Transitioning out of elite sport: The central role of groups in support experiences
Bibliographic record
Abstract
In the present study, we explored the perceived impact of changes in athletes' social group memberships on their identities and social support experienced during transition to retirement. Using interpretative phenomenological analysis, we explored how athletes interpreted their experiences and connected them to their personal and social environments. Participants were seven (5 male, 2 female) former elite athletes, aged 26 and 40 years (Mage = 34 ± 4.96 years). They represented badminton, basketball, football/soccer, and rugby, having transitioned from their sport careers 9 months to 11 years prior to data collection (M = 5.25 ± 3.85 years). Data were collected through semi-structured interviews, and analysis included reflexivity and an independent audit trail. We identified four main themes: (a) support received from maintaining existing social groups, (b) support opportunities gained by joining new social groups, (c) the support lost through identity changes in retirement, and finally, (d) the support offered by adopting a retired athlete identity. The results highlight the importance of approaching athlete identity and retirement from a social identity perspective. Our results also suggest that social groups and subsequent social identities may influence psychosocial outcomes through group-based social support, while arguing that the effectiveness of social support depends on the compatibility of these identities with an athlete's existing or gained identities. Finally, we offer applied considerations for athletes and sport organizations, suggesting that retired athletes benefit from mentoring and engaging in organizations supporting transitioned athletes to build meaningful connections during this 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".