Perceptions and Challenges Experienced by African Physicians When Prescribing Methotrexate for Rheumatic Disease: An Exploratory Study
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Bibliographic record
Abstract
OBJECTIVE: Guidelines for methotrexate (MTX) use in rheumatic disease may not be feasible for physicians practicing in the least developed countries. We aimed to understand the experiences of MTX prescribers relating to MTX use for rheumatic disease in African countries to inform the development of culturally and geographically appropriate recommendations. METHODS: African physicians who self-identified as MTX prescribers from countries classified as having a low versus a medium or high Human Development Index (L-HDI versus MH-HDI) participated in semistructured interviews between August 2016 and September 2017. Interviews were transcribed verbatim, coded thematically, and stratified by HDI. RESULTS: Physicians (23 rheumatologists; six internists) from 29 African countries were interviewed (15 L-HDI; 14 MH-HDI). Identified barriers to MTX use included inconsistent MTX supply (reported by 87% L-HDI versus 43% MH-HDI), compounded by financial restrictions (reported by 93% L-HDI versus 64% MH-HDI), patient hesitancy based partly on cultural beliefs and societal roles (reported by 71%), few prescribers (reported by 33%), prevalent infections (especially viral hepatitis, tuberculosis, and human immunodeficiency virus), and both availability and cost of monitoring tests. MTX pretreatment evaluation and starting and maximal doses were similar between L-HDI countries and MH-HDI countries. CONCLUSION: The challenges of treating rheumatic disease in African countries include unreliable drug availability and cost, limited subspecialists, and patient beliefs. Adapting recommendations for MTX use in the context of prevalent endemic infections; ensuring safe but feasible MTX monitoring strategies, enhanced access to stable drug supply, and specialized rheumatology care; and improving patient education are key to reducing the burden of rheumatic diseases in L-HDI countries.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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