research on sports performance

• Open access
• Published: 21 May 2024

The bright side of sports: a systematic review on well-being, positive emotions and performance

• David Peris-Delcampo 1 ,
• Antonio Núñez 2 ,
• Paula Ortiz-Marholz 3 ,
• Aurelio Olmedilla 4 ,
• Enrique Cantón 1 ,
• Javier Ponseti 2 &
• Alejandro Garcia-Mas 2  

BMC Psychology volume  12 , Article number:  284 ( 2024 ) Cite this article

Metrics details

The objective of this study is to conduct a systematic review regarding the relationship between positive psychological factors, such as psychological well-being and pleasant emotions, and sports performance.

This study, carried out through a systematic review using PRISMA guidelines considering the Web of Science, PsycINFO, PubMed and SPORT Discus databases, seeks to highlight the relationship between other more ‘positive’ factors, such as well-being, positive emotions and sports performance.

The keywords will be decided by a Delphi Method in two rounds with sport psychology experts.

Participants

There are no participants in the present research.

The main exclusion criteria were: Non-sport thema, sample younger or older than 20–65 years old, qualitative or other methodology studies, COVID-related, journals not exclusively about Psychology.

Main outcomes measures

We obtained a first sample of 238 papers, and finally, this sample was reduced to the final sample of 11 papers.

The results obtained are intended to be a representation of the ‘bright side’ of sports practice, and as a complement or mediator of the negative variables that have an impact on athletes’ and coaches’ performance.

Conclusions

Clear recognition that acting on intrinsic motivation continues to be the best and most effective way to motivate oneself to obtain the highest levels of performance, a good perception of competence and a source of personal satisfaction.

Peer Review reports

Introduction

In recent decades, research in the psychology of sport and physical exercise has focused on the analysis of psychological variables that could have a disturbing, unfavourable or detrimental role, including emotions that are considered ‘negative’, such as anxiety/stress, sadness or anger, concentrating on their unfavourable relationship with sports performance [ 1 , 2 , 3 , 4 ], sports injuries [ 5 , 6 , 7 ] or, more generally, damage to the athlete’s health [ 8 , 9 , 10 ]. The study of ‘positive’ emotions such as happiness or, more broadly, psychological well-being, has been postponed at this time, although in recent years this has seen an increase that reveals a field of study of great interest to researchers and professionals [ 11 , 12 , 13 ] including physiological, psychological, moral and social beneficial effects of the physical activity in comic book heroes such as Tintin, a team leader, which can serve as a model for promoting healthy lifestyles, or seeking ‘eternal youth’ [ 14 ].

Emotions in relation to their effects on sports practice and performance rarely go in one direction, being either negative or positive—generally positive and negative emotions do not act alone [ 15 ]. Athletes experience different emotions simultaneously, even if they are in opposition and especially if they are of mild or moderate intensity [ 16 ]. The athlete can feel satisfied and happy and at the same time perceive a high level of stress or anxiety before a specific test or competition. Some studies [ 17 ] have shown how sports participation and the perceived value of elite sports positively affect the subjective well-being of the athlete. This also seems to be the case in non-elite sports practice. The review by Mansfield et al. [ 18 ] showed that the published literature suggests that practising sports and dance, in a group or supported by peers, can improve the subjective well-being of the participants, and also identifies negative feelings towards competence and ability, although the quantity and quality of the evidence published is low, requiring better designed studies. All these investigations are also supported by the development of the concept of eudaimonic well-being [ 19 ], which is linked to the development of intrinsic motivation, not only in its aspect of enjoyment but also in its relationship with the perception of competition and overcoming and achieving goals, even if this is accompanied by other unpleasant hedonic emotions or even physical discomfort. Shortly after a person has practised sports, he will remember those feelings of exhaustion and possibly stiffness, linked to feelings of satisfaction and even enjoyment.

Furthermore, the mediating role of parents, coaches and other psychosocial agents can be significant. In this sense, Lemelin et al. [ 20 ], with the aim of investigating the role of autonomy support from parents and coaches in the prediction of well-being and performance of athletes, found that autonomy support from parents and coaches has positive relationships with the well-being of the athlete, but that only coach autonomy support is associated with sports performance. This research suggests that parents and coaches play important but distinct roles in athlete well-being and that coach autonomy support could help athletes achieve high levels of performance.

On the other hand, an analysis of emotions in the sociocultural environment in which they arise and gain meaning is always interesting, both from an individual perspective and from a sports team perspective. Adler et al. [ 21 ] in a study with military teams showed that teams with a strong emotional culture of optimism were better positioned to recover from poor performance, suggesting that organisations that promote an optimistic culture develop more resilient teams. Pekrun et al. [ 22 ] observed with mathematics students that individual success boosts emotional well-being, while placing people in high-performance groups can undermine it, which is of great interest in investigating the effectiveness and adjustment of the individual in sports teams.

There is still little scientific literature in the field of positive emotions and their relationship with sports practice and athlete performance, although their approach has long had its clear supporters [ 23 , 24 ]. It is comforting to observe the significant increase in studies in this field, since some authors (e.g [ 25 , 26 ]). . , point out the need to overcome certain methodological and conceptual problems, paying special attention to the development of specific instruments for the evaluation of well-being in the sports field and evaluation methodologies.

As McCarthy [ 15 ] indicates, positive emotions (hedonically pleasant) can be the catalysts for excellence in sport and deserve a space in our research and in professional intervention to raise the level of athletes’ performance. From a holistic perspective, positive emotions are permanently linked to psychological well-being and research in this field is necessary: firstly because of the leading role they play in human behaviour, cognition and affection, and secondly, because after a few years of international uncertainty due to the COVID-19 pandemic and wars, it seems ‘healthy and intelligent’ to encourage positive emotions for our athletes. An additional reason is that they are known to improve motivational processes, reducing abandonment and negative emotional costs [ 11 ]. In this vein, concepts such as emotional intelligence make sense and can help to identify and properly manage emotions in the sports field and determine their relationship with performance [ 27 ] that facilitates the inclusion of emotional training programmes based on the ‘bright side’ of sports practice [ 28 ].

Based on all of the above, one might wonder how these positive emotions are related to a given event and what role each one of them plays in the athlete’s performance. Do they directly affect performance, or do they affect other psychological variables such as concentration, motivation and self-efficacy? Do they favour the availability and competent performance of the athlete in a competition? How can they be regulated, controlled for their own benefit? How can other psychosocial agents, such as parents or coaches, help to increase the well-being of their athletes?

This work aims to enhance the leading role, not the secondary, of the ‘good and pleasant side’ of sports practice, either with its own entity, or as a complement or mediator of the negative variables that have an impact on the performance of athletes and coaches. Therefore, the objective of this study is to conduct a systematic review regarding the relationship between positive psychological factors, such as psychological well-being and pleasant emotions, and sports performance. For this, the methodological criteria that constitute the systematic review procedure will be followed.

Materials and methods

This study was carried out through a systematic review using PRISMA (Preferred Reporting Items for Systematic Reviews) guidelines considering the Web of Science (WoS) and Psycinfo databases. These two databases were selected using the Delphi method [ 29 ]. It does not include a meta-analysis because there is great data dispersion due to the different methodologies used [ 30 ].

The keywords will be decided by the Delphi Method in two rounds with sport psychology experts. The results obtained are intended to be a representation of the ‘bright side’ of sports practice, and as a complement or mediator of the negative variables that have an impact on athletes’ and coaches’ performance.

It was determined that the main construct was to be psychological well-being, and that it was to be paired with optimism, healthy practice, realisation, positive mood, and performance and sport. The search period was limited to papers published between 2000 and 2023, and the final list of papers was obtained on February 13 , 2023. This research was conducted in two languages—English and Spanish—and was limited to psychological journals and specifically those articles where the sample was formed by athletes.

Each word was searched for in each database, followed by searches involving combinations of the same in pairs and then in trios. In relation to the results obtained, it was decided that the best approach was to group the words connected to positive psychology on the one hand, and on the other, those related to self-realisation/performance/health. In this way, it used parentheses to group words (psychological well-being; or optimism; or positive mood) with the Boolean ‘or’ between them (all three refer to positive psychology); and on the other hand, it grouped those related to performance/health/realisation (realisation; or healthy practice or performance), separating both sets of parentheses by the Boolean ‘and’’. To further filter the search, a keyword included in the title and in the inclusion criteria was added, which was ‘sport’ with the Boolean ‘and’’. In this way, the search achieved results that combined at least one of the three positive psychology terms and one of the other three.

Results (first phase)

The mentioned keywords were cross-matched, obtaining the combination with a sufficient number of papers. From the first research phase, the total number of papers obtained was 238. Then screening was carried out by 4 well-differentiated phases that are summarised in Fig.  1 . These phases helped to reduce the original sample to a more accurate one.

Phases of the selection process for the final sample. Four phases were carried out to select the final sample of articles. The first phase allowed the elimination of duplicates. In the second stage, those that, by title or abstract, did not fit the objectives of the article were eliminated. Previously selected exclusion criteria were applied to the remaining sample. Thus, in phase 4, the final sample of 11 selected articles was obtained

Results (second phase)

The first screening examined the title, and the abstract if needed, excluding the papers that were duplicated, contained errors or someone with formal problems, low N or case studies. This screening allowed the initial sample to be reduced to a more accurate one with 109 papers selected.

Results (third phase)

This was followed by the second screening to examine the abstract and full texts, excluding if necessary papers related to non-sports themes, samples that were too old or too young for our interests, papers using qualitative methodologies, articles related to the COVID period, or others published in non-psychological journals. Furthermore, papers related to ‘negative psychological variables’’ were also excluded.

Results (fourth phase)

At the end of this second screening the remaining number of papers was 11. In this final phase we tried to organise the main characteristics and their main conclusions/results in a comprehensible list (Table  1 ). Moreover, in order to enrich our sample of papers, we decided to include some articles from other sources, mainly those presented in the introduction to sustain the conceptual framework of the concept ‘bright side’ of sports.

The usual position of the researcher of psychological variables that affect sports performance is to look for relationships between ‘negative’ variables, first in the form of basic psychological processes, or distorting cognitive behavioural, unpleasant or evaluable as deficiencies or problems, in a psychology for the ‘risk’ society, which emphasises the rehabilitation that stems from overcoming personal and social pathologies [ 31 ], and, lately, regarding the affectation of the athlete’s mental health [ 32 ]. This fact seems to be true in many cases and situations and to openly contradict the proclaimed psychological benefits of practising sports (among others: Cantón [ 33 ], ; Froment and González [ 34 ]; Jürgens [ 35 ]).

However, it is possible to adopt another approach focused on the ‘positive’ variables, also in relation to the athlete’s performance. This has been the main objective of this systematic review of the existing literature and far from being a novel approach, although a minority one, it fits perfectly with the definition of our area of knowledge in the broad field of health, as has been pointed out for some time [ 36 , 37 ].

After carrying out the aforementioned systematic review, a relatively low number of articles were identified by experts that met the established conditions—according to the PRISMA method [ 37 , 38 , 39 , 40 ]—regarding databases, keywords, and exclusion and inclusion criteria. These precautions were taken to obtain the most accurate results possible, and thus guarantee the quality of the conclusions.

The first clear result that stands out is the great difficulty in finding articles in which sports ‘performance’ is treated as a well-defined study variable adapted to the situation and the athletes studied. In fact, among the results (11 papers), only 3 associate one or several positive psychological variables with performance (which is evaluated in very different ways, combining objective measures with other subjective ones). This result is not surprising, since in several previous studies (e.g. Nuñez et al. [ 41 ]) using a systematic review, this relationship is found to be very weak and nuanced by the role of different mediating factors, such as previous sports experience or the competitive level (e.g. Rascado, et al. [ 42 ]; Reche, Cepero & Rojas [ 43 ]), despite the belief—even among professional and academic circles—that there is a strong relationship between negative variables and poor performance, and vice versa, with respect to the positive variables.

Regarding what has been evidenced in relation to the latter, even with these restrictions in the inclusion and exclusion criteria, and the filters applied to the first findings, a true ‘galaxy’ of variables is obtained, which also belong to different categories and levels of psychological complexity.

A preliminary consideration regarding the current paradigm of sport psychology: although it is true that some recent works have already announced the swing of the pendulum on the objects of study of PD, by returning to the study of traits and dispositions, and even to the personality of athletes [ 43 , 44 , 45 , 46 ], our results fully corroborate this trend. Faced with five variables present in the studies selected at the end of the systematic review, a total of three traits/dispositions were found, which were also the most repeated—optimism being present in four articles, mental toughness present in three, and finally, perfectionism—as the representative concepts of this field of psychology, which lately, as has already been indicated, is significantly represented in the field of research in this area [ 46 , 47 , 48 , 49 , 50 , 51 , 52 ]. In short, the psychological variables that finally appear in the selected articles are: psychological well-being (PWB) [ 53 ]; self-compassion, which has recently been gaining much relevance with respect to the positive attributional resolution of personal behaviours [ 54 ], satisfaction with life (balance between sports practice, its results, and life and personal fulfilment [ 55 ], the existence of approach-achievement goals [ 56 ], and perceived social support [ 57 ]). This last concept is maintained transversally in several theoretical frameworks, such as Sports Commitment [ 58 ].

The most relevant concept, both quantitatively and qualitatively, supported by the fact that it is found in combination with different variables and situations, is not a basic psychological process, but a high-level cognitive construct: psychological well-being, in its eudaimonic aspect, first defined in the general population by Carol Ryff [ 59 , 60 ] and introduced at the beginning of this century in sport (e.g., Romero, Brustad & García-Mas [ 13 ], ; Romero, García-Mas & Brustad [ 61 ]). It is important to note that this concept understands psychological well-being as multifactorial, including autonomy, control of the environment in which the activity takes place, social relationships, etc.), meaning personal fulfilment through a determined activity and the achievement or progress towards goals and one’s own objectives, without having any direct relationship with simpler concepts, such as vitality or fun. In the selected studies, PWB appears in five of them, and is related to several of the other variables/traits.

The most relevant result regarding this variable is its link with motivational aspects, as a central axis that relates to different concepts, hence its connection to sports performance, as a goal of constant improvement that requires resistance, perseverance, management of errors and great confidence in the possibility that achievements can be attained, that is, associated with ideas of optimism, which is reflected in expectations of effectiveness.

If we detail the relationships more specifically, we can first review this relationship with the ‘way of being’, understood as personality traits or behavioural tendencies, depending on whether more or less emphasis is placed on their possibilities for change and learning. In these cases, well-being derives from satisfaction with progress towards the desired goal, for which resistance (mental toughness) and confidence (optimism) are needed. When, in addition, the search for improvement is constant and aiming for excellence, its relationship with perfectionism is clear, although it is a factor that should be explored further due to its potential negative effect, at least in the long term.

The relationship between well-being and satisfaction with life is almost tautological, in the precise sense that what produces well-being is the perception of a relationship or positive balance between effort (or the perception of control, if we use stricter terminology) and the results thereof (or the effectiveness of such control). This direct link is especially important when assessing achievement in personally relevant activities, which, in the case of the subjects evaluated in the papers, specifically concern athletes of a certain level of performance, which makes it a more valuable objective than would surely be found in the general population. And precisely because of this effect of the value of performance for athletes of a certain level, it also allows us to understand how well-being is linked to self-compassion, since as a psychological concept it is very close to that of self-esteem, but with a lower ‘demand’ or a greater ‘generosity’, when we encounter failures, mistakes or even defeats along the way, which offers us greater protection from the risk of abandonment and therefore reinforces persistence, a key element for any successful sports career [ 62 ].

It also has a very direct relationship with approach-achievement goals, since precisely one of the central aspects characterising this eudaimonic well-being and differentiating it from hedonic well-being is specifically its relationship with self-determined and persistent progress towards goals or achievements with incentive value for the person, as is sports performance evidently [ 63 ].

Finally, it is interesting to see how we can also find a facet or link relating to the aspects that are more closely-related to the need for human affiliation, with feeling part of a group or human collective, where we can recognise others and recognise ourselves in the achievements obtained and the social reinforcement of those themselves, as indicated by their relationship with perceived social support. This construct is very labile, in fact it is common to find results in which the pressure of social support is hardly differentiated, for example, from the parents of athletes and/or their coaches [ 64 ]. However, its relevance within this set of psychological variables and traits is proof of its possible conceptual validity.

Analysing the results obtained, the first conclusion is that in no case is an integrated model based solely on ‘positive’ variables or traits obtained, since some ‘negative’ ones appear (anxiety, stress, irrational thoughts), affecting the former.

The second conclusion is that among the positive elements the variable coping strategies (their use, or the perception of their effectiveness) and the traits of optimism, perfectionism and self-compassion prevail, since mental strength or psychological well-being (which also appear as important, but with a more complex nature) are seen to be participated in by the aforementioned traits.

Finally, it must be taken into account that the generation of positive elements, such as resilience, or the learning of coping strategies, are directly affected by the educational style received, or by the culture in which the athlete is immersed. Thus, the applied potential of these findings is great, but it must be calibrated according to the educational and/or cultural features of the specific setting.

Limitations

The limitations of this study are those evident and common in SR methodology using the PRISMA system, since the selection of keywords (and their logical connections used in the search), the databases, and the inclusion/exclusion criteria bias the work in its entirety and, therefore, constrain the generalisation of the results obtained.

Likewise, the conclusions must—based on the above and the results obtained—be made with the greatest concreteness and simplicity possible. Although we have tried to reduce these limitations as much as possible through the use of experts in the first steps of the method, they remain and must be considered in terms of the use of the results.

Future developments

Undoubtedly, progress is needed in research to more precisely elucidate the role of well-being, as it has been proposed here, from a bidirectional perspective: as a motivational element to push towards improvement and the achievement of goals, and as a product or effect of the self-determined and competent behaviour of the person, in relation to different factors, such as that indicated here of ‘perfectionism’ or the potential interference of material and social rewards, which are linked to sports performance—in our case—and that could act as a risk factor so that our achievements, far from being a source of well-being and satisfaction, become an insatiable demand in the search to obtain more and more frequent rewards.

From a practical point of view, an empirical investigation should be conducted to see if these relationships hold from a statistical point of view, either in the classical (correlational) or in the probabilistic (Bayesian Networks) plane.

The results obtained in this study, exclusively researched from the desk, force the authors to develop subsequent empirical and/or experimental studies in two senses: (1) what interrelationships exist between the so called ‘positive’ and ‘negative’ psychological variables and traits in sport, and in what sense are each of them produced; and, (2) from a global, motivational point of view, can currently accepted theoretical frameworks, such as SDT, easily accommodate this duality, which is becoming increasingly evident in applied work?

Finally, these studies should lead to proposals applied to the two fields that have appeared to be relevant: educational and cultural.

Application/transfer of results

A clear application of these results is aimed at guiding the training of sports and physical exercise practitioners, directing it towards strategies for assessing achievements, improvements and failure management, which keep them in line with well-being enhancement, eudaimonic, intrinsic and self-determined, which enhances the quality of their learning and their results and also favours personal health and social relationships.

Data availability

There are no further external data.

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Sport psychology and performance meta-analyses: A systematic review of the literature

Roles Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Kinesiology and Sport Management, Texas Tech University, Lubbock, Texas, United States of America, Education Academy, Vytautas Magnus University, Kaunas, Lithuania

Roles Data curation, Methodology, Writing – original draft

Affiliation Department of Psychological Sciences, Texas Tech University, Lubbock, Texas, United States of America

Roles Data curation, Methodology

Roles Writing – original draft, Writing – review & editing

Affiliation Department of Kinesiology and Sport Management, Honors College, Texas Tech University, Lubbock, Texas, United States of America

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Affiliation Faculty of Education, Health and Well-Being, University of Wolverhampton, Walsall, West Midlands, United Kingdom

Roles Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Affiliation Division of Research & Innovation, University of Southern Queensland, Toowoomba, Queensland, Australia

• Marc Lochbaum, 
• Elisabeth Stoner, 
• Tristen Hefner, 
• Sydney Cooper, 
• Andrew M. Lane, 
• Peter C. Terry

• Published: February 16, 2022
• https://doi.org/10.1371/journal.pone.0263408
• Peer Review
• Reader Comments

Sport psychology as an academic pursuit is nearly two centuries old. An enduring goal since inception has been to understand how psychological techniques can improve athletic performance. Although much evidence exists in the form of meta-analytic reviews related to sport psychology and performance, a systematic review of these meta-analyses is absent from the literature. We aimed to synthesize the extant literature to gain insights into the overall impact of sport psychology on athletic performance. Guided by the PRISMA statement for systematic reviews, we reviewed relevant articles identified via the EBSCOhost interface. Thirty meta-analyses published between 1983 and 2021 met the inclusion criteria, covering 16 distinct sport psychology constructs. Overall, sport psychology interventions/variables hypothesized to enhance performance (e.g., cohesion, confidence, mindfulness) were shown to have a moderate beneficial effect ( d = 0.51), whereas variables hypothesized to be detrimental to performance (e.g., cognitive anxiety, depression, ego climate) had a small negative effect ( d = -0.21). The quality rating of meta-analyses did not significantly moderate the magnitude of observed effects, nor did the research design (i.e., intervention vs. correlation) of the primary studies included in the meta-analyses. Our review strengthens the evidence base for sport psychology techniques and may be of great practical value to practitioners. We provide recommendations for future research in the area.

Citation: Lochbaum M, Stoner E, Hefner T, Cooper S, Lane AM, Terry PC (2022) Sport psychology and performance meta-analyses: A systematic review of the literature. PLoS ONE 17(2): e0263408. https://doi.org/10.1371/journal.pone.0263408

Editor: Claudio Imperatori, European University of Rome, ITALY

Received: September 28, 2021; Accepted: January 18, 2022; Published: February 16, 2022

Copyright: © 2022 Lochbaum et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper.

Funding: The author(s) received no specific funding for this work.

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

Introduction

Sport performance matters. Verifying its global importance requires no more than opening a newspaper to the sports section, browsing the internet, looking at social media outlets, or scanning abundant sources of sport information. Sport psychology is an important avenue through which to better understand and improve sport performance. To date, a systematic review of published sport psychology and performance meta-analyses is absent from the literature. Given the undeniable importance of sport, the history of sport psychology in academics since 1830, and the global rise of sport psychology journals and organizations, a comprehensive systematic review of the meta-analytic literature seems overdue. Thus, we aimed to consolidate the existing literature and provide recommendations for future research.

The development of sport psychology

The history of sport psychology dates back nearly 200 years. Terry [ 1 ] cites Carl Friedrich Koch’s (1830) publication titled [in translation] Calisthenics from the Viewpoint of Dietetics and Psychology [ 2 ] as perhaps the earliest publication in the field, and multiple commentators have noted that sport psychology experiments occurred in the world’s first psychology laboratory, established by Wilhelm Wundt at the University of Leipzig in 1879 [ 1 , 3 ]. Konrad Rieger’s research on hypnosis and muscular endurance, published in 1884 [ 4 ] and Angelo Mosso’s investigations of the effects of mental fatigue on physical performance, published in 1891 [ 5 ] were other early landmarks in the development of applied sport psychology research. Following the efforts of Koch, Wundt, Rieger, and Mosso, sport psychology works appeared with increasing regularity, including Philippe Tissié’s publications in 1894 [ 6 , 7 ] on psychology and physical training, and Pierre de Coubertin’s first use of the term sport psychology in his La Psychologie du Sport paper in 1900 [ 8 ]. In short, the history of sport psychology and performance research began as early as 1830 and picked up pace in the latter part of the 19 th century. Early pioneers, who helped shape sport psychology include Wundt, recognized as the “father of experimental psychology”, Tissié, the founder of French physical education and Legion of Honor awardee in 1932, and de Coubertin who became the father of the modern Olympic movement and founder of the International Olympic Committee.

Sport psychology flourished in the early 20 th century [see 1, 3 for extensive historic details]. For instance, independent laboratories emerged in Berlin, Germany, established by Carl Diem in 1920; in St. Petersburg and Moscow, Russia, established respectively by Avksenty Puni and Piotr Roudik in 1925; and in Champaign, Illinois USA, established by Coleman Griffith, also in 1925. The period from 1950–1980 saw rapid strides in sport psychology, with Franklin Henry establishing this field of study as independent of physical education in the landscape of American and eventually global sport science and kinesiology graduate programs [ 1 ]. In addition, of great importance in the 1960s, three international sport psychology organizations were established: namely, the International Society for Sport Psychology (1965), the North American Society for the Psychology of Sport and Physical Activity (1966), and the European Federation of Sport Psychology (1969). Since that time, the Association of Applied Sport Psychology (1986), the South American Society for Sport Psychology (1986), and the Asian-South Pacific Association of Sport Psychology (1989) have also been established.

The global growth in academic sport psychology has seen a large number of specialist publications launched, including the following journals: International Journal of Sport Psychology (1970), Journal of Sport & Exercise Psychology (1979), The Sport Psychologist (1987), Journal of Applied Sport Psychology (1989), Psychology of Sport and Exercise (2000), International Journal of Sport and Exercise Psychology (2003), Journal of Clinical Sport Psychology (2007), International Review of Sport and Exercise Psychology (2008), Journal of Sport Psychology in Action (2010), Sport , Exercise , and Performance Psychology (2014), and the Asian Journal of Sport & Exercise Psychology (2021).

In turn, the growth in journal outlets has seen sport psychology publications burgeon. Indicative of the scale of the contemporary literature on sport psychology, searches completed in May 2021 within the Web of Science Core Collection, identified 1,415 publications on goal setting and sport since 1985; 5,303 publications on confidence and sport since 1961; and 3,421 publications on anxiety and sport since 1980. In addition to academic journals, several comprehensive edited textbooks have been produced detailing sport psychology developments across the world, such as Hanrahan and Andersen’s (2010) Handbook of Applied Sport Psychology [ 9 ], Schinke, McGannon, and Smith’s (2016) International Handbook of Sport Psychology [ 10 ], and Bertollo, Filho, and Terry’s (2021) Advancements in Mental Skills Training [ 11 ] to name just a few. In short, sport psychology is global in both academic study and professional practice.

Meta-analysis in sport psychology

Several meta-analysis guides, computer programs, and sport psychology domain-specific primers have been popularized in the social sciences [ 12 , 13 ]. Sport psychology academics have conducted quantitative reviews on much studied constructs since the 1980s, with the first two appearing in 1983 in the form of Feltz and Landers’ meta-analysis on mental practice [ 14 ], which included 98 articles dating from 1934, and Bond and Titus’ cross-disciplinary meta-analysis on social facilitation [ 15 ], which summarized 241 studies including Triplett’s (1898) often-cited study of social facilitation in cycling [ 16 ]. Although much meta-analytic evidence exists for various constructs in sport and exercise psychology [ 12 ] including several related to performance [ 17 ], the evidence is inconsistent. For example, two meta-analyses, both ostensibly summarizing evidence of the benefits to performance of task cohesion [ 18 , 19 ], produced very different mean effects ( d = .24 vs d = 1.00) indicating that the true benefit lies somewhere in a wide range from small to large. Thus, the lack of a reliable evidence base for the use of sport psychology techniques represents a significant gap in the knowledge base for practitioners and researchers alike. A comprehensive systematic review of all published meta-analyses in the field of sport psychology has yet to be published.

Purpose and aim

We consider this review to be both necessary and long overdue for the following reasons: (a) the extensive history of sport psychology and performance research; (b) the prior publication of many meta-analyses summarizing various aspects of sport psychology research in a piecemeal fashion [ 12 , 17 ] but not its totality; and (c) the importance of better understanding and hopefully improving sport performance via the use of interventions based on solid evidence of their efficacy. Hence, we aimed to collate and evaluate this literature in a systematic way to gain improved understanding of the impact of sport psychology variables on sport performance by construct, research design, and meta-analysis quality, to enhance practical knowledge of sport psychology techniques and identify future lines of research inquiry. By systematically reviewing all identifiable meta-analytic reviews linking sport psychology techniques with sport performance, we aimed to evaluate the strength of the evidence base underpinning sport psychology interventions.

Materials and methods

This systematic review of meta-analyses followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 20 ]. We did not register our systematic review protocol in a database. However, we specified our search strategy, inclusion criteria, data extraction, and data analyses in advance of writing our manuscript. All details of our work are available from the lead author. Concerning ethics, this systematic review received a waiver from Texas Tech University Human Subject Review Board as it concerned archival data (i.e., published meta-analyses).

Eligibility criteria

Published meta-analyses were retained for extensive examination if they met the following inclusion criteria: (a) included meta-analytic data such as mean group, between or within-group differences or correlates; (b) published prior to January 31, 2021; (c) published in a peer-reviewed journal; (d) investigated a recognized sport psychology construct; and (e) meta-analyzed data concerned with sport performance. There was no language of publication restriction. To align with our systematic review objectives, we gave much consideration to study participants and performance outcomes. Across multiple checks, all authors confirmed study eligibility. Three authors (ML, AL, and PT) completed the final inclusion assessments.

Information sources

Authors searched electronic databases, personal meta-analysis history, and checked with personal research contacts. Electronic database searches occurred in EBSCOhost with the following individual databases selected: APA PsycINFO, ERIC, Psychology and Behavioral Sciences Collection, and SPORTDiscus. An initial search concluded October 1, 2020. ML, AL, and PT rechecked the identified studies during the February–March, 2021 period, which resulted in the identification of two additional meta-analyses [ 21 , 22 ].

Search protocol

ML and ES initially conducted independent database searches. For the first search, ML used the following search terms: sport psychology with meta-analysis or quantitative review and sport and performance or sport* performance. For the second search, ES utilized a sport psychology textbook and used the chapter title terms (e.g., goal setting). In EBSCOhost, both searches used the advanced search option that provided three separate boxes for search terms such as box 1 (sport psychology), box 2 (meta-analysis), and box 3 (performance). Specific details of our search strategy were:

Search by ML:

• sport psychology, meta-analysis, sport and performance
• sport psychology, meta-analysis or quantitative review, sport* performance
• sport psychology, quantitative review, sport and performance
• sport psychology, quantitative review, sport* performance

Search by ES:

• mental practice or mental imagery or mental rehearsal and sports performance and meta-analysis
• goal setting and sports performance and meta-analysis
• anxiety and stress and sports performance and meta-analysis
• competition and sports performance and meta-analysis
• diversity and sports performance and meta-analysis
• cohesion and sports performance and meta-analysis
• imagery and sports performance and meta-analysis
• self-confidence and sports performance and meta-analysis
• concentration and sports performance and meta-analysis
• athletic injuries and sports performance and meta-analysis
• overtraining and sports performance and meta-analysis
• children and sports performance and meta-analysis

The following specific search of the EBSCOhost with SPORTDiscus, APA PsycINFO, Psychology and Behavioral Sciences Collection, and ERIC databases, returned six results from 2002–2020, of which three were included [ 18 , 19 , 23 ] and three were excluded because they were not meta-analyses.

• Box 1 cohesion
• Box 2 sports performance
• Box 3 meta-analysis

Study selection

As detailed in the PRISMA flow chart ( Fig 1 ) and the specified inclusion criteria, a thorough study selection process was used. As mentioned in the search protocol, two authors (ML and ES) engaged independently with two separate searches and then worked together to verify the selected studies. Next, AL and PT examined the selected study list for accuracy. ML, AL, and PT, whilst rating the quality of included meta-analyses, also re-examined all selected studies to verify that each met the predetermined study inclusion criteria. Throughout the study selection process, disagreements were resolved through discussion until consensus was reached.

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https://doi.org/10.1371/journal.pone.0263408.g001

Data extraction process

Initially, ML, TH, and ES extracted data items 1, 2, 3 and 8 (see Data items). Subsequently, ML, AL, and PT extracted the remaining data (items 4–7, 9, 10). Checks occurred during the extraction process for potential discrepancies (e.g., checking the number of primary studies in a meta-analysis). It was unnecessary to contact any meta-analysis authors for missing information or clarification during the data extraction process because all studies reported the required information. Across the search for meta-analyses, all identified studies were reported in English. Thus, no translation software or searching out a native speaker occurred. All data extraction forms (e.g., data items and individual meta-analysis quality) are available from the first author.

To help address our main aim, we extracted the following information from each meta-analysis: (1) author(s); (2) publication year; (3) construct(s); (4) intervention based meta-analysis (yes, no, mix); (5) performance outcome(s) description; (6) number of studies for the performance outcomes; (7) participant description; (8) main findings; (9) bias correction method/results; and (10) author(s) stated conclusions. For all information sought, we coded missing information as not reported.

Individual meta-analysis quality

ML, AL, and PT independently rated the quality of individual meta-analysis on the following 25 points found in the PRISMA checklist [ 20 ]: title; abstract structured summary; introduction rationale, objectives, and protocol and registration; methods eligibility criteria, information sources, search, study selection, data collection process, data items, risk of bias of individual studies, summary measures, synthesis of results, and risk of bias across studies; results study selection, study characteristics, risk of bias within studies, results of individual studies, synthesis of results, and risk of bias across studies; discussion summary of evidence, limitations, and conclusions; and funding. All meta-analyses were rated for quality by two coders to facilitate inter-coder reliability checks, and the mean quality ratings were used in subsequent analyses. One author (PT), having completed his own ratings, received the incoming ratings from ML and AL and ran the inter-coder analysis. Two rounds of ratings occurred due to discrepancies for seven meta-analyses, mainly between ML and AL. As no objective quality categorizations (i.e., a point system for grouping meta-analyses as poor, medium, good) currently exist, each meta-analysis was allocated a quality score of up to a maximum of 25 points. All coding records are available upon request.

Planned methods of analysis

Several preplanned methods of analysis occurred. We first assessed the mean quality rating of each meta-analysis based on our 25-point PRISMA-based rating system. Next, we used a median split of quality ratings to determine whether standardized mean effects (SMDs) differed by the two formed categories, higher and lower quality meta-analyses. Meta-analysis authors reported either of two different effect size metrics (i.e., r and SMD); hence we converted all correlational effects to SMD (i.e., Cohen’s d ) values using an online effect size calculator ( www.polyu.edu.hk/mm/effectsizefaqs/calculator/calculator.html ). We interpreted the meaningfulness of effects based on Cohen’s interpretation [ 24 ] with 0.20 as small, 0.50 as medium, 0.80 as large, and 1.30 as very large. As some psychological variables associate negatively with performance (e.g., confusion [ 25 ], cognitive anxiety [ 26 ]) whereas others associate positively (e.g., cohesion [ 23 ], mental practice [ 14 ]), we grouped meta-analyses according to whether the hypothesized effect with performance was positive or negative, and summarized the overall effects separately. By doing so, we avoided a scenario whereby the demonstrated positive and negative effects canceled one another out when combined. The effect of somatic anxiety on performance, which is hypothesized to follow an inverted-U relationship, was categorized as neutral [ 35 ]. Last, we grouped the included meta-analyses according to whether the primary studies were correlational in nature or involved an intervention and summarized these two groups of meta-analyses separately.

Study characteristics

Table 1 contains extracted data from 30 meta-analyses meeting the inclusion criteria, dating from 1983 [ 14 ] to 2021 [ 21 ]. The number of primary studies within the meta-analyses ranged from three [ 27 ] to 109 [ 28 ]. In terms of the description of participants included in the meta-analyses, 13 included participants described simply as athletes, whereas other meta-analyses identified a mix of elite athletes (e.g., professional, Olympic), recreational athletes, college-aged volunteers (many from sport science departments), younger children to adolescents, and adult exercisers. Of the 30 included meta-analyses, the majority ( n = 18) were published since 2010. The decadal breakdown of meta-analyses was 1980–1989 ( n = 1 [ 14 ]), 1990–1999 ( n = 6 [ 29 – 34 ]), 2000–2009 ( n = 5 [ 23 , 25 , 26 , 35 , 36 ]), 2010–2019 ( n = 12 [ 18 , 19 , 22 , 27 , 37 – 43 , 48 ]), and 2020–2021 ( n = 6 [ 21 , 28 , 44 – 47 ]).

https://doi.org/10.1371/journal.pone.0263408.t001

As for the constructs covered, we categorized the 30 meta-analyses into the following areas: mental practice/imagery [ 14 , 29 , 30 , 42 , 46 , 47 ], anxiety [ 26 , 31 , 32 , 35 ], confidence [ 26 , 35 , 36 ], cohesion [ 18 , 19 , 23 ], goal orientation [ 22 , 44 , 48 ], mood [ 21 , 25 , 34 ], emotional intelligence [ 40 ], goal setting [ 33 ], interventions [ 37 ], mindfulness [ 27 ], music [ 28 ], neurofeedback training [ 43 ], perfectionism [ 39 ], pressure training [ 45 ], quiet eye training [ 41 ], and self-talk [ 38 ]. Multiple effects were generated from meta-analyses that included more than one construct (e.g., tension, depression, etc. [ 21 ]; anxiety and confidence [ 26 ]). In relation to whether the meta-analyses included in our review assessed the effects of a sport psychology intervention on performance or relationships between psychological constructs and performance, 13 were intervention-based, 14 were correlational, two included a mix of study types, and one included a large majority of cross-sectional studies ( Table 1 ).

A wide variety of performance outcomes across many sports was evident, such as golf putting, dart throwing, maximal strength, and juggling; or categorical outcomes such as win/loss and Olympic team selection. Given the extensive list of performance outcomes and the incomplete descriptions provided in some meta-analyses, a clear categorization or count of performance types was not possible. Sufficient to conclude, researchers utilized many performance outcomes across a wide range of team and individual sports, motor skills, and strength and aerobic tasks.

Effect size data and bias correction

To best summarize the effects, we transformed all correlations to SMD values (i.e., Cohen’s d ). Across all included meta-analyses shown in Table 2 and depicted in Fig 2 , we identified 61 effects. Having corrected for bias, effect size values were assessed for meaningfulness [ 24 ], which resulted in 15 categorized as negligible (< ±0.20), 29 as small (±0.20 to < 0.50), 13 as moderate (±0.50 to < 0.80), 2 as large (±0.80 to < 1.30), and 1 as very large (≥ 1.30).

https://doi.org/10.1371/journal.pone.0263408.g002

https://doi.org/10.1371/journal.pone.0263408.t002

Study quality rating results and summary analyses

Following our PRISMA quality ratings, intercoder reliability coefficients were initially .83 (ML, AL), .95 (ML, PT), and .90 (AL, PT), with a mean intercoder reliability coefficient of .89. To achieve improved reliability (i.e., r mean > .90), ML and AL re-examined their ratings. As a result, intercoder reliability increased to .98 (ML, AL), .96 (ML, PT), and .92 (AL, PT); a mean intercoder reliability coefficient of .95. Final quality ratings (i.e., the mean of two coders) ranged from 13 to 25 ( M = 19.03 ± 4.15). Our median split into higher ( M = 22.83 ± 1.08, range 21.5–25, n = 15) and lower ( M = 15.47 ± 2.42, range 13–20.5, n = 15) quality groups produced significant between-group differences in quality ( F 1,28 = 115.62, p < .001); hence, the median split met our intended purpose. The higher quality group of meta-analyses were published from 2015–2021 (median 2018) and the lower quality group from 1983–2014 (median 2000). It appears that meta-analysis standards have risen over the years since the PRISMA criteria were first introduced in 2009. All data for our analyses are shown in Table 2 .

Table 3 contains summary statistics with bias-corrected values used in the analyses. The overall mean effect for sport psychology constructs hypothesized to have a positive impact on performance was of moderate magnitude ( d = 0.51, 95% CI = 0.42, 0.58, n = 36). The overall mean effect for sport psychology constructs hypothesized to have a negative impact on performance was small in magnitude ( d = -0.21, 95% CI -0.31, -0.11, n = 24). In both instances, effects were larger, although not significantly so, among meta-analyses of higher quality compared to those of lower quality. Similarly, mean effects were larger but not significantly so, where reported effects in the original studies were based on interventional rather than correlational designs. This trend only applied to hypothesized positive effects because none of the original studies in the meta-analyses related to hypothesized negative effects used interventional designs.

https://doi.org/10.1371/journal.pone.0263408.t003

In this systematic review of meta-analyses, we synthesized the available evidence regarding effects of sport psychology interventions/constructs on sport performance. We aimed to consolidate the literature, evaluate the potential for meta-analysis quality to influence the results, and suggest recommendations for future research at both the single study and quantitative review stages. During the systematic review process, several meta-analysis characteristics came to light, such as the number of meta-analyses of sport psychology interventions (experimental designs) compared to those summarizing the effects of psychological constructs (correlation designs) on performance, the number of meta-analyses with exclusively athletes as participants, and constructs featuring in multiple meta-analyses, some of which (e.g., cohesion) produced very different effect size values. Thus, although our overall aim was to evaluate the strength of the evidence base for use of psychological interventions in sport, we also discuss the impact of these meta-analysis characteristics on the reliability of the evidence.

When seen collectively, results of our review are supportive of using sport psychology techniques to help improve performance and confirm that variations in psychological constructs relate to variations in performance. For constructs hypothesized to have a positive effect on performance, the mean effect strength was moderate ( d = 0.51) although there was substantial variation between constructs. For example, the beneficial effects on performance of task cohesion ( d = 1.00) and self-efficacy ( d = 0.82) are large, and the available evidence base for use of mindfulness interventions suggests a very large beneficial effect on performance ( d = 1.35). Conversely, some hypothetically beneficial effects (2 of 36; 5.6%) were in the negligible-to-small range (0.15–0.20) and most beneficial effects (19 of 36; 52.8%) were in the small-to-moderate range (0.22–0.49). It should be noted that in the world of sport, especially at the elite level, even a small beneficial effect on performance derived from a psychological intervention may prove the difference between success and failure and hence small effects may be of great practical value. To put the scale of the benefits into perspective, an authoritative and extensively cited review of healthy eating and physical activity interventions [ 49 ] produced an overall pooled effect size of 0.31 (compared to 0.51 for our study), suggesting sport psychology interventions designed to improve performance are generally more effective than interventions designed to promote healthy living.

Among hypothetically negative effects (e.g., ego climate, cognitive anxiety, depression), the mean detrimental effect was small ( d = -0.21) although again substantial variation among constructs was evident. Some hypothetically negative constructs (5 of 24; 20.8%) were found to actually provide benefits to performance, albeit in the negligible range (0.02–0.12) and only two constructs (8.3%), both from Lochbaum and colleagues’ POMS meta-analysis [ 21 ], were shown to negatively affect performance above a moderate level (depression: d = -0.64; total mood disturbance, which incorporates the depression subscale: d = -0.84). Readers should note that the POMS and its derivatives assess six specific mood dimensions rather than the mood construct more broadly, and therefore results should not be extrapolated to other dimensions of mood [ 50 ].

Mean effects were larger among higher quality than lower quality meta-analyses for both hypothetically positive ( d = 0.54 vs d = 0.45) and negative effects ( d = -0.25 vs d = 0.17), but in neither case were the differences significant. It is reasonable to assume that the true effects were derived from the higher quality meta-analyses, although our conclusions remain the same regardless of study quality. Overall, our findings provide a more rigorous evidence base for the use of sport psychology techniques by practitioners than was previously available, representing a significant contribution to knowledge. Moreover, our systematic scrutiny of 30 meta-analyses published between 1983 and 2021 has facilitated a series of recommendations to improve the quality of future investigations in the sport psychology area.

Recommendations

The development of sport psychology as an academic discipline and area of professional practice relies on using evidence and theory to guide practice. Hence, a strong evidence base for the applied work of sport psychologists is of paramount importance. Although the beneficial effects of some sport psychology techniques are small, it is important to note the larger performance benefits for other techniques, which may be extremely meaningful for applied practice. Overall, however, especially given the heterogeneity of the observed effects, it would be wise for applied practitioners to avoid overpromising the benefits of sport psychology services to clients and perhaps underdelivering as a result [ 1 ].

The results of our systematic review can be used to generate recommendations for how the profession might conduct improved research to better inform applied practice. Much of the early research in sport psychology was exploratory and potential moderating variables were not always sufficiently controlled. Terry [ 51 ] outlined this in relation to the study of mood-performance relationships, identifying that physical and skills factors will very likely exert a greater influence on performance than psychological factors. Further, type of sport (e.g., individual vs. team), duration of activity (e.g., short vs. long duration), level of competition (e.g., elite vs. recreational), and performance measure (e.g., norm-referenced vs. self-referenced) have all been implicated as potential moderators of the relationship between psychological variables and sport performance [ 51 ]. To detect the relatively subtle effects of psychological effects on performance, research designs need to be sufficiently sensitive to such potential confounds. Several specific methodological issues are worth discussing.

The first issue relates to measurement. Investigating the strength of a relationship requires the measured variables to be valid, accurate and reliable. Psychological variables in the meta-analyses we reviewed relied primarily on self-report outcome measures. The accuracy of self-report data requires detailed inner knowledge of thoughts, emotions, and behavior. Research shows that the accuracy of self-report information is subject to substantial individual differences [ 52 , 53 ]. Therefore, self-report data, at best, are an estimate of the measure. Measurement issues are especially relevant to the assessment of performance, and considerable measurement variation was evident between meta-analyses. Some performance measures were more sensitive, especially those assessing physical performance relative to what is normal for the individual performer (i.e., self-referenced performance). Hence, having multiple baseline indicators of performance increases the probability of identifying genuine performance enhancement derived from a psychological intervention [ 54 ].

A second issue relates to clarifying the rationale for how and why specific psychological variables might influence performance. A comprehensive review of prerequisites and precursors of athletic talent [ 55 ] concluded that the superiority of Olympic champions over other elite athletes is determined in part by a range of psychological variables, including high intrinsic motivation, determination, dedication, persistence, and creativity, thereby identifying performance-related variables that might benefit from a psychological intervention. Identifying variables that influence the effectiveness of interventions is a challenging but essential issue for researchers seeking to control and assess factors that might influence results [ 49 ]. A key part of this process is to use theory to propose the mechanism(s) by which an intervention might affect performance and to hypothesize how large the effect might be.

A third issue relates to the characteristics of the research participants involved. Out of convenience, it is not uncommon for researchers to use undergraduate student participants for research projects, which may bias results and restrict the generalization of findings to the population of primary interest, often elite athletes. The level of training and physical conditioning of participants will clearly influence their performance. Highly trained athletes will typically make smaller gains in performance over time than novice athletes, due to a ceiling effect (i.e., they have less room for improvement). For example, consider runner A, who takes 20 minutes to run 5km one week but 19 minutes the next week, and Runner B who takes 30 minutes one week and 25 minutes the next. If we compare the two, Runner A runs faster than Runner B on both occasions, but Runner B improved more, so whose performance was better? If we also consider Runner C, a highly trained athlete with a personal best of 14 minutes, to run 1 minute quicker the following week would almost require a world record time, which is clearly unlikely. For this runner, an improvement of a few seconds would represent an excellent performance. Evidence shows that trained, highly motivated athletes may reach performance plateaus and as such are good candidates for psychological skills training. They are less likely to make performance gains due to increased training volume and therefore the impact of psychological skills interventions may emerge more clearly. Therefore, both test-retest and cross-sectional research designs should account for individual difference variables. Further, the range of individual difference factors will be context specific; for example, individual differences in strength will be more important in a study that uses weightlifting as the performance measure than one that uses darts as the performance measure, where individual differences in skill would be more important.

A fourth factor that has not been investigated extensively relates to the variables involved in learning sport psychology techniques. Techniques such as imagery, self-talk and goal setting all require cognitive processing and as such some people will learn them faster than others [ 56 ]. Further, some people are intuitive self-taught users of, for example, mood regulation strategies such as abdominal breathing or listening to music who, if recruited to participate in a study investigating the effects of learning such techniques on performance, would respond differently to novice users. Hence, a major challenge when testing the effects of a psychological intervention is to establish suitable controls. A traditional non-treatment group offers one option, but such an approach does not consider the influence of belief effects (i.e., placebo/nocebo), which can either add or detract from the effectiveness of performance interventions [ 57 ]. If an individual believes that, an intervention will be effective, this provides a motivating effect for engagement and so performance may improve via increased effort rather than the effect of the intervention per se.

When there are positive beliefs that an intervention will work, it becomes important to distinguish belief effects from the proposed mechanism through which the intervention should be successful. Research has shown that field studies often report larger effects than laboratory studies, a finding attributed to higher motivation among participants in field studies [ 58 ]. If participants are motivated to improve, being part of an active training condition should be associated with improved performance regardless of any intervention. In a large online study of over 44,000 participants, active training in sport psychology interventions was associated with improved performance, but only marginally more than for an active control condition [ 59 ]. The study involved 4-time Olympic champion Michael Johnson narrating both the intervention and active control using motivational encouragement in both conditions. Researchers should establish not only the expected size of an effect but also to specify and assess why the intervention worked. Where researchers report performance improvement, it is fundamental to explain the proposed mechanism by which performance was enhanced and to test the extent to which the improvement can be explained by the proposed mechanism(s).

Limitations

Systematic reviews are inherently limited by the quality of the primary studies included. Our review was also limited by the quality of the meta-analyses that had summarized the primary studies. We identified the following specific limitations; (1) only 12 meta-analyses summarized primary studies that were exclusively intervention-based, (2) the lack of detail regarding control groups in the intervention meta-analyses, (3) cross-sectional and correlation-based meta-analyses by definition do not test causation, and therefore provide limited direct evidence of the efficacy of interventions, (4) the extensive array of performance measures even within a single meta-analysis, (5) the absence of mechanistic explanations for the observed effects, and (6) an absence of detail across intervention-based meta-analyses regarding number of sessions, participants’ motivation to participate, level of expertise, and how the intervention was delivered. To ameliorate these concerns, we included a quality rating for all included meta-analyses. Having created higher and lower quality groups using a median split of quality ratings, we showed that effects were larger, although not significantly so, in the higher quality group of meta-analyses, all of which were published since 2015.

Conclusions

Journals are full of studies that investigate relationships between psychological variables and sport performance. Since 1983, researchers have utilized meta-analytic methods to summarize these single studies, and the pace is accelerating, with six relevant meta-analyses published since 2020. Unquestionably, sport psychology and performance research is fraught with limitations related to unsophisticated experimental designs. In our aggregation of the effect size values, most were small-to-moderate in meaningfulness with a handful of large values. Whether these moderate and large values could be replicated using more sophisticated research designs is unknown. We encourage use of improved research designs, at the minimum the use of control conditions. Likewise, we encourage researchers to adhere to meta-analytic guidelines such as PRISMA and for journals to insist on such adherence as a prerequisite for the acceptance of reviews. Although such guidelines can appear as a ‘painting by numbers’ approach, while reviewing the meta-analyses, we encountered difficulty in assessing and finding pertinent information for our study characteristics and quality ratings. In conclusion, much research exists in the form of quantitative reviews of studies published since 1934, almost 100 years after the very first publication about sport psychology and performance [ 2 ]. Sport psychology is now truly global in terms of academic pursuits and professional practice and the need for best practice information plus a strong evidence base for the efficacy of interventions is paramount. We should strive as a profession to research and provide best practices to athletes and the general community of those seeking performance improvements.

Supporting information

S1 checklist..

https://doi.org/10.1371/journal.pone.0263408.s001

Acknowledgments

We acknowledge the work of all academics since Koch in 1830 [ 2 ] for their efforts to research and promote the practice of applied sport psychology.

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Article contents

Motivation in sport and performance.

• Glyn C. Roberts , Glyn C. Roberts Department of Coaching and Psychology, Norwegian School of Sport Science
• Christina G. L. Nerstad Christina G. L. Nerstad Department of Public Administration and Leadership, Oslo Metropolitan University
•  and  P. Nicolas Lemyre P. Nicolas Lemyre Department of Coaching and Psychology, Norwegian School of Sport Science
• https://doi.org/10.1093/acrefore/9780190236557.013.150
• Published online: 30 July 2018

Motivation is the largest single topic in psychology, with at least 32 theories that attempt to explain why people are or are not motivated to achieve. Within sport psychology research, there are a plethora of techniques of how to increase and sustain motivation (strategies to enhance agency beliefs, self-regulation, goal setting, and others). However, when explaining the conceptual undergirding of motivation in sport, the why of motivation, two theories predominate: Achievement Goal Theory (AGT) and Self-Determination Theory (SDT). Both theories predict the same outcomes, such as increased achievement striving, sustained behavior change, and perceptions of well-being, but they differ in why those outcomes occur. AGT assumes that individuals cognitively evaluate the competence demands and meaningfulness of the activity, and that those perceptions govern behavior. SDT assumes that individuals are driven by three basic needs, competence, autonomy, and relatedness, and the satisfaction of those needs govern behavior. The following discusses both theories and concludes that each has their strengths and weaknesses.

• achievement orientations
• basic needs
• motivational climate
• behavior change
• Achievement Goal Theory
• Self-Determination Theory

Introduction

We can never have equality of achievement, but we can have equality of motivation : That was the mission of John Nicholls ( 1979 ). His goal was “equality of optimal motivation” (p. 1071) so that everyone should achieve the best that is possible for him or her to fulfill their potential. This enshrines the conceptual basis of enhancing motivation for sustained behavior change evident in the extant literature. For optimal motivation, it is argued that strategies need to be developed where individuals adopt and sustain achievement striving. Whether it is business leaders trying to motivate people in the workplace, the health industry trying to halt the rise in childhood obesity and sedentary lifestyles, parents and teachers bemoaning the study habits of children and adolescents, or coaches and administrators within the sport and performance communities wondering how to get better “results,” all are concerned with the issue of sustained motivated behavior.

How do we develop motivation for sustained striving? If we take our cues from everyday life, then it may be associated with arousal, such as the “motivational” tirades of coaches in the locker room. Former players of Manchester United Football Club have often remarked about the halftime locker room “hairdryer treatment” talks of the legendary coach of Manchester United Sir Alex Ferguson. Some believe it is a measure of confidence, a winning attitude that motivates one to better performance. Some believe it is a simple matter of positive thinking: Believe and you will achieve! Some believe it is a personal entity or is genetically endowed; you either “have it, or not”! However, these beliefs do not begin to capture the complexity and richness of contemporary motivational theory and research.

The term motivation is a very overused and vague term, especially in the “trenches”—the classroom, the gymnasium, the exercise room, the playing fields, the sport arenas, the workplace, etc. (e.g., Ford, 1992 ; Roberts, 2012 ; Roberts, Treasure, & Conroy, 2007 ). We have former successful sports stars, politicians, businesspeople who earn “big bucks” on the lecture circuit giving what are termed “motivational talks”! We have sports commentators and business correspondents who argue that the successful are more motivated to achieve than the unsuccessful. But their definitions and understanding of what motivation is differs. Even among motivation researchers, motivation is defined broadly by some, and narrowly by others, so that the term is useless as an organizing construct. Ford ( 1992 ) has argued that there are at least 32 theories of motivation that have their own definitions and explanations of the construct. In contemporary motivation research, because the term is so vague, the solution has been to abandon the term and use descriptions of cognitive processes such as self-regulation or other self-systems that affect motivational processes. However, the important assumption agreed to by most contemporary theorists is that motivation is not an entity but is a process (e.g., Maehr & Braskamp, 1986 ). Typically, motivation is the process that influences the initiation, direction, magnitude, perseverance, continuation, and quality of goal-directed behavior (Maehr & Zusho, 2009 ). To understand motivation, we must attempt to understand the process of motivation and the constructs that drive the process and how they apply to sustained behavior change.

The history of motivation theory has been the search for the overarching theory, and, as such, it was assumed that when that theory evolved, a whole range of achievement behaviors would not only be better understood, but intervention opportunities would also present themselves (Roberts, 1992 , 2012 ). Despite the efforts of many, and the arguments of some (e.g., Bandura, 1986 ), this overarching theory remains elusive and certainly not within our grasp yet. One of the reasons is that there is not universal agreement on how the psyche works to foster motivation. However, the search continues. There is excellent work in both sport and other achievement arenas that are ongoing in search of theoretical concepts and processes to understand and enhance achievement behaviors.

The study of motivation and its effect on achievement behavior is the investigation of the energization, direction, and regulation of behavior. Thus, while some avenues of research that describe the direction and/or the regulation of behavior without specifying why the behavior is energized are not “true” motivational theories, even though they may describe achievement behavior very well. Goal setting is such a case in sport and performance (e.g., Locke & Latham, 1985 ). Goal setting specifies the direction and regulation of achievement behavior, but to date there is no sufficient psychological explanation to explain why behavior from a goal-setting perspective is initiated (Hall & Kerr, 2001 ). Motivation theories are predicated upon a set of assumptions about individuals and about the factors that give impetus to achievement behavior (Roberts, 1992 ). Motivation theories ask why .

Typically, in the research literature pertaining to motivation in sport and performance, motivation theories refer to needs, dispositions, social variables, and/or cognitions that come into play when a person undertakes a task at which he or she is evaluated, enters into competition with others, or attempts to attain some standard of excellence. At such times, the individual is assumed to be responsible for the outcome of the task and that some level of challenge is inherent in the task. Moreover, such circumstances are assumed to facilitate various needs, motivational dispositions, and/or cognitive assessments that affect achievement striving. Specifically, it has been hypothesized that the energizing constructs of achievement behavior are basic needs, approach and/or avoidance dispositions, expectancies, incentive values of success and failure, and/or cognitive assessments of what it takes to achieve success and/or avoid failure.

Understanding the Process of Motivation

Motivation theories are on a continuum ranging from deterministic to mechanistic to organismic to cognitive (for a more extensive treatment of motivation theories, see Ford, 1992 ). Deterministic and mechanistic theories view humans as being passive, at least partially, and driven by psychological needs and/or drives. Organismic theories include innate needs but also recognize that a dialectic occurs between the organism and the social context. Social cognitive theories view humans as being active and initiating action through subjective interpretation of the achievement context. When motivation matters, theoretical models governing motivation and achievement behavior abound. There is no shortage of theories! However, since the late 1970s, theories that encompass social cognitive dynamics have dominated the research literature.

Weiner ( 1972 ) signaled the beginning of the cognitive revolution by arguing that individuals who were high or low in motivation were likely to think differently about why success and failure occurred. The notion that thoughts, rather than needs or drives, were the critical variables transformed the study of motivation. As Harwood, Spray, and Keegan ( 2008 ) stated, the development of social cognitive theories has been a watershed for our understanding of sport achievement behavior. Harwood and colleagues continue to state that achievement goal theory, in particular, has “triggered a penetrating wave of research into the interpersonal and environmental influences on athlete behavior in achievement settings” (p. 158). The majority of motivation research in sport performance contexts over the past 40 years has adopted a social cognitive approach, at least partially. The most popular contemporary theories in sport psychology tend to be based on organismic (e.g., Self-Determination theory, Deci & Ryan, 1985 ; Hierarchical goal model, Elliot, 1999 ) or social cognitive criteria (e.g., Achievement Goal Theory, Nicholls, 1989 ) and are based on the more dynamic and sophisticated conceptions that assume the human is an active participant in decision making and in planning achievement.

We have confined our review to include only the most important theories for sport and performance. It may be debated whether we have included all of the important theories. However, even a cursory review of the motivation literature in sport immediately reveals that the most cited theories are Achievement Goal Theory (e.g., Dweck, 2006 ; Nicholls, 1989 ) and Self-Determination Theory (e.g., Deci & Ryan, 1985 ). These are the most used theories in the sport and performance arena. Thus, for sport performance, we take a critical eye to Self-Determination Theory (SDT) (e.g., Ntoumanis, 2012 ; Standage & Ryan, 2012 ) and Achievement Goal Theory (AGT) (e.g., Duda, 2001 ; Roberts, 2001 , 2012 ) and their principal advocates.

We will discuss each theory in turn and identify the process of motivation within each, and we will briefly cite the research in sport and performance to support the basic tenets and findings. Then we will discuss the similarities and differences of each theory and conclude with a series of suggestions for future research in sport and performance contexts.

The Theories

First, we will discuss AGT in its various guises.

Achievement Goal Theory and Research

The history and development of AGT in sport has been reviewed in several recent publications (e.g., Duda, 2005 ; Duda & Hall, 2001 ; Harwood et al., 2008 ; Lochbaum, Kazak Cetinkalp, Graham, Wright, & Zazo, 2016 ; Roberts, 2012 ; Roberts Treasure, & Conroy, 2007 ). We will not exhaustively review the literature in the present article, rather we will focus on identifying key constructs, tenets, and constraints to the theory; review the basic conceptual infrastructure and empirical support; and present recent proposals for expanding and/or restructuring the approach, with some rebuttals and counterpoints! AGT is a social cognitive theory that assumes that the individual is an intentional, rational, goal-directed organism and that achievement goals govern achievement beliefs and guide subsequent decision making and behavior in achievement contexts. It is these goals that reflect the purposes of achievement striving. Once adopted, the achievement goal determines the integrated pattern of beliefs that energize approach and avoid strategies, the differing engagement levels, and the differing responses to achievement outcomes. Goals are what give an activity purpose or meaning (Kaplan & Maehr, 2007 ; Maehr & Nicholls, 1980 ). By recognizing the importance of the meaning of behavior, it becomes clear that there may be multiple goals of action, not one (Maehr & Braskamp, 1986 ). Thus, an individual’s investment of personal resources such as effort, talent, and time in an activity is dependent on the achievement goal of the individual.

The overall goal of action in AGT, thereby becoming the conceptual energizing force, is the desire to develop and demonstrate competence and to avoid demonstrating incompetence in an achievement context (Nicholls, 1984 ). However, competence has more than one meaning. Based on previous research on learned helplessness (Dweck, 1975 ), cooperation/competition (Ames, 1984 ), and his own work on children’s understanding of the concepts of effort and ability ( 1976 ), Nicholls’s conceptual contribution was to argue that more than one conception of ability exists, and that achievement goals and behavior may differ depending on the conception of ability held by the person. Two conceptions of ability (at least) manifest themselves in achievement contexts, namely an undifferentiated concept of ability , where ability and effort are not differentiated by the individual; and a differentiated concept of ability , where ability and effort are differentiated (Nicholls, 1984 , 1989 ).

Nicholls ( 1978 , 1989 ) argued that children originally possess an undifferentiated conception of ability and associate ability with learning through effort so that the more effort one puts forth, the more learning (and ability) one achieves. Following a series of experiments, Nicholls ( 1978 ; Nicholls & Miller, 1983 , 1984 ) determined that by the age of 12, children are able to differentiate luck, task difficulty, and effort from ability, enabling a differentiated perspective. When utilizing this differentiated perspective, children begin to see ability as capacity and that the demonstration of competence involves outperforming others. In terms of effort, high ability is inferred when outperforming others and expending equal or less effort or performing equal to others while expending less effort.

An individual will approach a task or activity with certain goals of action reflecting their personal perceptions and beliefs about the form of ability they wish to demonstrate (Nicholls, 1984 , 1989 ). They interpret their performance in terms of these perceptions and beliefs and form a personal theory of achievement at the activity (Nicholls, 1989 ) that reflects the individual’s perception of how things work in achievement situations. The adopted personal theory of achievement (Dweck, 2006 , terms this as an implicit person theory ) affects one’s beliefs about how to achieve success and avoid failure at the activity. Therefore, based on their personal theory of achievement, people will differ in which of the conceptions of ability and criteria of success and failure they use.

State of Involvement

The two conceptions of ability thereby become the source of the criteria by which individuals assess success and failure. The goals of action are to meet the criteria. Nicholls ( 1989 ) identifies achievement behavior utilizing the undifferentiated conception of ability as being task involved and achievement behavior utilizing the differentiated conception of ability as being ego involved .

When task involved, the goal of action is to develop mastery, improvement, or learning; and the demonstration of ability is self-referenced, internal, and autonomous. Success is realized when mastery or improvement is attained. Perceived ability becomes less relevant as the individual is trying to demonstrate or develop mastery at the task rather than demonstrate normative ability. The achievement behaviors are adaptive in that the individual is more likely to persist in the face of failure, to exert effort, select challenging tasks, and be intrinsically interested in the task (e.g., Duda & Hall, 2001 ; Nicholls, 1989 ; Roberts, 2012 ).

When ego involved, the goal of action is to demonstrate ability relative to others, or to outperform others, making ability other referenced and external. Success is realized when the performance of others is exceeded, especially when expending less effort (Nicholls, 1984 , 1989 ). Perceived ability is relevant as the individual is trying to demonstrate normative ability, or avoid demonstrating inability, to determine how his/her ability fares with comparative others. These people seek competitive contests and want to demonstrate superiority. When perceived ability is high, demonstrating high-normative ability is likely; therefore, the individual is motivated to persist and demonstrate that competence to pertinent others. The ego-involved person is inclined to use the least amount of effort to realize the goal of action (Nicholls, 1989 ). If the perception of ability is low, then the individual recognizes that ability is unlikely to be demonstrated, and he/she manifests maladaptive achievement behaviors because he/she wishes to avoid demonstrating incompetence (Nicholls, 1989 ). Maladaptive behaviors are avoiding the task; avoiding challenge; reducing persistence in the face of difficulty; exerting little effort; and, in sport, even dropping out if achievement of the desired goal appears difficult. These people avoid competitive contests, as their lack of competence may be exposed. While the participant may view these avoidance behaviors as adaptive, because a lack of ability is disguised, they are considered maladaptive in terms of achievement behavior.

One of the most important tenets of AGT is that the states of involvement are mutually exclusive (e.g., Nicholls, 1989 ; Treasure et al., 2001 ). One is either ego or task involved. One’s state of motivational involvement ranges on a continuum from task to ego involvement. The goal state is very dynamic and can change from moment to moment as information is processed (Gernigon, d’Arippe-Longueville, Delignières, & Ninot, 2004 ). An athlete may begin a task with strong task-involved motivation, but contextual events may make the athlete wish to demonstrate superiority to others, and the athlete becomes ego involved in the task (as an example, when a coach publicly highlights a mistake). Similarly, an athlete may begin a competitive event with a strong ego-involved state of involvement, but as the event unfolds, the athlete may realize he or she will win easily (or lose emphatically) and therefore begin to work on mastery criteria instead and become task involved. Thus, goal states are dynamic and ebb and flow depending on the perception of the athlete.

In this article, when we refer to the motivated state of involvement of the individual, we use the terms ego and task involvement to be consistent with Nicholls’s use of the terms. However, other theorists use different terms such as mastery and performance (e.g., Ames, 1992a ; Dweck, 1986 ). In addition, when we refer to individual dispositions, we use the terms task and ego orientation to be consistent with Nicholls. Again, other motivation theorists (e.g., Dweck, 1986 , 2006 ; Elliot, 1999 ; Maehr & Braskamp, 1986 ) have used different terms (e.g., self-schemas, personal theories of achievement, implicit personal theories, personal investment) to describe the same phenomena.

Goal Orientations, an Individual Difference Variable

When individuals are predisposed (e.g., through their personal theory of achievement) to act in an ego- or task-involved manner, these predispositions are called achievement goal orientations . Individual differences in the disposition to be ego or task involved may be the result of socialization through task or ego-involving contexts in the home or other significant achievement contexts (e.g., classrooms, sport). The way Elliott and Dweck ( 1988 ) explain it is that each of the achievement goals runs off a different “program with different commands, decision rules, and inference rules, and hence, with different cognitive, affective, and behavioral consequences. Each goal, in a sense, creates and organizes its own world—each evoking different thoughts and emotions and calling forth different behaviors” (p. 11).

Goal orientations are not “traits” or based on needs. They are cognitive schemas that are dynamic and subject to change as information pertaining to one’s performance on the task is processed. The orientations have some stability over time and are relatively enduring in sport (Duda & Whitehead, 1998 ; Roberts, Treasure, & Balague, 1998 ). Thus, being task or ego oriented refers to the inclination of the individual to be task or ego involved in sport.

The important attribute of achievement goal orientations is that they are orthogonal and independent. One can be high or low in each or both orientations at the same time. Based on developmental research with children, Nicholls ( 1989 ) concluded that by the age of 12, it is possible for an individual to be high or low in both task and ego goal orientation, or high in one and low in the other. In the sport and exercise literature, this orthogonality has been supported (e.g., Duda, 2001 ; Lemyre, Roberts, & Ommundsen, 2002 ; Lochbaum et al., 2016 ; Pensgaard & Roberts, 2000 ; Roberts, Treasure, & Kavussanu, 1996 ; Walling & Duda, 1995 ). For qualitative reviews, see Duda and Whitehead ( 1998 ), and Roberts ( 2012 ) and colleagues (Roberts, Treasure, & Kavussanu, 1997 ; Roberts, Treasure, & Conroy, 2007 ).

The implications of the orthogonality of goal orientations are important. The research evidence in sport suggests that individuals with high task and high ego or high task and low ego orientations have the most adaptive motivational profiles (e.g., Fox, Goudas, Biddle, Duda, & Armstrong, 1994 ; Hodge & Petlichkoff, 2000 ; Pensgaard & Roberts, 2002 ; Roberts, Treasure, & Kavussanu, 1996 ; Smith, Balaguer, & Duda, 2006 ). As one would expect, when an individual has been high in ego and low in task, or high in task and low in ego, then the findings are consistent with the findings reported above for task and ego orientation (task orientation is adaptive; ego orientation, especially when coupled with low perception of competence, is generally maladaptive). However, we find that high ego orientation when coupled with high (or moderate) task orientation is not maladaptive (e.g., Cumming, Hall, Harwood, & Gammage, 2002 ; Harwood, Cumming, & Fletcher, 2004 ; Pensgaard & Roberts, 2002 ; Smith et al., 2006 ; Wang & Biddle, 2001 ). Therefore, rather than focusing on whether an individual is task or ego oriented, it is important to consider the simultaneous combination of task and ego orientation (Kaplan & Maehr, 2007 ; Roberts et al., 2007 ).

The Research Evidence

Two strategies are used to determine the goal orientation profiles (high in each, high in one and low in the other, and low in each). One strategy has been to create the four profile groups through a mean or median split of the task and ego scores (e.g., Fox et al., 1994 ; Roberts et al., 1996 ). A weakness of this approach is that individuals may be misclassified. An alternative is to use cluster analysis to obtain the goal profiles (e.g., Hodge & Petlichkoff, 2000 ). Researchers in sport have used cluster analysis (Hair, Anderson, Tatham, & Black, 1998 ) to investigate goal orientations and in general have supported the use of cluster analysis to produce the goal orientation profiles (e.g., Cumming et al., 2002 ; Harwood et al., 2004 ; Hodge & Petlichkoff, 2000 ; Smith et al., 2006 ; Wang & Biddle, 2001 ). The clusters have varied across these studies, but importantly, participants with high ego/high task and high task/moderate or low in ego goal orientations have consistently reported more desirable responses on the variables under study (e.g., greater imagery use, more physical activity, higher self-determination, better social relationships). Thus, the motivational implications of the orthogonality of goals are a very important attribute of AGT.

Elite athletes are likely to be high task and high ego (e.g., Pensgaard & Roberts, 2000 ) or high ego and low or moderate in task orientation. In sport, the individuals most at risk are the high ego and low task oriented. These are the people most likely to exhibit maladaptive motivation, drop out, and are the athletes most likely to burn out when they believe they cannot demonstrate competence (Lemyre, Roberts, & Stray-Gundersen, 2007 ). The low ego and low task people are the least motivated, and they may not even commit to achievement tasks. The important issue in the present discussion is that the orthogonality of the goal orientations has been demonstrated quite conclusively (see Lochbaum et al., 2016 ), and the orthogonality of the goals is an important factor determining sustained motivated behavior in sport. The avenue of research related to achievement goals in the context of sport and performance has demonstrated that individual differences in goal orientations are associated with different motivational processes and different achievement behaviors (e.g., Lemyre et al., 2007 ). In comprehensive previous reviews, the hypotheses pertinent to the goal orientations are consistently supported (e.g., Duda, 2001 ; Duda & Hall, 2001 ; Lochbaum et al., 2016 ; Roberts, 2001 , 2012 ). Task orientation is associated with adaptive achievement strategies, positive affect, well-being, less cheating, better performance, and intrinsic forms of motivation. Ego orientation is associated with maladaptive achievement strategies, negative affect, ill-being, and extrinsic forms of motivation.

Goal Orientations and Mindsets

Dweck ( 2012 ) differs from Nicholls somewhat in that she argues that one’s personal theory of motivation gives rise to implicit theories about how things work in achievement settings. Dweck ( 2000 ) agrees with Nicholls ( 1989 ) that there exist specific individual difference variables that stimulate the pursuit of different goals; such variables are implicit person theories (IPTs). These theories reflect beliefs individuals have about themselves and their assumptions about the plasticity of personal characteristics such as personality, abilities (e.g., athletic), and intelligence, which guides human behavior (Dweck, 1986 ). Because they are not explicitly enunciated in the mind of the individual holding them, these person theories are typically referred to as implicit (Burnette, O’Boyle, VanEpps, Pollack, & Finkel, 2013 ). Thus, IPTs portray schematic knowledge structures that include beliefs about the stability of a characteristic, which in turn classifies the way individuals assign meanings to various occasions (Burnette et al., 2013 ; Ross, 1989 ). According to Dweck ( 1986 , 2012 ), there are two such IPTs. An entity IPT, also referred to as a fixed mindset , assumes that personal attributes are entities that reside within individuals and cannot be changed much over time (Dweck, 2000 , 2012 ). Thus, a so-called entity theorist believes that individuals have given abilities that cannot really be changed or developed (Dweck, 2006 ).

On the other hand, incremental IPT, also referred to as a growth mindset , assumes that personal attributes are relatively changeable (Dweck, 1999 ). Thus, individuals with a growth mindset, also called incremental theorists, believe that with effort, guidance, and effective strategies, all individuals can develop and increase their abilities over time (Dweck, 1999 , 2006 ).

The two mindsets are operationalized in such a manner that individuals lie somewhere along a continuum between the fixed and growth mindset prototypes; thus, one of the implicit theories is likely to be dominant (Heslin & Vandewalle, 2008 ; Spray, Wang, Biddle, Chatzisarantis, & Warburton, 2006 ). Still, it should be noted that it may be possible and beneficial for individuals to hold a combination of both growth and fixed mindsets (Dweck & Leggett, 1988 ; Harwood, Spray, & Keegan, 2008 ): That is, when present differences in relative ability are recognized, but blended with an emphasis on individual growth in ability (Dweck & Elliot, 1983 ; Dweck & Leggett, 1988 ). Sport psychological research has provided support for this suggestion given the typically negative, but weak, relationship between higher-ordered growth and fixed mindset dimensions (Biddle, Wang, Chatzisarantis, & Spray, 2003 ; Spray et al., 2006 ; Wang, Woon, Biddle, & Spray, 2005 ).

The IPTs (or mindsets) are relatively stable dispositions, and empirical evidence supports such a conceptualization (Dweck, 1999 ; Dweck, Chiu, & Hong, 1995 ; Dweck & Leggett, 1988 ). However, there is also empirical evidence indicating that IPTs may be modified through interventions where changes in IPTs and behavior have been found to sustain for periods of six to nine weeks (e.g., Aronson, Fried, & Good, 2002 ; Heslin, Latham, & Vandewalle, 2005 ).

IPTs (or mindsets) have been studied comprehensively in the educational achievement domain typically with experimental designs, although scholars have extended the IPT applicability to other domains such as work (Heslin & Vandewalle, 2008 ) and sport/physical education (Ommundsen, 2003 ; Spray et al., 2006 ). Accordingly mindsets have been shown to be important for success in various domains such as physical and emotional health, in social relationships, in academics, and in the workplace (Dweck, 2012 ). In sport, existing research has mainly been conducted with student participants, and thus IPTs have typically been measured with reference to physical education and sport where the majority of studies have been cross-sectional (Harwood et al., 2008 ), with a few exceptions (e.g., Spray et al., 2006 ). In the next paragraph, we will briefly present the main findings from various achievement domains, focusing on sport, physical education, and education.

Research based on diverse populations suggests that individuals can hold different IPTs in different domains such as in sport or schoolwork; growth and fixed mindsets are endorsed approximately equally; further, IPTs are generally uncorrelated with the Big Five trait dimensions, cognitive complexity, self-esteem, and education (Burnette et al., 2013 ). IPTs have previously been linked to self-regulatory processes such as social comparison, selective information attention, goal setting, and overcoming stereotype threat (Aronson et al., 2002 ; Mangels, Butterfield, Lamb, Good, & Dweck, 2006 ; Nussbaum & Dweck, 2008 ; Robins & Pals, 2002 ). In the sport domain, a fixed mindset of ability has been associated with self-reported amotivation, increased levels of anxiety, reduced levels of satisfaction, more acceptance of cheating behavior that was partly mediated by approach, and avoidance-performance goal orientation. On the other hand, a growth mindset predicts positively enjoyment, satisfaction, and reduced acceptance of cheating behavior through perceptions of approach and avoidance-mastery goal orientation (Biddle et al., 2003 ; Corrion et al., 2010 ; Ommundsen, 2001c ).

Based on an experimental design, Cury, Da Fonséca, Zahn, and Elliot ( 2008 ) found that a fixed mindset has a detrimental influence on performance. Specifically, holding a fixed mindset facilitated concerns about the implications of failure. Such worry further led to decreased practice that directly undermined performance. This finding aligns with several other studies suggesting that individuals with a growth mindset perform better on various tasks (e.g., Aronson et al., 2002 ; Blackwell, Trzesniewski, & Dweck, 2007 ; Mangels et al., 2006 ; Moser, Schroder, Heeter, Moran, & Lee, 2011 ; Paunesku et al., 2015 ).

IPTs and Goal Orientation

According to Dweck ( 1986 , 1999 ), individuals have different goals in achievement situations, and these goals have their basis in the individuals’ IPTs. Dweck’s approach to goal orientations may be referred to as a person-oriented approach, where personality plays a major role in goal adoption (Maehr & Zusho, 2009 ). Specifically, Dweck and Leggett ( 1988 ) argue that goal orientations have their basis in the individuals’ IPTs, although they may be responsive to change (e.g., Aronson et al., 2002 ; Paunesku et al., 2015 ; Spray et al., 2006 ).

The goals, which Dweck terms either performance or mastery goals, that individuals adopt help create mastery-oriented or helpless responses (Dweck, 1999 ). Individuals with a growth mindset view their ability as something they can improve over time and are thus more likely to adopt mastery goals (Dweck, 1999 ; Dweck & Leggett, 1988 ; Payne, Youngcourt, & Beaubien, 2007 ). Conversely, individuals with a fixed mindset are more likely to endorse performance goals (ability judgments), which creates vulnerability to a helpless pattern of behavior, particularly when their perceived ability is low (Dweck & Leggett, 1988 ; Maehr & Zusho, 2009 ). When helpless, individuals may attribute their failures to personal inadequacy, deficient abilities, or intelligence, and they experience negative affect (Dweck, 1999 ; Dweck & Leggett, 1988 ). Given that mastery goals concern mastery of new things, such as a new technical skill in ski jumping, growth mindset individuals respond to difficult problem solving with a clear mastery-oriented pattern (Elliott & Dweck, 1988 ). This was evident even when facing failure, where individuals managed to continue their focus on the task and how to solve it.

Fixed mindset individuals show a clear helpless pattern in response to difficult problem solving, especially when failing. In sport and physical education research, similar empirical evidence has emerged where a fixed mindset predicts performance goals while a growth mindset predicts mastery goals (e.g., Biddle, Seos, & Chatzisarantis, 1999 ; Biddle et al., 2003 ; Cury, Da Fonséca, Rufo, & Sarrazin, 2002 ; Ommundsen, 2001a , 2001b ; Spray et al., 2006 ). A meta-analysis of the goal orientation nomological net also found support for Dweck’s ( 1986 , 1999 ) predictions that a fixed mindset is negatively correlated with a mastery orientation and positively correlated with performance orientation (Payne et al., 2007 ). However the effect sizes were very small, indicating limited evidence for Dweck’s ( 1986 ) propositions of IPTs being the primary underlying antecedents of goal orientations.

However, a more recent meta-analysis (Burnette et al., 2013 ) including 28,217 respondents from various achievement domains (68% academic), representing 10 different nations covered in 113 different studies, investigated the relationship between IPTs and self-regulation. The results revealed that IPTs predicted distinct self-regulatory processes (performance and mastery orientation, helpless and mastery strategies, negative emotions, and expectations), which in turn predicted goal achievement. The results indicated that a growth mindset significantly and negatively predicted performance orientation, positively predicted mastery orientation, negatively predicted helpless strategies, positively predicted mastery-oriented strategies, negatively predicted negative emotions, and positively predicted expectations. The effects on goal orientation and helpless/mastery strategies were even stronger in the absence versus presence of ego threats such as failure feedback (Burnette et al., 2013 ). These findings lend additional support for Dweck’s initial propositions that IPTs are important predictors of individual goal orientation.

The Re-Introduction of Approach and Avoid Goals

A provocative theory challenging AGT has emerged from work on the hierarchical model of achievement motivation (e.g., Elliot, 1999 ; Elliot & Conroy, 2005 ). The hierarchical model claims to revise and extend AGT. The theory is based on the premise that approach and avoidance motivation are also important in considering achievement striving. Briefly, the hierarchical model of achievement motivation asserts that the dynamic states of involvement are influenced by both the definition of competence and the valence of the goals.

The arguments are similar to arguments made within Need Achievement Theory and research relative to approach success and avoid failure dispositions (e.g., Atkinson & Feather, 1966 ). Contemporary researchers suggest that an approach and an avoid motivation exist (e.g., Elliot, 1997 ; Elliot & Harackiewicz, 1996 ; Middleton & Midgley, 1997 ; Skaalvik, 1997 ) and that individuals strive to be competent (an appetitive or approach valence) or strive to avoid appearing incompetent (an aversive or avoid valence). Thus, it is possible to differentiate goals based on their valence or the degree to which the focal outcome is pleasant or unpleasant.

In reviewing the achievement goal literature, Elliot ( 1994 ) observed that performance goals that focus on the pleasant possibility of demonstrating competence (approach goals) lead to different outcomes than performance goals focused on the unpleasant possibility of demonstrating incompetence (avoidance goals). Performance-avoidance goals reduce both free-choice behavior and self-reported interest in a task, whereas performance-approach goals did not have any consistent effect on intrinsic motivation indices (Rawsthorne & Elliot, 1999 ). This finding led to the introduction of a tripartite model of achievement goals comprising mastery, performance-approach, and performance-avoidance goals (Elliot & Harackiewicz, 1996 ). Following a series of studies by Cury and colleagues (e.g., Cury, Elliot, Sarrazin, Da Fonséca, & Rufo, 2002 ; Cury et al., 2002 ; Cury, Da Fonséca, et al., 2003 ), the model expanded to include a fourth possible achievement goal: mastery-avoidance goal (e.g., Elliot & Conroy, 2005 ). Thus, the argument was proffered that achievement goals should consider both the definition of competence and the valence of the striving . The model now became 2 by 2 with two definitions of competence (mastery vs. performance) and two valences of striving (approaching competence vs. avoiding incompetence) (see Papaioannou, Ziurbanos, Krommidas & Ampatatzoglou, 2012 ; Roberts et al., 2007 ).

The introduction of the hierarchical model has challenged many of the tenets and underlying assumptions of traditional AGT. In particular, it expanded the mastery and performance dichotomy to expand the theory from two goals to four goals. A body of evidence has accumulated to support these assertions, and some argue that the new model is a “better” theory to explain motivated behavior (e.g., Elliot & Conroy, 2005 ). However, the extension is criticized in that it violates some of the basic tenets of AGT (e.g., it negates the orthogonality of orientations) and adds little conceptual understanding to the motivational equation (e.g., Maehr & Zusho, 2009 ; Roberts, 2012 ) and undermines the parsimony and elegance of AGT.

It is not the only source of criticism of the traditional model, or the only expansion of the number of goals. AGT has had strong criticism from Harwood and colleagues (e.g., Harwood, Hardy, & Swain, 2000 ; Harwood & Hardy, 2001 ; Harwood et al., 2008 ) who raise what they term as conceptual and methodological issues. Others have argued for multiple goals, such as process, performance, and outcome goals (e.g., Burton & Weiss, 2008 ; Gould, 2010 ; Hardy, Jones, & Gould, 1996 ; Kingston & Wilson, 2009 ). Harwood and colleagues also argue for multiple states of task involvement and multiple goals (e.g., Harwood et al., 2008 ). Initially, Harwood and colleagues argued that achievement goal theory was not as useful in sport as in education, and they argued that task involvement, as a state, did not exist in sport because of the ego-involving nature of the sport experience: The goal pertinent to sport was termed “self-referenced ego involvement” (Harwood et al., 2000 , p. 244). They proposed that there were three states of involvement that were termed task involvement, self-referenced ego involvement, and norm-referenced ego involvement. This argument was strongly rebutted by Treasure and colleagues (Treasure et al., 2001 ) where the conceptual logic behind the multiple states of involvement was seriously questioned. However, it is for the reader to read the articles and decide for himself or herself.

The above documents the various approaches to arguing for the emergence of goal orientations within AGT. However, the approaches all agree that a personal theory of motivation, an implicit theory, or valence determine the goal orientation (task or ego, mastery or performance) of the individual. The orientation, in turn, determines the state of involvement (task or ego) of the individual.

The Motivational Climate: Mastery and Performance Criteria

One of the most powerful aspects of AGT is that it incorporates not only the individual difference variables of task and ego orientations, growth and entity orientations, but also the situational determinants of task and ego involvement. The situation plays a central role in the motivation process (Ames, 1992a , 1992b , 1992c ; Nicholls, 1984 , 1989 ). Consistent with other motivation research that has emphasized the situational determinants of behavior (e.g., Ames, 1984 ; deCharms, 1976 , 1984 ; Dweck, 2006 ), research within AGT has examined how the structure of the environment can make it more or less likely that an individual will become task or ego involved. The premise of this line of research is that the individual perceives the degree to which task and ego criteria are salient within the context. Through their perception of the criteria inherent in the context and the behaviors necessary to achieve success and/or avoid failure, this affects the achievement behaviors, cognition, and affective responses of individuals (Ames, 1992b ; Roberts, Treasure, & Conroy, 2007 ; Roberts, Treasure, & Kavussanu, 1997 ). When we refer to the achievement cues within the context, the schemas emerging from achievement situations, we will be consistent with Ames and refer to the task-involving aspect of the context as mastery criteria and the ego-involving aspect of the context as performance criteria.

The premise of the research from a situational perspective is that the nature of an individual’s experiences and how he/she interprets these experiences influence the degree to which a mastery and/or a performance set of criteria to achieve success is perceived as salient. A performance climate is created when the criteria of success and failure are other referenced and ego involving (Ames, 1992b ), and the athlete perceives that the demonstration of normative ability is valued. A mastery climate is created when the criteria of success and failure are self-referenced and task involving (Ames, 1992b ), and the athlete perceives that the demonstration of mastery and learning are valued. This is assumed to affect an individual’s interpretation of the criteria of success and failure extant in the context and to affect achievement behavior. The individual will adopt adaptive achievement strategies (namely, to work hard, seek challenging tasks, persist in the face of difficulty) in the climate in which he or she feels comfortable. For most people, and especially children, this is in the climate that emphasizes mastery (e.g., Biddle, 2001 ; Roberts, Treasure, & Conroy, 2007 ; Roberts, Treasure, & Kavussanu, 1997 ; Treasure, 1997 , 2001 ). In mastery-oriented situations, an individual is assumed to adopt adaptive achievement strategies such as working hard, seeking challenging tasks, and persisting in the face of difficulty (Harwood et al., 2015 ; Roberts, 2012 ). Certainly, the extant research supports that assumption (e.g., Treasure, 2001 ). However, we must not forget that some people function well in a performance climate. These are people who are high in perceived competence at the activity and who wish to demonstrate their competence and enjoy demonstrating superiority to others. As long as the perception of high ability lasts, these people seek challenging tasks and revel in demonstrating their ability. But as soon as the perception of ability wavers, because of age, injury, or an individual enters into a more elite context, then these people are likely to adopt maladaptive achievement strategies (namely, to seek easy tasks, reduce effort, or give up in the face of difficulty).

The extant literature in sport suggests that the creation of a mastery motivational climate is likely to be important in optimizing positive (i.e., well-being, sportsmanship, persistence, task perseverance, adaptive achievement strategies) and attenuating negative (i.e., overtraining, self-handicapping, stress responses, burning-out, cheating) attributes (e.g., Fry & Gano-Overway, 2010 ; Iwasaki & Fry, 2016 ; Kuczka & Treasure, 2005 ; Miller et al., 2004 ; Ommundsen & Roberts, 1999 ; Sarrazin, Roberts, Cury, Biddle, & Famose, 2002 ; Standage, Duda, & Ntoumanis, 2003 ; Standage, Treasure, Hooper, & Kuczka, 2007 ; Treasure & Roberts, 2001 ; Wilhelmsen, Sorensen, & Seippel, in press ). This pattern of findings has been confirmed in a comprehensive qualitative and quantitative review using 104 studies (n=34,156) that found that perceptions of a mastery climate were associated with adaptive motivational outcomes including perceived competence, self-esteem, objective performance improvement, intrinsic motivation, positive affective states, experienced flow, and were less likely to cheat (Harwood et al., 2015 ). Conversely, perceptions of a performance climate were associated with extrinsic motivation, negative affective states, maladaptive performance strategies, perfectionism, and likelihood to cheat. The extant evidence, therefore, supports the position that perceptions of a mastery motivational climate are associated with more adaptive motivational and affective response patterns than perceptions of a performance climate in the context of sport engagement.

For the purposes of the present discussion, it is well to realize that dispositional goal orientations and perceptions of the climate are two independent dimensions of motivation within AGT that interact to affect behavior (Nicholls, 1989 ). But the powerful and parsimonious aspect of AGT is that both the individual dispositions and the perception of the motivational climate are encompassed by the theory. It is true that research to date primarily deals with dispositional goal orientations and perceptions of the motivational climate as separate constructs in isolation to each other (e.g., Harwood et al., 2015 ; Lochbaum et al., 2016 ). It has been suggested that an interactionist approach that looks to combine both variables promises to provide a more complete understanding of achievement behaviors in the sport and physical education experience (e.g., Duda, Chi, Newton, Walling, & Catley, 1995 ; Papaioannou, 1994 ; Roberts, 1992 , 2012 ; Roberts & Treasure, 1992 ; Roberts et al., 2007 ; Roberts, Treasure, & Kavussanu, 1997 ; Treasure, 2001 ).

In a qualitative review, Roberts ( 2012 ) argued that instead of looking at achievement goals and the motivational climate separately, as is the custom, AGT should focus on an integrated perspective because dispositional goal orientations and the perceived motivational climate are part of the same theoretical platform and that the energizing force for motivated behavior is the resultant state of involvement. It supports meaningful relationships between personal goals of achievement and/or the perceived criteria of success and failure in the motivational climate with cognitive and affective beliefs about involvement in physical activity, as well as achievement striving.

However, there are few studies that have investigated the interactive effect of both the goal orientations and the motivational climate within the same study. One exception is a recent study investigating the perceived physical and pedagogical inclusion of disabled students in physical education. Wilhelmsen and colleagues ( in press ) found that to feel socially and physically included it is important to have a high mastery climate and a low performance climate. In addition, the children felt more social and pedagogical inclusion when high in task and ego orientation, or high in task orientation, but only when in a mastery climate. Another exception is a study conducted by Cury and colleagues (Cury, Biddle, Famose, Goudas, Sarrazin & Durand, 1996 ). In this study, the researchers utilized structural equation modeling (SEM) to examine the interest of adolescent girls in physical education. The researchers conclude by suggesting that their findings support the positive effects of a mastery-oriented motivational climate in physical education and offer evidence of a possible shaping effect of the climate on an individual’s goal orientation. This has been supported in more recent studies (e.g., Iwasaki & Fry, 2016 ).

SEM and multilevel SEM may be appropriate techniques to examine potential relationships among achievement goals and perceptions of the motivational climate, including the testing of interactive effects (e.g., Preacher, Zyphur, & Zhang, 2016 ). Particularly the multilevel SEM approach may provide some interesting insights into how goal orientations and the motivational climate may interplay by simultaneously accounting for the individual and group level of analysis (cf. Lam, Ruzek, Schenke, Conley, & Karabenick, 2015 ).

Research has found interesting relationships between orientations and the climate (e.g., Swain & Harwood, 1996 ; Treasure & Roberts, 1998 ; Wilhelmsen et al., in press ), but some research has failed to find the hypothesized effects (e.g., Harwood & Swain, 1998 ). Although moderated hierarchical analysis does enable researchers to examine the separate, as well as the interactive effects of goal orientations and the motivational climate, this type of analysis is not powerful. However, the fact that significant main effects emerged for both climate and orientations appears to confirm the veracity of investigating the effects of goal orientations and perceptions of the motivational climate that the majority of achievement goal research has taken to date. Even though some have discussed the implications of both goal orientations and the motivational climate within a model (e.g., Roberts, 1992 ; Treasure, 2001 ), we have to agree with Harwood and colleagues ( 2008 ) that research in sport has not yet fully examined the interaction of dispositions and the situational criteria of the motivational climate on the manifestation of goal involvement.

Conclusions From AGT Research

There are two important conclusions we may draw from the evidence of the research effort on AGT over the past 40 years. The first one is that ego involving and IPT focusing on entity goals are more likely to lead to maladaptive achievement behavior, especially when participants perceive competence to be low, are concerned with failure, or invested in protecting self-worth. In such circumstances, the evidence is quite clear: Motivation ebbs, task investment is low, persistence is low, performance suffers, satisfaction and enjoyment are lower, peer relationships suffer, cheating is more likely, burnout is more likely, and participants feel more negatively about themselves and the achievement context. But as we have been at pains to note, this does not mean that ego-involving goals are always negative; in some situations and for some people they are positive. When one is ego oriented with a high perception of competence, then that goal is facilitative of achievement and functions as a motivating construct (e.g., Pensgaard & Roberts, 2002 ). This is precisely why being ego involved in sport can be very motivating and lead to sustained achievement behavior. But even then, ego-involving goals are more “fragile” and can lead to maladaptive achievement striving as context information is processed (Dweck & Leggett, 1988 ) such as when age begins to become a factor in elite sport performance or when injury strikes.

Second, the research is unequivocal that task involving (mastery) and IPT focusing on growth goals are adaptive. When task involved, whether through personal dispositions or participants perceive mastery criteria in the context, or both, then motivation is optimized, participants are invested in the task, persist longer, performance is higher, satisfaction and enjoyment are higher, peer relationships are fostered, burnout and cheating are less likely, and participants feel more positively about themselves and the task. Being task involved has been consistently associated with desirable cognitive-, affective-, and achievement-striving responses. The research is clear that if we wish to optimize motivation in sport and physical activity, we ought to promote task involvement. It does not matter whether we do it through enhancing socialization experiences so that the individual has a task-goal orientation and is naturally task involved (Nicholls, 1989 ) or we structure the physical activity context to be more task involving (Ames, 1992a ; Treasure & Roberts, 1995 , 2001 ). The crucial issue is that the participant has task-involving goals of achievement. The evidence has led many sport psychologists to conclude that being task involved better enables participants to manage motivation in the sport experience (e.g., Brunel, 2000 ; Duda & Hall, 2001 ; Iwasaki & Fry, 2016 ; Hall & Kerr, 1997 ; Pensgaard & Roberts, 2002 ; Roberts, 2001 , 2012 ; Roberts, Treasure, & Conroy, 2007 ; Roberts, Treasure, & Kavussanu, 1997 ; Theeboom, de Knop, & Weiss, 1995 ; Treasure & Roberts, 1995 ).

Now let us discuss Self-Determination Theory and its principal advocates.

Self-Determination Theory and Research

A central element of Self-Determination Theory (SDT; Deci & Ryan, 1985 ) is the concept of psychological needs. Basic Psychological Needs Theory (BPNT; Deci & Ryan, 2000 ) is one of five mini-theories that constitute the meta-theory of SDT. Within BPNT, Deci and Ryan proposed that individuals have innate and fundamental psychological needs that individuals seek to satisfy in order to achieve psychological adjustment, internalization, well-being, and personal growth. However, a dialectic occurs between the active organism and the social-contextual conditions that constitute the basis for the theory’s predictions about behavior, experience, and development processes. They propose that individuals will develop and function most effectively when their immediate psychosocial environment provides support for their basic psychological needs.

Three basic psychological needs have been identified, namely, the need for autonomy, the need for competence, and the need for relatedness. The need for autonomy refers to the perception that one is an “origin” of his or her own actions (Milyavskaya et al., 2009 ). The need for competence is associated with the perception of experiencing mastery and efficiency in a given environment and social context (Deci & Ryan, 1991 ). The need for relatedness is linked to the perception of experiencing meaningful interactions to significant others in a given context (Milyavskaya et al., 2009 ). Frustration of these needs is believed to have a negative impact on the individual’s psychological development, integrity, and well-being. Self-protective accommodations may be developed by individuals experiencing basic psychological needs thwarting to cope with the associated psychological deficit (Ryan, Sheldon, Kasser, & Deci, 1996 ). While these adjustments may provide some compensating satisfaction, these strategies ultimately fail to satisfy the thwarted basic needs, potentially leading to serious psychological maladjustments or pathologies (Froreich, Vartanian, Zawadzki, Grisham, & Touyz, 2017 ; Thogersen-Ntoumani, Ntoumanis, & Nikitaras, 2010 ).

SDT (Deci & Ryan, 1985 , 2000 ) stipulates that individuals in achievement settings will adopt a more or less self-determined motivational style because of the perceived level of satisfaction and fulfillment of the three basic psychological needs. When all three needs are satisfied within an activity, individuals will feel a high degree of autonomous and self-determined motivation. In different sport and achievement contexts, numerous studies have linked high autonomous motivation to active information seeking, higher levels of performance, task perseverance, goal attainment, and increased well-being (Amabile, Goldfarb, & Brackfield, 1990 ; Van den Broeck, Ferris, Chang, & Rosen, 2016 ; Koestner & Losier, 2002 ). However, lower levels of perceived autonomy have been linked to ineffective goal striving; impaired performance and persistence; increased feelings of stress, anxiety, self-criticism; vulnerability to persuasion, as well as exhaustion and burnout (Van den Broeck et al., 2016 ; Gagné & Forest, 2008 ; Koestner & Losier, 2002 ; Treasure, Lemyre, Kuczka, & Standage, 2007 ). Needs thwarting, defined as the intentional obstruction of the needs (Bartholomew, Ntoumanis, Ryan, & Thøgersen-Ntoumani, 2011 ; Vansteenkiste & Ryan, 2013 ), has been reported to be more detrimental than experiencing low levels of need satisfaction. It is linked to higher reported levels of ill-being and exhaustion in a performance context (Bentzen, Lemyre, & Kenttä, 2016a ). SDT also describes how different perceptions of a performance environment can either promote or undermine well-being (Deci & Ryan, 2000 ). An autonomy-supportive environment is characterized by an understanding and acknowledgment of one’s perspectives and provides a meaningful rationale for arduous tasks, offering opportunities for personal solutions and minimizing performance pressure (Deci & Ryan, 2000 ; Ryan & Deci, 2002 ). On the other hand, a controlling environment will typically put normative constraints on how one is expected to behave in a given environment, imposing predetermined goals, setting up a variety of restraints, imposing contingent pressure and rewards, and often expecting performance levels beyond reason (Deci & Ryan, 2000 , Gagné & Deci, 2005 ). An autonomy-supportive environment believed to promote basic psychological needs satisfaction while controlling environment will likely challenge the satisfaction of those needs and thwart the process to achieve a healthy balance (Ryan & Deci, 2002 ).

From an SDT perspective, individuals can be motivated for different reasons (Deci & Ryan, 1985 ; Ryan & Deci, 2000 ). These different reasons for being involved in an activity are typically placed on a continuum of autonomy ranging from high to low self-determination. The assumption is that it is the perceived incentive for the initiation of a behavior that influences subsequent levels of motivation. The most autonomous motivation regulation is labeled intrinsic motivation. An activity is intrinsically motivated and autonomous when it is freely experienced and self-endorsed. Intrinsic motivation emanates from the target behavior itself with the locus of causality being perceived as internal. However, some actions can be motivated by external sources of regulations that are not necessarily endorsed by the self. In this case people do not feel as autonomous, perceiving an external locus of causality (deCharms, 1968 ). Behaviors are perceived as being extrinsically motivated when individuals perform an activity because they value its associated outcomes more than the activity itself. SDT (Deci & Ryan, 1985 , 2008 ) contends that there is a continuum of extrinsic motivation, with each type of motivation differing as a function of the level of self-determination. The first extrinsic regulation is termed integrated regulation. Executed volitionally, integrated extrinsically motivated behaviors differ from intrinsically motivated actions in that they are aimed at obtaining personally important outcomes. The next extrinsic regulation on the continuum is identified regulation, corresponding to when the individual decides to participate in a task judged important for him/herself though not really interesting, such as exercising only for health benefits. The following regulation is termed introjected whereby behavior is fueled by inner pressures, such as guilt, to perform when the individual is not intrinsically interested but feels he/she ought to participate in the activity. The fourth extrinsic regulation is labeled external and represents extrinsic motivation as it was originally defined in the literature, for example, behavior controlled by specific external factors (Deci & Ryan, 2000 ). An externally regulated individual typically engages in the behavior to obtain something (e.g., an award) or to avoid a negative consequence (e.g., punishment). Finally, individuals can also behave in some contexts without any motivational reasons for participating in the activity. This construct is termed amotivation and it results from not valuing an activity (Deci & Ryan, 2000 ). Motivated individuals lack intention to participate in a given activity, and they do not perceive contingencies between their behavior and achievement outcomes. They are entirely lacking any form of self-determination, they have no relationship to any achievement goal, and their somewhat automatized behavior is solely controlled by the environment.

The different motivational regulations can thus be differentiated on a motivational continuum based on their relative autonomy, reflecting the level of self-determination within each regulation (Ryan & Connell, 1989 ). Intrinsic motivation is purely self-determined as it is defined through being involved in an activity for its own sake, because it is interesting and satisfying (Ryan, 1995 ). There are two extrinsically motivated forms of regulations that are also autonomous: namely, integrated and identified (Ryan & Deci, 2000 ). Integrated regulation is seen as is wholly autonomous as it reflects a behavior that is close to one’s own values and identity, while it is not necessarily interesting. Identified regulation is an autonomous form of motivational regulation as it reflects to what degree an athlete values sport participation. On the motivational continuum, these three autonomous regulations are followed by three less self-determined forms of motivation. Two of them are often seen as controlled motivational regulations, namely, introjected and extrinsic regulations. Introjected regulation refers to an athlete acting to avoid guilt and shame or to attain ego enhancements, such as pride (Deci & Ryan, 2000 ). External regulation is the least self-determined form of motivation on the continuum as it is characterized by behaviors conducted to satisfy external demands or to reward contingency (Chemolli & Gagné, 2014 ). Amotivation has been interpreted as a separate construct, outside of the continuum.

In an attempt to simplify these concepts and for the sake of parsimony, motivational regulations have often been collapsed into two types, based on whether they refer to more autonomous (intrinsic and identified) or more controlled (introjected and external) forms of motivation (Deci & Ryan, 2008 ; Williams, Gagné, Ryan, & Deci, 2002 ). While autonomous motivation refers to athletes feeling self-determined and involved because their sport is personally important or interesting (Williams et al., 2002 ), controlled motivation refers to behaviors of athletes feeling pressured or coerced by internal or external sources (Ryan & Deci, 2000 ). Research clearly indicates that these two dimensions of motivation lead to very different outcomes in performance settings (Deci & Ryan, 2008 ).

In an attempt to further simplify the use and the interpretation of the theoretical framework, some researchers have used a single score Self-Determination Index (SDI; e.g., Frenet, Guay, & Senecal, 2004 ; Vallerand, Fortier, & Guay, 1997 ; Vallerand, & Rousseau, 2001 ). The SDI has typically been computed using this formula: [(2*(IM knowledge + IM accomplishment + IM stimulation)/3 + 1*Identified Regulation]−[(1*Introjected Regulation + 1*External Regulation)/2 + 2*Amotivation]. The advantage to using such an approach is that it allows for a simplification of the interpretation of an individual’s quality of motivation where the higher the positive index score, the more self-determined the motivation. Some researchers (e.g., Lemyre, Treasure, & Roberts, 2006 ) have demonstrated that it can be a useful methodology when investigating shifts in motivation over time. Lemyre and colleagues have also reported that this approach has important limitations as it collapses regulations with potentially very different effects on how individuals interpret the reasons for participating in different activities. Additionally, incorporating the amotivation subscale to the SDI may seem counterintuitive as it refers to the absence of regulation and should perhaps be interpreted independently from the continuum. In order to truly grasp the influence of each type of regulations and their potential interaction, Chemolli and Gagné ( 2014 ) argued that the quality of motivation should be measured with separate regulation scores rather than a sum score of regulations, as each motivational regulation should be seen as a temperature scale on its own. Recent studies investigating changes in quality of motivation over time have adopted this approach with advanced statistical analyses.

Research Evidence

SDT states that intrinsic motivation and more self-determined forms of extrinsic motivation (identified, integrated regulations) are associated with adaptive emotional, cognitive, and behavioral consequences. The non-self-determined forms of motivation (introjected and extrinsic regulations) and amotivation have been associated with a variety of maladaptive participation outcomes in different performance settings (Deci & Ryan, 2000 ). Even though some researchers (e.g., Martinent & Decret, 2015 ) have clearly argued that higher levels of self-determined forms of motivation generally increase chances to succeed and reach the elite level in sports, Vallerand and colleagues ( 2008 ) have suggested that a combination of different motivational regulations (self-determined and controlled) may be optimal in achieving high levels of performance depending on the context and the time frame. That is, the quality of motivation of participants in sports and other performance contexts will often reflect a motivational profile based on a combination of self-determined and controlled forms of motivation, also leading to positive outcomes. Hypothetically, the presence of certain self-determined reasons for engaging in activity may neutralize the negative influence of other controlled reasons for participation, while the presence of these regulations may significantly add to the motivation and the determination of an athlete.

In a study by DiBartolo, Frost, Chang, LaSota, and Grills ( 2004 ), the authors state that individuals in a performance context pursuing challenging goals and high, personal standards may experience different levels of self-determined motivation because of perceiving these goals and standards of performance as a challenge or a required level of performance necessary to attain or to maintain self-worth. The assumption is that intrinsic motivation translates well in a challenge-seeking state, as the athlete is able to maintain intrinsic interest for the activity. In contrast, if those high, personal standards are in order to maintain or attain a sense of self-worth, it may hinder self-determined behavior. Autonomous and self-determined motivation is expected to lead to more adaptive coping skills accompanied by more flexible and positive stress appraisals (Mouratidis & Michou, 2011 ). When motivation is not self-determined and the athlete’s behavior is externally regulated, the athlete will perceive less control, which may lead to maladaptive achievement outcomes such as performance impairment, physical, and emotional exhaustion, which are all symptoms of burnout (Lemyre et al., 2007 ). Research in this area has suggested that athlete burnout is a result of a negative shift toward a less self-determined quality of motivation and a continuous experience of stress. This is due to personal factors such as maladaptive forms of passion and perfectionism or situational factors such as parental pressure or physical overtraining (Gould, 1996 ; Lemyre et al., 2007 ; Lemyre, Treasure, & Roberts, 2006 ). Athletes who suffer from burnout will typically show signs of demotivation because of the reduced sense of accomplishment and devaluation of the sport experience in general (Lemyre et al., 2007 ). Burnout seems to share many commonalities with amotivation. Amotivation reflects a state where an athlete who was originally showing great motivation for an activity experienced a gradual deterioration of the quality of his or her motivation over time, often in the face of adversity and an inability to achieve important goals. The athlete ends up by feeling that there is no relationship between the investment in the activity and the return for this investment (Lemyre et al., 2006 ). These findings support the use of Self-Determination Theory to understand better the factors leading to maladaptive achievement outcomes in sports such as burnout. In addition, Quested and Duda ( 2011 ) found that promoting autonomous motivation is relevant to reduce the risk of burnout in vocational dancers.

In a series of articles investigating psychological adjustment, well-being, and prevention of exhaustion in elite sport coaches, Bentzen and colleagues (Bentzen, Lemyre, & Kenttä, 2014 , 2016a , 2016b ) used an SDT framework to better understand the complex challenges associated with performing in a position of leadership in sports. In one of their articles (Bentzen et al., 2016a ), the authors used the SDT-process model (Ryan, Patrick, Deci, & Williams, 2008 ) to highlight how personal and environmental variables interact. While SDT assumes that people have natural developmental tendencies for growth, experiencing mastery, and integrating new experiences into a coherent sense (Ryan & Deci, 2002 ), the SDT-process model presents a framework explaining how these tendencies are fueled and supported in the interaction with the social environment (Deci & Ryan, 2000 ). The process from the individual interacting with the environment to outcomes is described as the SDT-process model (Ryan et al., 2008 ). The proposed sequential development model has four important components where (1) the perceived environment predicts, (2) psychological need satisfaction predicts, (3) the quality of motivation finally predicting, (4) and outcomes (Bentzen et al., 2016a ; Fortier, Sweet, O’Sullivan, & Williams, 2007 ; Halvari, Halvari, Bjørnebekk, & Deci, 2013 ; Williams, McGregor, Zeldman, Freedman, & Deci, 2004 ). Following this framework, Bentzen and colleagues ( 2016a ) investigated changes in motivation indices relative to burnout symptoms in high-performance coaches over the course of a sport season. The authors found that lower levels of need satisfaction in coaches as well as the experience of having their needs thwarted led to maladaptive outcomes. They also found that high levels of autonomous motivation had a preventive effect on the development of exhaustion in elite-level coaches. Their research underlined the importance of a performance environment promoting the development and maintenance of autonomous motivation in individuals to ensure performance and well-being, as well as preventing exhaustion.

Similarities and Differences Between AGT and SDT

As is clear to the reader from the preceding, there are some remarkable similarities in the cognitive, behavioral, and emotional outcomes predicted by SDT and AGT. In both theories, participants become invested in the task, persist longer, performance is higher, satisfaction and enjoyment are higher, peer relationships are fostered, well-being is enhanced, and participants feel more positively about themselves and the task when motivation is task involving and/or self-determined. Being task involved and self-determined have been consistently associated with desirable cognitive-, affective-, and achievement-striving responses. The research is now clear that if we wish to optimize motivation in sport and performing contexts, we ought to promote task involvement and/or autonomous forms of motivation. It does not matter whether we do it through enhancing socialization experiences so that we encourage the individual to be task involved or autonomous or the person is naturally task involved through their disposition to be task oriented (AGT) or to satisfy basic needs (SDT).

However, the theories do have some basic differences. First, and most obvious, AGT and SDT differ in the energization of achievement behavior. SDT argues that the person is motivated to satisfy the basic needs of competence, relatedness, and autonomy. It is striving to satisfy these basic needs that stoke the motivational engine. In terms of “nature versus nature,” SDT assumes that nature is the major underlying energization of motivated behavior, and there are universal basic needs that every person has and seeks to satisfy, even though a dialectic occurs between the context and the individual. Conversely, AGT argues that we are motivated to achieve because we wish to demonstrate competence: to others and ourselves. We learn through our socialization experiences that the demonstration of competence is a valued attribute in society. There is a long history in psychology of how individuals are socialized to recognize that the demonstration of competence is a valued social attribute (e.g., Roberts & Sutton Smith, 1962 ). AGT assumes that the demonstration of competence is a learned attribute; therefore, it is nurtured by socialization processes. Thus, whether we choose SDT or AGT, it becomes an issue of how one believes the psyche functions: Do we have basic needs that drive the human organism, or is the human organism intentional and rational and makes decisions based on how one thinks things work in achievement settings? One’s choice of theory may simply come down to that basic question.

A second major difference in the two theories is in terms of scope. SDT purports to be a meta “theory of everything,” which is concerned with the global nature of human beings (Deci & Ryan, 2012 ). SDT is a meta-theory with five mini-theories within it, with Basic Needs Theory being the motivational “engine” that drives the theory. SDT argues that all people need to experience the basic psychological nutrients of competence, relatedness, and autonomy for effective functioning, psychological health, well-being, and the development of personality and cognitive structures. The degree to which the three basic needs are satisfied or thwarted has positive and negative influence on a wide range of outcomes, including motivation. AGT, on the other hand, is a more restricted theory dealing with achievement-motivated behavior in pursuit of a specified goal that is valued and meaningful to the individual. When one is trying to demonstrate ability in a valued context to self and/or others, then AGT is a parsimonious and elegant theory to describe and explain the social cognitive dynamics of pursuing an achievement goal or outcome (Maehr & Zusho, 2009 ), which is why it lends itself to competitive sport and performance so well.

A third difference is in the arguments pertaining to the relevance of the social context to affect achievement behavior. Both SDT and AGT emphasize the importance of the social environment (AGT: Mastery, Performance; SDT: Autonomy support, Controlling), but there are substantive differences. According to SDT, social factors influence human motivation through the mediating variables of autonomy, competence, and relatedness (Vallerand, 1997 ). On the other hand, AGT focuses on how perceptions of the extant criteria of success and failure that create either a mastery or a performance climate, which in turn interacts with dispositional goals to influence affect, behavior, and cognition in achievement contexts (Ntoumanis, 2001 ). Still, there is a “general convergence of evidence from achievement goal theories and SDT concerning the optimal design of learning environments” (Deci & Ryan, 2000 , p. 260). Specifically, both conceptual frameworks suggest that intrinsic motivation is nurtured in environments that promote self-mastery and choice. On the other hand, intrinsic motivation is thwarted, or supplanted by ego involvement, in environments in which normative comparison operates and rewards are provided contingent on performance.

AGT and SDT also have similarities, and not only in outcome predictions. There are similarities in achievement goals. Achievement goals are relevant to SDT, and researchers have looked at the influence of what is termed goal content (intrinsic vs. extrinsic) on the quality of motivation of individuals in different performance contexts (e.g., Solberg & Halvari, 2009 ). SDT differentiates between intrinsic and extrinsic goal content. Intrinsic goal content is associated to reasons such as learning and personal growth, friendship, and social contribution (Kasser & Ryan, 1996 ). It is assumed to lead to adaptive outcomes. This is very similar to the goal of task involvement in AGT, which is associated with learning, personal growth, and mastery. Extrinsic goal content is associated to reasons such as financial success, status, and physical appearance. Extrinsic goal content increases the risk for an athlete to experience maladaptive participation outcomes (e.g., Solberg & Halvari, 2009 ). This is very similar to the goal of ego involvement in AGT that is associated with status relative to others and the demonstration of normative competence. The conceptual rationale behind the achievement goals is, of course, quite different. In SDT, the assumption is that intrinsic goal content is expected to promote the fulfillment of the three basic needs (Deci & Ryan, 2000 , 2012 ) while extrinsic goals are not instrumental to basic need satisfaction as they lead an individual to focus on external outcomes and social comparison (Kasser & Ryan, 1996 ; Solberg & Halvari, 2009 ). In AGT, because it has a more limited focus on demonstrating a valued social attribute, then the demonstration of competence as one defines competence is expected to influence one’s motivational stance. These concepts in SDT have yet to be exhaustively investigated in the context of sport and performance; however, research has suggested that intrinsic goal content mediated the relationship between sport participation and psychological well-being (Chatzisarantis & Hagger, 2009 ) in a similar way to AGT research findings. In a study of elite athletes, Solberg and Halvari ( 2009 ) found that athletes experiencing autonomy support from their coach were more likely to have autonomous and intrinsic reasons for their goals and reported more positive emotional well-being. This is similar to the research findings with the mastery motivational climate in AGT (e.g., Ames, 1992c ).

All motivation theories over time have a focus on competence, in one form or another. SDT and AGT are no different. SDT’s focus is on the need for competence as a unitary human need that when satisfied will facilitate autonomous motivation (Ntoumanis, 2001 ). SDT has been criticized for not providing a well-articulated and internally consistent conceptualization of the role of competence in maintaining autonomous motivation (Butler, 1987 ). According to Butler, SDT has not sufficiently distinguished between different kinds of competence goals or the relation between the perception of autonomy and different conceptions of ability. It may be argued that SDT has contributed more to the understanding of how social contexts may foster intrinsic motivation by the support of autonomy instead of clarifying how these contexts may contribute to continuing motivation by promoting either one rather than another conception of ability (Butler, 1987 ). This is supported by Spinath and Steinmayr ( 2012 ) who argue also that different aspects of competence are important. For people with competence-demonstration goals, measuring competence relative to others or certain external criteria is important, while for people with competence-development goals, it is important to “measure one’s own competence against intraindividual temporal standards” (p. 1144). The distinction is not captured with measurement of the need for competence. On the other hand, AGT is more concerned with how thoughts and perceptions energize motivated behavior. The focus is on how being task or ego involved influences task difficulty choices and sustained achievement striving. Being “task involved” is important to both theories. Task involvement “bears a considerable relation to intrinsic motivation when applied to the achievement domain” (Deci & Ryan, 2000 , p. 260). When individuals are task involved, their motivation to perform a task derives from intrinsic properties and not from the expected outcomes of the task. When intrinsically motivated, people do an activity because the behavior in itself is interesting as well as spontaneously satisfying. When individuals are task involved, the intrinsic motivation system is involved in initiating, sustaining, and rewarding a specific behavior or activity (Deci & Ryan, 2000 ). Being task involved indicates that the individual strives for mastery, while being intrinsically motivated makes the mastery a reward in itself. Therefore, task involvement facilitates autonomous behavior as well as the need for competence (Ntoumanis, 2001 ).

Despite the partial convergence of constructs (performance climate/controlling climate; mastery climate/autonomous climate; need for competence, task involvement), and similar outcome predictions, the two theories are based on different theoretical perspectives that may make it inappropriate to combine them (Marsh, Craven, Hinkley, & Debus, 2003 ). However, an attempt has been made: Duda ( 2013 ) proposed a hierarchical reconceptualization of the motivational climate in sport, specifically for children, by combining the two conceptual frameworks. Duda introduced “empowering” and “disempowering” dimensions to coaching behavior to integrate SDT and AGT. When coaches are empowering, they will be autonomy supportive, mastery involving, and support social relatedness. Coaches will promote self-referenced criteria of success when assessing competence and will satisfy basic needs in the participants. When coaches are disempowering, they will be controlling and use performance criteria of success. Coaches will promote other referenced criteria of success when assessing competence and be less concerned with satisfying basic needs. Can the concepts of empowerment and disempowerment integrate SDT and AGT to become a unified theory? A recent study would suggest probably not: Using a Bayesian approach, Solstad and colleagues (in review) failed to confirm the hierarchical nature of the coach-created motivational climate as proposed by Duda. Solstad and colleagues agree with Marsh and colleagues ( 2003 ) who argued that the two theories are based on different conceptual arguments, which make it inappropriate to combine them. The empowerment concepts are proposed to integrate the theories, but in fact they make a descriptive and pragmatic case to use both theories to maximize the likelihood of creating a supportive, task-involving, autonomous-coaching climate for the benefit of the children in the sport experience. Future attempts to create a unified theory need to address developing unique energizing constructs because, at the present time, both theories maintain their own unique energizing mechanisms. However, that does not mean that the children do not benefit from the pragmatic inclusion of both theories as argued cogently by Duda; they clearly do (Solstad, 2016 ).

Conclusions and Future Directions

As we have stated above, in both theories, when motivation is task involving and/or self-determined, participants become invested in the task, persist longer, perform better, satisfaction and enjoyment are higher, peer relationships are fostered, well-being is enhanced, and participants feel more positively about themselves and the task. Being task involved and self-determined have been consistently associated with desirable cognitive-, affective-, and achievement-striving responses. The research is now clear that if we wish to optimize motivation in sport and performing contexts, we should promote task involvement and/or autonomous forms of motivation. Both theories recognize the importance of personal variables and the impact of the perceived context on motivation for sustained achievement behavior.

Which theory should we use? Well, that clearly depends on your understanding of how the psyche works. Do you believe that satisfying basic needs drive the human organism? If so, SDT is for you. Do you believe that the human organism is rational and intentional and is driven by how one perceives the social context or believes in trying to demonstrate either task or ego-involved competence? Then AGT is for you. SDT is a more global theory of personality; AGT is limited to achievement tasks that are valued by the person. It is a choice, but the predictions of both theories are remarkably similar. However, it would seem that trying to integrate the theories is not viable at this time (Marsh et al., 2003 ; Solstad et al., forthcoming ), but that does not mean we should stop trying.

It is interesting to note that a mastery/autonomy-supportive climate has been found to facilitate positive outcomes while a performance/controlling climate is associated with negative outcomes. But these climates may be interdependent and may thus exist simultaneously, certainly within AGT (Ames, 1992a , 1992b , 1992c ). An interesting line of inquiry for future research may be to investigate further the interplay between the opposing climates. To the best of our knowledge, there are only two studies that address this, and then only from an AGT approach (Buch, Nerstad, & Safvenbom, 2017 ; Ommundsen & Roberts, 1999 ). For example, Buch and colleagues found a positive relationship between perceived mastery climate and increased intrinsic motivation only when combined with low levels of perceived performance climate. An important task for future research would be to attempt to clarify what may represent a beneficial balance between mastery (autonomous) and performance (controlling) climates in sport and performance.

Another interesting direction could be to question whether being task involved is beneficial for everyone. There is evidence that being ego involved is beneficial for some individuals in competitive contexts when the individual has a high perception of competence (Pensgaard & Roberts, 2000 ). This research showed also that elite athletes seem to benefit from being high in both task and ego orientations. It may be that individuals who are simply high in task orientation may not function well in a highly competitive environment.

Given that mastery (autonomous) and performance (controlling) climates have such profound influence on achievement behavior, future research should address what may be the crucial antecedents of such climates in sport. This would also inform coaching behaviors. As an example, one study has addressed how leadership style (e.g., Baric & Bucik, 2009 ) may be such a relevant antecedent. Other possible and important antecedents may exist.

Some researchers have questioned whether IPTs can operate at the situational level. Although IPTs have been found to be temporarily changeable (interventions), the fact that IPTs initially are operationalized as relatively stable dispositions may confuse an operationalization at the situational level. Perhaps a better and more theoretically sound approach could be to investigate the predictive value of the perceived motivational climate as operationalized by Nicholls ( 1984 ) and Ames ( 1992c ). Dweck’s approach builds on Nicholls’s ( 1981 ) initial ideas, and thus it would facilitate theoretical coherence to link the IPTs with the perceived motivational climate. One study did test this showing that a performance climate induced a fixed mindset of ability, while a mastery climate generated a growth mindset in physical education students (Ommundsen, 2001c ). This study’s findings are based on cross-sectional data that suggests the need for more rigorous designs and data to support the findings. This could also facilitate an answer to how IPTs are socialized in ongoing interactions in various achievement domains. Specifically, the extant criteria of success and failure signaled through the policies, practices, and procedures in sports, at school or in organizations, may contribute to elicit the different beliefs (Maehr & Braskamp, 1986 ).

We began with the philosophical approach of Nicholls ( 1979 ), and we end with a quote from his 1989 book that pertains to both AGT and SDT equally: “If all students are optimally motivated, we are on the way to the goal of equality in the fulfillment of potential” (Nicholls, 1989 , p. 151). Nicholls was interested in the academic domain, but the same is certainly true in the sport domain.

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Keywords : Performance analysis, individual sport, collective sports, adapted sports, parasports, match analysis, high performance, tactics, technique, female sport, women's sport

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Editorial: Performance Analysis in Sport

Miguel-angel gomez-ruano.

1 Faculty of Physical Activities and Sport Sciences, Polytechnic University of Madrid, Madrid, Spain

Sergio José Ibáñez

2 Faculty of Sport Sciences, University of Extremadura, Badajoz, Spain

Anthony S. Leicht

3 Sport and Exercise Science, James Cook University, Townsville, QLD, Australia

Performance analysis is a sub-discipline of Sport Science research (Borms, 2008 ) that has attained great interest for many stakeholders (i.e., coaches, technical staff, performance analysts, managers, media, fans, and players) at different levels of performance (i.e., youth, semi-professional, or professional players). The development and implementation of new technologies to measure individual or team's performances (e.g., tracking systems such as local positioning systems, LPS; video tracking, or observational video analysis systems) with multiple practical applications have intensified the focus of performance analysis in sport (Hughes and Franks, 2007 ). Traditional approaches have included static analysis focused on retrospective performances; however, dynamic and complex analyses (i.e., non-linear Multi-Dimensional Scaling, classification and regression tree, logistic regression, etc.) have become increasingly utilized by researchers for a deeper understanding of sport performance during training and competition (O'Donoghue, 2009 ). In particular, a holistic and multidisciplinary perspective such as the Grand Unified Theory analyses (GUT, see Glazier, 2017 ) has been suggested to be fundamental for sports performance. This approach, provides a framework to examine the inter- and intra-athlete's behavior dimensions under the environmental and task-related (ecological) factors that affect the performance. Specifically, isolated approaches have been suggested to be avoided with the integration of the biomechanical, physiological, psychological, technical, tactical, positional, motor development and/or strength and conditioning perspectives recommended when evaluating match-related contexts and training tasks (Glazier, 2017 ). Additionally, Woods et al. ( 2020 ) highlighted the importance of ecological dynamics to guide the control, preparation and assessment of athletes and teams. Subsequently, the use of interdisciplinary research designs would provide clear and well-described rationales, powerful data collection and analyses, resulting in robust findings. Innovative sports performance analyses that incorporate new technologies to understand individual's behaviors within real-based and ecological contexts would provide a greater understanding of how players and teams act and react for greater performance development and application (Bertollo et al., 2020 ). In fact, as Robertson ( 2020 ) argued, the development of professionalism and data gathering in sport had lead to a new scenario for coaching staff, athletes, and performance analysts where adaptative tools are essentially required to understand the needs of sports performance (e.g., human-machine interaction, perspective, innovation, versatility, visualization, evaluation, feedback, generalization, and future planning).

This special issue was initiated to gain a greater insight of current sport performance theory considering analytics and a wide range of sport disciplines (e.g., individual, dual, team sports) and variables studied (e.g., physical, positional, technical, tactical, psychological, or pedagogical). Of note was that this special issue drew immense attention resulting in the publication of 65 articles (and one corrigendum) improving the research knowledge of the following topics: performance profiling (18 articles), performance measurement (13 articles), reliability and validity of coding systems (eight articles), non-linear performances (seven articles), performances of females (four articles), tactical analysis (four articles), gender analysis (three articles), technical analysis (three articles), psychological aspects of performance (three articles), referees' performance (two articles), coaching issues (two articles), contextual variables (two articles), and new technologies in sport (two articles).

A focus on performance-related variables within sport has been the key issue studied for performance analysis. In particular, the use of fundamental indicators to model performance and establish performance profiling has provided the basis with high applicability for coaching staff to manage performance during training and competition. This approach was widely acknowledged in this Research Topic with 18 studies published. The analysis of soccer was presented in five studies from different perspectives and included the importance of technical indicators in the Big five teams of the UEFA Champions League ( Yi, Groom et al. ), running performances differentiated by Confederations ( Tuo et al. ), player's age and performance trends within the UEFA Champions League ( Kalén et al. ), and player migration and nationality ( Lago-Peñas et al. ). The analysis of other team sports showed the importance of multifactorial benchmarking and longitudinal performance in Australian football ( McIntosh et al. ), the long-term analysis of basketball players' performances ( Lorenzo et al. ), the multifactorial performance (physical, technical, and anthropometrical) of youth basketball players ( Matulaitis et al. ), the key determinants to succeed in wheelchair basketball [ Francis et al. (a)], the positional, in-match running demands in rugby union ( Donkin et al. ), and the importance of ball type and innings in cricket batter's performance (Connor, Sinclair et al. ). Individual sports were also investigated from different approaches including the relative age effect of track and field athletes ( Brustio et al. ), the world record profiles of long distance runners ( Knechtle et al. ), the spatiotemporal performance of 60 m hurdle athletes ( González-Frutos et al. ), the race strategies for long distance open-water swimmers ( Veiga et al. ), the longitudinal performance of elite rhythmic gymnasts ( Sierra-Palmeiro et al. ) and the pathway to succeed in elite swimming ( Yustres et al. ). Lastly, dual sports were studied with Torres-Luque, Fernández-García, Blanca-Torres et al. examining badminton (statistical analysis of men's/women's players), and Murray et al. examining squash (performance profiles of the top two players when considering the opponent's performance).

Measurement of performance analysis in sport was another main feature presented within this Research Topic with 13 articles covering different approaches and variables. Specific articles focused on postural skills and body related measures associated with sport expertise ( Paillard ), anthropometric measures ( Eriksrud et al. ; Gomez-Campos et al. ), ranges of movement related to pain ( Cejudo et al. ), post-activation potentiation in soccer ( Petisco et al. ), and the effect of thermal conditions on performance ( Gasparetto and Nesseler ). Additionally, articles focused on physical fitness measures and performances in junior tennis players ( Colomar et al. ) and academy soccer players ( Raya-González et al. ) while physiological measures were considered when assessing elite male wheelchair basketball players' performance ( Marszałek, Kosmol et al. ). Finally, two studies investigated a research framework for the importance of several measures in Australian football ( Bonney et al. ) and the beginning of a senior career in team sports ( Lupo et al. ).

While the measurement of performance has been focused upon in this Research Topic, the reliability and validity of match-observation, as well as the observation systems used in performance analysis, were also extremely important with eight articles incorporated. In particular, the design and validation of observational instruments of technical and tactical actions were examined by Ortega-Toro et al. in soccer and Torres-Luque, Fernández-García, Cabello-Manrique et al. in tennis. A similar approach was undertaken by Francis et al. (b) who quantified actions in elite wheelchair basketball, and by Gong et al. who studied the validity of the CHAMPDAS match analysis system in elite soccer. Additionally, four studies considered reliability/validity procedures via various techniques; Belli et al. studied the reproducibility and validity of the stroke effectiveness in table tennis based on game temporal structure; Ibáñez et al. employed a learning and performance assessment instrument in basketball; Colino et al. validated an indoor tracking system that assessed activity distance and time for court-based sports; and Premelč et al. analyzed the reliability of judging artistic sport (danceSport).

A novel feature of this Research Topic was the coverage (seven studies) of the complexity and non-linear nature of sports that required different approaches to control for performance variability under unpredictable contexts. First, Ribeiro et al. focused their attention on bidirectional self-organizing tendencies in team sports with a specific approach based upon the game model and the principles of play. With this framework in mind, four studies analyzed soccer including: the interpersonal coordination perspective (i.e. importance of team dyads and task design) by Santos et al. with comments by Gesbert and Hauw in their commentary letter; the effect of interpersonal dynamics within 2 vs. 1 playing contexts (importance of field location and player roles) by Laakso et al. ; and the effect of temporary numerical imbalances in youth players by Canton et al. . In addition, non-linear approaches were examined in beach volleyball ‘winning streaks' that considered the impact of failure in the temporal series ( Link and Wenninger ), and in padel which analyzed the effect of return of serve on the athlete movement patterns and rally outcome ( Ramón-Llin et al. ).

One of the most relevant and important issues in our collection of performance analysis, due to its high applicability, was tactical analysis with the following four studies: (i) Spencer et al. studied the quality of player's passing decisions in Australian football using commitment modeling that accounted for spatial influence and bounds/density of players; (ii) Méndez et al. analyzed the attacking patterns of elite futsal teams from Spain, Italy, and Russia that also considered the importance of efficiency, offensive organization, match type, scoring first and match outcome; (iii) Kim et al. investigated the attacking process in soccer from a goal scoring approach with the establishment of a taxonomy of how teams developed their attack when creating scoring opportunities; and (iv) Scharfen and Memmert analyzed the importance of cognitive function and specific-related motor skills during different tasks by elite youth soccer players.

A distinctive gender focus in performance analysis was also of importance within this Research Topic. Firstly, Pedersen et al. focused on the gender differences of soccer players based upon physiological and anthropometrical factors. Specifically, they presented a detailed approach to analyse and tailor-design training and competition based on gender differences. Secondly, Mclean et al. presented a work domain analysis that allowed the modeling of performance in women's netball. This research established the importance of complex relationships between key performance indicators, such as passing and possession measures, cognitive performance, and physical demands. Finally, two studies focused on the technical and tactical actions of elite soccer female players during the FIFA World Cup ( Sainz de Baranda et al. ) and the physical and external loads experienced by amateur women's basketball players ( Reina et al. ).

The importance of the technical analysis was also reflected in three studies with each focused on a different sport (i.e., cross-country, soccer, and cricket). Tjønnås et al. identified the basic motion patterns of cross-country skiing athletes and the need to control for physical, track, and environmental factors that influence these patterns. Additionally, Yi, Liu et al. studied the technical performance indicators of soccer players over nine seasons of the UEFA Champions league. Their results via Poisson regression and autocorrelation models showed trivial changes for shooting variables and defensive actions, but higher variability of passing and attacking-related variables. Lastly, Connor, Mann et al. studied the performance advantages of junior cricket batters based upon batting stance, lateral dominance, and type of technique. Their results highlighted the left-handed advantage and the need to control for these factors during team selection practices.

Two studies focused on the importance of contextual-related variables and their impact on players and teams' performance. Firstly, Pino-Ortega et al. analyzed the importance of the situational factors that effected external loads of Under-18 basketball players according to their playing position (i.e., team quality, match period, and consecutive matches). Secondly, Marszalek, Gryko et al. studied the heart rate profile of elite wheelchair basketball players who were classified according to their functional classification and playing time. Their results identified different performance trends according to the contextual factors of tournament level, game type, and game quarter.

The psychological approach in performance analysis was covered by three studies reflecting the importance of multifactorial analyses as key factors in sports performance. These articles focused on: analysis of self-control during pressure situations of penalty kicks in soccer (Navia et al.); the importance of competitive psychological disposition and self-perception of performance in youth female soccer players ( Olmedilla et al. ); and the psychological demands and well-being needs of Elite South African rugby players ( Kruyt and Grobbelaar ).

While a focus of the articles in this special issue was on players, the referee and coach were also examined. For referees, Kolbinger and Stöckl analyzed two common rule violations that were rarely penalized (i.e., misbehavior during penalty kicks and the goalkeeper holding the ball for more than 6 s) with their results from the German Bundesliga indicating that when players committed offenses, the referee's accuracy was only 20.8% for these situations. Likewise, Kraak et al. studied the rate of sanctioning illegal and dangerous ruck cleanouts in the 2018 Super Rugby competition with some dangerous illegal rucks not sanctioned by the referees (i.e., shoulder charge, neck roll, and contact above the shoulder). For coaches, Tozetto et al. analyzed the importance of coach turnover on team's performance in the Brazilian professional soccer league (2012-2017). Their results highlighted the impact of replacing the coach in terms of short-term performances and the minimal influence of the coach's prior experience. The second study by Bateman and Jones highlighted the importance of coach and performance analyst relationships in professional soccer. Their study used the COMPASS (conflict, openness, motivation, preventative strategies, assurance, support, and social networks) framework and identified the importance of all aspects to maintain a positive coach-analyst relationship. These articles highlighted the practical applications of this special issue for stakeholders (i.e., players, coaches, referees, and analysts).

Finally, the use of new technologies was also addressed in this Research Topic with a data driven visual prototype reported by Benito Santos et al. . This software technology employed geospatial data and visualization techniques and allowed stakeholders to understand the collective behaviors of soccer teams during competitions and training.

In light of the positive engagement and great number of high-quality articles published, this special issue has made an important contribution to exemplify and stimulate the evolving research sub-discipline of performance analysis in sport. We look forward to the current articles supporting future research approaches that consider the complex nature, emerging techniques and “big data” associated with sport.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Guest Editors : Hugo G. Espinosa, Aimee Mears, Andy Stamm, Yuji Ohgi & Christine Coniglio The Topical Collection on Wearable Sensor Technology in Sports Monitoring  is dedicated to recent advances in research and development in wearable sensor technology with emphasis on inertial measurement units (IMUs), textile-based, flex, pressure and strain sensors, among others.

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Melissa l. gaskill, science in space: may 2024.

Future missions to the Moon and Mars must address many challenges, including preventing loss of bone and muscle tissue in astronauts. Research on the International Space Station is helping to address this challenge.

Without Earth’s gravity, both bone and muscle atrophy, or become smaller and weaker. Early on, scientists realized that exercise is a critical part of maintaining healthy bones and muscles in space, just as it is on Earth. From simple elastic bands on early missions, exercise hardware has become increasingly advanced. Current equipment includes the Advanced Resistive Exercise Device ( ARED ) weight-lifting system, a second generation-treadmill called T2 , and the Cycle Ergometer with Vibration Isolation and Stabilization System ( CEVIS ) cycling machine. Studies continue to refine this equipment as well as the intensity and duration of how astronauts use it, with crew members now averaging two hours of exercise per day.

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Installed in 2008, ARED uses a piston and flywheel system to provide loading that essentially mimics weightlifting in weightlessness. A current investigation from ESA (European Space Agency), ARED Kinematics analyzes the effect of this type of exercise on the body in microgravity to help determine optimal workout programs before, during, and after spaceflight. Results have shown that preflight exercise training improves an individual’s performance while on the space station just as pre-season training helps athletes in later competition. 1

From 2001 to 2011, crew members used the Interim Resistive Exercise Device ( IRED ), which could be configured for at least 18 different exercises using both upper and lower body muscles with up to 300 pounds of resistive force. A retrospective evaluation showed some correlation between preflight strength and postflight changes, and analysis suggested that a resistance device that provides higher loads and improved exercise prescriptions could provide greater benefits. 2

CEVIS, installed in 2001 and upgraded in 2023, uses friction and resistance and is computer-controlled to maintain an accurate workload. The system displays parameters such as cycling speed, heart rate, elapsed time, and exercise prescription details. A study using the data collected by CEVIS concluded that up to 17% of astronauts could experience loss of muscle performance, bone health, and cardiorespiratory fitness if future missions continue to use current exercise countermeasures. The researchers note that this highlights the need to further refine current regimens, add other interventions, or enhance conditioning preflight. 3

Appropriate equipment is important, but so is the way it is used. Early exercise regimens included running on a treadmill at low velocity and conducting resistance exercise at low loads for long periods of time. Despite spending up to 10 hours per week exercising, astronauts continued to lose muscle mass and bone density. Growing evidence showed that high-intensity, low-volume exercise was more effective at maintaining fitness on Earth. The Integrated Resistance and Aerobic Training Study ( Sprint ) compared results of low-intensity, high-volume with high-intensity, low-volume workouts in microgravity. The outcomes were similar, but shorter workouts save crew time – a valuable resource on missions – and reduce wear and tear on exercise equipment. 4 Future missions may be limited to a single device for both aerobic and resistance exercise, necessitating shorter workouts so each crew member gets a turn. Higher intensity exercise could compensate for these limits.

An investigation called VO2max documented changes in maximum oxygen uptake, which is considered a standard measure of a person’s aerobic and physical working capacity. Long-duration spaceflight caused a significant decrease in maximal oxygen uptake and aerobic exercise capacity. 5 These results have important implications for future long-duration space missions, adding to the evidence that current countermeasures may not be adequate.

Muscle Biopsy , an investigation from ESA (European Space Agency), analyzed molecular changes in skeletal muscle before and after spaceflight and identified an enzyme product that could be used as a possible indicator of muscle health. The findings suggest that current exercise protocols are effective in preventing muscle deconditioning and support improvements in countermeasures to protect crew health and performance on future deep space exploration missions. 6

While current exercise programs appear to moderate changes in musculoskeletal systems, individual results vary. In addition, current regimens likely cannot directly transfer to longer exploration missions due to space constraints, environmental issues such as removal of heat and moisture, device maintenance and repair needs, and the challenges of finding time for exercise and avoiding interference with the work of other crew members. 7

Planned missions to explore the Moon and deep space may last up to three years. Research continues to zero in on the combination of diet, exercise, and medication that could keep astronauts healthy during spaceflight, when they set foot on the Moon or Mars, and when they return to Earth. Because aging, sedentary lifestyles, and illnesses cause bone and muscle loss on Earth, this research also can benefit people on the ground.

Melissa Gaskill International Space Station Research Communications Team NASA’s Johnson Space Center

Search this database of scientific experiments to learn more about those mentioned above.

1 Lambrecht G, Petersen N, Weerts G, Pruett CJ, Evetts SN, et al. The role of physiotherapy in the European Space Agency strategy for preparation and reconditioning of astronauts before and after long duration space flight. Musculoskeletal Science & Practice. 2017 January; 27 Suppl 1S15-S22. DOI: 10.1016/j.math.2016.10.009

2 English KL, Lee SM, Loehr JA, Ploutz-Snyder RJ, Ploutz-Snyder LL. Isokinetic strength changes following long-duration spaceflight on the ISS. Aerospace Medicine and Human Performance. 2015 December 1; 86(12): 68-77. DOI: 10.3357/AMHP.EC09.2015.

3 Scott JM, Feiveson AH, English KL, Spector ER, Sibonga JD, et al. Effects of exercise countermeasures on multisystem function in long duration spaceflight astronauts. npj Microgravity. 2023 February 3; 9(1): 11. DOI: 10.1038/s41526-023-00256-5.

4 English KL, Downs ME, Goetchius EL, Buxton RE, Ryder JW, et al. High intensity training during spaceflight: results from the NASA Sprint Study. npj Microgravity. 2020 August 18; 6(1): 21. DOI:  10.1038/s41526-020-00111-x.

5 Ade CJ, Broxterman RM, Moore Jr. AD, Barstow TJ. Decreases in maximal oxygen uptake following long-duration spaceflight: Role of convective and diffusive O2 transport mechanisms. Journal of Applied Physiology. 2017 April; 122(4): 968-975. DOI: 10.1152/japplphysiol.00280.2016.

6 Blottner D, Moriggi M, Trautmann G, Furlan S, Block K, et al. Nitrosative Stress in Astronaut Skeletal Muscle in Spaceflight. Antioxidants. 2024 April; 13(4): 432. DOI:  10.3390/antiox13040432

7 Scott JP, Weber T, Green DA. Introduction to the Frontiers Research Topic: Optimisation of Exercise Countermeasures for Human Space Flight – Lessons from Terrestrial Physiology and Operational Considerations. Frontiers in Physiology. 2019 10173. DOI: 10.3389/fphys.2019.00173.

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Energy Drinks

Plain water is the best hydrating beverage for most people, but sports and energy drinks are advertised to appeal to those who exercise or need a boost of energy to get through the day.

Though sometimes confused with sports beverages , energy drinks are a different product entirely. They are marketed to increase alertness and energy levels, containing significant amounts of caffeine and as much or more sugar as in soda. Many energy drinks pack about 200 mg of caffeine, the amount in two cups of brewed coffee. Other substances purported to increase energy may be added, like B vitamins and herbs such as ginseng and guarana. Most concerning is a lack of regulation about the safety of these drinks, as well as aggressive marketing tactics geared toward adolescents. [1] The Centers for Disease Control and Prevention reported that in 2007, 1,145 adolescents ages 12 to 17 went to the emergency room for an energy drink-related emergency. In 2011 that number climbed to 1,499. [2]

After water, sugar is the main ingredient in energy drinks. A nutritional comparison shows that a 12-ounce cola drink contains about 39 grams of sugar, 41 grams of sugar in an energy drink. Research has found that consuming high-sugar drinks of any kind can lead to weight gain and an increased risk of type 2 diabetes, cardiovascular disease, and gout.

Because of the amount of sugar and stimulant ingredients, there is concern that these beverages may not be helpful, and even worse, harmful to adolescents and people with certain health conditions.  

Energy Drinks and Health

Sipping a beverage that offers quick energy may appeal to people who feel fatigued or who believe the caffeine can provide an edge when exercising or playing competitive sports. Although statements on the websites of energy drinks warn that these beverages may not be suitable for children, youth are among their largest consumers. An energy drink may be used by adolescents or college students cramming for exams through the night, or by a young athlete before an important game. While it is true that some controlled trials have shown temporary improved alertness and reversal of fatigue after taking energy drinks, as well as enhanced physical performance in young athletes, the majority of studies show an association with negative health effects. These include increased stress, aggressive behaviors like fighting, alcohol/cigarette abuse, increased blood pressure, increased risk of obesity and type 2 diabetes, poor sleep quality, and stomach irritation. [1]

A typical energy drink may contain the following: carbonated water, around 40 grams of sugar (from sucrose and/or glucose), 160 mg or more of caffeine, artificial sweetener , and herbs/substances associated with mental alertness and performance but that lack scientific evidence with controlled trials (taurine, panax ginseng root extract, L-carnitine, L-tartarate, guarana seed extract, B vitamins).

Special concerns with energy drinks:

• Amplified negative health effects in adolescents. Children and teens may experience heightened effects from the high amounts of caffeine, added sugars including high fructose corn syrup, low-calorie sweeteners , and herbal stimulants, partly due to their smaller body size. [3]
• Marketing tactics towards youth. Estimates show more than a 240% increase in U.S. and worldwide sales of energy drinks. It is a $21 billion industry, with marketing campaigns targeting youth and being sold in places that are easily accessed by this age group. [1,4] Youth are exposed to energy drink advertising on children’s websites, computer games, television, supermarkets, and sporting events. [5] Research has shown that adolescents lack maturity in key areas of the brain and are more likely to engage in risk-taking behavior, making them vulnerable to risky behaviors sometimes portrayed in energy drink marketing. Youth are attracted to energy drinks due to effective marketing, influence from peers, and lack of knowledge about their potential harmful effects. [4]
• Negative health outcomes. Emerging evidence has linked energy drink consumption with negative health consequences in youth like risk-seeking behaviors, poor mental health, adverse cardiovascular effects, and metabolic, renal, or dental problems. [1]
• Excessive caffeine. Too much caffeine from any beverage, particularly when several are taken in one day in sensitive individuals, can lead to anxiety, insomnia, heart problems like irregular heartbeat and elevated blood pressure, and in rare cases seizures or cardiac arrest. Some energy drinks may contain as much as 500 mg per can (the amount in 14 cans of cola). [4.6]
• High sugar content. Because of the excessive sugar content in some energy drinks, they carry the same health risks associated with other sugar-sweetened beverages. See Sugary Drinks .
• Dangers with alcohol. A greater danger is introduced if energy drinks are combined with alcohol, a trend largely seen in underage drinkers and associated with binge drinking. Studies suggest that drinking this type of cocktail leads to a greater alcohol intake than if just drinking alcohol alone. This may be because energy drinks increase alertness that masks the signs of inebriation, leading one to believe they can consume even more alcohol. [1] In case reports, high consumption of energy drinks—especially when mixed with alcohol—has been linked to adverse cardiovascular, psychological, and neurologic events, including fatal events. [2]
• Lack of regulation. The Food and Drug Administration (FDA) does not regulate energy drinks but enforces a caffeine limit of 71 mg per 12 ounces of soda; energy drinks typically contain about 120 mg per 12 ounces. However, energy drink manufacturers may choose to classify their product as a supplement to sidestep the caffeine limit. For companies that classify their energy drinks as beverages, the American Beverage Association published voluntary guidelines that advise accurate listings of caffeine content, restriction of marketing to children, and reporting of adverse events to the FDA. However, compliance to these guidelines has been found to be low. [1]
• The International Society of Sports Nutrition (ISSN) issued a position statement on energy drinks after analyzing their safety and efficacy. (8) They concluded that consuming energy drinks 10-60 minutes before exercise can improve mental focus, alertness, anaerobic performance, and endurance in adults, largely through the effects of caffeine. However, other ingredients in these drinks require more study to demonstrate their safety and effects on performance. ISSN cautioned that higher-calorie energy drinks can lead to weight gain, and that their high glycemic load could negatively affect blood glucose and insulin levels. They discouraged use of energy drinks for children and adolescents unless under careful parental monitoring, and for people with diabetes or cardiovascular disease who could be negatively affected by the stimulant ingredients.
• The American Academy of Pediatrics’ Committee on Nutrition and the Council on Sports Medicine and Fitness encourage pediatric health care providers to discourage the use of and discuss potential health risks of stimulant ingredients in energy drinks with youth and parents, and to limit or avoid sugar-sweetened beverages of any kind in youth due to risk of excessive calorie intake and weight gain, as well as dental erosion. [7]  

Bottom Line

Water that is calorie-free and accessible without cost to most people is the beverage of choice taken with and between meals. Energy drinks are a source of caffeine that people may choose as an alternative to coffee or tea. However, they also contain high amounts of sugar, vitamins, and herbs that may not be necessary for the average person. Energy drinks can pose a health risk in vulnerable groups including children, teenagers, pregnant women, and those with medical conditions like diabetes and cardiovascular disease. Adults who choose to consume energy drinks should check the label for caffeine content and avoid high consumption (over 200 mg of caffeine per drink); consumption in combination with alcohol should be avoided. [9] Pediatricians should discuss the use of energy drinks with their young patients and parents to ensure that all are aware of the health risks, and if used, are monitored carefully. [7]  

Sugary Drinks Sports Drinks

• Al-Shaar L, Vercammen K, Lu C, Richardson S, Tamez M, Mattei J. Health Effects and Public Health Concerns of Energy Drink Consumption in the United States: A Mini-Review. Front Public Health . 2017;5:225.
• Ehlers A, Marakis G, Lampen A, Hirsch-Ernst KI. Risk assessment of energy drinks with focus on cardiovascular parameters and energy drink consumption in Europe. Food and Chemical Toxicology . 2019 Aug 1;130:109-21.
• Centers for Disease Control and Prevention. The Buzz on Energy Drinks.  https://www.cdc.gov/healthyschools/nutrition/energy.htm Accessed 8/21/19.
• Pound CM, Blair B; Canadian Paediatric Society, Nutrition and Gastroenterology Committee, Ottawa, Ontario. Energy and sports drinks in children and adolescents. Paediatr Child Health . 2017 Oct;22(7):406-410.
• De Sanctis V, Soliman N, Soliman AT, Elsedfy H, Di Maio S, El Kholy M, Fiscina B. Caffeinated energy drink consumption among adolescents and potential health consequences associated with their use: a significant public health hazard. Acta Biomed . 2017 Aug 23;88(2):222-231.
• Wiggers D, Asbridge M, Baskerville NB, Reid JL, Hammond D. Exposure to Caffeinated Energy Drink Marketing and Educational Messages among Youth and Young Adults in Canada. Int J Environ Res Public Health . 2019 Feb 21;16(4).
• Schneider MB, Benjamin HJ. Sports drinks and energy drinks for children and adolescents: Are they appropriate? Pediatrics . 2011;127(6):1182–9.
• Campbell B, Wilborn C, La Bounty P, Taylor L, Nelson MT, Greenwood M, Ziegenfuss TN, Lopez HL, Hoffman JR, Stout JR, Schmitz S, Collins R, Kalman DS, Antonio J, Kreider RB. International Society of Sports Nutrition position stand: energy drinks. J Int Soc Sports Nutr . 2013 Jan 3;10(1):1.
• van Dam RM, Hu FB, Willett WC. Coffee, Caffeine, and Health.  NEJM .  2020 Jul 23; 383:369-378

Last reviewed July 2020

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Media Center 5/17/2024 1:00:00 PM Saquandra Heath

Sports betting culture negatively impacts mental health; NCAA works to support student-athletes

Imagine playing a sport you love, giving it your all in every game. In addition, you're balancing your academic studies as you pressure yourself to succeed in the classroom and on the field. If that weren't enough pressure, you also have strangers harassing you via social media, spouting abusive threats because they've lost money based on your performance or that of your team. 

It's a mental health nightmare.

Harassment related to sports betting can cause serious harm to student-athlete mental health and well-being. The NCAA is doing more than ever to address the rise of sports betting — including monitoring and flagging abusive social media content, providing e-learning content, educating on campuses and even lobbying states to change sports betting laws. The NCAA believes bets placed on individual college athletes' performances, known as prop bets, should be eliminated. These types of bets target the individual for harassment and are more easily manipulated, threatening competition integrity. That's why the NCAA is  advocating  for elimination of player-specific prop bets in collegiate competitions. The NCAA's efforts are paying off.

For example, in  Ohio , student-athletes, campus leaders, athletics administrators and the national office collaborated with gaming regulators to remove prop bets from their books across the state. Since Ohio's action, Vermont, Maryland, Louisiana and others have moved to prohibit prop bets. The NCAA is also urging states to implement antiharassment measures, including implementation of a reporting system to allow states to place certain bettors who harass student-athletes on a list that excludes them from being able to place bets.  West Virginia  has taken action in this space, creating a framework that other states are interested in modeling. Student-athletes are speaking out about this issue and working to create awareness about the detrimental impacts of harassment. Their voices are critical to this effort. 

Just 12 days after North Carolina legalized sports betting, including player prop bets on college competitions, North Carolina men's basketball student-athlete Armando Bacot publicly reported receiving betting-related abuse via private social media direct messages after his performance. 

"It's terrible. Even at the last game, I guess I didn't get enough rebounds or something. I thought I played pretty good last game, but I looked at my DMs, and I got like over 100 messages from people telling me I sucked and stuff like that because I didn't get enough rebounds," Bacot said.

Since these remarks and NCAA outreach, North Carolina lawmakers have  filed bills  to ban college player prop bets. State legislators in New Jersey have also filed a  bill , which has bipartisan support, that would ban college prop bets.

Earlier this year, Cody Shimp and Morgan Wynne, chair and vice chair of the Division I Student-Athlete Advisory Committee, joined NCAA President Charlie Baker in writing a memo to college athletics leaders about the severity of online harassment. They urged campus stakeholders to use their voice to effect change and increase safeguards to protect student-athletes from abuse.

"The sports betting landscape in America is rapidly evolving and requires careful consideration of all involved stakeholders," Shimp, Wynne and Baker said in the memo. "The NCAA will continue to do its part to lead in this space to identify practical solutions to guard against the dangers of sports betting, such as harassment. Your role is critical in driving change locally. Together, we can help our student-athletes compete in a safer college sports atmosphere."

The NCAA has launched several initiatives to address harassment, including engaging  Signify Group . Its Threat Matrix artificial intelligence service supports the Association in studying and responding to online abuse and threats directed at NCAA championship participants, including student-athletes, coaches, officials and committee members for the 2023-24 championship season. This unique initiative is intended to further promote the mental health and well-being of the college sports community through data collection and analytics.

While the championship season is still underway, some trends the data already shows include:

• One in 3 high-profile athletes receive abusive messages from someone with a betting interest. 
• Higher-profile events with sports betting markets attract increased volumes of abuse or threats.
• Ninety percent of harassment is generated online or through social media. 
• In sports with high volumes of betting, 15%-25% of all abuse surrounding that competition is betting related. 
• During March Madness, Signify covered nearly 1,000 Division I men's and women's basketball student-athletes, 64 teams, over 280 coaches and 120 NCAA match officials. 
• Across the Division I Men's and Women's Basketball Championships, over 54,000 posts/comments were flagged by Signify's AI for potential abuse or threats and reviewed by human in-house analysts. 
• Of those 54,000, 4,000 were confirmed as abusive or threatening and reported to the relevant social media platforms, with some elevated to law enforcement.
• More than 540 abusive betting-related messages were directed at men's and women's basketball student-athletes, including death threats. 
• Women's basketball student-athletes received approximately three times more threats than men's basketball student-athletes.
• Student-athletes are not the only group experiencing these threats and abuse. Game officials, administrators and other athletics employees have been harassed related to their respective involvement in competitions.

Insights from the initial set of championships covered by the service will be released later and will be used as a benchmark for monitoring efforts at future NCAA championships. Furthermore, Signify's unique DM risk management service will also be offered to student-athletes and officials to protect them from the type of abuse experienced by Bacot. 

Additionally, the NCAA has expanded programming through  e-learning content  and with EPIC Global Solutions to educate student-athletes not only about how to handle abusive threats, but more broadly on the risks of sports betting and problem gambling. The program won  Player Protection Initiative of the Year  at the 2024 SBC Summit, a conference and trade show focused on the online betting and gambling industry.

To date, more than 55,000 student-athletes have been educated through EPIC Global Solutions lived-experience sessions, leaving a lasting impact: 

"This seminar really changed my perspective on gambling and the severity of it. … It was very educational and informative on the risks, factors and harm betting can do," said one student-athlete in an anonymous survey following an EPIC session. "Really caught my attention on how this can really be a problem. I've seen people with betting addiction but just never knew how to help."

Increasing education and growing awareness of the complexities of sports betting fueled the NCAA's  Draw the Line  campaign, launched at the start of March Madness. 

The campaign prioritizes student-athlete education on the effects of sports betting while also addressing responsible gambling for all who consume and participate in college sports.

While the campaign is focused on social media promotion to reach student-athletes where they are, it also includes a  membership toolkit  for member schools and conferences to access resources that extend the campaign for on-campus education. 

All these initiatives have been developed and implemented to help protect student-athlete well-being and mental health to safeguard the overall student-athlete experience in a rapidly evolving landscape. 

If you are a student-athlete or campus administrator and want to learn more about the resources the NCAA is making available,  click here . If you are a student-athlete, you live in a state that permits prop bets and you want to help get these bets pulled from the market, please email  [email protected] .

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China’s Lenovo extends revenue growth streak, beats expectations

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