A sport-specific ACT group intervention for promoting athletes’ mental well-being: a randomized controlled trial
Bibliographic record
Abstract
The aim of the present study was to investigate the effects of a sport-specific acceptance and commitment therapy (ACT) group intervention on mental well-being and stress symptoms in athletes. In this randomized controlled superiority trial (RCT), national level athletes (n = 95; 55% female, 45% male; mean age 19.9 years) were pair-matched and randomly assigned to either an ACT intervention group (INT, n = 49) or a waitlist control group (WLC, n = 46). All the measures were administered pre- and post-intervention, which comprised of six face-to-face group sessions supplemented by home exercises over a 6-week period. Primary outcomes were mental well-being and stress. Other outcomes were experienced recovery, self-esteem, depression symptoms, and psychological flexibility skills. The results show improved mental well-being (d = 0.33, small difference) and reduced stress symptoms (d = 1.13, large difference) in the ACT group compared to the WLC condition between pre- and post-measurement. Also, the ACT group reported increased psychological flexibility (d = 0.31 − 0.53, small to medium difference). Evidence was found that athletes’ mental well-being and psychological flexibility skills improved after the brief 6-week ACT group intervention. Our findings indicate that a sport-specific ACT group intervention model might be an effective option for promoting the mental well-being of athletes.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".