Self-Presentation Concerns Among Injured Adolescent Athletes: A Qualitative Investigation
Bibliographic record
Abstract
Sport psychology research has shown that athletes might experience self-presentation concerns. However, fairly limited work has examined these specific concerns among athletes experiencing an injury, particularly among adolescent populations. Therefore, the purpose of this qualitative study was to explore the nature, precursors, and implications of injured adolescent athletes’ self-presentation concerns. Semi-structured interviews were conducted with female (n = 12) and male (n = 2) competitive adolescent athletes (Mage = 15.1 years) who experienced a variety of serious injuries (e.g., ACL rupture, labrum tear) as a result of competing in various sports. Braun and Clark’s thematic analysis (2006) was used to develop themes pertaining to the nature, precursors, and implications of injury. Findings highlight a range of specific types of self-presentation concerns (e.g., concerns over “faking” an injury, lacking capability, disappointing others), the impact of the closeness of relationships with significant others, key implications (e.g., future sport apprehensions, negative emotions, motivational enhancements), and coping strategies. Results identify factors for targeted interventions aimed at managing self-presentation concerns among injured adolescents.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".