Transitioning Out of Elite Sport: The Experience of Integrated Support-Team Members
Bibliographic record
Abstract
Integrated support teams (ISTs) are composed of multidisciplinary performance-support professionals dedicated to enhancing the performance of elite athletes. IST roles involve unique demands, particularly during the understudied career transitions. This study explored lived experiences of IST members transitioning out of elite sport roles, emphasizing the barriers and facilitators to successful transitions. Using an interpretive description framework, six former IST members (four physicians and two physiotherapists; four women and two men) who supported Canadian international-level teams participated in semistructured interviews conducted between October 2022 and January 2023. Themes encapsulated pretransition (preparing transition plan), during-transition (service continuity, communication variation, lack of support, and seeking mentorship), and posttransition phases (coping with emotions, managing identity, and reconciling aspirations). Barriers included poor organizational oversight, role instability, and ego involvement, and facilitators were social support, continuing meaningful work, and transition involvement. Our findings suggest that formalized processes, mentoring, and resource provision are essential for IST member support and service continuity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".