Analysing interventions designed to reduce tuberculosis-related stigma: A scoping review
Bibliographic record
Abstract
Stigma is a critical barrier for TB care delivery; yet data on stigma reduction interventions is limited. This review maps the available literature on TB stigma reduction interventions, using the Health Stigma and Discrimination framework and an implementation analysis to identify research gaps and inform intervention design. Using search terms for TB and stigma, we systematically searched PubMed, EMBASE and Web of Science. Two independent reviewers screened all abstracts, full-texts, extracted data, conducted a quality assessment, and assessed implementation. Results were categorized by socio-ecological level, then sub-categorized by the stigma driver or manifestation targeted. After screening 1865 articles, we extracted data from nine. Three studies were implemented at the individual and interpersonal level using a combination of TB clubs and interpersonal support to target internal and anticipated stigma among persons with TB. Two studies were implemented at the interpersonal level using counselling or a video based informational tool delivered to households to reduce stigma drivers and manifestations. Three studies were implemented at the organizational level, targeting drivers of stigma among healthcare workers (HW) and enacted stigma among HWs. One study was implemented at the community level using an educational campaign for community members. Stakeholder consultation emphasized the importance of policy level interventions and education on the universality of risk to destigmatize TB. Review findings suggest that internal and anticipated TB stigma may be addressed effectively with interventions targeted towards individuals using counselling or support groups. In contrast, enacted TB stigma may be better addressed with information-based interventions implemented at the organizational or community level. Policy level interventions were absent but identified as critical by stakeholders. Implementation barriers included the lack of high-quality training and integration with mental health services. Three key gaps must be addressed in future research: consistent stigma definitions, standardized stigma measurement, and measurement of implementation outcomes.
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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 | 0.040 | 0.162 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.024 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".