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A Scoping Review Using the Almere Model to Understand Factors Facilitating and Hindering the Acceptance of Social Robots in Nursing Homes.

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Title: A Scoping Review Using the Almere Model to Understand Factors Facilitating and Hindering the Acceptance of Social Robots in Nursing Homes.
Authors: Felding, Simone Anna1,2 (AUTHOR) simone.felding@dzne.de, Koh, Wei Qi3,4 (AUTHOR), Teupen, Sonja1,2 (AUTHOR), Budak, Kübra Beliz1,2 (AUTHOR), Laporte Uribe, Franziska1,2 (AUTHOR), Roes, Martina1,2 (AUTHOR)
Source: International Journal of Social Robotics. Jul2023, Vol. 15 Issue 7, p1115-1153. 39p.
Subjects: Social acceptance, Nursing care facilities, Social robots, Human-robot interaction, Evidence gaps, Older people, CINAHL database
Abstract: Social robots are increasingly used in the care of older adults, including people living with dementia. An important prerequisite for effective use is knowledge about which factors facilitate and hinder the acceptance of social robots. The aim of this review at the intersection of health care research and human–robot interaction research is to understand factors facilitating and hindering the acceptance of social robots for older adults and people living with dementia in nursing homes based on the Almere model and to identify research gaps. We conducted a scoping review, systematically searching MEDLINE, PsycINFO, CINAHL and Compendex. The Almere model of acceptance was used to guide the development and conduct of this review. We used the principles of deductive content analysis, and we narratively present the review results. Twenty-six studies were included in the review. We found facilitating and/or hindering factors for all constructs of the Almere model. Perceived usefulness, perceived ease of use and perceived enjoyment were the most studied constructs, whereas trust and intention to use were the least studied constructs. Across constructs, seeing robots positively impacting residents was one of the key facilitating factors, and practical difficulties were a hindering factor. The Almere model provided useful insight into the acceptance of social robots. Nevertheless, we found the concept of engagement, the nursing home context, the intervention characteristics and the individual user groups important for the acceptance of social robots in nursing homes and therefore argue for future research expanding on the model. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Social robots are increasingly used in the care of older adults, including people living with dementia. An important prerequisite for effective use is knowledge about which factors facilitate and hinder the acceptance of social robots. The aim of this review at the intersection of health care research and human–robot interaction research is to understand factors facilitating and hindering the acceptance of social robots for older adults and people living with dementia in nursing homes based on the Almere model and to identify research gaps. We conducted a scoping review, systematically searching MEDLINE, PsycINFO, CINAHL and Compendex. The Almere model of acceptance was used to guide the development and conduct of this review. We used the principles of deductive content analysis, and we narratively present the review results. Twenty-six studies were included in the review. We found facilitating and/or hindering factors for all constructs of the Almere model. Perceived usefulness, perceived ease of use and perceived enjoyment were the most studied constructs, whereas trust and intention to use were the least studied constructs. Across constructs, seeing robots positively impacting residents was one of the key facilitating factors, and practical difficulties were a hindering factor. The Almere model provided useful insight into the acceptance of social robots. Nevertheless, we found the concept of engagement, the nursing home context, the intervention characteristics and the individual user groups important for the acceptance of social robots in nursing homes and therefore argue for future research expanding on the model. [ABSTRACT FROM AUTHOR]
ISSN:18754791
DOI:10.1007/s12369-023-01012-1