A Web-Based Computer-Tailored Program to Improve Treatment Adherence in Patients With Type 2 Diabetes: Randomized Controlled Trial
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Abstract
Background: Adherence to core type 2 diabetes mellitus (T2DM) treatment behaviors is suboptimal, and nonadherence is generally not limited to one treatment behavior. The internet holds promise for programs that aim to improve adherence. We developed a computer-tailored eHealth program for patients with T2DM to improve their treatment adherence, that is, adherence to both a healthy lifestyle and medical behaviors. Objective: The objective of this study is to examine the effectiveness of the eHealth program in a randomized controlled trial. Methods: Patients with T2DM were recruited by their health professionals and randomized into either the intervention group, that is, access to the eHealth program for 6 months, or a waiting-list control group. In total, 478 participants completed the baseline questionnaire, of which 234 gained access to the eHealth program. Of the 478 participants, 323 were male and 155 were female, the mean age was 60 years, and the participants had unfavorable BMI and HbA1c levels on average. Outcome data were collected through web-based assessments on physical activity (PA) levels, caloric intake from unhealthy snacks, and adherence to oral hypoglycemic agents (OHAs) and insulin therapy. Changes to separate behaviors were standardized and summed into a composite change score representing changes in the overall treatment adherence. Further standardization of this composite change score yielded the primary outcome, which can be interpreted as Cohen d (effect size). Standardized change scores observed in separate behaviors acted as secondary outcomes. Mixed linear regression analyses were conducted to examine the effectiveness of the intervention on overall and separate treatment behavior adherence, accommodating relevant covariates and patient nesting. Results: After the 6-month follow-up assessment, 47.4% (111/234) of participants in the intervention group and 72.5% (177/244) of participants in the control group were retained. The overall treatment adherence improved significantly in the intervention group compared with the control group, reflected by a small effect size (d=0.27; 95% CI 0.032 to 0.509; P=.03). When considering changes in separate treatment behaviors, a significant decrease was observed only in caloric intake from unhealthy snacks in comparison with the control group (d=0.36; 95% CI 0.136 to 0.584; P=.002). For adherence to PA (d=−0.14; 95% CI −0.388 to 0.109; P=.27), OHAs (d=0.27; 95% CI −0.027 to 0.457; P=.08), and insulin therapy (d=0.35; 95% CI −0.066 to 0.773; P=.10), no significant changes were observed. These results from the unadjusted analyses were comparable with the results of the adjusted analyses, the per-protocol analyses, and the sensitivity analyses. Conclusions: Our multibehavior program significantly improved the overall treatment adherence compared with the control group. To further enhance the impact of the intervention in the personal, societal, and economic areas, a wide-scale implementation of our eHealth intervention is suggested. Trial Registration: Netherlands Trial Register NL664; https://www.trialregister.nl/trial/6664
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A web-based, computer-tailored e-health program in T2DM did not change medication-specific adherence.
“A web-based, computer-tailored e-health program in T2DM improved overall treatment adherence and reduced unhealthy snacking but did not change physical activity or medication-specific adherence [22].”
From Multilevel Interventions to Improve Medication Adherence in Older Adults: A Systematic Review and Meta-Analysis of Cognitive, Digital, Behavioral, and Socioeconomic Strategies (2015–2025) (2026) · cites this paper as [22]
The Discussion (Principal Findings and Comparison With Previous Work) reports no statistically significant effect on adherence to oral hypoglycemic agents or insulin therapy. It also reports positive, though nonsignificant, effect sizes for both, so the categorical statement that adherence “did not change” overstates the finding. (LLM, conf=0.84)
Experimental — accuracy not yet measuredVluggen et al. (2021) demonstrated that an internet-based, computer-tailored intervention improved overall treatment adherence in type 2 diabetic patients by providing individualized recommendations.
“Vluggen et al. (2021) demonstrated that an internet-based, computer-tailored intervention improved overall treatment adherence in type 2 diabetic patients by providing individualized recommendations [22].”
A web-based, computer-tailored e-health program in T2DM did not change physical activity.
“A web-based, computer-tailored e-health program in T2DM improved overall treatment adherence and reduced unhealthy snacking but did not change physical activity or medication-specific adherence [22].”
A web-based, computer-tailored e-health program in T2DM reduced unhealthy snacking.
“A web-based, computer-tailored e-health program in T2DM improved overall treatment adherence and reduced unhealthy snacking but did not change physical activity or medication-specific adherence [22].”
A web-based, computer-tailored e-health program in T2DM improved overall treatment adherence.
“A web-based, computer-tailored e-health program in T2DM improved overall treatment adherence and reduced unhealthy snacking but did not change physical activity or medication-specific adherence [22].”
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- Authors
- Vluggen, S., Candel, M., Hoving, C., Schaper, N. C., & de Vries, H.
- Affiliations
- Maastricht University (NL)
- Maastricht University Medical Centre (NL)
- Corresponding author
- Vluggen, Stan
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2021-02-23
- Volume
- 23
- Issue
- 2
- Pages
- e18524
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC7943340
- OpenAlex
- W3117295052
- Cited by
- 26
- References
- 84
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 4 · 2023: 11 · 2022: 4
- FWCI
- 4.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Funders
- Universiteit Maastricht
- Maastricht Universitair Medisch Centrum
- Topics
- Health Sciences › Medicine › Family Practice › Medication Adherence and Compliance
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Keywords
- type 2 diabetes, medication adherence, online intervention, oral antidiabetic drugs, insulin therapy, physical activity, energy intake, unhealthy snacks, healthy lifestyle behaviors, patient retention, diabetes self-management education, patient-centered outcome measures
- MeSH terms
- Treatment Adherence and Compliance, Adult, Aged, Diabetes Mellitus, Type 2, Female, Humans, Male, Middle Aged, Telemedicine, Internet, Young Adult
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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