The role of counselling in tuberculosis diagnostic evaluation and contact tracing: scoping review and stakeholder consultation of knowledge and research gaps
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) care cascade analyses show large gaps at early stages, including care-seeking and diagnostic evaluation, where promising interventions to decrease attrition are urgently needed. Person-centered care is prioritized in the World Health Organization's End TB strategy; yet little is known about how it is delivered and can be optimized. Recommendations for counselling, a core component of person-centered care, are largely limited to its role in improving TB treatment adherence. The role of counselling to close key diagnostic gaps in the care cascade is poorly understood. METHODS: We conducted a scoping review to identify evidence on the use of counselling at TB diagnosis, for both people with presumptive TB and index patients to promote patient retention and contact tracing. Using search terms for TB, diagnosis and counselling, we systematically searched PubMed, EMBASE and Web of Science. Two independent reviewers screened all abstracts, full-texts, extracted data and conducted a quality assessment. We used thematic analysis to identify key themes. RESULTS: After screening 1785 articles, we extracted data from 15 studies and determined that the major themes best corresponded to the following gaps in the TB care cascade: care-seeking, pre-diagnosis, and pre-treatment. Studies were conducted across varied settings including pharmacies, primary health centres, and clinics, primarily in high TB incidence countries. No study directly evaluated the impact of counselling on outcomes such as treatment initiation or retention in care. Included studies suggested counselling may play an important role in improving the uptake of diagnostic testing and contact tracing. Barriers to counselling included time and personnel requirements. Stakeholder consultation emphasized the importance of high-quality counselling as a core tenet of TB care. CONCLUSION: Data on the impact of counselling to improve TB case detection are absent from the literature. The shift towards person-centred care for TB presents an opportunity to incorporate counselling during earlier stages of the TB care cascade; however, evidence-based approaches are needed. Implementation research is needed to operationalize and evaluate counselling to strengthen high-quality TB care delivery.
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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 | 0.185 | 0.377 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.043 | 0.033 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".