ArticleJMIR mHealth and uHealth2017
Processes and Recommendations for Creating mHealth Apps for Low-Income Populations.
Article in JMIR mHealth and uHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 59 citations in OpenAlex.
- Mobile-Based Application Interventions to Enhance Cancer Control and Care in Low- and Middle-Income Countries: A Systematic Review.International journal of public health · 2023Pooled it
- Shared Decision Making Tools for People Facing Stroke Prevention Strategies in Atrial Fibrillation: A Systematic Review and Environmental Scan.Medical decision making : an international journal of the Society for Medical Decision Making · 2021Pooled it
- Efficacy, Safety, and Cost-Effectiveness of "Internet + Pharmacy Care" Via the Alfalfa App in Warfarin Therapy Management After Cardiac Valve Replacement: Randomized Controlled Trial.JMIR mHealth and uHealth · 2025Trial
- Applying user-centered design to enhance the usability and acceptability of an mHealth supervision tool for community health workers delivering an evidence-based intervention in rural Sierra Leone.Global mental health (Cambridge, England) · 2025Article
- Streamlining atrial fibrillation ablation management using a digitization solution.European heart journal. Digital health · 2024Article
- Mobile Health Interventions for Substance Use Disorders.Annual review of clinical psychology · 2024Review
- Education of Patients With Atrial Fibrillation and Evaluation of the Efficacy of a Mobile Virtual Patient Environment: Protocol for a Multicenter Pseudorandomized Controlled Trial.JMIR research protocols · 2024Article
- Development of the Mobile Application to Prevent Suicide (MAPS), a Personalized Smartphone App for Suicide Prevention: Feedback from Individual Interviews.Journal of technology in human services · 2024Article
- Developing culturally-adapted mobile mental health interventions: a mixed methods approach.mHealth · 2023Article
- Exploring Saudi Individuals' Perspectives and Needs to Design a Hypertension Management Mobile Technology Solution: Qualitative Study.International journal of environmental research and public health · 2022Article
- Measuring Mobile Phone Application Usability for Anticoagulation from the Perspective of Patients, Caregivers, and Healthcare Professionals.International journal of environmental research and public health · 2022Article
- Evaluation of mHealth Apps for Diverse, Low-Income Patient Populations: Framework Development and Application Study.JMIR formative research · 2022Article
- Identification Level of Awareness and Knowledge of Emirati Men about HPV.Journal of healthcare engineering · 2022Article
- Adaptation of a Theory-Based Social Networking and Gamified App-Based Intervention to Improve Pre-Exposure Prophylaxis Adherence Among Young Men Who Have Sex With Men in Bangkok, Thailand: Qualitative Study.Journal of medical Internet research · 2021Article
- Effective German and English Language mHealth Apps for Self-management of Bronchial Asthma in Children and Adolescents: Comparison Study.JMIR mHealth and uHealth · 2021Article
- The use of mobile phones for the prevention and control of arboviral diseases: a scoping review.BMC public health · 2021Article
- Research on the Impact of mHealth Apps on the Primary Healthcare Professionals in Patient Care.Applied bionics and biomechanics · 2021Article
- Association Between Usage of an App to Redeem Prescribed Food Benefits and Redemption Behaviors Among the Special Supplemental Nutrition Program for Women, Infants, and Children Participants: Cross-Sectional Study.JMIR mHealth and uHealth · 2020Article
- Article
- Identifying Frameworks for Validation and Monitoring of Consensual Behavioral Intervention Technologies: Narrative Review.Journal of medical Internet research · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMobile health (mHealth) apps have shown to improve health indicators, but concerns remain about the inclusion of populations from low- and medium-income countries (LMIC) in these new technologies. Atrial fibrillation (AF) is a chronic condition with a challenging management. Previous studies have shown socioeconomic differences in the prescription of anticoagulant treatment and shared decision strategies are encouraged to achieve better outcomes. mHealth can aid both doctors and patients in this matter.
objectiveWe describe the development of an mHealth app (aFib) idealized to aid shared decision between doctor and patient about anticoagulation prophylaxis in AF in a low-income and low-literacy population in Brazil. On the basis of our research, we suggest the processes to be followed when developing mHealth apps in this context.
methodsA multidisciplinary team collected information about the target population and its needs and detected the best opportunity to insert the app in their current health care. Literature about the subject was reviewed and important data were selected to be delivered through good navigability, easy terminology, and friendly design. The app was evaluated in a multimethod setting.
resultsThe steps suggested to develop an mHealth app target to LMIC are: (1) characterize the problem and the target user, (2) review the literature, (3) translate information to knowledge, (4) protect information, and (5) evaluate usability and efficacy.
conclusionsWe expect that these recommendations can guide the development of new mHealth apps in LMIC, on a scientific basis.
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.