Adaptation to life after sport for retired athletes: A scoping review of existing reviews and programs
Bibliographic record
Abstract
Retirement from sport is a life transition that has significant implications for athletes' physical and mental health, as well as their social and professional development. Although extensive work has been done to review the retirement experiences of athletes, relatively less work has been done to examine and reflect on this expansive body of literature with a pragmatic aim of deciding what needs to happen to better support retiring athletes. This study used scoping review methodology to review current academic reviews, gray literature articles, and support programs on athletic retirement. This review followed the Joanna Briggs Institute reviewer's manual guide on scoping reviews and adhered to the PRISMA-ScR checklist. Academic articles were identified from PubMed, Embase, Web of Science and Scopus. Gray literature articles and support programs were identified using advanced Google searches. This study identified 23 academic reviews, 44 gray literature articles, and 15 support programs. Generally, the results suggest that athletic retirement encompasses a drastic shift in identity, a loss of social networks, a lack of career ambitions, and potential risks to physical and mental health. While there was a gap in the academic literature regarding practical strategies to support retiring athletes, the gray literature suggests many creative ideas. Stepwise programming may be beneficial to help athletes: (a) make sense of their athletic experience and see retirement as an ongoing process; (b) develop a well-rounded sense of self identity and understand how to apply their unique skills and strengths in new ways; (3) gain control over their retirement transition by establishing a clear plan and adjusting to new routines and opportunities; and (4) normalize the transition experience by "living in the next" and building confidence in new life directions. Future research may benefit from developing and evaluating more programming to support athletes through the retirement transition.
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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 | 0.019 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.025 | 0.022 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".