Which psychosocial factors are associated with return to sport following concussion? A systematic review
Bibliographic record
Abstract
BACKGROUND: Psychosocial factors predict recurrent injury and return to preinjury level of performance following orthopedic injury but are poorly understood following concussion. Current management protocols prioritize physical measures of recovery. Therefore, the objective of this study was to describe the psychosocial factors associated with return to sport (RTS) and how they are measured in athletes who sustained a concussion. METHODS: MEDLINE, Embase, APA PsycINFO, CINAHL, and SPORTDiscus were searched through February 2, 2021. Eligible studies included original peer-reviewed publications describing psychosocial factors associated with RTS following a diagnosed concussion. The primary outcome was scales or measures employed and/or key thematic concepts. RESULTS: Of the 3615 studies identified, 10 quantitative cohort studies (Oxford Centre for Evidence-Based Medicine Level-3) representing 2032 athletes (85% male; high-school and collegiate collision/contact athletes) and 4 qualitative studies representing 66 athletes (74% male; 70% American football; aged 9-28 years) were included. We identified 3 overarching themes and 10 outcome measures related to psychosocial factors associated with RTS following concussion: (a) fear (e.g, of recurrent concussion, of RTS, of losing playing status); (b) emotional factors (e.g, depression, anxiety, perceived stress, mental health, disturbance mood); and (c) contextual factors (e.g, social support, pressure, sense of identity). CONCLUSION: Although current medical clearance decisions prioritize physical measures of recovery, evidence suggests diverse psychosocial factors influence RTS following concussion. It remains unclear which psychosocial factors contribute to a successful RTS, including the influence of sex/gender and age. Future studies should evaluate the association of psychological readiness with physical measures of recovery at medical clearance, preinjury level of performance, and risk of recurrent concussion to support RTS clinical decision-making.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".