Physical Activity Counseling Education: The Use of Theory in Development, Implementation, and Evaluation
Bibliographic record
Abstract
INTRODUCTION: Implementing evidence-based physical activity (PA) counseling for clients with spinal cord injury (SCI) may help address the decline in PA typically observed after discharge from rehabilitation. Engaging practitioners in educational intervention development may improve uptake of such a practice change. The purpose of this study is to (1) describe the theory-based development of a PA counseling education intervention and (2) evaluate the intervention's effects on PA counseling behavior and determinants (eg, knowledge, skills, confidence) among rehabilitation hospital physiotherapists and community SCI peers. METHODS: The Knowledge to Action (KTA) Framework supplemented by the quality implementation framework was used to guide the engagement of physiotherapists and SCI peers in developing a PA counseling education intervention. A within-subjects, repeated measures design was used to evaluate the effects of the intervention. PA counseling behavior and determinants were evaluated using a survey guided by the theoretical domains framework, administered before and immediately after training, 2 months post, and 6 months post-training. Data were analyzed using one-way repeated-measures ANOVAs. RESULTS: Physiotherapists and SCI peers (n = 10) demonstrated significant, medium-large-sized effects on PA counseling behaviors from baseline to 2 and 6 months ( P' s < 0.05). These behavioral improvements were supported by significant increases over time in all theoretical domains framework assessed ( P' s < 0.05), except intentions. DISCUSSION: The combined use of the KTA and quality implementation framework provides a structure for engaging practitioners in education intervention design. This work shows promise for the use of theory to develop an education intervention that improves both PA counseling knowledge and behavior.
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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 | 0.104 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".