Improving diabetic retinopathy screening in Africa: Patient satisfaction with teleophthalmology versus ophthalmologist-based screening
Bibliographic record
Abstract
PURPOSE: To assess patient preference for diabetic retinopathy (DR) screening with teleophthalmology or face-to-face ophthalmologist evaluation in Nairobi, Kenya. MATERIALS AND METHODS: Fifty seven diabetic patients from a one-stop multidisciplinary diabetic clinic (consisting of a diabetologist, nurse educator, foot specialist, nutritionist, ophthalmologist, and neurologist) in Nairobi, Kenya were included if they had undergone both a teleophthalmology (stereoscopic digital retinal photographs graded by an ophthalmologist remotely) and a traditional clinical screening exam (face to face examination). A structured questionnaire with a 5-point Likert scale was developed in both English and Swahili. The questionnaire was administered over the telephone. Ten questions were used to compare patient experience and preferences between teleophthalmology and a traditional clinical examination for DR. A mean score >3.25 on the Likert scale was considered favourable. RESULTS: Successfully telephone contact was possible for 26 (58% male, 42% females) of the 57 patients. The mean ages of the male and female patients were 52.4 and 46.5 years respectively. Patients were satisfied with their teleophthalmology examination (mean 4.15 ± 0.97). Patients preferred the teleophthalmology option for future screenings (mean 3.42 ± 1.52). This preference was driven primarily by convenience, reduced examination time, and being able to visualize their own retina. CONCLUSION: In this study, diabetic patients preferred a teleophthalmology based screening over a traditional ophthalmologist-based screening. The use of teleophthalmology in Africa warrants further study and has the potential to become the screening model of choice. Cost effectiveness in comparison to an ophthalmologist-based screening also requires evaluation.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".