SynthesisTropical medicine & international health : TM & IH2025
Effects of Communication Strategies on Treatment Adherence and Success in Tuberculosis: A Systematic Review and Meta-Analysis.
Synthesis in Tropical medicine & international health : TM & IH, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Effects of Communication Strategies on Treatment Adherence and Success in Tuberculosis: A Systematic Review and Meta-Analysis.Tropical medicine & international health : TM & IH · 2025Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
introductionTuberculosis, although curable, presents challenges related to treatment adherence, which compromises treatment effectiveness. Individual, social and structural barriers interfere with patients' ability to properly follow the therapeutic regimen, thereby impacting treatment outcomes. Given the limitations of the conventional healthcare model, which relies primarily on in-person consultations and standard treatment protocols without additional adherence support technologies, new approaches have been explored to improve patient outcomes. This study seeks to identify effective communication approaches in this context.
objectiveTo identify the most effective communication strategies to optimise treatment adherence and improve therapeutic success in patients diagnosed with tuberculosis.
methodsA systematic review with meta-analysis was conducted. We included studies available in the MEDLINE (via PubMed), EMBASE and SCOPUS databases, with publication dates between January 2005 and December 2024. The primary outcomes were adherence to and success in tuberculosis treatment.
resultsThis systematic review included 17 studies on tuberculosis treatment adherence. Of these, 12 were included in the meta-analysis for adherence and 8 for treatment success. The most effective strategies for adherence were community education (2 studies; RR: 0.25, 95% CI: 0.11-0.56) and video observed therapy (VDOT) (2 studies; RR: 0.29, 95% CI: 0.21-0.40). The combination of electronic devices with SMS also showed positive results (3 studies; RR: 0.53, 95% CI: 0.37-0.77). SMS alone (5 studies) and electronic devices alone (3 studies) were not effective. For treatment success, only the combination of electronic devices with SMS (RR: 0.31, 95% CI: 0.17-0.55) and community education (RR: 0.51, 95% CI: 0.40-0.64) were effective.
conclusionThe combination of electronic devices with SMS and community education is an effective strategy for improving adherence and therapeutic success in tuberculosis treatment. Isolated interventions with SMS or electronic technologies did not show significant results. Adapting approaches to local realities is crucial for optimising outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.