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Effect of self-managed lifestyle treatment on glycemic control in patients with type 2 diabetes
University of Gothenburg,.
Lund University, Sweden.
RISE Research Institutes of Sweden, Digital Systems, Data Science.
Swedish Institute for Health Economics, Sweden.
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2022 (English)In: npj Digital Medicine, ISSN 2398-6352, Vol. 5, no 1, article id 60Article in journal (Refereed) Published
Abstract [en]

The lack of effective, scalable solutions for lifestyle treatment is a global clinical problem, causing severe morbidity and mortality. We developed a method for lifestyle treatment that promotes self-reflection and iterative behavioral change, provided as a digital tool, and evaluated its effect in 370 patients with type 2 diabetes (ClinicalTrials.gov identifier: NCT04691973). Users of the tool had reduced blood glucose, both compared with randomized and matched controls (involving 158 and 204 users, respectively), as well as improved systolic blood pressure, body weight and insulin resistance. The improvement was sustained during the entire follow-up (average 730 days). A pathophysiological subgroup of obese insulin-resistant individuals had a pronounced glycemic response, enabling identification of those who would benefit in particular from lifestyle treatment. Natural language processing showed that the metabolic improvement was coupled with the self-reflective element of the tool. The treatment is cost-saving because of improved risk factor control for cardiovascular complications. The findings open an avenue for self-managed lifestyle treatment with long-term metabolic efficacy that is cost-saving and can reach large numbers of people. © 2022, The Author(s).

Place, publisher, year, edition, pages
Nature Research , 2022. Vol. 5, no 1, article id 60
Keywords [en]
Blood, Blood pressure, Digital devices, Insulin, Iterative methods, Metabolism, Natural language processing systems, Behavioral changes, Clinical problems, Cost saving, Digital tools, Glycemic control, IS costs, Scalable solution, Self reflection, Self-managed, Type-2 diabetes, Patient treatment
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Clinical Medicine
Identifiers
URN: urn:nbn:se:ri:diva-60532DOI: 10.1038/s41746-022-00606-9Scopus ID: 2-s2.0-85129954140OAI: oai:DiVA.org:ri-60532DiVA, id: diva2:1704688
Note

 Funding details: Knut och Alice Wallenbergs Stiftelse; Funding text 1: Supported by grants from the Knut and Alice Wallenberg Foundation. We thank Svetlana Johansson, Paul Tyler, Anna-Maria Veljanovska Ramsay, Jasmina Kravic, as well as Louise Qvist, Maria Fälemark, Helene Ferm and Jessica Hedin for managing study visits. We also thank the patients and colleagues who participated in the development and evaluation of the tool.

Available from: 2022-10-19 Created: 2022-10-19 Last updated: 2025-09-23Bibliographically approved

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