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Empirical evaluation of care robots for care workers using the technology acceptance model : a structural equation modeling analysis

Year: 2026

Type: article

Abstract: Transfer tasks are a leading cause of musculoskeletal injuries among care workers, yet the adoption of transfer assistive robots remains limited. While South Korea is advancing efforts to develop and deploy these technologies, little is known about the psychological factors influencing their acceptance. This study applies a Technology Acceptance Model to examine how self-efficacy and anxiety affect care workers’ intention to use these robots. Data were collected from 463 care workers in South Korea and analyzed using structural equation modeling and multivariate linear regression. The study followed the STROBE guidelines for cross-sectional research. Structural equation modeling showed that perceived usefulness and attitude had significant direct effects on behavioral intention to use. Self-efficacy influenced behavioral intention indirectly through the Technology Acceptance Model(TAM) pathways. Anxiety influenced behavioral intention only indirectly through perceived ease of use, and its total indirect effect was not statistically significant. Regression analysis also confirmed that perceived usefulness, perceived ease of use, and attitude positively predicted intention to use. The findings demonstrate that perceived ease of use and perceived usefulness are key determinants of transfer-assistive robot acceptance, with self-efficacy indirectly facilitating behavioral intention through the TAM pathways. Although anxiety negatively affected perceived ease of use, its influence on behavioral intention was limited. Enhancing perceived ease of use through improved robot usability and strengthening care workers’ self-efficacy through hands-on training may facilitate adoption and support the safe and effective integration of robotic systems in care settings.

Source: BMC Geriatrics

DOI: 10.1186/s12877-026-08143-w

Authors: Young Sun Kim, Hye Ri Shin, Heejeong Yoon, Won Chul Shin, Seung Don Yoo, Ji-Ho Park

Institutions: Kyung Hee University, Kyung Hee University Hospital at Gangdong

Language: English

Topic: Technology Adoption and User Behaviour

Subfield: Information Systems and Management

Field: Decision Sciences

Domain: Social Sciences

SDGs: Good health and well-being, Decent work and economic growth

Open Access status: gold

Estimated APC paid: $3,190