“When Treatment Is More Challenging than the Disease”: A Qualitative Study of MDR-TB Patient Retention
Bibliographic record
Abstract
BACKGROUND: One-fifth of the patients on multidrug-resistant tuberculosis treatment at the Drug-Resistant-TB (DR-TB) Site in Gujarat are lost-to-follow-up(LFU). OBJECTIVE: To understand patients' and providers' perspectives on reasons for LFU and their suggestions to improve retention-in-care. DESIGN: Qualitative study conducted between December 2013-March 2014, including in-depth interviews with LFU patients and DOT-providers, and a focus group discussion with DR-TB site supervisors. A thematic-network analysis approach was utilised. RESULTS: Three sub-themes emerged: (i) Struggle with prolonged treatment; (ii) Strive against stigma and toward support; (iii) Divergent perceptions and practices. Daily injections, pill burden, DOT, migratory work, social problems, prior TB treatment, and adverse drugs effects were reported as major barriers to treatment adherence and retention-in-care by patients and providers. Some providers felt that despite their best efforts, LFU patients remain. Patient movements between private practitioners and traditional healers further influenced LFU. CONCLUSION: The study points to a need for repeated patient counselling and education, improved co-ordination between various tiers of providers engaged in DR-TB care, collaboration between the public, private and traditional practitioners, and promotion of social and economic support to help patients adhere to MDR-TB treatment and avoid LFU.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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 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".