Author: Baek, Juha; Lin, Sherry; Bolin, Jane N; Ory, Marcia; Flores, Starr; Kash, Bita A
Title: 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. Cord-id: x365qgx6 Document date: 2021_6_1
ID: x365qgx6
Snippet: 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 devi
Document: 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.
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