Adherence to tuberculosis (TB) treatment in high compared to low TB burden countries: study protocol for a systematic review and meta-analysis with a qualitative meta-synthesis of themes
Bibliographic record
Abstract
INTRODUCTION: Non-adherence to tuberculosis (TB) treatment poses a significant challenge to effective TB management globally and is a major contributor to the emergence of multidrug-resistant TB. Although adherence to TB treatment has been widely studied, a comprehensive evaluation of the comparative levels of adherence in high- versus low-TB burden settings remains lacking. The objective of this systematic review and meta-analysis is to assess the levels of adherence to TB treatment in high-TB burden countries compared to low-burden countries. Additionally, it seeks to identify the unique facilitators and barriers to treatment adherence in these distinct settings. METHODS AND ANALYSIS: This systematic review and meta-analysis will be conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols Statement. Using key medical subject heading terms and free-text terms related to TB treatment adherence, a systematic search of the literature will be performed in Medline, Embase, CINAHL, Scopus, Global Health and the Cochrane Databases of Systematic Reviews. A medical librarian will assist with developing the search strategy. Two independent reviewers will independently screen studies against predefined inclusion and exclusion criteria at both the title/abstract and full-text stages. Working in duplicate, the same two reviewers will independently extract relevant study and outcomes data, including study descriptors, TB burden, adherence levels and adherence measures, from eligible studies. Countries will be classified according to TB burden based on the WHO's high-burden country list from the post-2015 era (2015-2025). The quality of the included studies will be appraised using the Cochrane Risk of Bias tool and the Newcastle-Ottawa Scale. Qualitative data will be appraised using the Critical Appraisal Skills Programme tool. Studies will be pooled using the DerSimonian-Laird random-effects meta-analysis. Additionally, a meta-synthesis of the qualitative data from the included studies may be conducted to identify emergent themes related to facilitators and barriers of TB treatment adherence in high- vs low-TB burden countries. ETHICS AND DISSEMINATION: Ethics approval is not required for this study as it does not involve the recruitment or collection of data from participants. The findings from this systematic review and meta-analysis will be disseminated through publication in peer-reviewed journals, presentations at scientific conferences, and via social media channels to enhance visibility, particularly within programmatic and policy spheres. PROSPERO REGISTRATION NUMBER: CRD42021273336.
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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 | 0.103 | 0.134 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.023 | 0.031 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.056 | 0.005 |
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".