Are online learning modules an effective way to deliver hand trauma management continuing medical education to emergency physicians?
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
Background The enormity of modern medical knowledge and the rapidity of change have created increased need for ongoing or continuing medical education (CME) for physicians. Online CME is attractive for its availability at any time and any place, low cost and potentially increased effectiveness compared with traditional face-to-face delivery. Objective To determine whether online CME modules are an effective method for delivering plastic surgery CME to primary care physicians. Methods A needs assessment survey was conducted among all emergency and family physicians in Nova Scotia. Results indicated that this type of program was appealing, and that hand trauma related topics were most desired for CME. 7 Lesson Builder (SoftChalk LLC, www.softchalk.com ) was used to construct a multimedia e-learning module that was distributed along with a pretest, post-test and feedback questionnaire. Quantitative (pre- and post-test scores) and qualitative (feedback responses) data were analyzed. Results The 32 participants who completed the study indicated that it was a positive and enjoyable experience, and that there was a need for more resources like this. Compared with pretest scores, there was a significant gain in knowledge following completion of the module (P=0.001). Conclusion The present study demonstrated that an e-learning format is attractive for this population and effective in increasing knowledge. This positive outcome will lead to development of additional modules.
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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 | 0.001 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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