Factors Influencing Caregivers’ Intention to Use Transfer-care Robots

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Authors: Kyung-Ja Kang, Young Ae Song, Ji Yeon Park, Seo Yeon Bae, Ji Sup Hwang, Ji Eun Song
Cited by: 1
References: 23

Abstract

Few studies have examined the acceptance of transfer-care robots across diverse caregiver roles and practice settings, with most research limited to single professional groups or institutional environments. This mixed-methods study integrates nurses, personal care assistants, and family caregivers from hospitals, long-term care facilities, and home care to capture a holistic perspective on technology adoption across the continuum of care. Employing a sequential explanatory design guided by Davis’ Technology Acceptance Model, we conducted a quantitative survey (n=224) followed by focus group interviews (n=15). Quantitative findings revealed that job relevance was the strongest predictor of intention to use ( β =0.50, P

Fields of Study & Subjects

Social Robot Interaction and HRI Healthcare Technology and Patient Monitoring Human-Automation Interaction and Safety

Publication details

Journal / source
CIN Computers Informatics Nursing
Publisher
Ovid Technologies (Wolters Kluwer Health)
Publication date
16 June 2026
Language
EN