Effects on readiness to change of an educational intervention on depressive disorders for general physicians in primary care based on a modified Prochaska model--a randomized controlled study
Bibliographic record
Abstract
BACKGROUND: The Prochaska model of readiness to change has been proposed to be used in educational interventions to improve medical care. OBJECTIVE: To evaluate the impact on readiness to change of an educational intervention on management of depressive disorders based on a modified version of the Prochaska model in comparison with a standard programme of continuing medical education (CME). METHODS: This is a randomized controlled trial within primary care practices in southern Tehran, Iran. The participants included 192 general physicians working in primary care (GPs) were recruited after random selection and randomized to intervention (96) and control (96). Intervention consisted of interactive, learner-centred educational methods in large and small group settings depending on the GPs' stages of readiness to change. Change in stage of readiness to change measured by the modified version of the Prochaska questionnaire was the RESULTS: The final number of participants was 78 (81%) in the intervention arm and 81 (84%) in the control arm. Significantly (P < 0.01), more GPs (57/96 = 59% versus 12/96 = 12%) in the intervention group changed to higher stages of readiness to change. The intervention effect was 46% points (P < 0.001) and 50% points (P < 0.001) in the large and small group setting, respectively. CONCLUSIONS: Educational formats that suit different stages of learning can support primary care doctors to reach higher stages of behavioural change in the topic of depressive disorders. Our findings have practical implications for conducting CME programmes in Iran and are possibly also applicable in other parts of the world.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".