Feasibility and Acceptability of a US National Telemedicine Curriculum for Medical Students and Residents: Multi-institutional Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: Telemedicine use increased as a response to health care delivery changes necessitated by the COVID-19 pandemic. However, lack of standardized curricular content creates gaps and inconsistencies in effectively integrating telemedicine training at both the undergraduate medical education and graduate medical education levels. OBJECTIVE: This study evaluated the feasibility and acceptability of a web-based national telemedicine curriculum developed by the Society of Teachers of Family Medicine for medical students and family medicine (FM) residents. Based on the Association of American Medical Colleges telehealth competencies, the asynchronous curriculum featured 5 self-paced modules; covered topics include evidence-based telehealth uses, best practices in communication and remote physical examinations, technology requirements and documentation, access and equity in telehealth delivery, and the promise and potential perils of emerging technologies. METHODS: A total of 17 medical schools and 17 FM residency programs implemented the curriculum between September 1 and December 31, 2021. Participating sites represented 25 states in all 4 US census regions with balanced urban, suburban, and rural settings. A total of 1203 learners, including 844 (70%) medical students and 359 (30%) FM residents, participated. Outcomes were measured through self-reported 5-point Likert scale responses. RESULTS: A total of 92% (1101/1203) of learners completed the entire curriculum. Across the modules, 78% (SD 3%) of participants agreed or strongly agreed that they gained new knowledge, skills, or attitudes that will help them in their training or career; 87% (SD 4%) reported that the information presented was at the right level for them; 80% (SD 2%) reported that the structure of the modules was effective; and 78% (SD 3%) agreed or strongly agreed that they were satisfied. Overall experience using the national telemedicine curriculum did not differ significantly between medical students and FM residents on binary analysis. No consistent statistically significant relationships were found between participants' responses and their institution's geographic region, setting, or previous experience with a telemedicine curriculum. CONCLUSIONS: Both undergraduate medical education and graduate medical education learners, represented by diverse geographic regions and institutions, indicated that the curriculum was broadly acceptable and effective.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".