Videoconferencing for practice-based small-group continuing medical education: Feasibility, acceptability, effectiveness, and cost
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Small-group, practice-based learning is an effective and well-accepted method of continuing medical education (CME). However, one limitation is that many physicians work in communities with fewer than the minimum number recommended for an effective learning group. Videoconferencing has the potential to remove this limitation. The purpose of this study was to evaluate the feasibility, acceptability, effectiveness, and cost of conducting practice-based, small-group CME learning by videoconference. METHODS: Through a videoconferencing link, 10 learners in three communities were guided through four practice-based learning modules by a trained facilitator at a fourth site. Data were collected through evaluation questionnaires, direct observation by the research team, pre- and post-knowledge tests, a focus group, and an interview. RESULTS: A total of 31 learners participated in the four modules. Videoconferencing was generally well accepted by learners. The facilitator and research team observers noted that muting microphones, video quality, audio quality, and audio lag all somewhat hindered discussion. Overall, the facilitator found moderating by videoconference only slightly more difficult than a face-to-face session. There was evidence of knowledge gain, with post-test scores being 20% higher than pretest scores (p = .006). Learners reported nine practice changes from taking the modules. At commercial rates, telecommunications costs per videoconferenced module were approximately CAN$1,200. DISCUSSION: Videoconferencing has the potential to bring the benefits of small-group, practice-based learning to many physicians; however, strict attention to videoconferencing techniques is required. Cost is also an important consideration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.017 |
| 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 | 0.001 |
| 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 it