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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.

Researchers have extensively examined and reviewed the relationship of the profile of mood states (POMS) with sport performance since the 1970s. Two decades have passed since the last POMS quantitative review. Our overall objective was to quantify the POMS research with competitive athletes with a prospective measured POMS and a sport performance outcome in the published literature. Additionally, we tested potential moderators of the mental health model (i.e., sport duration, type, and skill) with meta-analytic techniques while considering potential risk bias across study sources. Based on a systematic review, the articles were found using EBSCO and comparing these articles with extensive past POMS in sport and exercise bibliographies. Search terms included profile of mood states (POMS) or iceberg profile or the mental health model with sport and performance or sports performance. For selection, articles must have reported data on competitive athletes, an athletic performance outcome, and a valid form of the POMS measured prospectively. After screening more than 600 articles for inclusion, 25 articles provided sufficient data for effect size calculations. The included articles spanned from 1975 to 2011, with 1497 unique participants. Hedges’ g values were generally small for the six POMS scales: tension (−0.21), depression (−0.43), anger (−0.08), vigor (0.38), fatigue (−0.13), and confusion (−0.41). However, the total mood disturbance (TMD) score effect size was medium in magnitude at −0.53. When corrected for potential publication bias, the effect size values increased in magnitude for tension (−0.47), depression (−0.64), vigor (0.44), fatigue (−0.34), and TMD (−0.84). Moderator analyses for Terry’s (1995) propositions and for risk of bias across studies, statistically, resulted in few differences based on conventional statistical significance (p < 0.05). Measured before performance, most of the POMS scales and TMD are reliable predictors of sport performance in competitive athletes across a wide variety of sports and athletic performance outcomes. Morgan’s (1980, 1985) mental health model or iceberg profile minus anger is still a viable method for understanding and improving athletic performances.

Sport psychology embraced the study of athletic identity in the 1990s. The Athletic Identity Measurement Scale (AIMS) is at the forefront of athletic identity measurement. This quantitative review examined two hypotheses: individual who are most engaged in sports identify most as athletes and thus score higher on the AIMS, and athletic identity relates to positive (e.g., intrinsic motivation) and negative (negative emotions) factors. In addition to our two hypotheses, we explored whether the AIMS subscales influenced our two hypotheses. After completing a systematic search of SPORTDiscus, APA PsycINFO, ERIC, and Psychology and Behavioral Sciences Collection APA within the EBSCOhost platform along with some hand searching, 101 articles published between 1993 and our end date of August 2021 met the inclusion criteria. The included studies investigated 20,498 athletes competing in a variety of sports from the following continents: Australia, Asia, Europe, and North America. We based all analyses on random- and mixed-effects statistics. Higher-achieving athletes, as expected, self-reported a higher degree of athletic identity. The differences between athlete groups were significant (p < 0.001) and meaningful (g values ranged from 1.55 to 1.93). The AIMS total score correlations with positive and negative factors (correlates) were small in magnitude (r = 0.22 and 0.17). However, the relationships differed across correlate subcategories (e.g., intrinsic motivation/commitment, r = 0.51, and body issues, r = 0.14). Minimal AIMS subscale reporting occurred across the 101 studies; thus, we could not assess their importance with certainty. In conclusion, a higher degree of athletic identity related to valued sport correlates such as intrinsic motivation/commitment and the mastery goal orientation. These correlations were small in relation to negative or less desirable factors in sport such as body disorder issues and negative emotions. We recommend future research of greater complexity and the reporting of athletes’ competitive backgrounds to understand athletic identity. In addition, researchers should report AIMS subscale data.

Motivational climate is known to relate to individual behaviors, emotions, and thoughts. Hedonic or subjective well-being includes self-assessed positive affect (i.e., pleasant affect, moods, and emotions), negative affect (i.e., unpleasant affect, moods, and emotions), and life or domain-specific satisfaction. The aim of this review was to quantify the relationships between task and ego motivational climate scales and measures representing hedonic well-being with sports participants. Potential moderators of the motivational climate and hedonic well-being were examined. This review followed the PRISMA guidelines (PROSPERO ID CRD42023470462, registered 28 October 2023). From five relevant databases, one relevant review, and hand searching, 82 articles totaling 26,378 participants (46.3% female) met the inclusion criteria. The articles spanned publication dates from 1993 to 2023, representing 18 countries, various team and individual sports, and athletes competing in elite (e.g., Olympic) to grassroot (e.g., club sport) competitions. To meta-analyze the motivational climate and hedonic well-being relationships, the random-effects model was used. For the moderation analyses, the mixed-effects model was used. The task or mastery climate relationships were medium in magnitude with positive affect and satisfaction and small with negative affect. The ego or performance climate relationships were small in magnitude for positive affect, negative affect, and satisfaction. Evidence of bias existed in the motivational climate and hedonic well-being relationships. For moderation analyses, athlete level (i.e., elite vs. non-elite) moderated (p < 0.05) the task (elite, r = 0.23; non-elite, r = 0.34) and ego motivational climate (elite, r = −0.02; non-elite, r = −0.13) and positive affect and satisfaction combined relationships. In conclusion, the motivational climate and hedonic well-being relationships were stronger for the task climate than for the ego climate. The finding that elite athlete correlations appeared dampened is important for future research. Even with the damped relationships, practitioners, from the Olympics to local clubs, should ensure the promotion of the task climate to maximize positive affect and satisfactions in and around the sport experience.

Achievement goal theory has been a dominant motivation framework since the 1980s. The 3 × 2 achievement goal framework emerged in the literature in 2011. We aimed to conduct a systematic review with meta-analysis following the PRISMA guidelines of the 3 × 2 achievement goal research in education, sport, and occupation settings. We retrieved articles from searching EBSCOhost and Google Scholar platforms. Eligible articles contained the 3 × 2 achievement goal in education, sport, or occupation, were published in a peer-reviewed journal, and provided mean data or correlate data. We tested hypotheses concerned with (1) the overall pattern of achievement goal endorsement, (2) achievement goal differences by domain (education, sport) and compulsory nature of the domains or sub-domains, and (3) achievement goal relationships with correlates (e.g., learning strategies, motivations, performance). After screening, 56 articles met all inclusion criteria, providing 58 samples across education (n = 44), sport (n = 10), and occupation (n = 4) settings with 35,031 unique participants from 15 countries. Participants endorsed the task- and self-approach goals more than the counterpart avoidance goals, other-avoidance goals more than other-approach goals, and the intercorrelations and reliability coefficients were acceptable. Minimal impact results from examining within and across study bias statistics. Of importance, the domain (i.e., education, sport) and the compulsory nature of the domain or sub-domains (i.e., primary-secondary education, sport) moderated goal endorsement (group mixed-effects p < 0.05, g values medium to very large). These groupings also moderated the other goal differences. Concerning our correlates analyses, most meta-analyzed correlations among the achievement goals and correlates were small in meaningfulness with the largest correlations (0.30–0.42) between the approach goals merged and the task- and self-approach goals and facilitative learning strategies and desired motivations. In conclusion, the 3 × 2 achievement goals literature is diverse. Furthering the study and application of this model requires overcoming inherent limitations (i.e., consistent response scale sets), teasing out differences between the task- and self-goals, measuring performance outcomes, and cross-cultural collaborations.

Background Personal social capital, which refers to the scope and quality of an individual’s social networks within a community, has received increasing attention as a potential sociological factor associated with better individual health; yet, the mechanism relating social capital to health is still not fully understood. This study examined the associations between social capital and self-rated health while exploring the roles of leisure-time physical activity (LTPA) and socioeconomic status (SES) among middle-aged and older adults. Methods Cross-sectional data were collected from 662 middle-aged and older adults (Mean age: 58.11 ± 10.59 years old) using the Qualtrics survey panel. Personal Social Capital Scale was used to measure bonding and bridging social capital and the International Physical Activity Questionnaire was used to assess LTPA levels. SES was assessed by education and household income levels. Self-rated health was assessed using a single item, by which the participants were categorized into the two groups, having ‘good’ vs. ‘not good’ self-rated health. A series of univariate and multivariate logistic regression models were established to examine the independent and adjusted associations of social capital with self-rated health and to test mediating and moderating roles of LTPA and SES, respectively. Results Bonding and bridging social capital were positively associated with self-rated health (Odds ratios = 1.11 and 1.09; P ’s < .05, respectively), independent of LTPA that was also significantly associated with greater self-rated health ( P -for-linear trends = .007). After adjusting SES, the associations of social capital were significantly attenuated and there was a significant interaction effect by household income ( P -for-interaction = .012). Follow-up analyses stratified by household income showed that beneficial associations of social capital with self-rated health were more apparent among the people with low and high levels of household income; yet, LTPA was the stronger predictor of self-rated health among those in the middle class of household income. Conclusions Findings suggest that both social capital and LTPA are associated with better self-rated health; yet, these associations vary by SES. The health policymakers should address both social capital and LTPA for enhancing perceived health among aging populations but may need to consider varying SES backgrounds.

Adolescence is a vulnerable period for experiencing poor sleep health. Growing studies have demonstrated lifestyle behaviors including physical activity (PA), screen time (SCT), and sedentary behaviors (SED) as the potential factors associated with sleep health in adolescents; yet, the evidence is inconclusive and the directionality of temporal associations across school days are not well understood. This study examined the day-to-day bidirectional associations of lifestyle behaviors with sleep health parameters in adolescents. A total of 263 adolescents (58% boys) in 6th - 8th grades wore an accelerometer for 24-hour across the three consecutive school days and completed recording SCT in time-diary and answering sleep quality (SQ) questions for each day. Sleep-wake patterns as well as time spent in moderate- and vigorous-intensity PA (MVPA) and SED were objectively quantified from the wrist-worn accelerometry data across the two segments of the day (during and after school hours). Mixed model analyses were conducted to test bidirectional associations between lifestyle factors and sleep health parameters in each temporal direction across the days. Additionally, indirect associations across the days were tested using an autoregressive cross-lagged model analysis in the framework of path analysis. MVPA minutes in a day did not predict sleep health parameters that night. The bidirectional associations were partially observed between SED and sleep health, but the significance and direction of the associations largely varied by the time segment of a day as well as types of sleep health parameters. Additionally, greater SCT during the day was associated with lower SQ that night (b = -0.010; P = .018), and greater SQ was associated with greater MVPA during school hours (b = 6.45; P = .028) and lower SED after school hours (b = -39.85; P = .029) the next day. Lastly, there were significant indirect associations of SCT with sleep health parameters across the days indicating multi-day lagged effects of SCT on sleep health the later nights. This study highlights the importance of lowering SCT for better sleep health in adolescents during school days. Additionally, perceived SQ is shown to be a potential significant predictor promoting healthy behaviors the next day independent of sleep-wake patterns. Further studies are warranted to confirm the observed temporal associations between SCT, SQ, and behavioral outcomes in this vulnerable population.

The purpose of this systematic review and meta-analysis (PROSPERO ID: CRD42024575181) was to quantify the relationships between dispositional and situational achievement goal involvement and sport confidence. A secondary purpose was to examine potential moderators of these relationships. Published studies reporting sufficient data, including one achievement goal measure from the dichotomous framework and one measure of sport confidence in an athlete sample, were included. Information sources included EBSCOhost databases, Web of Science databases, and relevant meta-analyses. The random-effects correlational coefficient (r) served as the summary statistic. Thirty-six studies yielding 37 independent samples, published between 1988 and 2026, which met all inclusion criteria, representing a total of 10,461 participants from youth to elite sports across four continents. Meta-analyzed random-effects correlations between task climate (k = 15, r = 0.33 [95% CI 0.23, 0.43]), ego climate (k = 13, r = −0.08 [95% CI −0.16, −0.00]), task orientation (k = 26, r = 0.27 [95% CI 0.21, 0.32]), ego orientation (k = 26, r = 0.11 [95% CI 0.06, 0.17]), and sport confidence ranged from small and negative to medium and positive in magnitude. Mixed-effects moderator analyses revealed significant differences (p < 0.05) for task climate when comparing state (r = 0.24) versus trait (r = 0.41) sport confidence measures, for task orientation scale (TEOSQ r = 0.31 vs. POSQ r = 0.18) in relation to sport confidence, and for study quality (lowest r = 0.35, medium r = 0.18, highest r = 0.24) in the task orientation–sport confidence relationship. However, nearly all prediction intervals for the examined relationships crossed zero, with the exception of a few TEOSQ- and POSQ-based moderator analyses. Thus, researchers and practitioners are cautioned that relationships between dispositional achievement goals, motivational climate perceptions, and sport confidence might be minimal or vary based on the dispositional achievement goal measure.

The purposes of this systematic review (PROSPERO ID: CRD42024510614, no funding source) were to quantify relationships between situational and dispositional dichotomous achievement goals and sport performance and explore potential relationship moderators. Published studies that reported at least one situational or dispositional achievement goal and a performance score were included. Studies without performance scores or based in a non-sport context were excluded. Information sources consisted of studies found in relevant published meta-analyses and EBSCOhost databases (finalized September 2024). The following statistics were conducted to assess the risk of bias: class-fail-safe n, Orwin’s fail-safe n, and funnel plots with trim and fill estimates. The summary statistics were r and d. Thirty studies from 1994 to 2024 met all inclusion criteria with 8708 participants from Europe, Asia, North America, and Oceania. The majority of samples were non-elite male youths and adolescents. The random-effects relationships (r) between task climate, 0.20 [0.14, 0.25], task orientation, 0.17 [0.12, 0.23], ego orientation, 0.09 [0.03, 0.16], and sport performance were small and significantly different (p < 0.05) from zero, while the ego motivational climate relationship was not, −0.00 [−0.48, 0.05]. The random-effects standard differences in means (d) for both the task orientation, 0.08 [0.02, 0.14], and ego orientation, 0.11 [−0.05, 0.26] were minimal in meaningfulness. Mixed-effects moderator analyses resulted in the following significant (p < 0.05) sub-group differences: subjective compared to objective performance measures (task orientation), elite compared to non-elite samples (task climate), and athlete-completed compared to coach-completed performance measures and performance records (task orientation). Finding only 30 studies meeting the inclusion criteria, which limited sub-group samples for moderation analyses, was the main limitation. Despite this limitation, AGT provides athletes and practitioners performance enhancement strategies. However, caution is warranted regarding relationship expectations given the small mean effect size values and the true prediction interval ranging from negative to positive, perhaps as a result of the heterogeneous samples and performance measures. A clear line of future research, considering the reviewed studies, with elite athletes is needed to verify the performance benefits of the task climate and ego orientation as well as the use of the ego goal orientation in selection decisions.

MMA is a global sport with a growing body of psychological literature. Our main objective was to replicate and extend a past review concerning the sport psychology literature with MMA participants. We conducted our electronic search in EBSCO with the following databases: SPORTDiscus, PsycINFO, ERIC, and Psychology and Behavioral Sciences Collection. Our eligibility criteria were research articles (a) found in academic journals, (b) with MMA participants, and (c) at least one topic found in sport psychology literature. After conducting a PRISMA-guided search, 16 studies met our inclusion criteria. The studies spanned from 2011 to 2021, with 795 MMA participants from the USA (n = 7), Brazil (n = 4), and one study each from Czechia, Poland, Spain, Sweden, and the United Kingdom. From studies reporting mean ages, MMA participants were in their mid-20s (M = 26.55 ± 2.38 years of age). The results section includes risk of bias ratings across five areas (i.e., subject selection, sample’s MMA background, participant anonymity, data collection procedures, and questionnaire or qualitative theme reporting). More risk of bias concerns resulted with the quantitative than qualitative articles. To best represent the studies, we presented separate results tables with many specifics for both the quantitative (i.e., topic, main analysis, time frame, summary of results, and meaningfulness) and qualitative studies (topic, main analysis, time frame, and main themes). The included studies covered a variety of historic and meta-analyzed topics such as confidence, mood, motivations, and social facilitation. Based on our review, we discussed the literature strengths and limitations, and suggested future research directions. Last, we provided practical points for both MMA participants and their trainers.