Coach development programmes to improve interpersonal coach behaviours: a systematic review using the re-aim framework
Bibliographic record
Abstract
OBJECTIVE: Although evidence supports the effectiveness of interpersonal Coach Development Programmes (CDPs), which are designed to foster coach-athlete relationships, an intervention's impact is shaped by numerous factors over and above effectiveness. The purpose of this systematic review was to examine the extent that published articles describing interpersonal CDP trials reported on indicators of internal and external validity, as conceptualised in the RE-AIM framework (ie, Reach, Effectiveness, Adoption, Implementation and Maintenance). METHODS: The search strategy was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, involving a database search and supplemental manual search of key articles and journals. After initial screening, the full-text search strategy involved identifying articles describing CDP trials and then selecting a specific subgroup of articles involving interpersonal CDP trials and excluding ineligible articles. Resulting trials were coded using a 47-item sport coaching adaptation of the RE-AIM coding sheet. RESULTS: 17 published articles met eligibility criteria, representing 10 distinct CDP trials. After attaining coder agreement, global ratings of RE-AIM indicators within interpersonal CDP trials ranged from the low to moderate quality. Whereas indicators of effectiveness and implementation were reported to some extent across all studies, maintenance within sport organisations and a number of specific indicators from across dimensions were rarely reported. CONCLUSIONS: These findings inform the future design and evaluation of CDPs that have the potential to be adopted in numerous settings and reach athletes and coaches who can most benefit.
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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 | 0.030 | 0.086 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".