Digital health interventions for patient engagement: A systematic umbrella review
23 affiliations
- 1Institute for Evidence-Based Healthcare, Faculty of Health Sciences & Medicine, Bond University, Gold Coast, Queensland, Australia.
- 2Evidence-Based Practice Professorial Unit (EBPPU), Gold Coast Hospital & Health Service (GCHHS), Gold Coast, Queensland, Australia.
- 3Centre for Data Analytics, Bond Business School, Bond University, Gold Coast, Queensland, Australia.
- 4School of Population Health, Faculty of Medicine and Health, University of New South Wales (UNSW), Sydney, New South Wales, Australia.
- 5Master Program in Artificial Intelligence Applications and Management (AIAM), and Bachelor Program in Smart Sustainable Development and Management, International College of Sustainability Innovations, National Taipei University (NTPU), New Taipei city, Taiwan.
- 6Department of Nutrition and Dietetics, School of Health Sciences, University of Management and Technology, Lahore, Pakistan.
- 7Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- 8Integrated Engineering Centre of Excellence (IECE), The University of Lahore, Lahore, Pakistan.
- 9Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.
- 10Master of Public Health Program, Faculty of Medicine, Universitas Negeri Semarang (UNNES), Semarang, Indonesia.
- 11Department of Health Policy and Management, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.
- 12Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
- 13Department of Obstetrics and Gynaecology, Oslo University Hospital (OUS), Oslo, Norway.
- 14Biometry Hub, Faculty of Sciences, Engineering and Technology, Adelaide University, Waite Campus, Adelaide, South Australia, Australia.
- 15Department of Public Health and Community Medicine, Department of Medical Education (DME), SZMC Shaikh Khalifa Bin Zayed Al-Nahyan Medical College, Shaikh Zayed Postgraduate Medical Institute, Shaikh Zayed Medical Complex, Lahore, Pakistan.
- 16Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia.
- 17Laboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
- 18Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America.
- 19Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.
- 20International Centre for Health Information and Technology, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
- 21Department of Dermatology, Wan Fang Hospital, Taipei, Taiwan.
- 22Research Centre for Artificial Intelligence in Medicine, Taipei Medical University, Taipei, Taiwan.
- 23Sydney Nursing School, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Abstract
Digital tools are increasingly integrated into patient engagement (PE) in chronic disease management, yet findings remain fragmented across populations, modalities, and outcome definitions. The aim of this umbrella review was to systematically review evidence on the effectiveness of Digital Health Interventions (DHIs) to enhance PE and related health outcomes. Six databases were searched for eligible studies published from inception to June 2025. Systematic reviews with meta-analyses of DHIs targeting engagement outcomes (e.g., self-management, adherence, activation) were included. Forty-two reviews (853 primary studies; ≈ 574,676 participants) met inclusion criteria, with most rated low-quality using AMSTAR-2. Meta-meta-analyses suggested DHIs could improve medication adherence (SMD = 0.65, 95% CI: 0.22, 1.08). Secondary outcomes also demonstrated potential for DHIs to improve quality of life (SMD = 0.26) and HbA1c (MD = −0.45%). Subgroup analyses indicated variation in effects across age groups and conditions for medication adherence and quality of life. Thus, digital health interventions may provide scalable, though moderate, improvements in patient engagement behaviours and selected clinical outcomes across diverse populations and conditions. Despite statistically significant pooled estimates for selected outcomes, due to the predominance of low-quality reviews, findings should be interpreted as exploratory evidence of effectiveness. Future implementation should be informed by higher-quality systematic reviews, longer-term primary studies, and additional evidence on patient activation and satisfaction. Author summary: Digital technologies such as mobile apps, telehealth, text messaging, patient portals, and wearable devices are increasingly used to help people take a more active role in managing long-term health conditions. We brought together evidence from 42 systematic reviews covering 853 primary studies and more than 574,000 participants. Digital interventions showed potential to improve medication adherence and to achieve small improvements in quality of life and blood sugar. However, the evidence is much less certain than these numerical results alone may suggest. Forty of the 42 reviews were rated as low or critically low in terms of methodological rigor, while some pooled results relied on only three reviews and results often differed substantially across studies. We therefore interpret the pooled estimates as signals of potential benefit rather than proof that a particular digital approach will work for every patient or health system. Future studies should use clearer definitions of patient engagement, report outcomes consistently, follow participants for longer, and examine which digital formats work best for different populations. These improvements are needed before strong clinical, or policy recommendations can be made.
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BibTeX
@article{iqbal2026digital,
title = {{Digital health interventions for patient engagement: A systematic umbrella review}},
author = {Usman Iqbal and Dumisani Enricho Nkhoma and Yankuba B Manga and Afifa Tanweer and Syed Measum Haider Bokhari and Mochammad Fadjar Wibowo and Dina Nur Anggraini Ningrum and Annisa Ristya Rahmanti and Chih-Wei Huang and Hsuan-Chia Yang and Suleman Atique and Max Moldovan and Ayesha Humayun and Lutfan Lazuardi and Gulasekaran Rajaguru and Sharon Mickan and Leo Anthony Celi and Yu-Chuan Jack Li and Julie Redfern},
journal = {PLOS Digital Health},
year = {2026},
month = oct,
doi = {10.1371/journal.pdig.0001785},
url = {https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001785},
note = {CC BY},
}
RIS
TY - JOUR
TI - Digital health interventions for patient engagement: A systematic umbrella review
AU - Usman Iqbal
AU - Dumisani Enricho Nkhoma
AU - Yankuba B Manga
AU - Afifa Tanweer
AU - Syed Measum Haider Bokhari
AU - Mochammad Fadjar Wibowo
AU - Dina Nur Anggraini Ningrum
AU - Annisa Ristya Rahmanti
AU - Chih-Wei Huang
AU - Hsuan-Chia Yang
AU - Suleman Atique
AU - Max Moldovan
AU - Ayesha Humayun
AU - Lutfan Lazuardi
AU - Gulasekaran Rajaguru
AU - Sharon Mickan
AU - Leo Anthony Celi
AU - Yu-Chuan Jack Li
AU - Julie Redfern
PY - 2026
DA - 2026/10/01
JO - PLOS Digital Health
DO - 10.1371/journal.pdig.0001785
UR - https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001785
AB - Digital tools are increasingly integrated into patient engagement (PE) in chronic disease management, yet findings remain fragmented across populations, modalities, and outcome definitions. The aim of this umbrella review was to systematically review evidence on the effectiveness of Digital Health Interventions (DHIs) to enhance PE and related health outcomes. Six databases were searched for eligible studies published from inception to June 2025. Systematic reviews with meta-analyses of DHIs targeting engagement outcomes (e.g., self-management, adherence, activation) were included. Forty-two reviews (853 primary studies; ≈ 574,676 participants) met inclusion criteria, with most rated low-quality using AMSTAR-2. Meta-meta-analyses suggested DHIs could improve medication adherence (SMD = 0.65, 95% CI: 0.22, 1.08). Secondary outcomes also demonstrated potential for DHIs to improve quality of life (SMD = 0.26) and HbA1c (MD = −0.45%). Subgroup analyses indicated variation in effects across age groups and conditions for medication adherence and quality of life. Thus, digital health interventions may provide scalable, though moderate, improvements in patient engagement behaviours and selected clinical outcomes across diverse populations and conditions. Despite statistically significant pooled estimates for selected outcomes, due to the predominance of low-quality reviews, findings should be interpreted as exploratory evidence of effectiveness. Future implementation should be informed by higher-quality systematic reviews, longer-term primary studies, and additional evidence on patient activation and satisfaction. Author summary: Digital technologies such as mobile apps, telehealth, text messaging, patient portals, and wearable devices are increasingly used to help people take a more active role in managing long-term health conditions. We brought together evidence from 42 systematic reviews covering 853 primary studies and more than 574,000 participants. Digital interventions showed potential to improve medication adherence and to achieve small improvements in quality of life and blood sugar. However, the evidence is much less certain than these numerical results alone may suggest. Forty of the 42 reviews were rated as low or critically low in terms of methodological rigor, while some pooled results relied on only three reviews and results often differed substantially across studies. We therefore interpret the pooled estimates as signals of potential benefit rather than proof that a particular digital approach will work for every patient or health system. Future studies should use clearer definitions of patient engagement, report outcomes consistently, follow participants for longer, and examine which digital formats work best for different populations. These improvements are needed before strong clinical, or policy recommendations can be made.
SN - 2767-3170
ER -