British junior elite track and field athletes’ experience of maltreatment, psychological safety, and subjective vitality
Bibliographic record
Abstract
In this study, we examined 1) the prevalence of maltreatment in British junior elite track and field athletes, 2) relationships between maltreatment, psychological safety, and subjective vitality, and 3) whether maltreatment is indirectly related to subjective vitality via psychological safety. Using a cross-sectional design, British junior elite track and field athletes (N = 254) completed measures of maltreatment (physical, psychological, non-contact sexual and neglect), psychological safety and subjective vitality. Results showed that nearly three-quarters experienced maltreatment in sport (74.4%). Psychological maltreatment was most frequently reported (70.5%), followed by neglect (50.8%), physical (31.5%) and non-contact sexual (24.0%). Psychological and physical maltreatment, and neglect were indirectly related to subjective vitality via psychological safety (effect size range = −0.27 to −0.11), whereas no relationship was shown between non-contact sexual maltreatment and psychological safety. In conclusion, maltreatment is prevalent in British junior elite track and field athletes and that those who experience physical and psychological maltreatment, as well as neglect, are more likely to report lower psychological safety, and in turn, lower subjective vitality. International and national organisations aiming to protect athlete well-being should target psychological safety in their safeguarding interventions by supporting and encouraging athletes to speak out about their concerns.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".