Return to play following injury: whose decision should it be?
Bibliographic record
Abstract
BACKGROUND: Return-to-play (RTP) decision-making is required for every injured athlete. However, these decisions often lead to conflict between sport medicine professionals, athletes, coaches and sport associations. This study explores differences in professionals' opinion about which criteria should be used for RTP decisions, and who is best able to evaluate them. METHODS: We surveyed Canadian sport medicine physicians, physiotherapists, athletic therapists, chiropractors, massage therapists, athletes, coaches and representatives from three sport associations. The 10 min online survey asked respondents to rate criteria as mandatory to irrelevant on a five-point Likert scale, and to indicate which profession was best able to evaluate the criteria. RESULTS: In general, medical doctors, physiotherapists and athletic therapists were considered best able to assess factors related to risk of injury and complications from injury. Each clinician group (except sport massage therapists) generally believed their own profession has the best capacity to evaluate the criteria. Athletes, coaches and sport associations were considered to have the best capacity to assess factors related to competition (desire, psychological and financial impact and loss of competitive standing). There remained considerable heterogeneity both between and within stakeholder groups. CONCLUSIONS: We found that differences in approach to RTP decisions were generally greater within versus between-stakeholder groups. If shared decision-making is to become the norm in clinical sport medicine, we need to begin a discussion on which discrepancies are due to lack of training (resolved through education) or scientific knowledge (resolved through research) or simply reflect the divergence of personal/societal values.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".