Physicians’ Intention and Behavior After Continuing Professional Development Courses: A Pre - Post Study
Bibliographic record
Abstract
Context: Continuing professional development (CPD) is a common way for physicians to update their clinical practice. Providers of CPD seek to improve their courses, but to the best of our knowledge, few use theory-informed measurement tools to evaluate their impact. Objective: This study aimed to evaluate the impact of courses, identify factors that influence physicians9 intention to adopt a targeted clinical behavior after a course, and whether their intention influenced whether they actually adopted the behavior. Study Design and Analysis: Study with pre - post measures, guided by an integrated behavior change framework developed by Godin et al. Descriptive statistics were performed. A linear regression model was used for bivariate and multivariate analyses. Setting or Dataset: Data were collected online from the databases of the Federation of Medical Specialists of Quebec (FMSQ). Participants completed: 1) sociodemographic and CPD-REACTION questionnaires before courses (n=158), 2) CPD-REACTION questionnaire after courses (n=129) and 3) a self-reported behavior change questionnaire six months later (n=47). Population Studied: Specialist physicians who participated in one of 9 selected courses at a training day of the FMSQ in 2019. Intervention/Instrument: Participation in person at least one of 9 CPD courses at an interdisciplinary training day, completion of the CPD-REACTION questionnaire, and completion of a self-reported behavior change questionnaire. Outcome Measures: Intention to adopt the targeted behavior was measured with the CPD-REACTION questionnaire, a validated measurement tool designed to assess the impact of a CPD courses on the intention of health professionals. Scores vary between 1 and 7. Self-reported behavior change was collected 6 months later with a second questionnaire. Results: Intention increased after courses (means difference=0.45, p 0.002). Post-courses, moral norm, beliefs about capabilities and beliefs about consequences emerged as predictors of increased intention. The mean score of intention of participants who later self-reported as having adopted the targeted behavior was higher than the mean score of intention of participants who had not (6.63 vs 6.00, p 0.02). Conclusions: Findings suggested that intention increased after courses and was influenced by moral norm, beliefs about capabilities and beliefs about consequences. Intention after course was correlated to self-reported behavior 6 months later.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".