eLearning among Canadian anesthesia residents: a survey of podcast use and content needs
Bibliographic record
Abstract
BACKGROUND: Podcasts are increasingly being used in medical education. In this study, we conducted a survey of Canadian anesthesia residents to better delineate the content needs, format preferences, and usage patterns among anesthesia residents. METHODS: 10/16 Canadian anesthesia program directors, representing 443/659 Canadian anesthesia residents, allowed their residents to be included in the study. 169/659 (24%) residents responded to our survey. A 17-item survey tool developed by the investigators was distributed by email eliciting information on patterns of podcast use, preferred content, preferred format, and podcast adjuncts perceived to increase knowledge retention. RESULTS: 60% (91/151) had used medical podcasts with 67% of these users spending up to 1 hour per week on podcasts. 72.3% of respondents selected 'ability to review materials whenever I want' was selected by the majority of respondents (72%) as the reason they found podcasts to be valuable. No clear preference was shown for audio, video, or slidecast podcasts. Physiology (88%) and pharmacology (87%) were the most requested basic science topics while regional anesthesia (84%), intensive care (79%) and crisis resource management (86%) were the most requested for procedural, clinical and professional topics respectively. Respondents stated they would most likely view podcasts that contained procedural skills, journal article summaries and case presentations and that were between 5-15 minutes in duration A significantly greater proportion of senior residents (81%) requested podcasts on 'pediatric anesthesia' compared to junior residents 57% (P = 0.007). CONCLUSIONS: The majority of respondents are using podcasts. Anesthesia residents have preferred podcast content, types, length and format that educators should be cognizant of when developing and providing podcasts.
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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 | 0.002 | 0.074 |
| 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 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".