Mobile Intervention Design in Diabetes: Review and Recommendations
Abstract
Mobile technology enhances the potential to assess, prompt, educate, and engage individuals with diabetes. The near-ubiquitous presence of mobile phones allows real-time contextually relevant support for diabetes self-care. We review the design of mobile interventions included in a recent meta-analysis. Although mobile programs can lead to improvements in glycemic control, many aspects, such as the role of the diabetes clinician, real-time features, and patient engagement have not been documented. Studies with the greatest impact on hemoglobin A(1c) integrated patient feedback and a role for clinicians. Research is needed regarding feasible and efficacious roles for clinical support in mobile interventions. Recommendations for design and research include the following: consideration of patient and clinician burden; identification of patterns and metrics for patient treatment adherence and engagement; integration of goal setting and problem solving; enhancing patient education; a greater focus on patient-centered motivational strategies; and utilization of study designs that relate intervention design elements to outcomes.
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Recent reviews point out a lack of focus on detailed reporting on participants' long-term engagement with intervention tools.
“In addition, recent reviews [11,14,15] point out a lack of focus on detailed reporting on participants’ long-term engagement with the intervention tools.”
From Long-Term Engagement With a Mobile Self-Management System for People With Type 2 Diabetes (2013) · cites this paper as [14]
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- Authors
- Mulvaney, S. A., Ritterband, L. M., & Bosslet, L.
- Affiliations
- Vanderbilt University (US)
- University of Virginia (US)
- Vanderbilt University Medical Center (US)
- Corresponding author
- Mulvaney, Shelagh A.
- Venue
- Current Diabetes Reports
- Published
- 2011-09-30
- Volume
- 11
- Issue
- 6
- Pages
- 486-493
- ISSN
- 1534-4827 (ISSN-L)
- 1539-0829
- OpenAlex
- W1996851340
- Cited by
- 92
- References
- 46
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 1 · 2023: 4 · 2022: 3 · 2021: 6 · 2020: 9 · 2019: 8 · 2018: 4 · 2017: 9 · 2016: 9 · 2015: 13 · 2014: 6 · 2013: 11 · 2012: 6
- FWCI
- 1.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Current Diabetes Reports (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Keywords
- mobile health intervention, diabetes self-care, glycemic control, HbA1c, patient engagement, patient education, goal setting, motivational strategies, real-time feedback, medication adherence, intervention design
- MeSH terms
- Diabetes Mellitus, Glycated Hemoglobin, Humans, Patient Education as Topic, Self Care, Cell Phone
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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