Assessing the effectiveness of the transformational coaching workshop using behavior change theory
Bibliographic record
Abstract
Coach development programs (CDPs) provide an avenue for youth sport coaches to learn about the knowledge and behaviors necessary to facilitate positive athlete outcomes. More recently, an evidence-informed, interpersonal-focused CDP, the Transformational Coaching Workshop (TCW; Turnnidge & Côté, 2017), yielded promising findings for its effect on the observable leadership behaviors of youth sport coaches after participation (Lawrason et al., 2019). However, it is unknown what factors facilitated the changes in coaches' behaviors post-workshop. The COM-B of behavior change (Michie et al., 2011) suggests that there are three factors necessary for any behaviour to occur: capability, opportunity, and motivation. Therefore, this study used the COM-B model to identify coaches' perceptions of the barriers and facilitators that influence the effectiveness of the TCW. Sixty-three volunteer youth sport coaches participated in the study as part of an intervention (n = 31; Mage = 45.65 years; SDage = 8.82 years) or comparison group (n = 32; Mage = 44.59 years; SDage = 11.86 years). Using a two-arm, non-randomized pre- and post-intervention design, dependent- and independent-samples t-tests were conducted to assess within and between-group differences of coaches' perception of their capability, opportunity, and motivation to use transformational coaching behaviors. Although not statistically significant, effect sizes indicated that participants in the intervention group reported improvements in their perceived capability and opportunity to use transformational coaching behaviors at post-intervention. This study provides support for the effectiveness of the TCW, and continued application of behavior change frameworks into coaching intervention research.Acknowledgments: This research was supported by the Social Sciences and Humanities Research Council.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".