ArticlePloS one2018
"I am not telling. The mobile is telling": Factors influencing the outcomes of a community health worker mHealth intervention in India.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 2 syntheses or guidelines pooled it, 66 citations in OpenAlex.
- Effectiveness of mobile technology and utilization of maternal and neonatal healthcare in low and middle-income countries (LMICs): a systematic review.BMC women's health · 2023Pooled it
- Health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services: a qualitative evidence synthesis.The Cochrane database of systematic reviews · 2020Pooled it
- Mobile for Mothers mHealth Intervention to Augment Maternal Health Awareness and Behavior of Pregnant Women in Tribal Societies: Randomized Quasi-Controlled Study.JMIR mHealth and uHealth · 2022Trial
- Evaluation of community health worker's performance at home-based newborn assessment supported by mHealth in rural Bangladesh.BMC pediatrics · 2022Trial
- Logic Models on Health Information Technology-Related Interventions: Scoping Review Across Disciplines.JMIR medical informatics · 2026Article
- MANTRA game analytics: effectiveness of educational mobile game on knowledge gain and retention of Female Community Health Volunteers (FCHVs) and women in rural Nepal assessed through game analytics.BMC public health · 2026Article
- Differential acceptance of a national digital health platform among community and frontline health workers in Cote d'Ivoire: a cross-sectional study.Frontiers in digital health · 2026Article
- Barriers and facilitators for the use of telehealth by healthcare providers in India-A systematic review.PLOS digital health · 2024Article
- Article
- Designing and Developing a Mobile App for Management and Treatment of Gestational Diabetes in Nepal: User-Centered Design Study.JMIR formative research · 2024Article
- A systematic review and qualitative evidence synthesis of factors affecting mHealth adoption in India.Oxford open digital health · 2024Article
- Facilitators and Barriers in the Implementation of a Digital Surveillance and Outbreak Response System in Ghana Before and During the COVID-19 Pandemic: Qualitative Analysis of Stakeholder Interviews.JMIR formative research · 2023Article
- The Vinyasa Tool for mHealth Solutions: Supporting Human-Centered Design in Nascent Digital Health Ecosystems.JMIR formative research · 2023Article
- Barriers, facilitators and motivators of electronic community health information system use among health workers in Ethiopia.Frontiers in digital health · 2023Article
- Technology-assisted task-sharing to bridge the treatment gap for childhood developmental disorders in rural Pakistan: an implementation science case study.Implementation science communications · 2022Article
- Safe Delivery application with facilitation increases knowledge and confidence of obstetric and neonatal care among frontline health workers in India.Journal of family medicine and primary care · 2022Article
- The building blocks of community health systems: a systems framework for the design, implementation and evaluation of iCCM programs and community-based interventions.BMJ global health · 2022Review
- Sub-optimal knowledge with positive attitude and belief of frontline health workers toward the use of information technologies: A mixed-method study from rural Haryana, India.Journal of education and health promotion · 2022Article
- An mHealth tool for community health workers to improve caregiver knowledge of child health in the Amazon: An effectiveness-implementation hybrid evaluation.PLOS global public health · 2022Article
- Problematic problem diagnostics: why digital health interventions for community health workers do not always achieve their desired impact.BMJ global health · 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
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionImproving maternal health outcomes remains a priority in Low and Middle Income Countries. With the rapid proliferation of mobile health technologies, there is an increased interest in understanding how these technologies can effectively improve maternal health outcomes particularly maternal health seeking knowledge and behaviors. However, few studies present clear explanations of the program developers' rationale (theory of change) and contextual factors that could influence program outcomes. This mixed-methods study assesses Mobile for Mothers, a community health workers (CHW) utilized maternal mHealth intervention. We present the program developers' rationale and utilize it as a framework to guide our study that aimed to identify intervention-related and contextual factors, which influence the observed outcomes of a CHW, utilized mHealth intervention. MATERIALS AND
methodsQuantitative methods (a questionnaire with 740 women who received the intervention and survey of 57 CHWs who utilized the intervention) and qualitative methods (12 interviews and 4 group discussions with CHWs and 20 interviews and 5 group discussions with pregnant and lactating women and 15 interviews and 2 group discussions with men) were conducted. These were used to understand how the mHealth intervention was implemented and to gain insight into contextual factors that potentially influenced the observed intervention outcomes.
resultsResults were grouped following three categories: (1) perceptions and experiences of CHWs utilizing the mHealth technology; (2) CHW-related outcomes; and (3) contextual factors that influence maternal health-seeking behavior. The overall response of CHWs and community members to the intervention was positive. However, contextual factors like the relationship between the CHWs and their respective communities, the pregnant women's decision-making power and lack of access due to financial influenced the observed outcomes.
conclusionMobile health applications are promising interventions for improving the performance of CHWs and health-seeking behavior of pregnant women. However, the contextual factors play a crucial role in intervention outcomes and need to be explicated by program developers during intervention design and implementation.
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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 OpenQuestion graph.