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Robot-enhanced diabetes care for middle-aged and older adults living with diabetes in the community: A small sample size mixed-method evaluation

PURPOSE: This study assessed robot-enhanced healthcare in practical settings for the purpose of community diabetes care. METHODS: A mixed method evaluation collected quantitative and qualitative data on diabetes patients over 45 (N = 30) and community pharmacists (N = 10). It took 15–20 min for the...

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Detalles Bibliográficos
Autores principales: Chiu, Ching-Ju, Hua, Lin-Chun, Chou, Chieh-Ying, Chiang, Jung-Hsien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9012373/
https://www.ncbi.nlm.nih.gov/pubmed/35427359
http://dx.doi.org/10.1371/journal.pone.0265384
Descripción
Sumario:PURPOSE: This study assessed robot-enhanced healthcare in practical settings for the purpose of community diabetes care. METHODS: A mixed method evaluation collected quantitative and qualitative data on diabetes patients over 45 (N = 30) and community pharmacists (N = 10). It took 15–20 min for the diabetes patients to interact with the robot. Before and after the interaction, questionnaires including a diabetes knowledge test, self-efficacy for diabetes, and feasibility of use of the robot was administered. In-depth interviews with both pharmacists and patients were also conducted. RESULTS: After interacting with the robot, a statistically significant improvement in diabetes knowledge (p < .001) and feasibility of the robot (p = .012) was found, but self-efficacy (p = .171) was not significantly improved. Five themes emerged from interviewing the diabetes patients: Theme 1: meets the needs of self-directed learning for the elderly; Theme 2: reduces alertness and creates comfortable interaction; Theme 3: vividness and richness enhance interaction opportunities; Theme 4: Robots are not without disadvantages, and Theme 5: Every person has unique tastes. Three themes emerged from interviewing pharmacists: Theme 1: Technology must meet the real needs of the patient; Theme 2: creates new services, and Theme 3: The use of robots must conform to real-life situations. CONCLUSIONS: Both the diabetes patients and the pharmacist reported more positive feedback on the robot-enhanced diabetes care than concerns. Self-directed learning, comfortable interaction, and vividness were the most focuses when using robot to enhance self-management for the patients. Pharmacists were most receptive to fit conforming with reality and creating new services.