Athletes’ lived experiences recovering from and returning to sport following a sport-related concussion: a meta-synthesis of qualitative studies
Bibliographic record
Abstract
A small, but growing body of qualitative studies have explored athletes’ lived experiences with sport-related concussions (SRCs). For this meta-synthesis, we reviewed and synthesized qualitative, peer-reviewed studies on athletes’ lived experiences during recovery from and/or return to sport following SRC. Following PRISMA guidelines, we initially identified 5062 articles through PsycINFO, Embase, MedLine, SportDiscus, and Web of Science. After eliminating duplicates, screening titles, abstracts and full texts, 33 peer-reviewed articles matched our inclusion criteria. Subsequently, the authors appraised the quality of the included articles using the Critical Appraisal Skills Program. We followed guidelines for thematic synthesis, in which we initially developed 16 descriptive themes, each rooted in the original data extracted from the 33 articles. Subsequently, we developed four analytical themes that were informed by the descriptive themes and existing models and frameworks in the sport and exercise literature: (a) SRC characteristics: Identifying SRC features, (b) SRC consequences: Understanding the impact of the injury, (c) SRC outcomes: Discovering paths to recovery, and (d) Influential factors: Exploring the contextual factors affecting SRC consequences and outcomes. Our findings offer a comprehensive description of qualitative evidence on athletes’ lived experiences with SRC, including gaps in knowledge and insights for future research in the field.
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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 | 0.111 | 0.229 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".