Emerging digital health approaches for the detection of undiagnosed type 2 diabetes mellitus in underserved populations: A scoping review

  • Andi Sulfikar Department of Nursing, Pelamonia Institute of Health Sciences, Makassar, Indonesia
  • Rini Rachmawaty Department of Nursing Management, Faculty of Nursing, Hasanuddin University, Makassar, Indonesia
  • Elly Lilianty Sjattar Department of Medical Surgical Nursing, Faculty of Nursing, Hasanuddin University, Makassar, Indonesia
Keywords: diabetes mellitus, type 2; early diagnosis; mass screening; telemedicine; mobile applications; medically underserved area; health equity

Abstract

Background & Aim: Undiagnosed type 2 diabetes mellitus continues to pose a major global health challenge, especially in underserved populations facing limited access to screening. Digital health technologies present scalable alternatives to improve early detection and prevent complications. This scoping review aims to map digital health approaches for detecting undiagnosed type 2 diabetes mellitus in underserved adult communities and analyze screening outcomes, feasibility, and key implementation factors.

Materials & Methods: The review followed the Arksey and O’Malley scoping framework and was reported using PRISMA-ScR guidelines. Systematic searches were performed in PubMed/MEDLINE, Scopus, Web of Science, and CINAHL for studies published in English from 2015 onward. Two reviewers independently screened articles, with conflicts resolved through consensus. Data were synthesized narratively to identify digital modalities, screening strategies, effectiveness indicators, and enablers or barriers.

Results: Nineteen studies were included, identifying five categories of digital interventions. Electronic health record–driven screening was reported in 5 of  19 studiesand was the most frequently reported modality, alongside mHealth applications, SMS-based detection support, telehealth platforms, and wearable tools. Digital risk-based screening integrated within community or primary care pathways demonstrated the widest reach and highest identification of undiagnosed dysglycemia. Simpler digital solutions showed greater acceptability and feasibility than complex systems, particularly in settings with limited digital literacy or connectivity.

Conclusion: Digital health technologies show strong potential to expand early detection of undiagnosed type 2 diabetes mellitus in underserved populations. System-integrated, low-burden, and equity-centered screening models are most promising. Strengthening linkage to care and improving digital accessibility remainpriorities for future research.

Published
2026-05-06
Section
Articles