Toward an evidence-informed, theory-driven model for continuing medical education
Bibliographic record
Abstract
This thesis develops the basis for an evidence-informed, theory-driven educational model for planning, implementing and evaluating continuing medical education (CME). Using an historical and conceptual analysis the author argued current CME educational planning models, based on Tyler's Curriculum Model, failed to build a systematic body of knowledge to improve learning and teaching and are founded on historical, structural, organizational and pedagogical factors that arose from research and beliefs about learning prevalent at the turn of the twentieth century. Using a case study of a three-year province-wide, evidence-informed, multi-agency, comprehensive education program to enhance family and emergency physicians' knowledge and skills regarding the diagnosis and management of whiplash-associated disorders, the thesis demonstrates the feasibility and adaptability of using the PRECEDE-PROCEED Model for CME. The PRECEDEPROCEED Model is a community-oriented and epidemiological-based educational planning model that provides a systematic approach to identifying and organizing contextual factors influencing knowledge uptake and knowledge utilization. The case study provides a basis for modifying the PRECEDE-PROCEED Model as a tool for planning, implementing and evaluating CME programs. The changes are intended to assist CME planners in integrating behavioural and non-behaviour factors with theory and best practices in the actual "curriculum" or intervention-program design. In addition, the proposed modification to the PRECEDE-PROCEED Model adheres to the standards established by the Joint Committee on Standards for Educational Evaluation as to what a comprehensive evaluation should address. Based on the case study, the thesis recommends a modification to the current PRECEDE-PROCEED model of health promotion that provides a clearer conceptual understanding of the structure, components and theoretical underpinnings of an emerging evidence-informed, theory-based curriculum model.
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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 | 0.078 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.018 | 0.012 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.008 | 0.010 |
| 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".