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Determinants of Anxiety in Elite Athletes

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Determinants of Anxiety in Elite Athletes Systematic review Br J Sports Med: first published as 10.1136/bjsports-2019-100620 on 16 May 2019. Downloaded from Determinants of anxiety in elite athletes: a systematic review and meta-analysis Simon M Rice, 1,2 Kate Gwyther, 1,2 Olga Santesteban-Echarri, 3 David Baron,4 Paul Gorczynski,5 Vincent Gouttebarge,6,7 Claudia L Reardon, 8,9 Mary E Hitchcock,10 Brian Hainline, 11 Rosemary Purcell1,2 4 ► Additional material is ABSTRact (GAD) or social anxiety disorder. Additionally, published online only. To view Objective To identify and quantify determinants of anxiety can be a situationally or event-dependent please visit the journal online transitory state (eg, state anxiety), or a relatively (http:// dx. doi. org/ 10. 1136/ anxiety symptoms and disorders experienced by elite bjsports- 2019- 100620). athletes. stable personality characteristic (eg, trait anxiety). Design Systematic review and meta-analysis. State anxiety symptoms are more likely to occur in For numbered affiliations see Data sources Five online databases (PubMed, situations perceived as threatening.6 end of article. SportDiscus, PsycINFO, Scopus and Cochrane) were Athlete-specific factors may precipitate or exac- searched up to November 2018 to identify eligible erbate anxiety disorders, including pressures to Correspondence to citations. perform and public scrutiny,7 career uncertainty or Dr Simon M Rice, Research 8 9 10–12 and Translation, Orygen, The Eligibility criteria for selecting studies Articles dissatisfaction, and injury. General psychoso- National Centre of Excellence were included if they were published in English, were cial factors are also strongly implicated in the onset in Youth Mental Health, quantitative studies and measured a symptom-level and maintenance of anxiety disorders within the Melbourne, VIC 3052, Australia; anxiety outcome in competing or retired athletes at the general population. These include behavioural inhi- simon. rice@ orygen. org. au professional (including professional youth), Olympic or bition, social withdrawal or avoidance, and cogni- 13 Received 22 January 2019 collegiate/university levels. tive patterns of rumination. A recent meta-analysis Revised 13 March 2019 Results and summary We screened 1163 articles; 61 found that female gender, younger age and lower Accepted 14 March 2019 studies were included in the systematic review and 27 of athletic experience were associated with higher them were suitable for meta-analysis. Overall risk of bias competitive anxiety in athletes14; however, the for included studies was low. Athletes and non-athletes specific determinants of anxiety disorders in elite had no differences in anxiety profiles (d=−0.11, p=0.28). athlete populations has not yet been reported. Pooled effect sizes, demonstrating moderate effects, Identification of putative subgroup differences may were identified for (1) career dissatisfaction (d=0.45; assist with early identification and indicated preven- higher anxiety in dissatisfied athletes), (2) gender tion efforts in this population, improving the timely (d=0.38; higher anxiety in female athletes), (3) age management of anxiety disorders among elite (d=−0.34; higher anxiety for younger athletes) and (4) athletes. The objective of this study was to perform musculoskeletal injury (d=0.31; higher anxiety for injured a systematic review and meta-analysis to identify, http://bjsm.bmj.com/ athletes). A small pooled effect was found for recent quantify and analyse determinants of anxiety symp- adverse life events (d=0.26)—higher anxiety in athletes toms experienced by elite athletes. who had experienced one or more recent adverse life events. METHOD Conclusion Determinants of anxiety in elite The study was conducted in accordance with the populations broadly reflect those experienced by the Preferred Reporting Items for Systematic Reviews general population. Clinicians should be aware of these and Meta-Analyses guidelines. on September 26, 2021 by guest. Protected copyright. general and athlete-specific determinants of anxiety among elite athletes. Search strategy A systematic search strategy was developed by an experienced academic librarian (MEH). The INTRODUCTION search was executed in the PubMed, SportDiscus, Combined anxiety disorders affect the general PsycINFO, Scopus and Cochrane databases from population at an estimated (past 12 month) rate inception until November 2018. The search strategy of 10.6%–12.0%,1 2 with broadly similar rates and MeSH terms are presented in online supple- suggested among elite athlete populations (8.6%),3 mentary table 1. Citations were independently defined as those competing at professional, Olympic screened by SMR, RP and KG. or collegiate/university levels. Anxiety disorders are © Author(s) (or their characterised by emotional responses associated with Study inclusion employer(s)) 2019. Re-use permitted under CC BY-NC. No fear, apprehension, worry and tension in response Studies were selected if they included (1) data on 4 commercial re-use. See rights to an actual or perceived threat. Anxiety modu- elite athletes, including para-athletes, defined by and permissions. Published lates attentional networks, resulting in compro- standard of performance level,15 competing at the by BMJ. mised executive function, stimulus processing and professional (and professional youth, ie, members 5 To cite: Rice SM, Gwyther K, information selection —all important domains of elite sports schools), Olympic and collegiate/ Santesteban-Echarri O, for elite competition. While commonalities are university levels; (2) a symptomatic or diagnostic et al. Br J Sports Med present, diagnostic systems differentiate anxiety anxiety outcome measure (as per the Diagnostic and 2019;53:722–730. subtypes, such as generalised anxiety disorder Statistical Manual of Mental Disorders [DSM-5]4 Rice SM, et al. Br J Sports Med 2019;53:722–730. doi:10.1136/bjsports-2019-100620 1 of 10 Systematic review Br J Sports Med: first published as 10.1136/bjsports-2019-100620 on 16 May 2019. Downloaded from criteria) in relation to GAD, specific phobia, social anxiety, (current vs former). As subgroup analysis calculates an estimated panic disorders or obsessive-compulsive disorder (OCD); and effect size for each subgroup, a minimum of two subgroups with (3) currently competing or retired athletes (authors adopted a two contributing studies each were required to conduct a statis- maximum mean retirement length of 10 years to allow investi- tically sound analysis for a determinant.22 Additionally, sensi- gation of effects between anxiety and longer-term sport-specific tivity analysis was conducted when significant heterogeneity was outcomes [eg, concussion],16 and account for, yet limit the effect observed. Sensitivity analysis is a repeat of the initial analysis of retirement).17 which substitutes alternate inclusion or exclusion decisions to assess robustness of the results.24 Sensitivity analysis was calcu- Study exclusion lated by removing any visual outliers or studies with dissimilar Studies were excluded if they were not published in English, characteristics. were a case study or case report, used a qualitative design, were review articles or were not refereed journal articles (confer- Interpretation of forest plots ence abstracts were excluded), or focused solely on state-based A forest plot is a visual representation of the effect size for each performance or competitive anxiety (ie, included studies needed study, represented by squares, and the overall estimated effect to report on a measure/diagnosis of symptom-level anxiety as size, represented by a diamond. The side of the forest plot on per DSM-5). which the effect size estimate falls indicates a higher anxiety score in that group. For plots with subgroup analysis, overall Assessment of study quality effect size estimates are reported in the text. We assessed quality of studies with the Joanna Briggs Institute’s critical appraisal tools for systematic reviews.18 These tools are validated appraisal checklists specific to study design, capturing Heterogeneity and publication bias aspects of design quality, analysis and reporting. KG assessed The Q statistic measured the presence or absence of heteroge- studies using checklists for randomised controlled trials (RCTs), neity by testing the null hypothesis of no variation in true effect cohort studies, prevalence studies, cross-sectional studies and size across studies.25 Heterogeneity was assumed when the Q quasi-experimental studies. The appraisal score reported is the statistic was significant, as the null hypothesis of no variation proportion of ‘yes’ responses on the total number of criteria. If a is rejected. The I2 statistic describes the proportion of variance criterion was not applicable (N/A) to a given study, that item was in observed effects due to variance in true effects and can be not counted in the total number of criteria. interpreted as the percentage of variance that would remain if there was no sampling error.26 Low I2 scores indicate lower Data extraction heterogeneity. Publication bias was assessed using the Duval and 27 A standard template was designed for data extraction of study Tweedie trim-and-fill funnel plot method. A funnel plot is a and sample characteristics including study design, aim, loca- graphical representation of study size as a function of effect size; tion, gender ratio, sport population, anxiety outcome and key large studies generally appear at the top of the graph, close to findings. KG extracted the data and SMR reviewed
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