Evidence mapPaperPMID 41533959Full record

ArticleJMIR mHealth and uHealth2026

Digital Health Interventions to Support Chronic Disease Management: Systematic Scoping Review.

Abdullah Al Mahmud, Shane Joachim, Prem Prakash Jayaraman, Caitlin Learmonth, Shivani Tyagi, Abdur Rahim Mohammad Forkan, Muhammad Shuakat, Nilmini Wickramasinghe, Jack Wheeler, Stephanie Best and 1 more

Abstract readScoping Review
In one paragraph

Article in JMIR mHealth and uHealth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Abdullah Al MahmudCentre for Design Innovation, Department of Architectural and Industrial Design, Swinburne University of Technology, John St., Hawthorn, Melbourne, 3122, Australia, 61392143830.ORCID http://orcid.org/0000-0002-2801-723X
Shane JoachimDepartment of Computing Technologies, Swinburne University of Technology, Melbourne, Australia.ORCID http://orcid.org/0000-0002-3687-4346
Prem Prakash JayaramanSchool of Science, Computing and Engineering Technologies, Factory of the Future and Digital Innovation Lab, Swinburne University of Technology, Melbourne, Australia.ORCID http://orcid.org/0000-0003-4500-3443
Caitlin LearmonthSwinburne University of Technology, Melbourne, Australia.ORCID http://orcid.org/0000-0002-1742-3005
Shivani TyagiDepartment of Communication Design, School of Design and Architecture, Swinburne University of Technology, Melbourne, Australia.ORCID http://orcid.org/0000-0002-1276-0133
Abdur Rahim Mohammad ForkanDepartment of Computing Technologies, Swinburne University of Technology, Melbourne, Australia.ORCID http://orcid.org/0000-0003-0237-1705
Muhammad ShuakatLa Trobe University, Melbourne, Australia.ORCID http://orcid.org/0000-0003-2994-2790
Nilmini WickramasingheSchool of Computing, Engineering & Mathematical Sciences, La Trobe University, Melbourne, Australia.ORCID http://orcid.org/0000-0002-1314-8843
Jack WheelerParkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, Australia.ORCID http://orcid.org/0000-0002-1046-6985
Stephanie BestSchool of Health Sciences, University of Melbourne, Melbourne, Australia.ORCID http://orcid.org/0000-0002-1107-8976
Alison TrainerParkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, Australia.ORCID http://orcid.org/0000-0002-9847-3265

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Health interventions delivered by digital platforms are gaining popularity and are evolving to address the needs of patients with chronic diseases. The heterogeneity of chronic diseases requires that digital health platforms vary in their approaches to chronic disease management. Objective: This review aimed to explore the characteristics of digital health platforms and the corresponding digital interventions developed to support patients with chronic diseases. This includes those platforms' design, development, and the metrics by which any incremental benefits they provide are assessed. Methods: We searched electronic databases including Scopus, Web of Science, PsycINFO, IEEE Xplore, MEDLINE, and Embase. Relevant articles published from January 2013 to November 2024 were extracted. Extracted data were then synthesized using qualitative content analysis and presented in narrative form with relevant tables. Results: In total, we identified 69 digital health platforms supporting the management of 20 chronic diseases. Most platforms were mobile apps (n=22) or a combination of web and mobile apps (n=15). Most of the platforms (n=44) were tailored to support self-management of chronic diseases. These platforms also provided a web-based portal where health care providers could review and manage the information recorded by patients. In 77% (53/69) of the studies, patients reported that the digital interventions delivered by the platform improved their quality of life, their health, and their ability to self-manage their chronic diseases. In addition, health care providers reported positive outcomes, including improved clinical utility and patient communication. While short-term health outcomes of the digital health interventions were largely positive, long-term health outcomes remain unknown. This was because most of the studies were short-term pilots and often formative in nature (n=42). Many had limited sample sizes, limited participant uptake of the digital platforms, and technical issues. In many cases, further personalization of platforms was required to meet patients' self-management needs. Conclusions: Digital health interventions can be beneficial in the management of chronic disease. The adoption of digital interventions in combination with regular clinical care can improve health outcomes, support self-management, and enhance communication between patients and health care providers. However, long-term user engagement is the major barrier to their long-term success. High dropout rates, often resulting from a lack of motivation or technical issues, testify to the need for adaptive, low-burden interventions that function seamlessly in users' daily lives. Adopting user-centered and co-design approaches that engage both clinicians and patients in designing digital health platforms may enhance the usability and uptake of such platforms.

Indexed as

Disease ManagementChronic DiseaseDigital HealthHumansMobile ApplicationsTelemedicinechronic diseasechronic disease managementclinical utilityco-designdesigndevelopmentdigital health platformdigital technologymHealthpatient communicationqualitative content analysisquality of lifescoping reviewself-managementsupportuser centereduser-centered designweb-based

Identifiers

PMID41533959
PMCPMC12803440

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.