The reROOT Coaching Program: A Pilot Randomized Controlled Trial Evaluating Its Impact on Coaching Style and Athlete Sports Development
Bibliographic record
Abstract
The reROOT program teaches coaches 40 behaviors belonging to a need-supportive coaching style (including structure, involvement, and autonomy support), as defined by self-determination theory. This pilot randomized controlled trial, conducted during the COVID-19-related lockdown, evaluated the impact of this 18-hr program on coaching style (e.g., Problems in Sports Questionnaire) and on athlete motivation (Motivation Underlying Achievement Goals Questionnaire), performance (tactical, technical, physical, and psychological skills), and well-being (Satisfaction with Life Scale; Positive and Negative Affect Schedule). Twenty-three sports teams from two universities were randomized in the experimental or the wait-list control condition. Coaches in the experimental condition evaluated autonomy-supportive coaching styles more favorably than those in the control condition at the 1-year follow-up, but not 2 months after the end of the program. Athletes whose coaches participated in the program did not rate them as having a higher need-supportive coaching style, but experienced greater autonomous motivation and (potentially) performance, and under certain circumstances greater well-being and less controlled motivation 2 months after the end of the program compared with the wait-list condition. These findings suggest that the reROOT program could potentially improve readiness to rely on more autonomy-supportive skills and promote some aspects of sports development in 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".