Application of the behaviour change technique taxonomy to coaching strategies used in inclusive physical activity programming for children and youth
Bibliographic record
Abstract
Coaches play a vital role in shaping the experience of children and youth in the physical activity (PA) programs they deliver. This study focuses on an inclusive PA program, Igniting Fitness Possibilities (IFP), which embraces the emerging abilities and motivation levels of school-aged children and youth with diverse abilities. An integral component of IFP is individualized coaching where participants are provided with opportunities to learn, practice, and reflect on their PA development. The purpose of this study was to examine the use of behaviour change techniques (BCTs) during the coaching sessions. Methods: Coaching logs of 11 coaches in eight of the IFP pilot programs held across the Greater Toronto and Durham regions between Winter 2015 and Spring 2017 were coded by a trained research assistant. Data were extracted and coded across the entire sample of 42 children and youth using Michie et al.'s BCT Taxonomy (v1). Thirty-two of the 93 BCTs were coded across the eight IFP programs, with instruction on how to perform the behaviour, demonstration of the behaviour, and behavioural practice/rehearsal being the most frequently used BCTs by coaches. The number of BCTs per program ranged from eight to 19. Coaching strategies relating to 'providing choice' and 'modifying activities to participants' abilities' were often used, yet did not align with the BCT Taxonomy. Findings highlight key BCTs within the context of inclusive, community-based PA programs that are important to target for enhancing the PA experiences of children and youth with diverse abilities.Acknowledgments: This study was supported by the Social Sciences and Humanities Research Council of Canada. Insight Development Grant #430-?2014-?00157. We extend our gratitude to the study participants.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".