Evidence map›Paper›PMID 40480646›Full record

Trial reportBMJ global health2025

Effectiveness of a mobile health application on treatment outcomes among patients with tuberculosis in Shanghai, China: a multicentre randomised controlled trial.

Nan Qin, Jing Chen, Lili Chen, Weihong Hu, Yan Feng, Chunhua Xu, Huaiqing Zhang, Yun Hou, Lihong Tang, Xin Shen and 1 more

Abstract readMulticenter StudyRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BMJ global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
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

11 authors.

Nan QinShanghai Municipal Center for Disease Control and Prevention, Shanghai, China.ORCID http://orcid.org/0009-0001-2399-3514
Jing ChenShanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Lili ChenShanghai Pudong New Area Center for Disease Control and Prevention, Shanghai, China.
Weihong HuShanghai Baoshan District Center for Disease Control and Prevention, Shanghai, China.
Yan FengShanghai Jiading District Center for Disease Control and Prevention, Shanghai, China.
Chunhua XuShanghai Fengxian District Center for Disease Control and Prevention, Shanghai, China.
Huaiqing ZhangShanghai Jing'an District Center for Disease Control and Prevention, Shanghai, China.
Yun HouShanghai Yangpu District Center for Disease Control and Prevention, Shanghai, China.
Lihong TangShanghai Minhang District Center for Disease Control and Prevention, Shanghai, China.
Xin ShenShanghai Municipal Center for Disease Control and Prevention, Shanghai, China wuzheyuan@scdc.sh.cn shenxin@scdc.sh.cn.
Zheyuan WuShanghai Municipal Center for Disease Control and Prevention, Shanghai, China wuzheyuan@scdc.sh.cn shenxin@scdc.sh.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTreatment compliance is considered significant for curing tuberculosis (TB). Digital adherence technologies (DATs) have been recommended for improving treatment compliance and outcomes of patients with TB. Whereas the effectiveness of DATs on TB treatment remains indefinite, we estimated whether a mobile application has an effect on treatment adherence and outcomes among patients with TB in an urban area in China.

methodsWe conducted a multicentre, two-arm, open-label, equivalent, stratified block randomisation trial from 7 districts involving 4670 eligible new patients with TB in Shanghai, China. Patients in the intervention group were instructed to get access to the app through WeChat. In the control group, patients were treated with standard of care. The primary outcome of this study was a composite outcome, which included death, treatment failure, loss to follow-up and relapse. The secondary outcomes were mainly described as overall poor treatment adherence and monthly poor treatment adherence. A generalised estimating equation is used to estimate the correlation between the two groups' outcomes after adjusting for concomitant variables.

resultsBetween 1 March 2021 and 31 December 2022, 741 patients (371 in the intervention group and 370 in the control group) were included in the intention-to-treat population, 430 (58%) were male and the median age was 33 years (IQR 27-49). 80 (22%) patients in the intervention group and 104 (28%) patients in the control group had a primary composite outcome event. The adjusted risk difference for the intervention versus control was -7.04 percentage points (95% CI -13.25 to -1.14, p=0.025); secondary outcome included overall poor treatment adherence with an adjusted risk difference -16.39 percentage points (95% CI -22.13 to -9.62, p<0.001).

conclusionsThe mobile health application improved TB treatment adherence and outcomes significantly, especially for loss to follow-up. Future research should be focused on implementation problems in various settings and the improvement of patient-centred management strategies. TRIAL REGISTRATION NUMBER: ChiCTR2000037575.

Indexed as

Antitubercular AgentsMobile ApplicationsTuberculosisAdultChinaFemaleHumansMaleMiddle AgedTelemedicineTreatment OutcomeAntitubercular AgentsRandomised control trialTuberculosis

Identifiers

PMID40480646
PMCPMC12161389

What OpenQuestion holds

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Registered trials

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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.