What matters most? A qualitative study exploring priorities for supportive interventions for people with tuberculosis in urban Viet Nam
Bibliographic record
Abstract
INTRODUCTION: The health and economic burden of tuberculosis (TB) in urban Viet Nam is high. Social protection and support interventions can improve treatment outcomes and reduce costs. However, evidence regarding optimal strategies in this context is lacking. This study aimed to increase understanding of what people with TB and healthcare providers (HCPs) perceive as important to improve TB treatment outcomes and reduce costs. METHODS: We conducted qualitative focus group discussions (seven groups, n=30) and key informant interviews (n=4) with people with drug-susceptible and multidrug-resistant TB and HCPs in Ha Noi and Ho Chi Minh City. Topic guides covered perspectives on and prioritisation of different forms of social protection and support. Data were analysed using reflexive thematic analysis and interpreted using a Framework for Transformative Social Protection. RESULTS: We identified three themes and seven subthemes. The first theme, 'Existing financial safety nets are essential, but could go further to support people affected by TB', highlights that support to meet the medical costs of TB treatment and flexible cash transfers are a priority for people with TB and HCPs. The second, 'It is important to promote "physical and spiritual health" during TB treatment', demonstrates that extended psychosocial and nutritional support would encourage people with TB during their treatment. The third, 'Accessibility and acceptability are critical in designing social support interventions for people with TB', shows the importance of ensuring that support is accessible and proportional to the needs of people with TB and their families. CONCLUSIONS: Accessible interventions that incorporate financial risk protection, nutritional and psychosocial support matter most to people with TB and HCPs in urban Viet Nam to improve their treatment outcomes and reduce catastrophic costs. This study can inform the design of stronger person-centred interventions to advance progress towards the goals of the WHO's End TB Strategy.
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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 | 0.018 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".