ArticleSensors (Basel, Switzerland)2022
A Nudge-Inspired AI-Driven Health Platform for Self-Management of Diabetes.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 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
17 citing papers in PubMed, 3 syntheses or guidelines pooled it, 40 citations in OpenAlex.
- Digital nudging techniques for behaviour change in lifestyle medicine: a scoping review.Frontiers in digital health · 2026Pooled it
- Adherence to Usability and Accessibility Principles in Digital Health Applications for Patients With Diabetes: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Application of artificial intelligence in the health management of chronic disease: bibliometric analysis.Frontiers in medicine · 2024Pooled it
- Can AI help with the hardest thing: pro health behavior change.NPJ cardiovascular health · 2026Review
- Program cost and return on investment analysis of remote patient monitoring for hypertension management in the cardiology department of a large healthcare system.Journal of telemedicine and telecare · 2026Article
- Personalized Nutrition in the Era of Digital Health: A New Frontier for Managing Diabetes and Obesity.Food science & nutrition · 2025Review
- Loneliness by Design: The Structural Logic of Isolation in Engagement-Driven Systems.International journal of environmental research and public health · 2025Review
- Applications of Artificial Intelligence in Food Industry.Foods (Basel, Switzerland) · 2025Article
- Artificial intelligence in chronic disease self-management: current applications and future directions.Frontiers in public health · 2025Review
- Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review.PeerJ. Computer science · 2025Article
- A Scoping Review of Artificial Intelligence-Based Health Education Interventions for Patients with Type 2 Diabetes.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Review
- The Feasibility of AgileNudge+ Software to Facilitate Positive Behavioral Change: Mixed Methods Design.JMIR formative research · 2024Article
- Advancing Diabetes Self-Management: A Novel Smartphone Application Featuring a Scoring Algorithm for Tailored User Engagement.International journal of preventive medicine · 2024Article
- Implementing a Novel Machine Learning System for Nutrition Education in Diabetes Mellitus Nutritional Clinic: Predicting 1-Year Blood Glucose Control.Bioengineering (Basel, Switzerland) · 2023Article
- User Engagement and Weight Loss Facilitated by a Mobile App: Retrospective Review of Medical Records.JMIR formative research · 2023Article
- Advances in E-Health and Mobile Health Monitoring.Sensors (Basel, Switzerland) · 2022Article
- Article
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 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetes mellitus is a serious chronic disease that affects the blood sugar levels in individuals, with current predictions estimating that nearly 578 million people will be affected by diabetes by 2030. Patients with type II diabetes usually follow a self-management regime as directed by a clinician to help regulate their blood glucose levels. Today, various technology solutions exist to support self-management; however, these solutions tend to be independently built, with little to no research or clinical grounding, which has resulted in poor uptake. In this paper, we propose, develop, and implement a nudge-inspired artificial intelligence (AI)-driven health platform for self-management of diabetes. The proposed platform has been co-designed with patients and clinicians, using the adapted 4-cycle design science research methodology (A4C-DSRM) model. The platform includes (
Indexed as
Identifiers
What Socratic 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 Socratic graph.