ReviewIndian journal of endocrinology and metabolism
Mobile Health Technology in the Prevention and Management of Type 2 Diabetes.
Review in Indian journal of endocrinology and metabolism. 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, 72 citations in OpenAlex.
- The Use of Mobile Health Interventions for Outcomes among Middle-Aged and Elderly Patients with Prediabetes: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- Methods and Evaluation Criteria for Apps and Digital Interventions for Diabetes Self-Management: Systematic Review.Journal of medical Internet research · 2020Pooled it
- Effects of mobile phone application combined with or without self-monitoring of blood glucose on glycemic control in patients with diabetes: A randomized controlled trial.Journal of diabetes investigation · 2019Trial
- Article
- Co-Designing a Digital Stroke Prevention Platform: Leveraging Lived Experience and Expert Advice.Health expectations : an international journal of public participation in health care and health policy · 2025Article
- Effectiveness of mDiabetes intervention in enhancing diabetes awareness and promoting healthy lifestyle changes among the general population in rural India.Frontiers in public health · 2024Article
- Healthcare Professionals' Attitude to Using Mobile Health Technology and Its Associated Factors in a Resource-Limited Country-An Implication for Digital Health Implementers: A Cross Sectional Study.BioMed research international · 2024Article
- Design, development, and usability evaluation of a smartphone-based application for nutrition management in patients with type II diabetes.Journal of diabetes and metabolic disorders · 2023Article
- Willingness to Receive mHealth Services Among Patients with Diabetes on Chronic Follow-up in Public Hospitals in Eastern Ethiopia: Multicenter Mixed-Method Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Article
- Article
- Efficacy of Digitally Supported and Real-Time Self-Monitoring of Blood Glucose-Driven Counseling in Patients with Type 2 Diabetes Mellitus: A Real-World, Retrospective Study in North India.Diabetes, metabolic syndrome and obesity : targets and therapy · 2022Article
- Observational
- Health Internet Technology for Chronic Conditions: Review of Diabetes Management Apps.JMIR diabetes · 2021Article
- Article
- Smartphone-Based mHealth and Internet of Things for Diabetes Control and Self-Management.Journal of healthcare engineering · 2021Article
- Mobile phone usage in patients with type II diabetes and their intention to use it for self-management: a cross-sectional study in Iran.BMC medical informatics and decision making · 2020Article
- Smartphone App as Motivational Intervention to Improve Glycemic Control in Adolescents with Type 1 Diabetes.Indian journal of pediatrics · 2019Article
- Article
- The Role of Continuous Glucose Monitoring, Diabetes Smartphone Applications, and Self-Care Behavior in Glycemic Control: Results of a Multi-National Online Survey.Journal of clinical medicine · 2019Article
- Popular Diabetes Apps and the Impact of Diabetes App Use on Self-Care Behaviour: A Survey Among the Digital Community of Persons With Diabetes on Social Media.Frontiers in endocrinology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Essential steps in diabetes prevention and management include translating research into the real world, improving access to health care, empowering the community, collaborative efforts involving physicians, diabetes educators, nurses, and public health scientists, and access to diabetes prevention and management efforts. Mobile phone technology has shown wide acceptance across various ages and socioeconomic groups and offers several opportunities in health care including self-management as well as prevention of Type 2 diabetes mellitus (T2DM). The future seems to lie in mobile health (mHealth) applications that can use embedded technology to showcase advanced uses of a smartphone to help with prevention and management of chronic disorders such as T2DM. This article presents a narrative review of the mHealth technologies used for the prevention and management of T2DM. Majority (48%) of the studies used short message service (SMS) technology as their intervention while some studies (29%) incorporated applications for medication reminders and insulin optimization for T2DM management. Few studies (23%) showed that, along with mHealth technology, health-care professionals' support resulted in added positive outcomes for the patients. This review highlights the fact that an mHealth intervention need not be restricted to SMS alone.
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.