Predictors of Ophthalmology Resident Research Engagement
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
Purpose United States Ophthalmology Residency programs employ many strategies to foster resident academic productivity. The present study assesses the efficacy of these initiatives in promoting research engagement. Methods A 19-question electronic survey was administered to current PGY2 - PGY4 U.S. ophthalmology residents. Primary outcome measures included peer-reviewed publications and national conference presentations while in residency. Results Eighty-one ophthalmology residents completed the survey, including trainees across all ages, genders, and regions. Of respondents, 34.5% reported allocated research time, 96.3% a required research project, 32.1% a research mentor, and 27.1% a formal research curriculum. Only 7% of respondents had not yet published in residency, while the majority authored one (42%) or 2-3 (30%) peer reviewed publications. Predictors for PRPs included PGY year (p = 0.003), pre-residency PRPs (p = 0.018), required research presentation or project (p = 0.05) and post-residency plans to pursue an academic career track (p = 0.036). When excluding case reports, none of the variables were associated with increased academic productivity. A majority (79%) of respondents presented at a national conference during residency. Only pre-residency PRPs predicted national conference participation (p = 0.005). Program allotment of dedicated research time, research mentorship and lecture curriculum did not correlate with an increase in productivity. Conclusions The study herein suggests that PGY year, pre-residency PRPs, research project requirements and academic career aspirations predict increased research productivity; however, dedicated research time, assigned research mentors, and research curriculums do not. These findings may be considered by ophthalmology residency programs when developing curricula to promote academic productivity.
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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 | 0.019 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| 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 it