Research productivity of ophthalmology residents in Saudi Arabia: A comprehensive analysis
Bibliographic record
Abstract
PURPOSE: The purpose of the study was to assess the research productivity of ophthalmology residents in Saudi Arabia and identify factors associated with significant research output. METHODS: This is a cross-sectional study of ophthalmology training programs across Saudi Arabia from 2015 to 2019. RESULTS: The study included 225 ophthalmology residents, with a mean number of publications of 3.25 ± 4.59 and an average h-index of 1.20 ± 1.38. Statistically significant differences were observed between training programs in the mean number of publications ( P < 0.001), h-index ( P < 0.001), and citations ( P < 0.001). The programs with the highest mean publication counts were King Saud University (8.03 ± 8.00), King Khaled Eye Specialist Hospital (3.80 ± 3.87), and the Eastern program (3.07 ± 4.04). Residents pursuing subspecialty fellowships, particularly in oculoplastic surgery and cornea, exhibited higher research output. Furthermore, the mean number of publications ( P < 0.001), citations ( P < 0.001), and h-index ( P < 0.001) were associated with attaining future academic positions. Pursuing fellowship was significantly linked to the number of publications ( P = 0.009) and h-index ( P = 0.012). CONCLUSION: This study underscores the variability in research productivity among ophthalmology residents and highlights the influence of training programs, fellowship ambitions, and academic aspirations on research output.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".