Characteristics, Trends, and Factors Associated With Publication Among Residents of Oman Medical Specialty Board Programs
Bibliographic record
Abstract
ABSTRACT Background Research during residency is associated with better clinical performance, improved critical thinking, and increased interest in an academic career. Objective We examined the rate, characteristics, and factors associated with research publications by residents in Oman Medical Specialty Board (OMSB) programs. Methods We included residents enrolled in 18 OMSB residency programs between 2011 and 2016. Resident characteristics were obtained from the OMSB Training Affairs Department. In April 2018, MEDLINE and Google Scholar databases were searched independently by 2 authors for resident publications in peer-reviewed journals using standardized criteria. Results Over the study period, 552 residents trained in OMSB programs; 64% (351 of 552) were female, and the mean age at matriculation was 29.4 ± 2.2 years. Most residents (71%, 393 of 552) were in the early stages of specialty training (R ≤ 3) and 49% (268 of 552) completed a designated research block as part of their training. Between 2011 and 2016, 43 residents published 42 research articles (range, 1–5 resident authors per article), for an overall publication rate of 8%. Residents were the first authors in 20 (48%) publications. Male residents (odds ratio [OR] = 2.07; P = .025, 95% CI 1.1–3.91) and residents who completed a research block (OR = 2.57; P = .017, 95% CI 1.19–5.57) were significantly more likely to publish. Conclusions Research training during residency can result in tangible research output. Future studies should explore barriers to publication for resident research and identify interventions to promote formal scholarly activity during residency.
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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 | 0.004 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".