Barriers to the delivery of diabetes care in the Middle East and South Africa: a survey of 1,082 practising physicians in five countries
Bibliographic record
Abstract
AIMS: Developing countries face a high and growing burden of type 2 diabetes. We surveyed physicians in a diverse range of countries in the Middle East and Africa (Egypt, Kingdom of Saudi Arabia, United Arab Emirates, South Africa and Lebanon) with regard to their perceptions of barriers to type 2 diabetes care identified as potentially important in the literature and by the authors. METHODS: One thousand and eighty-two physicians completed a questionnaire developed by the authors. RESULTS: Most physicians enrolled in the study employed guideline-driven care; 80-100% of physicians prescribed metformin (with lifestyle intervention, where there are no contraindications) for newly diagnosed type 2 diabetes, with lifestyle intervention alone used where metformin was not prescribed. Sulfonylureas were prescribed widely, consistent with the poor economic status of many patients. About one quarter of physicians were not undertaking any form of continuing medical education, and relatively low proportions of practices had their own diabetes educators, dieticians or diabetic foot specialists. Physicians identified the deficiencies of their patients (unhealthy lifestyles, lack of education and poor diet) as the most important barriers to optimal diabetes care. Low-treatment compliance was not ranked highly. Access to physicians did not appear to be a problem, as most patients were seen multiple times per year. CONCLUSIONS: Physicians in the Middle East and South Africa identified limitations relating to their patients as the main barrier to delivering care for diabetes, without giving high priority to issues relating to processes of care delivery. Further study would be needed to ascertain whether these findings reflect an unduly physician-centred view of their practice. More effective provision of services relating to the prevention of complications and improved lifestyles may be needed.
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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 | 0.004 |
| 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 | 0.001 |
| 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".