Shared Decision-Making About Returning to Sport After Recovery From Pediatric Concussion: Clinician Perspectives
Bibliographic record
Abstract
OBJECTIVE: Describe how sports medicine clinicians support decision making about sport participation after concussion recovery with adolescent patients and their parents. Specific areas of inquiry related to how clinicians framed the decision, what factors they considered in how they approached the decision process, and how they navigated discordance within families. DESIGN: Qualitative study. SETTING: Tertiary care sports medicine clinics at 4 children's hospitals in the United States. PARTICIPANTS: Individual interviews were conducted with 17 clinicians practicing in sports medicine settings. INTERVENTIONS: N/A. MAIN OUTCOME MEASURES: Semi-structured interviews explored clinician approaches to supporting decision making, with the question guide informed by components of the Ottawa Decision Support Framework. RESULTS: Clinicians routinely incorporated aspects of shared decision making (SDM) into their conversations with families. This included ensuring all parties were informed about risk and aligned behind a shared value of adolescent well-being. Mediation strategies were used to manage discordance between adolescents and their parents, and between parents. These strategies aimed to facilitate a decision that was adolescent centered. When clinicians believed that there was a medical benefit to modifying the adolescent's sport participation practices, or when they did not believe the athlete was psychologically ready to return to the sport in which they were injured, they initiated conversations about alternative activities. In such situations, they used persuasive communication practices to encourage families to strongly consider this option. CONCLUSION: The strengths and strategies used by sports medicine clinicians in this study provide a foundation for guidance or intervention development aimed at supporting SDM after concussion with adolescents and their families.
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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 | 0.023 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".