Service robots in healthcare: Toward a healthcare service robot acceptance model (sRAM)
Weng Marc Lim, K. Mohamed Jasim, A. Christina Josephine Malathi
- 发表年份
- 2025
- 引用次数
- 14
摘要
Our research examines the perceptions and intentions surrounding the use of healthcare service robots. Guided by service robot acceptance model (sRAM) and stimulus-organism-response (S-O-R) model, we explore how perceptions of functional, social, emotional, and robotic features of service robots shape their trust and use in healthcare. Our research incorporated data from 398 responses collected via an online questionnaire, which was analyzed using partial least squares structural equation modeling (PLS-SEM) through the SmartPLS software, revealing that functional (ease of use), emotional (anxiety and enjoyment), and social (social interactivity and presence) features significantly influence healthcare service robots trust and use. Contrarily, usefulness—a functional feature—had no significant role in shaping healthcare service robots trust and use. Nevertheless, trust mediated perceptions relating to anxiety, ease of use, enjoyment, social interactivity, and social presence with healthcare service robots use. Interestingly, anthropomorphism—a robotic feature—had no moderating effect while subjective norms—a non-robotic feature—only moderated the impact of social interactivity on healthcare service robots use. Conclusively, our research organizes sRAM antecedents into clear, discrete categories (functional, emotional, and social) and delivers a comprehensive, structured acceptance model. This new and novel model supports systematic theory development and comparability in healthcare service robot research while also offering critical implications for enhancing the integration and utilization of service robots within healthcare. • Functional, emotional, and social features drive robot trust and use. • Usefulness does not affect robot trust or usage. • Trust mediates the impact of anxiety, ease, and social features. • Anthropomorphism does not alter robot perception effects. • Subjective norms only modify social interactivity's influence.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002