail to speak in specific social situations despite having normal language skills. Selective mutism usually occurs before the age of 5 and is often associated with extreme shyness, fear of social embarrassment, compulsive traits, withdrawal, clinging behavior, and temper tantrums. People diagnosed with selective mutism are often also diagnosed with other anxiety disorders.

What are the risk factors for anxiety?

Researchers are finding that both genetic and environmental factors contribute to the risk of developing an anxiety disorder.

The risk factors for each type of anxiety disorder vary. However, some general risk factors include:

• Shyness or feeling distressed or nervous in new situations in childhood
• Exposure to stressful and negative life or environmental events
• A history of anxiety or other mental disorders in biological relatives

Anxiety symptoms can be produced or aggravated by:

• Some physical health conditions, such as thyroid problems or heart arrhythmia
• Caffeine or other substances/medications

If you think you may have an anxiety disorder, getting a physical examination from a health care provider may help them diagnose your symptoms and find the right treatment.

How is anxiety treated?

Anxiety disorders are generally treated with psychotherapy, medication, or both. There are many ways to treat anxiety, and you should work with a health care provider to choose the best treatment for you.

Psychotherapy

Psychotherapy or “talk therapy” can help people with anxiety disorders. To be effective, psychotherapy must be directed at your specific anxieties and tailored to your needs.

Cognitive behavioral therapy

Cognitive behavioral therapy (CBT) is an example of one type of psychotherapy that can help people with anxiety disorders. It teaches people different ways of thinking, behaving, and reacting to situations to help you feel less anxious and fearful. CBT has been well studied and is the gold standard for psychotherapy.

Exposure therapy is a CBT method that is used to treat anxiety disorders. Exposure therapy focuses on confronting the fears underlying an anxiety disorder to help people engage in activities they have been avoiding. Exposure therapy is sometimes used along with relaxation exercises.

Acceptance and commitment therapy

Another treatment option for some anxiety disorders is acceptance and commitment therapy (ACT). ACT takes a different approach than CBT to negative thoughts. It uses strategies such as mindfulness and goal setting to reduce discomfort and anxiety. Compared to CBT, ACT is a newer form of psychotherapy treatment, so less data are available on its effectiveness.

Medication does not cure anxiety disorders but can help relieve symptoms. Health care providers, such as a psychiatrist or primary care provider, can prescribe medication for anxiety. Some states also allow psychologists who have received specialized training to prescribe psychiatric medications. The most common classes of medications used to combat anxiety disorders are antidepressants, anti-anxiety medications (such as benzodiazepines), and beta-blockers.

Antidepressants

Antidepressants are used to treat depression, but they can also be helpful for treating anxiety disorders. They may help improve the way your brain uses certain chemicals that control mood or stress. You may need to try several different antidepressant medicines before finding the one that improves your symptoms and has manageable side effects.

Antidepressants can take several weeks to start working so it’s important to give the medication a chance before reaching a conclusion about its effectiveness. If you begin taking antidepressants, do not stop taking them without the help of a health care provider. Your provider can help you slowly and safely decrease your dose. Stopping them abruptly can cause withdrawal symptoms.

In some cases, children, teenagers, and adults younger than 25 may experience increased suicidal thoughts or behavior when taking antidepressant medications, especially in the first few weeks after starting or when the dose is changed. Because of this, people of all ages taking antidepressants should be watched closely, especially during the first few weeks of treatment.

Anti-anxiety medications

Anti-anxiety medications can help reduce the symptoms of anxiety, panic attacks, or extreme fear and worry. The most common anti-anxiety medications are called benzodiazepines. Although benzodiazepines are sometimes used as first-line treatments for generalized anxiety disorder, they have both benefits and drawbacks.

Benzodiazepines are effective in relieving anxiety and take effect more quickly than antidepressant medications. However, some people build up a tolerance to these medications and need higher and higher doses to get the same effect. Some people even become dependent on them.

To avoid these problems, health care providers usually prescribe benzodiazepines for short periods of time.

If people suddenly stop taking benzodiazepines, they may have withdrawal symptoms, or their anxiety may return. Therefore, benzodiazepines should be tapered off slowly. Your provider can help you slowly and safely decrease your dose.

Beta-blockers

Although beta-blockers are most often used to treat high blood pressure, they can help relieve the physical symptoms of anxiety, such as rapid heartbeat, shaking, trembling, and blushing. These medications can help people keep physical symptoms under control when taken for short periods. They can also be used “as needed” to reduce acute anxiety, including to prevent some predictable forms of performance anxieties.

Choosing the right medication

Some types of drugs may work better for specific types of anxiety disorders, so people should work closely with a health care provider to identify which medication is best for them. Certain substances such as caffeine, some over-the-counter cold medicines, illicit drugs, and herbal supplements may aggravate the symptoms of anxiety disorders or interact with prescribed medication. People should talk with a health care provider, so they can learn which substances are safe and which to avoid.

Choosing the right medication, medication dose, and treatment plan should be done under an expert’s care and should be based on a person’s needs and their medical situation. Your and your provider may try several medicines before finding the right one.

Support groups

Some people with anxiety disorders might benefit from joining a self-help or support group and sharing their problems and achievements with others. Support groups are available both in person and online. However, any advice you receive from a support group member should be used cautiously and does not replace treatment recommendations from a health care provider.

Stress management techniques

Stress management techniques, such as exercise, mindfulness, and meditation, also can reduce anxiety symptoms and enhance the effects of psychotherapy. You can learn more about how these techniques benefit your treatment by talking with a health care provider.

How can I find a clinical trial for anxiety?

Clinical trials are research studies that look at new ways to prevent, detect, or treat diseases and conditions. The goal of clinical trials is to determine if a new test or treatment works and is safe. Although individuals may benefit from being part of a clinical trial, participants should be aware that the primary purpose of a clinical trial is to gain new scientific knowledge so that others may be better helped in the future.

Researchers at NIMH and around the country conduct many studies with patients and healthy volunteers. We have new and better treatment options today because of what clinical trials uncovered years ago. Be part of tomorrow’s medical breakthroughs. Talk to your health care provider about clinical trials, their benefits and risks, and whether one is right for you.

To learn more or find a study, visit:

• NIMH’s Clinical Trials webpage : Information about participating in clinical trials
• Clinicaltrials.gov: Current Studies on Anxiety Disorders  : List of clinical trials funded by the National Institutes of Health (NIH) being conducted across the country
• Join a Study: Adults - Anxiety Disorders : List of studies being conducted on the NIH Campus in Bethesda, MD
• Join a Study: Children - Anxiety Disorders : List of studies being conducted on the NIH Campus in Bethesda, MD

Where can I learn more about anxiety?

Free brochures and shareable resources.

• Generalized Anxiety Disorder (GAD): When Worry Gets Out of Control : This brochure describes the signs, symptoms, and treatment of generalized anxiety disorder.
• I’m So Stressed Out! : This fact sheet intended for teens and young adults presents information about stress, anxiety, and ways to cope when feeling overwhelmed.
• Obsessive-Compulsive Disorder: When Unwanted Thoughts Take Over : This brochure describes the signs, symptoms, and treatment of OCD.
• Panic Disorder: When Fear Overwhelms : This brochure describes the signs, symptoms, and treatments of panic disorder.
• Social Anxiety Disorder: More Than Just Shyness : This brochure describes the signs, symptoms, and treatment of social anxiety disorder.
• Shareable Resources on Anxiety Disorders : Help support anxiety awareness and education in your community. Use these digital resources, including graphics and messages, to spread the word about anxiety disorders.
• Mental Health Minute: Anxiety Disorders in Adults :Take a mental health minute to watch this video about anxiety disorders in adults.
• Mental Health Minute: Stress and Anxiety in Adolescents : Take a mental health minute to watch this video about stress and anxiety in adolescents.
• NIMH Expert Discusses Managing Stress and Anxiety : Learn about coping with stressful situations and when to seek help.
• GREAT : Learn helpful practices to manage stress and anxiety. GREAT was developed by Dr. Krystal Lewis, a licensed clinical psychologist at NIMH.
• Getting to Know Your Brain: Dealing with Stress : Test your knowledge about stress and the brain. Also learn how to create and use a “ stress catcher ” to practice strategies to deal with stress.
• Guided Visualization: Dealing with Stress : Learn how the brain handles stress and practice a guided visualization activity.
• Panic Disorder: The Symptoms : Learn about the signs and symptoms of panic disorder.

Federal resources

• Anxiety Disorders   (MedlinePlus – also en español  )

Research and statistics

• Journal Articles   : References and abstracts from MEDLINE/PubMed (National Library of Medicine).
• Statistics: Anxiety Disorder : This webpage provides information on the statistics currently available on the prevalence and treatment of anxiety among people in the U.S.

Last Reviewed: April 2024

Unless otherwise specified, the information on our website and in our publications is in the public domain and may be reused or copied without permission. However, you may not reuse or copy images. Please cite the National Institute of Mental Health as the source. Read our copyright policy to learn more about our guidelines for reusing NIMH content.

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Immune Cells: A Hidden Trigger for Anxiety, Depression, and Alzheimer’s Disease

By PNAS Nexus May 9, 2024

A study reveals that regulatory T cells, crucial components of the immune system, might also influence mood stability. Experiments on mice with temporarily depleted Tregs showed increased anxiety and depressive behaviors, which were reversible with the restoration of these cells. Additionally, Treg depletion in mice modeling Alzheimer’s disease led to cognitive impairments, highlighting Tregs’ broader role in both mood regulation and cognitive health. Credit: SciTechDaily.com

Research indicates that regulatory T cells (Tregs) might stabilize mood and prevent depression, with their depletion linked to increased anxiety and cognitive issues in Alzheimer’s models.

Regulatory T cells—known as the workhorses of the body’s immune system—may also play a role in stabilizing mood, a study suggests. The transcription factor Forkhead box P3 (Foxp3) controls the production of regulatory T cells (Tregs). While Tregs primarily regulate the adaptive immune system, research indicates they may also influence mood. Notably, reduced Foxp3 expression has been linked with major depressive disorders.

Experimental Findings on Tregs and Behavior

Giulio Maria Pasinetti and colleagues tested a line of lab mice whose Tregs can be temporarily depleted on standard tasks designed to measure depression and anxiety in the rodents. Treg-depleted mice were more likely to hide in darkness, moved less, and gave up on self-preservation actions more easily—suggesting that Treg-depleted mice were more anxious and depressed than control mice. These neurobehavioral changes in Treg-depleted mice were reversed after restoration of Foxp3-expressing cells, and Treg-restored mice were more similar to controls than Treg-depleted mice were.

Depletion of peripheral Foxp3-expressing cells leads to elevated levels of monocytes and granulocytes, causing disruption of blood-brain barrier, triggering the activation of inflammasome in the brain. Credit: Pasinetti et al.

Tregs in Neurological Disorders

Additionally, mice bred to model Alzheimer’s disease showed cognitive impairments when their Tregs were depleted. The authors posit that Treg depletion causes proliferation of peripheral immune cells, some of which can cross the blood-brain barrier into the brain and cause inflammatory responses in the hippocampal formation. This transient activation of innate immunity in the brain can cause anxiety, depression, or Alzheimer’s disease-type cognitive deterioration, according to the authors.

Reference: “Transient anxiety-and depression-like behaviors are linked to the depletion of Foxp3-expressing cells via inflammasome in the brain” by Eun-Jeong Yang, Md Al Rahim, Elizabeth Griggs, Ruth Iban-Arias and Giulio Maria Pasinetti, 22 August 2023, PNAS Nexus . DOI: 10.1093/pnasnexus/pgad251

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New Research From Clinical Psychological Science

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Threat Appraisal and Pediatric Anxiety: Proof of Concept of a Latent-Variable Approach Rachel Bernstein, Ashley Smith, Elizabeth Kitt, Elise Cardinale, Anita Harrewijn, Rany Abend, Kalina Michalska, Daniel Pine, and Katharina Kircanski  

Elevated threat appraisal is a postulated neurodevelopmental mechanism of anxiety disorders. However, laboratory-assessed threat appraisals are task-specific and subject to measurement error. We used latent-variable analysis to integrate youths’ self-reported threat appraisals across different experimental tasks; we next examined associations with pediatric anxiety and behavioral- and psychophysiological-task indices. Ninety-two youths ages 8 to 17 (M = 13.07 years, 65% female), including 51 with a primary anxiety disorder and 41 with no Axis I diagnosis, completed up to eight threat-exposure tasks. Anxiety symptoms were assessed using questionnaires and ecological momentary assessment. Appraisals both before and following threat exposures evidenced shared variance across tasks. Derived factor scores for threat appraisal were associated significantly with anxiety symptoms and variably with task indices; findings were comparable with task-specific measures and had several advantages. Results support an overarching construct of threat appraisal linked with pediatric anxiety, providing groundwork for more robust laboratory-based measurement. 

Investigating a Common Structure of Personality Pathology and Attachment Madison Smith and Susan South

Critical theoretical intersections between adult insecure attachment and personality disorders (PDs) suggest that they may overlap, but a lack of empirical analysis to date has limited further interpretation. The current study used a large sample (N = 812) of undergraduates (N = 355) and adults receiving psychological treatment (N = 457) to test whether a joint hierarchical factor structure of personality pathology and insecure attachment is tenable. Results suggested that attachment and PD indicators load together on latent domains of emotional lability, detachment, and vulnerability, but antagonistic, impulsigenic, and psychosis-spectrum factors do not subsume attachment indicators. This solution was relatively consistent across treatment status but varied across gender, potentially suggesting divergent socialization of interpersonal problems. Although further tests are needed, if attachment and PDs prove to be unitary, combining them has exciting potential for providing an etiologic-developmental substrate to the classification of interpersonal dysfunction. 

Does Major Depression Differentially Affect Daily Affect in Adults From Six Middle-Income Countries: China, Ghana, India, Mexico, Russian Federation, and South Africa? Vanessa Panaite and Nathan Cohen

Much of the research on how depression affects daily emotional functioning comes from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) countries. In the current study, we investigated daily positive affect (PA) and negative affect (NA) and PA and NA variability in a cross-cultural sample of adults with a depression diagnosis (N = 2,487) and without a depression diagnosis (N = 31,764) from six middle-income non-WEIRD countries: China, Ghana, India, Mexico, Russian Federation, and South Africa. Across countries, adults with depression relative to adults without depression reported higher average NA and NA variability and lower average PA but higher PA variability. Findings varied between countries. Observations are discussed within the context of new theories and evidence. Implications for current knowledge and for future efforts to grow cross-cultural and non-WEIRD affective science are discussed.

Depressive Symptoms and Their Mechanisms: An Investigation of Long-Term Patterns of Interaction Through a Panel-Network Approach Asle Hoffart, Nora Skjerdingstad, René Freichel, Alessandra Mansueto, Sverre Johnson, Sacha Epskamp, and Omid V. Ebrahimi  

The dynamic interaction between depressive symptoms, mechanisms proposed in the metacognitive-therapy model, and loneliness across a 9-month period was investigated. Four data waves 2 months apart were delivered by a representative population sample of 4,361 participants during the COVID-19 pandemic in Norway. Networks were estimated using the newly developed panel graphical vector-autoregression method. In the temporal network, use of substance to cope with negative feelings or thoughts positively predicted threat monitoring and depressed mood. In turn, threat monitoring positively predicted suicidal ideation. Metacognitive beliefs that thoughts and feelings are dangerous positively predicted anhedonia. Suicidal ideation positively predicted sleep problems and worthlessness. Loneliness was positively predicted by depressed mood. In turn, more loneliness predicted more control of emotions. The findings point at the theory-derived variables, threat monitoring, beliefs that thoughts and feelings are dangerous, and use of substance to cope, as potential targets for intervention to alleviate long-term depressive symptoms. 

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Privacy Overview

Effectiveness and implementation of a text messaging intervention to reduce depression and anxiety symptoms among Latinx and Non-Latinx white users during the COVID-19 pandemic

Author:  Adrian Aguilera Publication date:  June 30, 2023 Publication type:  Journal Article Citation:  Haro-Ramos, A. Y., Rodriguez, H. P., & Aguilera, A. (2023). Effectiveness and implementation of a text messaging intervention to reduce depression and anxiety symptoms among Latinx and Non-Latinx white users during the COVID-19 pandemic. Behaviour Research and Therapy, 165, 104318.

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