Active Assistance Technology Reduces Glycosylated Hemoglobin and Weight in Individuals With Type 2 Diabetes: Results of a Theory-Based Randomized Trial
Abstract
BACKGROUND: Type 2 diabetes is an individual health challenge requiring ongoing self-management. Remote patient reporting of relevant health parameters and linked automated feedback via mobile telephone have potential to strengthen self-management and improve outcomes. This research involved development and evaluation of a mobile telephone-based remote patient reporting and automated telephone feedback system, guided by health behavior change theory, aimed at improving self-management and health status in individuals with type 2 diabetes. SUBJECTS AND METHODS: This research comprised a randomized controlled trial. Inclusion criteria were diagnosis of type 2 diabetes, elevated glycosylated hemoglobin (HbA1c) levels (range, 6.5-11%) or use of oral diabetes medication, and 30-70 years of age. Intervention subjects (n=24) participated in remote patient reporting of health status parameters and linked health behavior change feedback. Control participants (n=24) received standard of care including diabetes education and healthcare provider counseling. Patients were followed for approximately 10 months. RESULTS: Intervention participants achieved, compared with controls and controlling for baseline, a significantly greater mean reduction in HbA1c of -0.40% (95% confidence interval [CI] -0.67% to -0.14%) versus 0.036% (95% CI -0.23% to 0.30%) (P<0.03) and significantly greater weight reduction of -2.1 kg (95% CI -3.6 to -0.6 kg) versus 0.4 kg (95% CI -1.1 to 1.9 kg). Nonsignificant trends for greater intervention compared with control improvement in systolic and diastolic blood pressure were observed. CONCLUSIONS: Sophisticated information technology platforms for remote patient reporting linked with theory-based health behavior change automated feedback have potential to improve patient outcomes in type 2 diabetes and merit scaled-up research efforts.
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Of the 27 papers, 12 focused on T2DM, with 743 patients in the intervention groups and 645 in the control groups.
“12 were focused on T2DM (743 patients in the intervention groups and 645 patients in the control groups) [50-61]”
From Effectiveness of Disease-Specific mHealth Apps in Patients With Diabetes Mellitus: Scoping Review (2021) · cites this paper as [51]
Of 11 T2DM studies that included control groups, 7 reported significant differences (mean difference: -0.78%, -1.51 to -0.35) in favor of the app intervention groups.
“Of 11 studies that included control groups in their study design, 7 studies reported significant differences (mean difference: –0.78%, –1.51 to –0.35) in favor of the app intervention groups [51,53-58]”
From Effectiveness of Disease-Specific mHealth Apps in Patients With Diabetes Mellitus: Scoping Review (2021) · cites this paper as [51]
In T2DM, eleven studies reported a decrease of HbA1c within the app intervention groups, yielding a mean difference of -0.42%.
“Eleven of the studies reported a decrease of HbA1c within the app intervention groups, yielding a mean difference of –0.42% [50-52,54-61], but only 1 study reported a significant change of –1.1% (P<.001) [56].”
From Effectiveness of Disease-Specific mHealth Apps in Patients With Diabetes Mellitus: Scoping Review (2021) · cites this paper as [51]
One T2DM study reported a significant difference between groups for body weight (-2.1 kg intervention vs 0.4 kg control; P=.021).
“One study reported a significant difference between the groups (–2.1 kg in the intervention group versus 0.4 kg in the control group; P=.021) [51].”
From Effectiveness of Disease-Specific mHealth Apps in Patients With Diabetes Mellitus: Scoping Review (2021) · cites this paper as [51]
None of the 7 T2DM studies that reported on blood pressure found significant differences either within or between groups.
“None of the 7 studies that reported on blood pressure found significant differences either within or between groups [51-53,55,57,58,61].”
From Effectiveness of Disease-Specific mHealth Apps in Patients With Diabetes Mellitus: Scoping Review (2021) · cites this paper as [51]
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- Authors
- Orsama, A.-L., Lähteenmäki, J., Harno, K., Kulju, M., Wintergerst, E., Schachner, H., Stenger, P., Leppänen, J., Kaijanranta, H., Salaspuro, V., & Fisher, W. A.
- Affiliations
- VTT Technical Research Centre of Finland, Helsinki, Finland.
- VTT Technical Research Centre of Finland (FI)
- University of Eastern Finland (FI)
- Bayer Diabetes Care, Tarrytown, New York.
- Mediconsult Ltd., Helsinki, Finland.
- Western University (CA)
- Corresponding author
- Fisher, William A.
- Venue
- Diabetes Technology & Therapeutics
- Publisher
- SAGE Publications
- Published
- 2013-08
- Volume
- 15
- Issue
- 8
- Pages
- 662-669
- ISSN
- 1520-9156 (ISSN-L)
- 1557-8593
- OpenAlex
- W2110115502
- Cited by
- 117
- References
- 32
- Citations by year
- 2025: 7 · 2024: 10 · 2023: 5 · 2022: 9 · 2021: 19 · 2020: 13 · 2019: 13 · 2018: 13 · 2017: 10 · 2016: 9 · 2015: 6 · 2014: 3
- FWCI
- 10.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Diabetes Technology & Therapeutics (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
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- type 2 diabetes, HbA1c, HbA1c reduction, weight loss, diabetes self-management, mobile health, health behavior change theories, blood pressure
- MeSH terms
- Aged, Combined Modality Therapy, Diabetes Mellitus, Type 2, Female, Follow-Up Studies, Glycated Hemoglobin, Humans, Hyperglycemia, Male, Medical Informatics Applications, Middle Aged, Motivation, Obesity, Psychological Theory, Self Care, Weight Loss, Health Behavior, Body Mass Index, Telemedicine, Feedback, Psychological, Overweight
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