Physician Preferences for Accredited Online Continuing Medical Education
Bibliographic record
Abstract
INTRODUCTION: The need for up-to-date and high-quality continuing medical education (CME) is growing while the financial investment in CME is shrinking. Despite online technology's potential to efficiently deliver electronic CME (eCME) to large numbers of users, it has not yet displaced traditional CME. The purpose of this study was to explore what health care providers want in eCME and how they want to use it. METHODS: This was a qualitative study. Two 3-hour focus groups were held with physicians in both academic and community practices as well as trainees knowledgeable in the hypertension clinical practice guidelines with a willingness to discuss eCME. Content/thematic analysis was used to examine the data. RESULTS: Three main themes emerged: credibility, content/context, and control. Credibility was the most consistent and dominant theme. Affiliations with medical organizations and accreditation were suggested as methods by which eCME can gain credibility. The content and need for discussion of the content emerged as a key pivot point between eCME and traditional CME: a greater need for discussion was linked to a preference for traditional face-to-face CME. Control over the content and how it was accessed was an emergent theme, giving learners the ability to control the depth of learning and the time spent. They valued the ability to quickly find information that was in a format (podcast, video, mobile device) that best suited their learning needs or preferences at the time. DISCUSSION: This study provides insight into physician preferences for eCME and hypotheses that can be used to guide further research.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".