ReviewJMIR mHealth and uHealth2016
Smartphone Applications to Support Tuberculosis Prevention and Treatment: Review and Evaluation.
Review in JMIR mHealth and uHealth, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05865626 (A Pilot Study to Evaluate Video Observed Treatment Among Tuberculosis Patients From Lambaréné Using an Instant Messenger Application), which is not on this map. Cited by 38 papers, 4 of them syntheses 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.
A Pilot Study to Evaluate Video Observed Treatment Among Tuberculosis Patients From Lambaréné Using an Instant Messenger Application
Who cites it
38 citing papers in PubMed, 4 syntheses or guidelines pooled it, 75 citations in OpenAlex.
- eHealth in TB clinical management.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022Pooled it
- Does phone messaging improves tuberculosis treatment success? A systematic review and meta-analysis.BMC infectious diseases · 2020Pooled it
- A Systematic Review of eHealth Interventions Addressing HIV/STI Prevention Among Men Who Have Sex With Men.AIDS and behavior · 2019Pooled it
- Criteria for assessing the quality of mHealth apps: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2018Pooled it
- Trial
- Impact of smartphone application usage by mothers in improving oral health and its determinants in early childhood: a randomised controlled trial in a paediatric dental setting.European archives of paediatric dentistry : official journal of the European Academy of Paediatric Dentistry · 2022Trial
- Insights from participant engagement with the tuberculosis treatment support tools intervention: Thematic analysis of interactive messages to guide refinement to better meet end user needs.International journal of medical informatics · 2021Trial
- User engagement in the tuberculosis treatment support tools intervention and its impact on treatment outcomes: A secondary analysis of a pragmatic trial.PLOS digital health · 2026Article
- Adaptation of a Smartphone-Based Mobile Health Program to Support Person-Centered Treatment of Tuberculosis in Kilimanjaro, Tanzania: Preimplementation Qualitative Needs Assessment.JMIR formative research · 2026Article
- An overview of mobile health applications (mHealth apps) supporting Tuberculosis elimination efforts.Frontiers in digital health · 2026Review
- User-Centered Refinement of a Digital Tool for Tuberculosis Treatment Support: Iterative Mixed Methods Study.Journal of medical Internet research · 2025Article
- Automated framework for comprehensive usability analysis of healthcare websites using web parsing.Scientific reports · 2025Article
- Impact of a pilot mHealth intervention on treatment outcomes of TB patients seeking care in the private sector using Propensity Scores Matching-Evidence collated from New Delhi, India.PLOS digital health · 2024Article
- Usability testing of a mobile health application to support individuals with active tuberculosis: a mixed methods study.Informatics for health & social care · 2024Article
- Design, development and evaluation of a mobile-based self-care application for patients with COVID-19 not requiring hospitalization; a study of Northwest of Iran.BMC medical informatics and decision making · 2023Article
- Effect of mobile health reminders on tuberculosis treatment outcomes in Shanghai, China: A prospective cohort study.Frontiers in public health · 2023Article
- Development of the SIKRIBO Mobile Health Application for Active Tuberculosis Case Detection in Semarang, Indonesia.Healthcare informatics research · 2022Article
- Patient-centered mobile tuberculosis treatment support tools (TB-TSTs) to improve treatment adherence: A pilot randomized controlled trial exploring feasibility, acceptability and refinement needs.Lancet regional health. Americas · 2022Article
- Digital Contact Tracing and COVID-19: Design, Deployment, and Current Use in Italy.Healthcare (Basel, Switzerland) · 2021Article
- Diagnosis of COVID-19, vitality of emerging technologies and preventive measures.Chemical engineering journal (Lausanne, Switzerland : 1996) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundTuberculosis (TB) remains a major global health problem and is the leading killer due to a single infectious disease. Mobile health (mHealth)-based tools such as smartphone apps have been suggested as tools to support TB control efforts (eg, identification, contact tracing, case management including patient support).
objectiveThe purpose of this review was to identify and assess the functionalities of mobile apps focused on prevention and treatment of TB.
methodsWe searched 3 online mobile app stores. Apps were included if they were focused on TB and were in English, Spanish, or Portuguese. For each included app, 11 functionalities were assessed (eg, inform, instruct, record), and searches were conducted to identify peer-review publications of rigorous testing of the available apps.
resultsA total of 1332 potentially relevant apps were identified, with 24 meeting our inclusion criteria. All of the apps were free to download, but 7 required login and password and were developed for specific clinics, regional sites, or research studies. Targeted users were mainly clinicians (n=17); few (n=4) apps were patient focused. Most apps (n=17) had 4 or fewer functions out of 11 (range 1-6). The most common functionalities were inform and record (n=15). Although a number of apps were identified with various functionalities to support TB efforts, some had issues such as incorrect spelling and grammar, inconsistent responses to data entry, problems with crashing, or links to features that had no data. Of more concern, some apps provided potentially harmful information to patients, such as links to natural remedies for TB and natural healers. One-third of the apps (8/24) had not been updated for more than a year and may no longer be supported. Peer-reviewed publications were identified for only two of the included apps. In the gray literature (not found in the app stores), three TB-related apps were identified as in progress, being launched, or tested.
conclusionsApps identified for TB prevention and treatment had minimal functionality, primarily targeted frontline health care workers, and focused on TB information (eg, general information, guidelines, and news) or data collection (eg, replace paper-based notification or tracking). Few apps were developed for use by patients and none were developed to support TB patient involvement and management in their care (eg, follow-up alerts/reminders, side effects monitoring) or improve interaction with their health care providers, limiting the potential of these apps to facilitate patient-centered care. Our evaluation shows that more refined work is needed to be done in the area of apps to support patients with active TB. Involving TB patients in treatment in the design of these apps is recommended.
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.