Evidence map›Paper›PMID 41087928›Full record

SynthesisBMC infectious diseases2025

The impact of digital adherence technologies on treatment outcomes, adherence, and patient-reported outcomes in tuberculosis: a systematic review and meta-analysis.

Mona S Mohamed, Miranda Zary, Cedric Kafie, Chimweta I Chilala, Shruti Bahukudumbi, Nicola Foster, Genevieve Gore, Katherine Fielding, Ramnath Subbaraman, Kevin Schwartzman

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Digital medicine for infectious diseases.Nature communications · 2026
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  5. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Mona S MohamedMcGill International Tuberculosis Centre, Research Institute of the McGill University Health Centre, Montréal, Canada.
Miranda ZaryMcGill International Tuberculosis Centre, Research Institute of the McGill University Health Centre, Montréal, Canada.
Cedric KafieMcGill International Tuberculosis Centre, Research Institute of the McGill University Health Centre, Montréal, Canada.
Chimweta I ChilalaTB Centre, London School of Hygiene and Tropical Medicine, London, UK.
Shruti BahukudumbiDepartment of Public Health and Community Medicine, Tufts University School of Medicine, Boston, USA.
Nicola FosterTB Centre, London School of Hygiene and Tropical Medicine, London, UK.
Genevieve GoreSchulich Library of Physical Sciences, Life Sciences, and Engineering, McGill University, Montréal, Canada.
Katherine FieldingTB Centre, London School of Hygiene and Tropical Medicine, London, UK.
Ramnath SubbaramanDepartment of Public Health and Community Medicine, Tufts University School of Medicine, Boston, USA.
Kevin SchwartzmanMcGill International Tuberculosis Centre, Research Institute of the McGill University Health Centre, Montréal, Canada. kevin.schwartzman@mcgill.ca.

Funding

Gates Foundation INV-038215
6 · The paper itself

Abstract

backgroundIncomplete tuberculosis (TB) treatment adherence may lead to unsuccessful treatment and relapse. Digital adherence technologies (DATs) may allow more person-centric approaches for supporting treatment adherence. We conducted a systematic review (PROSPERO- CRD42022313166) to evaluate the impact of DATs on adherence, treatment outcomes and patient-reported outcomes in persons treated for TB.

methodsWe searched MEDLINE, Embase, CENTRAL, CINAHL, Web of Science and preprints from Europe PMC, and clinicaltrials.gov for relevant literature from January 2000 to March 2024. We considered experimental or cohort studies reporting quantitative comparisons of adherence, treatment outcomes and patient-reported outcomes between a DAT and the standard of care in each setting. We excluded studies where the technology was used only to log visit attendance or for “routine telephone calls” to patients. Risk of bias was assessed using the Cochrane risk of bias assessment tool and the Newcastle- Ottawa Scale. Pre-specified subgroup analyses considered study design, specific DAT interventions as well as income levels in the countries where studies were conducted.

resultsSeventy-six studies (total 86,586 participants) were included evaluating SMS-based interventions (k = 18 studies), feature phone-based interventions (k = 8), medication sleeves with phone calls (branded as “99DOTS,” k = 6), video-observed therapy (VOT; k = 18), smartphone apps (k = 7), digital pillboxes (k = 21), ingestible sensors (k = 1), and interventions combining two DATs (k = 2). Overall, the use of DATs was associated with a modest increase in treatment success in TB disease in both RCTs (OR = 1.14 [0.99, 1.30]; I2 = 57%, k = 34, very low certainty evidence) and observational studies (OR = 1.11 [0.94, 1.30]; I2 = 74%, k = 22, very low certainty evidence). Additionally, DAT use was linked to a significant increase in reporting of adverse events in RCTs (OR = 1.57 [1.25, 1.97]; I2 = 12%, k = 6, moderate certainty) while observational studies showed a similar but non-significant finding (OR = 1.39 [0.93, 2.09]; I2 = 0%, k = 3, moderate certainty). VOT was associated with an increased likelihood of treatment completion in TB infection (OR 4.69 [2.08; 10.55]; I2 = 0%, k = 2, low certainty evidence). VOT also increased frequency of adverse event reporting, as demonstrated in RCTs (OR = 1.9 [1.27; 2.84]; I2 = 0%, k = 3, moderate certainty evidence) and a similar but non-significant effect in observational studies (OR = 1.48 [0.91; 2.42]; I2 = 0%, k = 2, low certainty evidence). Other interventions involving smartphone apps were associated with increased treatment success in TB disease, with a significant effect observed in RCTs (OR 2.17 [1.07; 4.4]; I2 = 20%, k = 3, low certainty evidence) and a non-significant effect in observational studies (OR 1.51 [0.53; 4.3]; I2 = 60%, k = 3, very low certainty evidence). In contrast, interventions with 99DOTS were not associated with improvements in short-term clinical outcomes. There was substantial methodological heterogeneity among studies reporting on adherence. Few studies assessed patient-reported outcomes, though satisfaction was generally higher with DATs.

conclusionSome DATs, notably VOT and smartphone apps, have been successfully used to support TB treatment. Although in many cases DATs did not improve clinical outcomes, they may improve efficiency and adherence, and may be preferred to traditional directly observed therapy by persons with TB. However, evidence remains highly variable, and generalizability limited. Higher quality data are needed.

trial registrationPROSPERO- CRD42022313166

Indexed as

Medication AdherencePatient Reported Outcome MeasuresTuberculosisAdherence InterventionsAntitubercular AgentsDigital HealthDigital MediaHumansTreatment OutcomeAntitubercular Agents99DOTSAdherenceDigital pillboxDigital technologySmartphone- applicationSMSTuberculosisVideo-observed treatment

Identifiers

PMID41087928
PMCPMC12523041

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.