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Peer-reviewed

Research Article

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

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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

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

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

PLOS

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

Fig 1

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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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 ]).

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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).

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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.

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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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  • Systematic review update
  • Open access
  • Published: 21 June 2023

The impact of sports participation on mental health and social outcomes in adults: a systematic review and the ‘Mental Health through Sport’ conceptual model

  • Narelle Eather   ORCID: orcid.org/0000-0002-6320-4540 1 , 2 ,
  • Levi Wade   ORCID: orcid.org/0000-0002-4007-5336 1 , 3 ,
  • Aurélie Pankowiak   ORCID: orcid.org/0000-0003-0178-513X 4 &
  • Rochelle Eime   ORCID: orcid.org/0000-0002-8614-2813 4 , 5  

Systematic Reviews volume  12 , Article number:  102 ( 2023 ) Cite this article

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Sport is a subset of physical activity that can be particularly beneficial for short-and-long-term physical and mental health, and social outcomes in adults. This study presents the results of an updated systematic review of the mental health and social outcomes of community and elite-level sport participation for adults. The findings have informed the development of the ‘Mental Health through Sport’ conceptual model for adults.

Nine electronic databases were searched, with studies published between 2012 and March 2020 screened for inclusion. Eligible qualitative and quantitative studies reported on the relationship between sport participation and mental health and/or social outcomes in adult populations. Risk of bias (ROB) was determined using the Quality Assessment Tool (quantitative studies) or Critical Appraisal Skills Programme (qualitative studies).

The search strategy located 8528 articles, of which, 29 involving adults 18–84 years were included for analysis. Data was extracted for demographics, methodology, and study outcomes, and results presented according to study design. The evidence indicates that participation in sport (community and elite) is related to better mental health, including improved psychological well-being (for example, higher self-esteem and life satisfaction) and lower psychological ill-being (for example, reduced levels of depression, anxiety, and stress), and improved social outcomes (for example, improved self-control, pro-social behavior, interpersonal communication, and fostering a sense of belonging). Overall, adults participating in team sport had more favorable health outcomes than those participating in individual sport, and those participating in sports more often generally report the greatest benefits; however, some evidence suggests that adults in elite sport may experience higher levels of psychological distress. Low ROB was observed for qualitative studies, but quantitative studies demonstrated inconsistencies in methodological quality.

Conclusions

The findings of this review confirm that participation in sport of any form (team or individual) is beneficial for improving mental health and social outcomes amongst adults. Team sports, however, may provide more potent and additional benefits for mental and social outcomes across adulthood. This review also provides preliminary evidence for the Mental Health through Sport model, though further experimental and longitudinal evidence is needed to establish the mechanisms responsible for sports effect on mental health and moderators of intervention effects. Additional qualitative work is also required to gain a better understanding of the relationship between specific elements of the sporting environment and mental health and social outcomes in adult participants.

Peer Review reports

Introduction

The organizational structure of sport and the performance demands characteristic of sport training and competition provide a unique opportunity for participants to engage in health-enhancing physical activity of varied intensity, duration, and mode; and the opportunity to do so with other people as part of a team and/or club. Participation in individual and team sports have shown to be beneficial to physical, social, psychological, and cognitive health outcomes [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. Often, the social and mental health benefits facilitated through participation in sport exceed those achieved through participation in other leisure-time or recreational activities [ 8 , 9 , 10 ]. Notably, these benefits are observed across different sports and sub-populations (including youth, adults, older adults, males, and females) [ 11 ]. However, the evidence regarding sports participation at the elite level is limited, with available research indicating that elite athletes may be more susceptible to mental health problems, potentially due to the intense mental and physical demands placed on elite athletes [ 12 ].

Participation in sport varies across the lifespan, with children representing the largest cohort to engage in organized community sport [ 13 ]. Across adolescence and into young adulthood, dropout from organized sport is common, and especially for females [ 14 , 15 , 16 ], and adults are shifting from organized sports towards leisure and fitness activities, where individual activities (including swimming, walking, and cycling) are the most popular [ 13 , 17 , 18 , 19 ]. Despite the general decline in sport participation with age [ 13 ], the most recent (pre-COVID) global data highlights that a range of organized team sports (such as, basketball, netball volleyball, and tennis) continue to rank highly amongst adult sport participants, with soccer remaining a popular choice across all regions of the world [ 13 ]. It is encouraging many adults continue to participate in sport and physical activities throughout their lives; however, high rates of dropout in youth sport and non-participation amongst adults means that many individuals may be missing the opportunity to reap the potential health benefits associated with participation in sport.

According to the World Health Organization, mental health refers to a state of well-being and effective functioning in which an individual realizes his or her own abilities, is resilient to the stresses of life, and is able to make a positive contribution to his or her community [ 20 ]. Mental health covers three main components, including psychological, emotional and social health [ 21 ]. Further, psychological health has two distinct indicators, psychological well-being (e.g., self-esteem and quality of life) and psychological ill-being (e.g., pre-clinical psychological states such as psychological difficulties and high levels of stress) [ 22 ]. Emotional well-being describes how an individual feels about themselves (including life satisfaction, interest in life, loneliness, and happiness); and social well–being includes an individual’s contribution to, and integration in society [ 23 ].

Mental illnesses are common among adults and incidence rates have remained consistently high over the past 25 years (~ 10% of people affected globally) [ 24 ]. Recent statistics released by the World Health Organization indicate that depression and anxiety are the most common mental disorders, affecting an estimated 264 million people, ranking as one of the main causes of disability worldwide [ 25 , 26 ]. Specific elements of social health, including high levels of isolation and loneliness among adults, are now also considered a serious public health concern due to the strong connections with ill-health [ 27 ]. Participation in sport has shown to positively impact mental and social health status, with a previous systematic review by Eime et al. (2013) indicated that sports participation was associated with lower levels of perceived stress, and improved vitality, social functioning, mental health, and life satisfaction [ 1 ]. Based on their findings, the authors developed a conceptual model (health through sport) depicting the relationship between determinants of adult sports participation and physical, psychological, and social health benefits of participation. In support of Eime’s review findings, Malm and colleagues (2019) recently described how sport aids in preventing or alleviating mental illness, including depressive symptoms and anxiety or stress-related disease [ 7 ]. Andersen (2019) also highlighted that team sports participation is associated with decreased rates of depression and anxiety [ 11 ]. In general, these reviews report stronger effects for sports participation compared to other types of physical activity, and a dose–response relationship between sports participation and mental health outcomes (i.e., higher volume and/or intensity of participation being associated with greater health benefits) when adults participate in sports they enjoy and choose [ 1 , 7 ]. Sport is typically more social than other forms of physical activity, including enhanced social connectedness, social support, peer bonding, and club support, which may provide some explanation as to why sport appears to be especially beneficial to mental and social health [ 28 ].

Thoits (2011) proposed several potential mechanisms through which social relationships and social support improve physical and psychological well-being [ 29 ]; however, these mechanisms have yet to be explored in the context of sports participation at any level in adults. The identification of the mechanisms responsible for such effects may direct future research in this area and help inform future policy and practice in the delivery of sport to enhance mental health and social outcomes amongst adult participants. Therefore, the primary objective of this review was to examine and synthesize all research findings regarding the relationship between sports participation, mental health and social outcomes at the community and elite level in adults. Based on the review findings, the secondary objective was to develop the ‘Mental Health through Sport’ conceptual model.

This review has been registered in the PROSPERO systematic review database and assigned the identifier: CRD42020185412. The conduct and reporting of this systematic review also follows the Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 30 ] (PRISMA flow diagram and PRISMA Checklist available in supplementary files ). This review is an update of a previous review of the same topic [ 31 ], published in 2012.

Identification of studies

Nine electronic databases (CINAHL, Cochrane Library, Google Scholar, Informit, Medline, PsychINFO, Psychology and Behavioural Sciences Collection, Scopus, and SPORTDiscus) were systematically searched for relevant records published from 2012 to March 10, 2020. The following key terms were developed by all members of the research team (and guided by previous reviews) and entered into these databases by author LW: sport* AND health AND value OR benefit* OR effect* OR outcome* OR impact* AND psych* OR depress* OR stress OR anxiety OR happiness OR mood OR ‘quality of life’ OR ‘social health’ OR ‘social relation*’ OR well* OR ‘social connect*’ OR ‘social functioning’ OR ‘life satisfac*’ OR ‘mental health’ OR social OR sociolog* OR affect* OR enjoy* OR fun. Where possible, Medical Subject Headings (MeSH) were also used.

Criteria for inclusion/exclusion

The titles of studies identified using this method were screened by LW. Abstract and full text of the articles were reviewed independently by LW and NE. To be included in the current review, each study needed to meet each of the following criteria: (1) published in English from 2012 to 2020; (2) full-text available online; (3) original research or report published in a peer-reviewed journal; (4) provides data on the psychological or social effects of participation in sport (with sport defined as a subset of exercise that can be undertaken individually or as a part of a team, where participants adhere to a common set of rules or expectations, and a defined goal exists); (5) the population of interest were adults (18 years and older) and were apparently healthy. All papers retrieved in the initial search were assessed for eligibility by title and abstract. In cases where a study could not be included or excluded via their title and abstract, the full text of the article was reviewed independently by two of the authors.

Data extraction

For the included studies, the following data was extracted independently by LW and checked by NE using a customized Google Docs spreadsheet: author name, year of publication, country, study design, aim, type of sport (e.g., tennis, hockey, team, individual), study conditions/comparisons, sample size, where participants were recruited from, mean age of participants, measure of sports participation, measure of physical activity, psychological and/or social outcome/s, measure of psychological and/or social outcome/s, statistical method of analysis, changes in physical activity or sports participation, and the psychological and/or social results.

Risk of bias (ROB) assessment

A risk of bias was performed by LW and AP independently using the ‘Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies’ OR the ‘Quality Assessment of Controlled Intervention Studies’ for the included quantitative studies, and the ‘Critical Appraisal Skills Programme (CASP) Checklist for the included qualitative studies [ 32 , 33 ]. Any discrepancies in the ROB assessments were discussed between the two reviewers, and a consensus reached.

The search yielded 8528 studies, with a total of 29 studies included in the systematic review (Fig.  1 ). Tables  1 and 2 provide a summary of the included studies. The research included adults from 18 to 84 years old, with most of the evidence coming from studies targeting young adults (18–25 years). Study samples ranged from 14 to 131, 962, with the most reported psychological outcomes being self-rated mental health ( n  = 5) and depression ( n  = 5). Most studies did not investigate or report the link between a particular sport and a specific mental health or social outcome; instead, the authors’ focused on comparing the impact of sport to physical activity, and/or individual sports compared to team sports. The results of this review are summarized in the following section, with findings presented by study design (cross-sectional, experimental, and longitudinal).

figure 1

Flow of studies through the review process

Effects of sports participation on psychological well-being, ill-being, and social outcomes

Cross-sectional evidence.

This review included 14 studies reporting on the cross-sectional relationship between sports participation and psychological and/or social outcomes. Sample sizes range from n  = 414 to n  = 131,962 with a total of n  = 239,394 adults included across the cross-sectional studies.

The cross-sectional evidence generally supports that participation in sport, and especially team sports, is associated with greater mental health and psychological wellbeing in adults compared to non-participants [ 36 , 59 ]; and that higher frequency of sports participation and/or sport played at a higher level of competition, are also linked to lower levels of mental distress in adults . This was not the case for one specific study involving ice hockey players aged 35 and over, with Kitchen and Chowhan (2016) Kitchen and Chowhan (2016) reporting no relationship between participation in ice hockey and either mental health, or perceived life stress [ 54 ]. There is also some evidence to support that previous participation in sports (e.g., during childhood or young adulthood) is linked to better mental health outcomes later in life, including improved mental well-being and lower mental distress [ 59 ], even after controlling for age and current physical activity.

Compared to published community data for adults, elite or high-performance adult athletes demonstrated higher levels of body satisfaction, self-esteem, and overall life satisfaction [ 39 ]; and reported reduced tendency to respond to distress with anger and depression. However, rates of psychological distress were higher in the elite sport cohort (compared to community norms), with nearly 1 in 5 athletes reporting ‘high to very high’ distress, and 1 in 3 reporting poor mental health symptoms at a level warranting treatment by a health professional in one study ( n  = 749) [ 39 ].

Four studies focused on the associations between physical activity and sports participation and mental health outcomes in older adults. Physical activity was associated with greater quality of life [ 56 ], with the relationship strongest for those participating in sport in middle age, and for those who cycled in later life (> 65) [ 56 ]. Group physical activities (e.g., walking groups) and sports (e.g., golf) were also significantly related to excellent self-rated health, low depressive symptoms, high health-related quality of life (HRQoL) and a high frequency of laughter in males and females [ 60 , 61 ]. No participation or irregular participation in sport was associated with symptoms of mild to severe depression in older adults [ 62 ].

Several cross-sectional studies examined whether the effects of physical activity varied by type (e.g., total physical activity vs. sports participation). In an analysis of 1446 young adults (mean age = 18), total physical activity, moderate-to-vigorous physical activity, and team sport were independently associated with mental health [ 46 ]. Relative to individual physical activity, after adjusting for covariates and moderate-to-vigorous physical activity (MVPA), only team sport was significantly associated with improved mental health. Similarly, in a cross-sectional analysis of Australian women, Eime, Harvey, Payne (2014) reported that women who engaged in club and team-based sports (tennis or netball) reported better mental health and life satisfaction than those who engaged in individual types of physical activity [ 47 ]. Interestingly, there was no relationship between the amount of physical activity and either of these outcomes, suggesting that other qualities of sports participation contribute to its relationship to mental health and life satisfaction. There was also some evidence to support a relationship between exercise type (ball sports, aerobic activity, weightlifting, and dancing), and mental health amongst young adults (mean age 22 years) [ 48 ], with ball sports and dancing related to fewer symptoms of depression in students with high stress; and weightlifting related to fewer depressive symptoms in weightlifters exhibiting low stress.

Longitudinal evidence

Eight studies examined the longitudinal relationship between sports participation and either mental health and/or social outcomes. Sample sizes range from n  = 113 to n  = 1679 with a total of n  = 7022 adults included across the longitudinal studies.

Five of the included longitudinal studies focused on the relationship between sports participation in childhood or adolescence and mental health in young adulthood. There is evidence that participation in sport in high-school is protective of future symptoms of anxiety (including panic disorder, generalised anxiety disorder, social phobia, and agoraphobia) [ 42 ]. Specifically, after controlling for covariates (including current physical activity), the number of years of sports participation in high school was shown to be protective of symptoms of panic and agoraphobia in young adulthood, but not protective of symptoms of social phobia or generalized anxiety disorder [ 42 ]. A comparison of individual or team sports participation also revealed that participation in either context was protective of panic disorder symptoms, while only team sport was protective of agoraphobia symptoms, and only individual sport was protective of social phobia symptoms. Furthermore, current and past sports team participation was shown to negatively relate to adult depressive symptoms [ 43 ]; drop out of sport was linked to higher depressive symptoms in adulthood compared to those with maintained participation [ 9 , 22 , 63 ]; and consistent participation in team sports (but not individual sport) in adolescence was linked to higher self-rated mental health, lower perceived stress and depressive symptoms, and lower depression scores in early adulthood [ 53 , 58 ].

Two longitudinal studies [ 35 , 55 ], also investigated the association between team and individual playing context and mental health. Dore and colleagues [ 35 ] reported that compared to individual activities, being active in informal groups (e.g., yoga, running groups) or team sports was associated with better mental health, fewer depressive symptoms and higher social connectedness – and that involvement in team sports was related to better mental health regardless of physical activity volume. Kim and James [ 55 ] discovered that sports participation led to both short and long-term improvements in positive affect and life satisfaction.

A study on social outcomes related to mixed martial-arts (MMA) and Brazilian jiu-jitsu (BJJ) showed that both sports improved practitioners’ self-control and pro-social behavior, with greater improvements seen in the BJJ group [ 62 ]. Notably, while BJJ reduced participants’ reported aggression, there was a slight increase in MMA practitioners, though it is worth mentioning that individuals who sought out MMA had higher levels of baseline aggression.

Experimental evidence

Six of the included studies were experimental or quasi-experimental. Sample sizes ranged from n  = 28 to n  = 55 with a total of n  = 239 adults included across six longitudinal studies. Three studies involved a form of martial arts (such as judo and karate) [ 45 , 51 , 52 ], one involved a variety of team sports (such as netball, soccer, and cricket) [ 34 ], and the remaining two focused on badminton [ 57 ] and handball [ 49 ].

Brinkley and colleagues [ 34 ] reported significant effects on interpersonal communication (but not vitality, social cohesion, quality of life, stress, or interpersonal relationships) for participants ( n  = 40) engaging in a 12-week workplace team sports intervention. Also using a 12-week intervention, Hornstrup et al. [ 49 ] reported a significant improvement in mental energy (but not well-being or anxiety) in young women (mean age = 24; n  = 28) playing in a handball program. Patterns et al. [ 57 ] showed that in comparison to no exercise, participation in an 8-week badminton or running program had no significant improvement on self-esteem, despite improvements in perceived and actual fitness levels.

Three studies examined the effect of martial arts on the mental health of older adults (mean ages 79 [ 52 ], 64 [ 51 ], and 70 [ 45 ] years). Participation in Karate-Do had positive effects on overall mental health, emotional wellbeing, depression and anxiety when compared to other activities (physical, cognitive, mindfulness) and a control group [ 51 , 52 ]. Ciaccioni et al. [ 45 ] found that a Judo program did not affect either the participants’ mental health or their body satisfaction, citing a small sample size, and the limited length of the intervention as possible contributors to the findings.

Qualitative evidence

Three studies interviewed current or former sports players regarding their experiences with sport. Chinkov and Holt [ 41 ] reported that jiu-jitsu practitioners (mean age 35 years) were more self-confident in their lives outside of the gym, including improved self-confidence in their interactions with others because of their training. McGraw and colleagues [ 37 ] interviewed former and current National Football League (NFL) players and their families about its impact on the emotional and mental health of the players. Most of the players reported that their NFL career provided them with social and emotional benefits, as well as improvements to their self-esteem even after retiring. Though, despite these benefits, almost all the players experienced at least one mental health challenge during their career, including depression, anxiety, or difficulty controlling their temper. Some of the players and their families reported that they felt socially isolated from people outside of the national football league.

Through a series of semi-structured interviews and focus groups, Thorpe, Anders [ 40 ] investigated the impact of an Aboriginal male community sporting team on the health of its players. The players reported they felt a sense of belonging when playing in the team, further noting that the social and community aspects were as important as the physical health benefits. Participating in the club strengthened the cultural identity of the players, enhancing their well-being. The players further noted that participation provided them with enjoyment, stress relief, a sense of purpose, peer support, and improved self-esteem. Though they also noted challenges, including the presence of racism, community conflict, and peer-pressure.

Quality of studies

Full details of our risk of bias (ROB) results are provided in Supplementary Material A . Of the three qualitative studies assessed using the Critical Appraisal Skills Program (CASP), all three were deemed to have utilised and reported appropriate methodological standards on at least 8 of the 10 criteria. Twenty studies were assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies, with all studies clearly reporting the research question/s or objective/s and study population. However, only four studies provided a justification for sample size, and less than half of the studies met quality criteria for items 6, 7, 9, or 10 (and items 12 and 13 were largely not applicable). Of concern, only four of the observational or cohort studies were deemed to have used clearly defined, valid, and reliable exposure measures (independent variables) and implemented them consistently across all study participants. Six studies were assessed using the Quality Assessment of Controlled Intervention Studies, with three studies described as a randomized trial (but none of the three reported a suitable method of randomization, concealment of treatment allocation, or blinding to treatment group assignment). Three studies showed evidence that study groups were similar at baseline for important characteristics and an overall drop-out rate from the study < 20%. Four studies reported high adherence to intervention protocols (with two not reporting) and five demonstrated that.study outcomes were assessed using valid and reliable measures and implemented consistently across all study participants. Importantly, researchers did not report or have access to validated instruments for assessing sport participation or physical activity amongst adults, though most studies provided psychometrics for their mental health outcome measure/s. Only one study reported that the sample size was sufficiently powered to detect a difference in the main outcome between groups (with ≥ 80% power) and that all participants were included in the analysis of results (intention-to-treat analysis). In general, the methodological quality of the six randomised studies was deemed low.

Initially, our discussion will focus on the review findings regarding sports participation and well-being, ill-being, and psychological health. However, the heterogeneity and methodological quality of the included research (especially controlled trials) should be considered during the interpretation of our results. Considering our findings, the Mental Health through Sport conceptual model for adults will then be presented and discussed and study limitations outlined.

Sports participation and psychological well-being

In summary, the evidence presented here indicates that for adults, sports participation is associated with better overall mental health [ 36 , 46 , 47 , 59 ], mood [ 56 ], higher life satisfaction [ 39 , 47 ], self-esteem [ 39 ], body satisfaction [ 39 ], HRQoL [ 60 ], self-rated health [ 61 ], and frequency of laughter [ 61 ]. Sports participation has also shown to be predictive of better psychological wellbeing over time [ 35 , 53 ], higher positive affect [ 55 ], and greater life satisfaction [ 55 ]. Furthermore, higher frequency of sports participation and/or sport played at a higher level of competition, have been linked to lower levels of mental distress, higher levels of body satisfaction, self-esteem, and overall life satisfaction in adults [ 39 ].

Despite considerable heterogeneity of sports type, cross-sectional and experimental research indicate that team-based sports participation, compared to individual sports and informal group physical activity, has a more positive effect on mental energy [ 49 ], physical self-perception [ 57 ], and overall psychological health and well-being in adults, regardless of physical activity volume [ 35 , 46 , 47 ]. And, karate-do benefits the subjective well-being of elderly practitioners [ 51 , 52 ]. Qualitative research in this area has queried participants’ experiences of jiu-jitsu, Australian football, and former and current American footballers. Participants in these sports reported that their participation was beneficial for psychological well-being [ 37 , 40 , 41 ], improved self-esteem [ 37 , 40 , 41 ], and enjoyment [ 37 ].

Sports participation and psychological ill-being

Of the included studies, n  = 19 examined the relationship between participating in sport and psychological ill-being. In summary, there is consistent evidence that sports participation is related to lower depression scores [ 43 , 48 , 61 , 62 ]. There were mixed findings regarding psychological stress, where participation in childhood (retrospectively assessed) was related to lower stress in young adulthood [ 41 ], but no relationship was identified between recreational hockey in adulthood and stress [ 54 ]. Concerning the potential impact of competing at an elite level, there is evidence of higher stress in elite athletes compared to community norms [ 39 ]. Further, there is qualitative evidence that many current or former national football league players experienced at least one mental health challenge, including depression, anxiety, difficulty controlling their temper, during their career [ 37 ].

Evidence from longitudinal research provided consistent evidence that participating in sport in adolescence is protective of symptoms of depression in young adulthood [ 43 , 53 , 58 , 63 ], and further evidence that participating in young adulthood is related to lower depressive symptoms over time (6 months) [ 35 ]. Participation in adolescence was also protective of manifestations of anxiety (panic disorder and agoraphobia) and stress in young adulthood [ 42 ], though participation in young adulthood was not related to a more general measure of anxiety [ 35 ] nor to changes in negative affect [ 55 ]). The findings from experimental research were mixed. Two studies examined the effect of karate-do on markers of psychological ill-being, demonstrating its capacity to reduce anxiety [ 52 ], with some evidence of its effectiveness on depression [ 51 ]. The other studies examined small-sided team-based games but showed no effect on stress or anxiety [ 34 , 49 ]. Most studies did not differentiate between team and individual sports, though one study found that adolescents who participated in team sports (not individual sports) in secondary school has lower depression scores in young adulthood [ 58 ].

Sports participation and social outcomes

Seven of the included studies examined the relationship between sports participation and social outcomes. However, very few studies examined social outcomes or tested a social outcome as a potential mediator of the relationship between sport and mental health. It should also be noted that this body of evidence comes from a wide range of sport types, including martial arts, professional football, and workplace team-sport, as well as different methodologies. Taken as a whole, the evidence shows that participating in sport is beneficial for several social outcomes, including self-control [ 50 ], pro-social behavior [ 50 ], interpersonal communication [ 34 ], and fostering a sense of belonging [ 40 ]. Further, there is evidence that group activity, for example team sport or informal group activity, is related to higher social connectedness over time, though analyses showed that social connectedness was not a mediator for mental health [ 35 ].

There were conflicting findings regarding social effects at the elite level, with current and former NFL players reporting that they felt socially isolated during their career [ 37 ], whilst another study reported no relationship between participation at the elite level and social dysfunction [ 39 ]. Conversely, interviews with a group of indigenous men revealed that they felt as though participating in an all-indigenous Australian football team provided them with a sense of purpose, and they felt as though the social aspect of the game was as important as the physical benefits it provides [ 40 ].

Mental health through sport conceptual model for adults

The ‘Health through Sport’ model provides a depiction of the determinants and benefits of sports participation [ 31 ]. The model recognises that the physical, mental, and social benefits of sports participation vary by the context of sport (e.g., individual vs. team, organized vs. informal). To identify the elements of sport which contribute to its effect on mental health outcomes, we describe the ‘Mental Health through Sport’ model (Fig.  2 ). The model proposes that the social and physical elements of sport each provide independent, and likely synergistic contributions to its overall influence on mental health.

figure 2

The Mental Health through Sport conceptual model

The model describes two key pathways through which sport may influence mental health: physical activity, and social relationships and support. Several likely moderators of this effect are also provided, including sport type, intensity, frequency, context (team vs. individual), environment (e.g., indoor vs. outdoor), as well as the level of competition (e.g., elite vs. amateur).

The means by which the physical activity component of sport may influence mental health stems from the work of Lubans et al., who propose three key groups of mechanisms: neurobiological, psychosocial, and behavioral [ 64 ]. Processes whereby physical activity may enhance psychological outcomes via changes in the structural and functional composition of the brain are referred to as neurobiological mechanisms [ 65 , 66 ]. Processes whereby physical activity provides opportunities for the development of self-efficacy, opportunity for mastery, changes in self-perceptions, the development of independence, and for interaction with the environment are considered psychosocial mechanisms. Lastly, processes by which physical activity may influence behaviors which ultimately affect psychological health, including changes in sleep duration, self-regulation, and coping skills, are described as behavioral mechanisms.

Playing sport offers the opportunity to form relationships and to develop a social support network, both of which are likely to influence mental health. Thoits [ 29 ] describes 7 key mechanisms by which social relationships and support may influence mental health: social influence/social comparison; social control; role-based purpose and meaning (mattering); self-esteem; sense of control; belonging and companionship; and perceived support availability [ 29 ]. These mechanisms and their presence within a sporting context are elaborated below.

Subjective to the attitudes and behaviors of individuals in a group, social influence and comparison may facilitate protective or harmful effects on mental health. Participants in individual or team sport will be influenced and perhaps steered by the behaviors, expectations, and norms of other players and teams. When individual’s compare their capabilities, attitudes, and values to those of other participants, their own behaviors and subsequent health outcomes may be affected. When others attempt to encourage or discourage an individual to adopt or reject certain health practices, social control is displayed [ 29 ]. This may evolve as strategies between players (or between players and coach) are discussion and implemented. Likewise, teammates may try to motivate each another during a match to work harder, or to engage in specific events or routines off-field (fitness programs, after game celebrations, attending club events) which may impact current and future physical and mental health.

Sport may also provide behavioral guidance, purpose, and meaning to its participants. Role identities (positions within a social structure that come with reciprocal obligations), often formed as a consequence of social ties formed through sport. Particularly in team sports, participants come to understand they form an integral part of the larger whole, and consequently, they hold certain responsibility in ensuring the team’s success. They have a commitment to the team to, train and play, communicate with the team and a potential responsibility to maintain a high level of health, perform to their capacity, and support other players. As a source of behavioral guidance and of purpose and meaning in life, these identities are likely to influence mental health outcomes amongst sport participants.

An individual’s level of self-esteem may be affected by the social relationships and social support provided through sport; with improved perceptions of capability (or value within a team) in the sporting domain likely to have positive impact on global self-esteem and sense of worth [ 64 ]. The unique opportunities provided through participation in sport, also allow individuals to develop new skills, overcome challenges, and develop their sense of self-control or mastery . Working towards and finding creative solutions to challenges in sport facilitates a sense of mastery in participants. This sense of mastery may translate to other areas of life, with individual’s developing the confidence to cope with varied life challenges. For example, developing a sense of mastery regarding capacity to formulate new / creative solutions when taking on an opponent in sport may result in greater confidence to be creative at work. Social relationships and social support provided through sport may also provide participants with a source of belonging and companionship. The development of connections (on and off the field) to others who share common interests, can build a sense of belonging that may mediate improvements in mental health outcomes. Social support is often provided emotionally during expressions of trust and care; instrumentally via tangible assistance; through information such as advice and suggestions; or as appraisal such feedback. All forms of social support provided on and off the field contribute to a more generalised sense of perceived support that may mediate the effect of social interaction on mental health outcomes.

Participation in sport may influence mental health via some combination of the social mechanisms identified by Thoits, and the neurobiological, psychosocial, and behavioral mechanisms stemming from physical activity identified by Lubans [ 29 , 64 ]. The exact mechanisms through which sport may confer psychological benefit is likely to vary between sports, as each sport varies in its physical and social requirements. One must also consider the social effects of sports participation both on and off the field. For instance, membership of a sporting team and/or club may provide a sense of identity and belonging—an effect that persists beyond the immediacy of playing the sport and may have a persistent effect on their psychological health. Furthermore, the potential for team-based activity to provide additional benefit to psychological outcomes may not just be attributable to the differences in social interactions, there are also physiological differences in the requirements for sport both within (team vs. team) and between (team vs. individual) categories that may elicit additional improvements in psychological outcomes. For example, evidence supports that exercise intensity moderates the relationship between physical activity and several psychological outcomes—supporting that sports performed at higher intensity will be more beneficial for psychological health.

Limitations and recommendations

There are several limitations of this review worthy of consideration. Firstly, amongst the included studies there was considerable heterogeneity in study outcomes and study methodology, and self-selection bias (especially in non-experimental studies) is likely to influence study findings and reduce the likelihood that study participants and results are representative of the overall population. Secondly, the predominately observational evidence included in this and Eime’s prior review enabled us to identify the positive relationship between sports participation and social and psychological health (and examine directionality)—but more experimental and longitudinal research is required to determine causality and explore potential mechanisms responsible for the effect of sports participation on participant outcomes. Additional qualitative work would also help researchers gain a better understanding of the relationship between specific elements of the sporting environment and mental health and social outcomes in adult participants. Thirdly, there were no studies identified in the literature where sports participation involved animals (such as equestrian sports) or guns (such as shooting sports). Such studies may present novel and important variables in the assessment of mental health benefits for participants when compared to non-participants or participants in sports not involving animals/guns—further research is needed in this area. Our proposed conceptual model also identifies several pathways through which sport may lead to improvements in mental health—but excludes some potentially negative influences (such as poor coaching behaviors and injury). And our model is not designed to capture all possible mechanisms, creating the likelihood that other mechanisms exist but are not included in this review. Additionally, an interrelationship exits between physical activity, mental health, and social relationships, whereby changes in one area may facilitate changes in the other/s; but for the purpose of this study, we have focused on how the physical and social elements of sport may mediate improvements in psychological outcomes. Consequently, our conceptual model is not all-encompassing, but designed to inform and guide future research investigating the impact of sport participation on mental health.

The findings of this review endorse that participation in sport is beneficial for psychological well-being, indicators of psychological ill-being, and social outcomes in adults. Furthermore, participation in team sports is associated with better psychological and social outcomes compared to individual sports or other physical activities. Our findings support and add to previous review findings [ 1 ]; and have informed the development of our ‘Mental Health through Sport’ conceptual model for adults which presents the potential mechanisms by which participation in sport may affect mental health.

Availability of data and materials

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

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Acknowledgements

We would like to acknowledge the work of the original systematic review conducted by Eime, R. M., Young, J. A., Harvey, J. T., Charity, M. J., and Payne, W. R. (2013).

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Eather, N., Wade, L., Pankowiak, A. et al. The impact of sports participation on mental health and social outcomes in adults: a systematic review and the ‘Mental Health through Sport’ conceptual model. Syst Rev 12 , 102 (2023). https://doi.org/10.1186/s13643-023-02264-8

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Role and Benefits of Sports Psychology for the Improvement of Performance of Sports Persons

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2022, International Journal for Research in Applied Science & Engineering Technology (IJRASET)

The acceptance of sport psychology, both as an academic discipline as well as an applied process, has grown considerably over the past 2 years. Sports performance is determined by a combination of physiological factors, technical skill, tactical insight and state of mind. Every top sportsperson knows that their best performances come from their mind as much as their body. Not many to the world of competitive athletics would argue with the significance of being psychologically ready just before an athletic competition along with the want to help keep this specific mindset during a competitive competition. As a result, the goal of this report is actually providing the viewer with a basic framework depicting how mental skills education translates into enhanced competition efficiency. This particular framework is meant to help bridge the common "understanding gap" that's presently being described by a lot of coaches and athletes, while simultaneously helping sport psychology practitioners market their valuable services to specific athletes & teams. The paper concluded by stating sport psychology must be used as scientific instruction ways for athletes to be able to improve sports performance.

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Motivation Measures in Sport: A Critical Review and Bibliometric Analysis

Rachel b. clancy.

1 Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland

Matthew P. Herring

2 Health Research Institute, University of Limerick, Limerick, Ireland

Mark J. Campbell

Associated data.

Motivation is widely-researched, in both sport psychology and other fields. As rigorous measurement is essential to understanding this latent construct, a critical appraisal of measurement instruments is needed. Thus, the purpose of this review was to evaluate the six most highly cited motivation measures in sport. Peer-reviewed articles published prior to August 2016 were searched to identify the six most highly cited motivation questionnaires in sport: Sport Motivation Scale (SMS), Intrinsic Motivation Inventory (IMI), Situational Motivational Scale (SIMS), Perceptions of Success Questionnaire (POSQ), Behavioural Regulation in Sport Questionnaire (BRSQ), and Task and Ego Orientation in Sport Questionnaire (TEOSQ). The questionnaires were then evaluated and discussed in four sections: Development, Reliability, Correlates, and Summary. Bibliometric data were also calculated (average weighted impact factor) and assessed (e.g., citations per year) to evaluate the impact of the use of each questionnaire. Despite some variance in their psychometric properties, conceptualization, structure, and utility, the six questionnaires are psychometrically strong instruments for quantifying motivation that are widely supported in the literature. Bibliometric analyses suggested that the IMI ranks first and the SMS ranks sixth according to the average weighted impact factors of their original publications. Consideration of each questionnaire's psychometric strengths/limitations, and conceptualization of motivation in the context of specific research questions should guide researchers in selecting the most appropriate instrument to measure motivation in sport. The average weighted impact factor of each questionnaire is a useful value to consider as well. With these points in mind, recommendations are provided.

Introduction

Motivation can be defined as the force that energizes and directs behavior (Roberts and Treasure, 2001 ). Thus, it comprises the perceived reasons for engaging in an activity. There is utility in studying motivation, as it provides a theoretical and practical insight into why one initiates, regulates, sustains, directs and discontinues behavior. Studies in education (e.g., Dweck, 1986 ; Deci and Ryan, 2016 ), the workplace (e.g., Ambrose and Kulik, 1999 ; Gagné and Deci, 2005 ), health and healthcare (e.g., Carter and Kulbok, 2002 ; Hardcastle and Hagger, 2016 ), physical activity and exercise (e.g., Buckworth et al., 2007 ; Gunnell et al., 2014 ), among other domains, indicate the widespread scale and importance of motivational research. In the area of sport psychology, there is similar interest in the psychological processes that influence behavior, which extends from academia to the playing field.

Motivation is a construct (or latent variable), rather than an observable entity, which contributes to the difficulty in accurately measuring it (Lavallee et al., 2003 ). Many early assessments of motivation were behavioral in nature or relied on participants to provide verbal reports as to why they engaged in a particular activity. For example, Lepper and Greene ( 1975 ) inferred participants' intrinsic motivation by observing their time on task following an experimental intervention. A comparable though less scientific sport-related example is as follows: an athlete who performs extra repetitions in the gym is often perceived by observers as highly motivated, though no measure of motivation has actually taken place. Clearly, methodologically rigorous measurement is needed to assess, understand, and predict the influence of any psychological construct on human behavior (Clancy et al., 2016 ). Thus, critical appraisal of the strengths and weaknesses of different measurement approaches is essential for our understanding of motivation, and would enhance researchers and practitioners' awareness of subsequent behavior.

Self-report questionnaires are the most commonly used measurement tools in motivation research, with Mayer et al. ( 2007 ) identifying over 75 questionnaires on motivation between 1930 and 2005. Specifically, in sport psychology, there is a plethora of motivation questionnaires (Clancy et al., 2016 ). Although, previous publications have compared the psychometric properties of two instruments (e.g., Lonsdale et al., 2014 ) or reviewed questionnaires (e.g., Duda and Whitehead, 1998 ; Vallerand and Fortier, 1998 ), there is no contemporary peer-reviewed manuscript that provides a comprehensive evaluation of the most widely used self-report questionnaires of motivation in sport psychology. Bibliometric methods (e.g., Lindahl et al., 2015 ) add depth to such an evaluation by exploring the cited literature in the field. This review sought to address the aforementioned gap by providing a critical appraisal and bibliometric analysis of such measures, and subsequent guidance regarding their use based on the specific research question.

Following ethical approval, six databases were searched in order to identify the most highly cited motivation questionnaires in sport prior to August 2016: Academic Search Complete; Google Scholar; PsycARTICLES; PsycINFO; SPORTDiscus; Web of Science. The search was conducted using the following terms:

(motiv * OR regulat * OR behav * ) AND sport * AND (questionnaire OR measur * OR instrument OR scale).

Reference lists of the obtained articles were searched by hand. The six most highly cited motivation questionnaires in sport were selected for review and are summarized in Table ​ Table1: 1 : the Sport Motivation Scale (SMS; Pelletier et al., 1995 ), the Intrinsic Motivation Inventory (IMI; McAuley et al., 1989 ), the Situational Motivational Scale (SIMS; Guay et al., 2000 ), the Perceptions of Success Questionnaire (POSQ; Roberts et al., 1998 ), the Behavioral Regulation in Sport Questionnaire (BRSQ; Lonsdale et al., 2008 ), and the Task and Ego Orientation in Sport Questionnaire (TEOSQ; Duda, 1989 ). In order to critically appraise each instrument, further searches were conducted using the questionnaire name combined with test evaluation-related terms (e.g., reliability, psychometric, factor analysis).

Overview of six highly cited motivation measures in sport .

Bibliometric data (Table ​ (Table2) 2 ) were obtained using the Cited Reference Search in Web of Science. The total number of citations of each original publication was reported, as well as the subset with an impact factor. Some sources (e.g., book series, conference proceedings) had no impact factor and, therefore, were excluded from further calculations. The average weighted impact factor for the original publication of each questionnaire was calculated as follows: (1) the number of articles (citations) in each journal was multiplied by the journal's 2015 impact factor; (2) this value for all the journals was summed and then divided by the total number of articles (citations). This process resulted in a single number describing the impact of the use of each questionnaire.

Bibliometric data for six highly cited motivation measures in sport .

In the following sections, each measure will be discussed in order of highest to lowest number of citations per year since the original publication date. Although, the bibliometric data (Table ​ (Table2) 2 ) indicate that the SMS is the most highly cited questionnaire under review (19.5 per year), the average weighted impact factor of the journals accounting for those citations is the lowest (~1.53). The IMI (~1.89) and SIMS (~1.85) have the highest average weighted impact factors, but many of the SIMS citations are in non-sport journals (e.g., International Journal of Engineering Education, Computers in Human Behavior). As such, the IMI could be interpreted as the questionnaire with the highest impact. Bibliometric data are provided in full in Supplementary Tables 1–6 .

In the current review, each measure is evaluated along four domains: (1) the questionnaires are described in Development , which outlines background information, structure, updated versions, scoring, and so forth; (2) reliability is briefly summarized in Reliability . Cronbach's alpha values are reported as a measure of internal consistency, with 0.70 being the acceptable cut-off for research purposes (Nunnally, 1978 ). Where possible, indices of temporal stability and model fit are reported. In line with guidelines from Vincent and Weir ( 1999 ), test-retest correlations and intraclass coefficients are interpreted as high (>0.90), moderate (0.80–0.90) or insufficient (≤ 0.80); (3) findings regarding the associations between questionnaire scores and related variables are provided in Correlates ; and, (4) a synopsis of the aforementioned material is presented in Summary .

Sport motivation scale

Development.

The Echelle de Motivation dans le Sport is a multidimensional and contextual measure of intrinsic motivation, extrinsic motivation, and amotivation toward sport (Briere et al., 1995 ). Pelletier et al. ( 1995 ) used two studies, the first with university athletes and the second with provincial soccer players, to translate and validate this questionnaire into English and, thereby, produce the SMS. The SMS contains seven subscales that measure three types of intrinsic motivation (to know, to accomplish things, to experience stimulation), three types of regulation for extrinsic motivation (identified, introjected, external), and amotivation. Each subscale contains four items, amounting to 28 items in total. In response to criticisms of the SMS, Mallett et al. ( 2007b ) developed the SMS-6, which comprises six subscales. In this measure, the intrinsic motivation subscales were combined into a single subscale, and items were added for integrated regulation, the most self-determined form of extrinsic motivation that was absent from the SMS (Mallett et al., 2007a , b ). However, Pelletier et al. ( 2007 ) did not conclude that the SMS-6 was superior to the SMS, or even that a revision of the measure was needed. Although the SMS has had a “significant impact on the measurement, prediction, and understanding of sport motivation” (Pelletier et al., 2013 , p. 331), a revised version was later developed, namely the SMS-II, to address some of the limitations of the SMS. The 18-item SMS-II, which contains a mix of SMS items and new items, includes a subscale for integrated regulation, and groups the different types of intrinsic motivation into a single subscale.

Scores from the SMS can be provided in three formats. Firstly, a score can be calculated for each subscale, amounting to seven scores per questionnaire. Secondly, subscales can be grouped into broader motivational categories. For example, identified, introjected, and external regulation can be averaged to give one score for extrinsic motivation. Thirdly, a self-determination (or relative autonomy) index can be calculated by assigning weights to each subscale score according to the subscale's position on the self-determination continuum (see Gillet et al., 2010 for an example). Subscale scores (mean followed by standard deviation in parentheses) for the SMS are provided in Table ​ Table3. 3 . Although there is not a children's version of the SMS, it has been found to have adequate internal reliability with youth athletes (Rottensteiner et al., 2015 ).

Sample composition and subscale scores for a range of papers using the SMS .

Reliability

Acceptable internal consistency has been found in most studies using the SMS. Pelletier et al. ( 1995 ) reported Cronbach's alpha values of 0.74–0.80, except for the identified regulation subscale (α = 0.63). Cronbach's alpha values of 0.73–0.90 were reported for Canadian athletes (Fortier et al., 1995 ), 0.72–0.83 for professional rugby players (Cresswell and Eklund, 2005 ), 0.71–0.85 for French judokas (Gillet et al., 2010 ), and 0.65–0.87 for British dancers (Quested and Duda, 2011 ). Mallett et al. ( 2007a ) reported Cronbach's alpha values of 0.78–0.86 for the SMS-6, except for the identified regulation subscale (α = 0.70). Pelletier et al. ( 2013 ) reported Cronbach's alpha values of 0.70–0.88 for the SMS-II. Test-retest correlations for the SMS range from 0.58 to 0.84 (Pelletier et al., 1995 ), which are insufficient to moderate. Confirmatory factor analysis was performed to evaluate the seven-factor structure of the SMS (Pelletier et al., 1995 ). Although the chi-square statistic suggests a lack of model fit, other statistics (chi-square/degrees of freedom ratio = 1.94; goodness of fit index = 0.94; the adjusted goodness of fit index = 0.92; root mean square residual = 0.048; normed fit index = 0.92) indicate that the model is acceptable (Pelletier et al., 1995 ).

Multiple types of correlational data support interpreting scores from the SMS as measures of intrinsic motivation, extrinsic motivation, and amotivation. In line with theoretical predictions, the SMS subscale scores correlate with numerous motivational determinants and consequences. For example, amotivation is negatively associated with perceived competence (determinant), and effort (consequence; Pelletier et al., 1995 ). Intrinsic motivation is positively correlated with a coach who provides competence-based feedback, and negatively correlated with distraction (Pelletier et al., 1995 ). Autonomy-supportive coaching positively predicts intrinsic motivation (Pelletier et al., 1995 ; Gillet et al., 2010 ; Quested and Duda, 2011 ). Competitive athletes demonstrate less intrinsic motivation than recreational athletes, reinforcing earlier findings that competition undermines intrinsic motivation due to its emphasis on external rewards (Fortier et al., 1995 ). Intrinsic motivation is significantly negatively associated with key characteristics of burnout, such as sport devaluation and exhaustion (Cresswell and Eklund, 2005 ). Contextual self-determined motivation is significantly correlated with situational self-determined motivation (Gillet et al., 2010 ). Extrinsic regulation positively predicts social physique anxiety among dancers, and amotivation negatively predicts self-esteem (Quested and Duda, 2011 ). Perceived competence is related to autonomous motivation, which positively influences persistence in team sport (Rottensteiner et al., 2015 ).

The available evidence supports using the SMS as a measure of intrinsic motivation, extrinsic motivation, and amotivation in sport. A limitation of the SMS is that it does not assess integrated regulation, though this can be overcome by using the SMS-II. The internal consistency of the identified regulation subscale (α = 0.63) is also below the acceptable threshold (Nunnally, 1978 ). Overall, the SMS is a well-supported, multidimensional questionnaire that is psychometrically sound, brief, and widely used in sport settings.

Intrinsic motivation inventory

The IMI is a multidimensional and situational measure of intrinsic motivation that was first developed for laboratory tasks (Ryan, 1982 ) and then adapted to sport (McAuley et al., 1989 ). Thus, it was originally a non-sport questionnaire that McAuley et al. ( 1989 ) successfully applied in a competitive sport setting using a sample of university physical education students. In its entirety, it contains 45 items across seven subscales: interest/enjoyment, perceived competence, effort, value/usefulness, felt pressure/tension, perceived choice, and relatedness. A smaller number of IMI items can be selected and modified depending on the activity and research question, without adversely affecting the psychometric properties of the measure. In developing the sport version of the IMI, McAuley et al. ( 1989 ) compared two versions containing 16/18 items across four subscales: interest/enjoyment, perceived competence, effort/importance, and pressure/tension. The interest/enjoyment subscale is considered the self-report measure of intrinsic motivation. In contrast, the remaining three subscales account for antecedents (competence) or outcomes (effort/importance, pressure tension) of intrinsic motivation, rather than intrinsic motivation itself. The perceived choice subscale is a common addition to the 16-item version (e.g., Amorose and Horn, 2001 ). Due to the flexible nature of the IMI, any number of subscale scores can be reported depending on the variable of interest. Accordingly, Table ​ Table4 4 shows scores for each subscale (mean followed by standard deviation in parentheses), and indicates that studies often use a smaller selection of subscales, rather than the maximum number of seven (number of items used is indicated for each subscale). There is not a children's version of the IMI but it has been found to have adequate internal reliability with youth samples (Williams and Gill, 1995 ).

Sample composition and subscale scores for a range of papers using the IMI .

In assessing the suitability of the IMI for use in the sport domain, McAuley et al. ( 1989 ) reported Cronbach's alpha values of 0.78–0.84 for three of the subscales, and 0.68 for pressure-tension. The alpha coefficient for the entire measure is 0.85 (McAuley et al., 1989 ), which is acceptable. Cronbach's alpha values of 0.73 (interest/enjoyment) were reported for American physical education students (Williams and Gill, 1995 ), 0.62–0.85 for American college athletes (Amorose and Horn, 2000 ), 0.78 (perceived competence) for British university athletes (Reinboth and Duda, 2006 ), and 0.85/0.90 (perceived competence/effort/importance) for Canadian rugby players (Pope and Wilson, 2012 ). For each subscale, the main effect for time across a competitive season is non-significant, demonstrating temporal stability (Amorose and Horn, 2001 ). The five-factor model of the 16-item IMI was examined using confirmatory factor analysis, and the goodness of fit index (0.788) and coefficient delta (0.76) indicate acceptable fit (McAuley et al., 1989 ).

Multiple types of correlational data support interpreting scores from the IMI as measures of different types of intrinsic motivation. Intrinsic interest/enjoyment has a significant positive association with task orientation and perceived competence, and a negative association with ego orientation (Williams and Gill, 1995 ). Task oriented individuals feel more competent, which leads to greater intrinsic interest and higher effort (Williams and Gill, 1995 ). Scholarship athletes exhibit greater intrinsic motivation than non-scholarship athletes (Amorose and Horn, 2000 ). Specifically, scholarship athletes scored higher on perceived competence than non-scholarship athletes, suggesting that being awarded a scholarship enhances intrinsic motivation by reinforcing perceptions of competence (Amorose and Horn, 2000 ). The influence of coaching style/climate on an athlete's need to feel competent, and the subsequent effects on motivation and effort are well-documented (Reinboth and Duda, 2006 ; Pope and Wilson, 2012 ). Similarly, Amorose and Horn ( 2001 ) found support for the relationship between perceived coaching behaviors and athlete intrinsic motivation.

The available evidence indicates that scores from the IMI can be interpreted as measures of situational intrinsic motivation in sport. Limitations of the IMI are that it predominantly assesses determinants and consequences of intrinsic motivation, rather than intrinsic motivation itself, and there are no subscales for extrinsic motivation or amotivation. Additionally, the internal consistency of the pressure-tension subscale (0.68) is below the acceptable value of 0.70 (Nunnally, 1978 ). Overall, the IMI is a very flexible instrument that affords the researcher the opportunity to select/modify relevant items to assess intrinsic motivation in any sport setting.

Situational motivational scale

The SIMS is a multidimensional and situational measure of intrinsic motivation, extrinsic motivation, and amotivation (Guay et al., 2000 ). It is a state measure (meaning it captures ongoing motivational regulations), focuses on the reasons why people engage in an activity (rather than consequences), and is worded such that it can be used in most settings. It is, however, not specifically a sport questionnaire, meaning it is cited across diverse domains (see Supplementary Table 3 ). Guay et al. ( 2000 ) conducted five studies with university student samples to develop and validate the SIMS, though one of these samples comprised student-athletes. The 16-item scale assesses extrinsic motivation multidimensionally (external and identified regulations), and intrinsic motivation and amotivation as unidimensional constructs. There is also a 14-item version, which may more soundly measure state motivational regulations (Standage et al., 2003 ). Four subscale scores are generally reported in the literature when the SIMS is used (Table ​ (Table5; 5 ; mean followed by standard deviation in parentheses). Although there is not a children's version of the SIMS, it is commonly and successfully used with youth samples (e.g., Podlog et al., 2015 ).

Sample composition and subscale scores for a range of papers using the SIMS .

Internal consistency is largely acceptable for the SIMS. Cronbach's alpha values of 0.62–0.95 and 0.67–0.93 were reported across four studies of college students and one study of collegiate athletes, respectively (Guay et al., 2000 ). Cronbach's alpha values of 0.83–0.90 were reported for American middle school students (Standage and Treasure, 2002 ), 0.69–0.90 for American youth swimmers (Conroy et al., 2006 ), 0.73–0.85 for French judokas (Gillet et al., 2010 ), 0.80–0.82 for Spanish swimmers (Fernandez-Rio et al., 2014 ), and 0.63–0.79 for Swedish junior skiers (Podlog et al., 2015 ). The SIMS has acceptable test-retest reliability, though changes in subscale scores are expected because it is a state measure (Guay et al., 2000 ). Confirmatory factor analysis of the four-factor structure was performed (Guay et al., 2000 ), producing a significant chi-square statistic and a non-normed fit index somewhat lower than the 0.90 cut-off value (Bentler, 1995 ). However, the comparative fit index (0.90) indicates satisfactory model fit (Guay et al., 2000 ).

Multiple types of correlational data support interpreting scores from the SIMS as measures of intrinsic motivation, extrinsic motivation, and amotivation at the situational level. In terms of motivational determinants and consequences, intrinsic motivation and identified regulation are positively associated with perceived competence and autonomy (determinants), and concentration, emotions, task interest and behavioral intentions of future persistence (consequences; Guay et al., 2000 ). The opposite patterns hold true for external regulation and amotivation. Individuals in task-focused experimental conditions report higher intrinsic motivation that those in controlling/reward conditions (Guay et al., 2000 ). Similarly, a task/mastery orientation is positively associated with self-determined motivational profiles (Standage and Treasure, 2002 ; Fernandez-Rio et al., 2014 ). Coach achievement goals affect athletes' achievement goals, which in turn influence their situational motivation (Conroy et al., 2006 ). Contextual self-determined motivation also impacts situational self-determined motivation and subsequent competitive performance (Gillet et al., 2010 ). Self-determined situational motivation serves as a mediator between basic psychological needs and athlete engagement (Podlog et al., 2015 ).

The available evidence supports using the SIMS as a measure of situational intrinsic motivation, extrinsic motivation, and amotivation in sport. A limitation of the SIMS is that intrinsic motivation is assessed unidimensionally, and two types of extrinsic regulation are absent. Overall, the SIMS is a brief, non-sport-specific measure of multidimensional and situational motivation, which can be applied to sport settings due to its open wording.

Perceptions of success questionnaire

The POSQ is a measure of achievement goals in sport that was first formulated using a sample of sport-playing university students (Roberts et al., 1998 ). In its development, an initial pool of 48 items was reduced to 26, and this version was found to have strong psychometric properties (Roberts et al., 1995 ). In seeking a more parsimonious scale, Roberts et al. ( 1998 ) tested a 16-item version, which was then reduced to 12 items equally divided across two subscales: task and ego orientations. The correlations between the short form and the long form are 0.98 (task) and 0.97 (ego), reinforcing the efficacy of the 12-item version to measure achievement goals in sport. Subscale scores (mean followed by standard deviation in parentheses) for task and ego orientations are provided in Table ​ Table6. 6 . Though the POSQ has demonstrated adequate reliability among youth samples (e.g., Harwood et al., 2004 ), there is also a children's version (Lemyre et al., 2002 ). The original publication found both the adult and children's versions to be reliable and valid instruments (Roberts et al., 1998 ).

Sample composition and subscale scores for a range of papers using the POSQ .

Internal consistency of the POSQ is acceptable. For task and ego orientations, respectively, Cronbach's alpha was reported as 0.82 and 0.87 for American university students (Roberts et al., 1998 ), 0.81 and 0.79 for Norwegian university physical education students (Ommundsen et al., 1998 ), 0.76 and 0.75 for Norwegian Olympians (Pensgaard and Roberts, 2000 ), 0.75 and 0.81 for Norwegian youth soccer players (Lemyre et al., 2002 ), 0.87 and 0.81 for British elite youth athletes (Harwood et al., 2004 ), and 0.83 and 0.91 for Finnish youth athletes (Rottensteiner et al., 2015 ). Test-retest reliability is moderate (0.80 for task and 0.78 for ego) across 1 week (Roberts et al., 1998 ). The two-factor structure was tested using confirmatory factor analysis (Roberts et al., 1998 ). Despite a significant chi-square statistic, the root mean square residual (0.09) and Tucker-Lewis index (0.90) indicate adequate model fit for the POSQ (Roberts et al., 1998 ).

Multiple types of correlational data support interpreting scores from the POSQ as measures of task and ego orientations in sport. Dispositional achievement goals are influenced by the motivational climate, and are related to a host of other variables, such as the perceived purposes of sport, perceived ability, perfectionism, and burnout (Ommundsen et al., 1998 ; Lemyre et al., 2008 ). Situational factors (e.g., motivational climate) influence the sources and levels of distress that athletes experience significantly more than dispositional factors (e.g., goal orientations; Pensgaard and Roberts, 2000 ). Achievement goal orientations affect athletes' sportspersonship attitudes, with a task orientation having a positive effect on moral functioning and an ego orientation decreasing some aspects of sportspersonship (Lemyre et al., 2002 ). Perceived ability moderates the relationship between goal orientation and sportspersonship, particularly for ego-oriented athletes (Lemyre et al., 2002 ). Task orientation is important for acquiring and using psychological skills (e.g., goal setting, imagery), though ego orientation can sometimes be adaptive, in that such athletes often engage in useful strategies to pursue their goals (Harwood et al., 2004 ). Maladaptive motivational profiles, of which an ego orientation is a component, are associated with higher levels of burnout (Lemyre et al., 2008 ). Goal orientations influence autonomous motivation both directly and indirectly (through their effects on perceived competence), and autonomous motivation then affects persistence in sport (Rottensteiner et al., 2015 ).

The available evidence indicates that scores from the POSQ can be interpreted as measures of achievement goals in sport. A potential limitation of the POSQ is its use of a five-point Likert scale, which may afford less sensitivity than a seven-point Likert scale. However, each questionnaire in the review could perhaps be improved if it had an even number of response options and was, therefore, forced-choice. With an odd number of response options, respondents can provide neutral data, which can be uninformative. Overall, the POSQ has strong psychometric properties and is easy to administer due to its brevity.

Behavioral regulation in sport questionnaire

The BRSQ is a contextual measure of competitive sport participants' intrinsic motivation, extrinsic motivation, and amotivation (Lonsdale et al., 2008 ). The measure was developed as an alternative to the SMS, which Lonsdale et al. ( 2008 ) found to have somewhat questionable psychometric properties. Four studies were used in questionnaire development, all of which had athlete samples; specifically, the participants in studies one and two were elite athletes (Lonsdale et al., 2008 ). Rather than modifying existing items from the SMS (as was the case with the SMS-6 and SMS-II), the BRSQ was created from an entirely new pool of items. In total, it comprises 36 items across nine subscales: four subscales for intrinsic motivation (general, to know, to experience stimulation, to accomplish), four subscales for extrinsically motivated regulations (integrated, identified, introjected, external), and a subscale for amotivation. Two alternative versions were compared by the original authors: the BRSQ-8 contains 32 items across eight subscales, and excludes the unidimensional conceptualisation of intrinsic motivation (intrinsic motivation general); the BRSQ-6 contains 24 items across six subscales, and excludes the tripartite conceptualisation of intrinsic motivation (to know, to experience stimulation, to accomplish). In this way, the BRSQ accounts for the multidimensional and unidimensional conceptualizations of intrinsic motivation, as there are subscales for intrinsic motivation and its three corresponding types. A single global score is usually reported for intrinsic motivation in the literature, whereas extrinsic motivation is broken down into its four components (Table ​ (Table7; 7 ; mean followed by standard deviation in parentheses). The children's version of the questionnaire is valid among youth athletes (Viladrich et al., 2013 ).

Sample composition and subscale scores for a range of papers using the BRSQ .

Internal consistency is acceptable for the nine BRSQ subscales, as Lonsdale et al. ( 2008 ) reported Cronbach's alpha values of 0.71–0.93 across three studies. Cronbach's alpha was reported as 0.73–0.87 for Belgian students from top sport schools (Assor et al., 2009 ), and 0.70–0.93 for Canadian athletes (Lonsdale et al., 2009 ). Test-retest reliability of the subscale scores is supported across a 1-week period, with intraclass coefficients ranging from 0.73 for intrinsic motivation general to 0.90 for integrated regulation and intrinsic motivation to experience stimulation (Lonsdale et al., 2008 ). Confirmatory factor analysis of the six-factor structure was conducted, producing fit statistics that are generally strong (Lonsdale et al., 2008 ), and meet cut-off criteria (root mean square error of approximation ≤ 0.06; comparative fit index ≥0.95; Tucker-Lewis index ≥0.95) suggested by Hu and Bentler ( 1999 ). Acceptable model fit has also been demonstrated among dancers (Hancox et al., 2015 ).

Multiple types of correlational data support interpreting scores from the BRSQ as measures of intrinsic motivation, extrinsic motivation, and amotivation. Autonomous subscale scores are positively correlated with dispositional flow (Lonsdale et al., 2008 ), and negatively correlated with burnout (Lonsdale and Hodge, 2011 ; Holmberg and Sheridan, 2013 ). Burnout may also precede reductions in self-determined extrinsic motivation (Lonsdale and Hodge, 2011 ). Identified regulation is associated with a more positive pattern of affective and performance correlates (e.g., positive affect, vitality, interindividual performance, intraindividual progress) than introjected regulation (Assor et al., 2009 ). Furthermore, when valence is considered, introjected avoidance motivation is related to a more negative pattern of correlates than introjected approach motivation (Assor et al., 2009 ).

The available evidence supports using the BRSQ as a measure of intrinsic motivation, extrinsic motivation, and amotivation in sport. A potential limitation of the BRSQ is that it was designed for use among competitive athletes, thus making it unsuitable for exercise or physical activity settings. This specificity, however, could also be interpreted as a strength. Overall, the BRSQ is an accurate and flexible instrument that facilitates unidimensional and multidimensional measurement through its various versions/subscales.

Task and ego orientation in sport questionnaire

The TEOSQ is an adaptation of an inventory created for scholastic settings (Nicholls, 1989 ) that assesses individual differences in the proneness for task and ego involvement in sport (Duda, 1989 ). One study comprising a sample of high school students was used in this process (Duda, 1989 ). Using 13 items across two subscales, the TEOSQ assesses personal dispositions that are relatively stable (but not fixed) over time. Task scores are typically higher and more stable than ego scores (Duda and Whitehead, 1998 ). Subscale scores (mean followed by standard deviation in parentheses) for the TEOSQ are provided in Table ​ Table8, 8 , and readers are directed to Duda and Whitehead ( 1998 ) for a table of subscale scores for papers between 1989 and 1997. The TEOSQ has been successfully used for both youth (e.g., Williams and Gill, 1995 ) and adult (e.g., Lameiras et al., 2014 ) samples.

Sample composition and subscale scores for a range of papers using the TEOSQ .

M, male; F, female; values are mean (standard deviation) .

The TEOSQ has acceptable internal consistency. For the task and ego subscales, respectively, Cronbach's alpha is 0.82 and 0.89 among high school basketball players (Duda, 1989 ), 0.84 and 0.86 for American middle school students (Williams and Gill, 1995 ), 0.88 and 0.82 for elite soccer players (Van-Yperen and Duda, 1999 ), 0.76 and 0.84 for British university athletes (Ntoumanis, 2001 ), 0.83 and 0.82 for Portuguese professional athletes (Lameiras et al., 2014 ), and 0.84 and 0.81 for Scottish athletes (Allen et al., 2015 ). Test-retest reliability of the subscale scores was reported as 0.58 (task) and 0.67 (ego) across one soccer season, which is insufficient (Van-Yperen and Duda, 1999 ). Numerous investigations containing confirmatory factor analyses support the two-factor structure of the TEOSQ (Duda and Whitehead, 1998 ).

Multiple types of correlational data support interpreting scores from the TEOSQ as measures of task and ego orientations in sport. Task orientation is positively associated with beliefs that sport should enhance self-esteem, and encourages effort, mastery, cooperation and rule-following (Duda, 1989 ). In contract, ego orientation positively predicts views about the extrinsic benefits and personal gains afforded by sport (Duda, 1989 ), and is positively associated with stronger pro-doping attitudes (Allen et al., 2015 ). The association between task orientation and cooperation/prosocial behavior was also reported by Lameiras et al. ( 2014 ). There are direct and positive links between task orientation, perceived competence, intrinsic motivation/interest and effort (Williams and Gill, 1995 ). Task orientation is also related to the belief that effort contributes to achievement, whereas ego-oriented athletes believe that ability/talent determines success (Van-Yperen and Duda, 1999 ). There is a further link between task orientation and season-long performance improvement (Van-Yperen and Duda, 1999 ). Ntoumanis ( 2001 ) found that task orientation predicts motivational variables high in self-determination, whereas ego orientation predicts the opposite.

The available evidence indicates that scores from the TEOSQ can be interpreted as measures of task and ego goal orientation in sport. As with the POSQ, a potential limitation of the TEOSQ is its use of a five-point Likert scale, which offers fewer response options than a seven-point Likert scale. Additionally, the test-retest reliabilities are low. The TEOSQ is a psychometrically sound instrument for measuring dispositional goal orientations that has been used extensively in sport settings without argument for any revisions.

This review set out to evaluate the six most highly cited motivation measures in sport. Each questionnaire attempts to capture the reasons underlying behavior in the sport domain, thereby assessing motivation in a broad sense. However, there is a distinctive difference between how motivation is conceptualized in each questionnaire. The SMS, IMI, SIMS, and BRSQ consider intrinsic motivation, extrinsic motivation, and/or amotivation. In contrast, the POSQ and TEOSQ adopt a goal perspective approach in their measurement of motivation. It is important to note that this distinction does not confer an advantage to one type of questionnaire over another. Rather, it is simply an essential element for the researcher to consider prior to deliberating the relative merits of a particular questionnaire. Should a researcher wish to quantify intrinsic and extrinsic motivation, the SMS, IMI, SIMS, or BRSQ would be suitable. In contrast, a researcher who would like to account for personal goals in their measurement of motivation may priorities the POSQ or TEOSQ. In addition to conceptualization, differences in development, scoring, and youth administration should be deliberated when appraising motivation measures in sport. Bibliometric data can also be useful for indicating the impact of the use of a specific questionnaire, though other methodological features and research design issues must also be considered (Clancy et al., 2016 ). In the current review, the IMI ranks first and the SMS ranks sixth according to their average weighted impact factors.

In terms of development, there are three distinct groups among the six questionnaires. First, the SIMS stands alone because it is not a sport-specific questionnaire, though it can be adapted for that purpose. Next, the IMI was originally a non-sport questionnaire, but it was modified for the sport domain, which is the version included in this review. Thirdly, the remaining four questionnaires were created specifically for sport. In addition to these distinctions, there are differences in development based on the sample used in the original publications. Five of the publications (SMS, IMI, SIMS, POSQ, TEOSQ) comprised student samples, four at university-level and one at high school-level, which could be indicative of convenience sampling. In contrast, the BRSQ was developed from data from elite and non-elite athletes, which may have been advantageous when developing a measure for this group. Scoring procedures for each questionnaire are straightforward, though the SMS provides more flexibility because subscale scores can be combined to give a single global score, which is frequently reported in the literature and contributes to its ease of use. Thus, while all of the measures provide component scores, only the SMS offers an established method for producing a single score for each participant. As a final comparison, the POSQ and BRSQ have children's versions available, which is ideal when examining youth samples. The remaining four questionnaires, however, have adequate internal reliability when administered to children, indicating their utility among participants of all ages.

The reviewed instruments account for the different conceptualizations of motivation, and are applicable at either the contextual or situational level. Although they vary in their development, scoring, and administration, the conceptualization and level of applicability are likely the most important considerations for researchers selecting a questionnaire. The SMS and BRSQ assess intrinsic motivation, extrinsic motivation and amotivation at the contextual level, and allow for intrinsic motivation to be measured as a unidimensional or multidimensional construct. Next, the IMI and SIMS adopt contrasting approaches to measuring situational motivation. The IMI facilitates an in-depth view of situational intrinsic motivation only, whereas the SIMS quantifies intrinsic motivation (unidimensionally), extrinsic motivation, and amotivation. Lastly, the POSQ and TEOSQ assess task and ego goal orientations in sport. It is clear that researchers have several questionnaires to choose from when attempting to answer a specific research question. Although each of the questionnaires reviewed here has limitations, they predominantly exhibit strong psychometric properties and are widely used, reinforcing their utility for measuring the underlying why of behavior in sport.

Valid and reliable measurement is a precursor to the understanding of any psychological construct. Although an unobservable variable can be challenging to measure, the enduring interest of researchers and practitioners in motivation has resulted in the development of numerous instruments for quantifying it. The six questionnaires are psychometrically strong self-report tools for assessing motivation that emerged between the late 1980s and late 2000s, and continue to be widely cited in sport psychology. As previously mentioned, there are clear distinctions between the questionnaires that make them applicable to certain research questions and not others. When considered as a group, however, the IMI has the greatest impact in terms of its use. The SMS ranks sixth in this regard, though it is the most highly cited instrument under review. It is evident that bibliometric analysis enhances the ability to critically appraise questionnaires, and moves understanding beyond simple description. As such, the current review contributes to the field of sport psychology by filling a gap in measurement-related literature, and providing objective guidance for researchers and practitioners who wish to quantify motivation. It may also indicate fruitful avenues for the development of future questionnaires or alternative methods to assess motivation in sport.

Author contributions

RC, MH, and MC have satisfied all the criteria for authorship: substantially contributing to the reviews conception and interpretation; drafting and revising the work; approving the version to be published; agreeing to be accountable for the work.

This work was supported by the Irish Research Council [GOIPG/2015/2665].

Conflict of interest statement

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.

Supplementary material

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpsyg.2017.00348/full#supplementary-material

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Since the early years of this century, it has been commonplace for computerized analyses of athletic statistics to guide a baseball manager’s choice of pinch hitter, a football coach’s decision to punt or pass, or a basketball team’s debate over whether to trade a star player for a draft pick.

But many sports experts who actually watch the games know that the secret to success is not solely in computer databases, but also inside the players’ heads. So perhaps psychologists can offer as much insight into athletic achievement as statistics gurus do.

Sports psychology has, after all, been around a lot longer than computer analytics. Psychological studies of sports appeared as early as the late 19th century. During the 1970s and ’80s, sports psychology became a fertile research field. And within the last decade or so, sports psychology research has exploded as scientists have explored the nuances of everything from the pursuit of perfection to the harms of abusive coaching.

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    Download Free PDF. Download Free PDF ... Advanced Research on Sport Psychology. 2015 • DR Julinamary Parnabas. ... The paper concluded by stating sport psychology must be used as scientific instruction ways for athletes to be able to improve sports performance. Keyword: sports psychology, athlete, performance I. INTRODUCTION Sport psychology ...

  17. Motivation Measures in Sport: A Critical Review and Bibliometric

    Motivation is widely-researched, in both sport psychology and other fields. As rigorous measurement is essential to understanding this latent construct, a critical appraisal of measurement instruments is needed. Thus, the purpose of this review was to evaluate the six most highly cited motivation measures in sport.

  18. PDF Defining the practice of sport and performance psychology-Final

    Abstract Twenty-five years after the formation of both the Association for the Advancement of Applied Sport Psychology and Division 47 (Exercise and Sport Psychology) of the American Psychology Association, the question of who may practice as a sport psychologist persists. Some confusion still exists because the field has not fully answered

  19. What We've Learned Through Sports Psychology Research

    Psychological studies of sports appeared as early as the late 19th century. During the 1970s and '80s, sports psychology became a fertile research field. And within the last decade or so, sports psychology research has exploded as scientists have explored the nuances of everything from the pursuit of perfection to the harms of abusive coaching.

  20. (PDF) THE ROLE OF SPORT PSYCHOLOGY IN SPORTS ...

    Some of the identified roles in the article include resolution of the Athlete's emotional conflict, mental preparation, team building discipline etc. Problems encountered by the sports...

  21. PDF Sport Psychology: A Students's Handbook

    successful book Sport Psychology (published by Routledge in 1999). Here he pro-vides a succinct but comprehensive account of major theory and research in sport psychology, whilst maintaining the readable style and student-centred approach which made the previous book so successful. Key issues covered include: • personality and sport ...

  22. The Impact of Physical Activity and Sport on Mental Health

    Psychology Mental Health The Impact of Physical Activity and Sport on Mental Health Authors: Tamadher Abdul aziz Muhsen University of Baghdad Abstract and Figures Scientists have researched...

  23. PDF Unit I: Introduction: Sports Psychology Introduction to Sport Psychology

    closing in 1932, he conducted research and practiced sport psychology in the field. The laboratory was used for the study of sport psychology; where different factors that influence athletic performance and the physiological and psychological requirements of sport competitions were investigated.

  24. (Pdf) Psychological Aspects of Motivation in Sport Achievement

    (PDF) PSYCHOLOGICAL ASPECTS OF MOTIVATION IN SPORT ACHIEVEMENT Home Psychology, Educational Achievement PSYCHOLOGICAL ASPECTS OF MOTIVATION IN SPORT ACHIEVEMENT Facta Universitatis Series...