Exploring Body Image Through the Injury and Rehabilitation Process of Female Intercollegiate Gymnasts: A Multi-Case Study
Bibliographic record
Abstract
Injury is a known inherent risk when participating in any physical activity. In particular, gymnasts exhibit high overuse and traumatic injury rates, attributed to the nature and volume of their training. The resulting injury and rehabilitation process can present many challenges, which are unique to each individual. During this time, body image perceptions may change which could potentially lead to unique cognitive, emotional, and behavioural responses. The purpose of this multiple case study was to explore body image throughout the injured female gymnasts’ rehabilitation experience and their return to intercollegiate sport. Participants included three National Collegiate Athletic Association (NCAA) Division 1 female gymnasts aged 18-23 who sustained a moderate to severe injury. Each participant completed three semi-structured interviews. Thematic data analysis produced three main themes: 1) Social Group Influences; 2) Heightened Body Image Awareness; and 3) College Gymnastics Culture. Knowledge gained from this study could be applied to the development of intervention strategies for body image disturbances in athletes, leading to a more comprehensive and individualized rehabilitation program.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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".