Examining physician counselling to promote the adoption of physical activity.
Bibliographic record
Abstract
BACKGROUND: While the benefits of physical activity are generally recognized, over half of adult Canadians are not active enough to receive those benefits. Physicians may influence patient activity through counselling; however, research is inconsistent regarding their effectiveness in doing so. Increasing patients' use of self-regulatory skills in managing their activity and additional telephone support are suggested as two means of improving physician counselling. When assessing the effectiveness of physician counselling, it may be important to measure both outcome and treatment adherence. We compared physician-directed activity counselling (modified PACE protocol) with a modified PACE protocol augmented with telephone-based counselling for patient support for both outcome and treatment adherence. METHODS: Physicians counselled 90 patients using a modified PACE protocol that included self-regulatory skills. Physical activity was assessed by questionnaire at baseline (prior to counselling) and one month later. Participants were divided into two groups: counselling (modified PACE counselling) and enhanced counselling (modified PACE counselling plus telephone support). RESULTS: The main outcome (mean energy expenditure) and secondary outcomes of treatment adherence (frequency, frequency of moderate activity, and duration) significantly increased over time (p < 0.05). No significant interactions between group and time were found. INTERPRETATION: Our results support the effectiveness of physician counselling for activity that included the use of self-regulation skills. The effectiveness of telephone support over and above that of physician counselling was not supported. Our results demonstrate that assessing treatment adherence provides a means of discerning whether the counselling intervention was delivered as intended.
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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 | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".