A Qualitative Longitudinal Exploration of Interactions Between Female Athletes and Sport Medicine Staff During Injury Rehabilitation
Bibliographic record
Abstract
CONTEXT: Sport injury is a prevalent setback experienced by athletes, wherein they are required to spend time in rehabilitation and interact with sport medicine staff. Sport medicine staff are a frequent line of contact line of contact for athletes at this time and represent an important part of their support network. There is little exploration surrounding the interactions that female athletes have with sport medicine staff during injury rehabilitation and how these interactions may impact the rehabilitation process. The purpose of this research is to explore the experiences of injured female athletes and their interactions with sport medicine staff during injury rehabilitation. DESIGN: Qualitative study using semistructured qualitative interviews and audio diaries. Interpretive descriptive methodology. METHODS: A total of 11 injured female varsity athletes who had sustained a musculoskeletal injury within 2 to 4 weeks of being recruited participated. A total of 6 upper body injuries and 5 lower body injuries are represented. Athletes completed 2 semistructured interviews and weekly audio diary entries across 6 weeks. Data were analyzed using reflexive thematic analysis. RESULTS: Results demonstrated that female athletes felt supported by sport medicine staff when provided with clear information about rehabilitation, when they perceived sport medicine staff as competent, and when sport medicine staff made a personal connection. An overarching theme of mattering was identified as underpinning the athletes' experiences of feeling supported by sport medicine staff during rehabilitation. CONCLUSIONS: When sport medicine staff made female athletes feel that they mattered, they were perceived as more supportive during rehabilitation. Sport medicine staff can help athletes to feel that they matter by engaging in supportive behaviors during the rehabilitation process.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".