Global Health in General Surgery Residency: A National Survey
Bibliographic record
Abstract
BACKGROUND: Interest in global health during postgraduate training is increasing across disciplines. There are limited data from surgery residency programs on their attitudes and scope of activities in this area. This study aims to understand how global health education fits into postgraduate surgical training in the US. STUDY DESIGN: In 2007 to 2008, we conducted a nationwide survey of program directors at all 253 US general surgery residencies using a Web-based questionnaire modified from a previously published survey. The goals of global health activities, type of activity (ie, clinical versus research), and challenges to establishing these programs were analyzed. RESULTS: Seventy-three programs responded to the survey (29%). Of the respondents, 23 (33%) offered educational activities in global health and 86% (n = 18) of these offered clinical rotations abroad. The primary goals of these activities were to prepare residents for a career in global health and to improve resident recruitment. The greatest barriers to establishing these activities were time constraints for faculty and residents, lack of approval from the Accreditation Council for Graduate Medical Education and Residency Review Committee, and funding concerns. Lack of interest at the institution level was listed by only 5% of program directors. Of the 47 programs not offering such activities, 57% (n = 27) were interested in establishing them. CONCLUSIONS: Few general surgery residency programs currently offer clinical or other educational opportunities in global health. Most residencies that responded to our survey are interested in such activities but face many barriers, including time constraints, Residency Review Committee restrictions, and funding.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".