Key ingredients for "changing minds": Determining the effectiveness and effective components of an educational intervention to enhance health care professionals' intentions to prescribe physical activity
Bibliographic record
Abstract
Health care professionals (HCPs) are vital conduits of leisure-time physical activity (LTPA) information; however, few discuss LTPA with patients with physical disabilities. Changing Minds, Changing Lives (CMCL) is a nationwide, theory- and evidence-based seminar aimed at increasing HCPs’ attitudes, subjective norms, and perceived behavioural control (PBC) for discussing LTPA. The purposes of the current study were to examine the effectiveness and maintenance of a CMCL seminar on HCPs’ social cognitions for discussing LTPA, and to explore the key implementation variables that predict changes in HCPs’ cognitions. Prior-to, as well as immediately-, 1-, and 6-months following a CMCL seminar, 97 HCPs (Mage±SD=36.23±10.42; 69% female; 38% rehabilitation therapists) from five Canadian provinces completed questionnaires that assessed the Theory of Planned Behavior (TPB) constructs with regard to discussing LTPA. Key implementation variables that may influence HCPs’ cognitions were extracted from presenter demographic questionnaires and seminar checklists. Separate repeated-measures ANOVAs and post-hocs revealed significant increases in HCPs’ cognitions for discussing LTPA post-seminar (ps<.002); however, increases were not maintained at follow-up. PBC emerged as the strongest predictor of participants’ post-CMCL intentions (β=.45, p<.001). Although several implementation characteristics were related to changes in perceptions, hierarchical regression analyses for each cognition revealed that the number of seminars the presenter delivered was the only significant negative predictor of post-seminar PBC (β=-.18, p<.05). Future iterations of CMCL should include additional strategies to sustain HCPs’ LTPA-related cognitions over time. Future CMCL evaluations should measure additional implementation variables so that the effective ingredients for “Changing Minds” can continue to be investigated.Acknowledgments: This research was partially supported by an Ontario Neurotrauma Foundation Award for Capacity Building in Knowledge Mobilization awarded to the first author and a Community-University Research Alliance from the Social Sciences and Humanities Research Council of Canada awarded to the second author. The authors would like to acknowledge The Canadian Paralympic Committee for their assistance with the dissemination of the new curriculum and data collection from the participants, as well as Krystina Malakovski, Krystn Orr, and Laura Tambosso for their assistance with data collection.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".