SynthesisFrontiers in medicine2026
The role of digital health interventions for adults with tuberculosis: a network meta-analysis of randomized controlled trials.
Synthesis in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Incomplete adherence to tuberculosis treatment increases the risk of delayed sputum culture conversion in the community, as well as elevated risks of treatment failure, recurrence, and the development or amplification of drug resistance. Through network meta-analysis, we aimed to comprehensively analyze the effects of digital health interventions for patients with tuberculosis. Methods: PubMed, Cochrane Library, Embase and Web of Science for randomized controlled trails that examined the efficacy of digital health intervention for tuberculosis treatment up to 18 May 2026. The main outcome included treatment success and adherence. Stata (version 17) and R software (version 4.3.1) were used for the data analysis. Results: From 17,643 publications, we included 29 randomized controlled trials involving 17,800 participants for quantitative analysis. Overall, digital health interventions showed a statistically higher treatment success rate than directly observed therapy (RR 1.03; 95% CI 1.00-1.07). Then a network meta-analysis of each intervention was conducted. Regarding treatment success, apart from video observed therapy showing significantly better outcomes compared to directly observed therapy (RR 1.18; 95% CI 1.02-1.37) and double-way short message service (RR 0.80; 95% CI 0.67-0.95), there was no statistically significant difference observed between medication event reminder monitor systems, monitors, single-way short message services, double-way short message service, video observed therapy, phone calls, and directly observed therapy. In terms of adherence, video observed therapy also demonstrated significantly higher adherence rates compared to other interventions. Additionally, video observed therapy was ranked as the top digital health intervention for achieving both treatment success and adherence. Conclusion: Video observed therapy has excellent effects on treatment success and adherence than other digital health interventions. Given its excellent efficacy, video observed therapy should be given more prominence in clinical care, especially for individuals with low adherence, where resources allow.
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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 Socratic graph.