Perceptions of ophthalmologists on the impact of trachoma in Egypt: a mixed-methods, nationwide survey
Bibliographic record
Abstract
PURPOSE: Understanding the perception and practices of ophthalmologists for trachoma is important to develop interventions aimed at disease elimination in Egypt. The survey investigated: (1) the views and practice patterns of Egyptian ophthalmologists for trachoma and (2) the influence of geographic location, setting, and years of practice on ophthalmologists' perceptions. METHODS: A questionnaire sent to ophthalmologists currently working in Egypt collected information on: (1) demographics, (2) caseload and practice patterns for trachoma, (3) 13 Likert scale questions regarding the current state of trachoma, and (4) two open-ended written response questions. RESULTS: Of the 500 recipients, 194 ophthalmologists participated. 98% of the respondents reported seeing trachoma patients in their practice. 28.8% agreed that trachoma is currently an active health problem in Egypt, with ophthalmologists in public practice having significantly higher agreement scores compared to private practitioners (p = 0.030). Rural ophthalmologists were significantly more likely to agree that a targeted trachoma control program is needed in their location of practice compared to their urban counterparts (p < 0.001). Open-ended questions revealed recurrent themes, including the rural distribution of trachoma patients and the high volume of patients with corneal opacity. CONCLUSION: Ophthalmologists' experiences with trachoma in Egypt differed based on practice setting, years in practice, and location, and the overall perception of the impact of the disease remains low. However, there was widespread agreement that trachoma is present in communities across the country. Practitioners in rural areas and in the public sector shared a disproportionate burden of the trachoma caseload. The perspectives of such ophthalmologists must be emphasized in decision-making related to trachoma interventions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".