Factors Affecting Adoption of a Technology-Based Tool for Diabetes Self-Management Education and Support Among Adult Patients with Type 2 Diabetes in South Texas. Issue 3 (June 2021)

• Record Type: Journal Article
• Authors: Baek, Juha; Lin, Sherry; Bolin, Jane N.; Ory, Marcia; Flores, Starr; Kash, Bita A.
• Is Part Of: Science of diabetes self-management and care. Volume 47:Issue 3(2021)
• Page Start: 189
• Page End: 198
• Publication Date: 2021-06
• Subjects: Diabetes -- Study and teaching -- Periodicals; Patient education -- Periodicals; 616.4620071
• DOI: 10.1177/26350106211004885
• Languages: English
• ISSNs: 2635-0114

Abstract

Purpose: The purpose of this study is to describe a novel computerized diabetes education tool and explore factors influencing self-selection and use among primarily Hispanic patients diagnosed with type 2 diabetes in south Texas. Methods: Study participants included 953 adult patients with type 2 diabetes enrolled in a diabetes education program between July 1, 2016, and June 30, 2017. Participants were asked to choose either a new technology-based diabetes education tool with a touch-screen device or a traditional face-to-face education method. Multivariate logistic regression analysis was applied to identify factors associated with adopting the computerized diabetes education tool among the patients. Results: When comparing technology-based tool adopters and nonadopters, several demographic and health-related factors differentiated technology use in bivariate analyses. The multivariate logistic regression model showed that Hispanic patients were less likely to choose a technology-based tool. Patients who perceived their health status as excellent/good were more likely to adopt the technologic education method than those with fair/poor perceived health status. A1C level was negatively associated with self-selection of technology. Conclusions: Specific demographic and health-related characteristics are significant contributing factors to patients' adoption of a technology-based diabetes education tool. Health care providers can utilize these findings to target and refer specific patients to a computerized diabetes education tool for more effective diabetes care and to optimize technology adoption success.