Elderly’s acceptance of companion robots from the perspective of user factors

Huang, Tianyang; Huang, Chiwu

doi:10.1007/s10209-019-00692-9

Cited by 10 publications

(11 citation statements)

References 51 publications

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“…Louie et al [43] reported that older people with a high level of education were more willing to interact with robots, which could have been because educated older adults had better recognition of the ability of SARs. Another study reported comparable findings that older adults with high education and medical backgrounds have more positive attitudes toward SARs [38].…”

Section: Technology Acceptance Eory Modelsmentioning

confidence: 68%

“…e need for SARs by older people was based on their health conditions, which should be considered in future research. Emotional companionship has also been reported to be an essential factor influencing robot acceptance [38,41]. Some participants raised ethical concerns [15,48].…”

Section: Discussionmentioning

confidence: 99%

“…ree explicit theoretical framework(s) were reported, including the Technology Acceptance Model (TAM) [24,35,39], UTAUT model [12,18,25,34,45], and Almere model [11,14,15,37,38,43].…”

Section: Technology Acceptance Eory Modelsmentioning

confidence: 99%

“…e willingness of older people to use robots was directly impacted by whether the features of robots met the needs of the people. e actual effect of SARs affects the willingness of older adults to use robots [18,31,38,41,46,48]. e elderly also emphasized the importance of risk prevention and healthcare applications, such as falls, safety detection of critical situations, and alarms when in danger [14].…”

Section: Concerns/problems Regarding Robotsmentioning

confidence: 99%

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Technology Acceptance in Socially Assistive Robots: Scoping Review of Models, Measurement, and Influencing Factors

Liu

2022

Journal of Healthcare Engineering

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Objectives. We summarized technology acceptance and the influencing factors of elderly people toward socially assistive robots (SARs). Methods. A scoping review whereby a literature search was conducted in Embase, Cochrane, Scopus, PubMed, and Web of Science databases (2006–2021) to retrieve studies. No restrictions on study methodology were imposed. Results. Out of the 1187 retrieved papers, 35 studies were finally included in the study. The articles covered various aspects, including general attitudes towards using SARs, technology acceptance theory models, and factors associated with technology acceptance. Twelve studies reported a positive attitude towards SARs. Three explicit theoretical frameworks were reported. Studies involving the elderly reported three themes that influence attitudes towards SARs: individual characteristics, concerns/problems regarding robots, and social factors. Conclusions. This review elucidates on the suitability of theory-based framework as applied to acceptance of SARs. We found that research on technology acceptance with regard to SARs is still in the developmental stages, and further studies of assessment tools for SARs are required. It is also essential to consider the factors that influence the acceptance of SARs by older people to ensure that they meet the end goal requirements of the user.

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Section: Technology Acceptance Eory Modelsmentioning

confidence: 68%

Section: Discussionmentioning

confidence: 99%

“…ree explicit theoretical framework(s) were reported, including the Technology Acceptance Model (TAM) [24,35,39], UTAUT model [12,18,25,34,45], and Almere model [11,14,15,37,38,43].…”

Section: Technology Acceptance Eory Modelsmentioning

confidence: 99%

Section: Concerns/problems Regarding Robotsmentioning

confidence: 99%

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Technology Acceptance in Socially Assistive Robots: Scoping Review of Models, Measurement, and Influencing Factors

Liu

2022

Journal of Healthcare Engineering

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“…The UTAUT Model adopted in this study is the acceptance and evaluation tool widely used in the application of science and technology to the users, and the calculation method and evaluation data adopted in this study are in accordance with the standard framework of UTAUT Model [45,46], and there is no difference. The UTAUT Model used in this study is only adjusted according to the elements of the structure, and uses the experimental procedures and methods set by the previous researchers [47,48]. The sample population of the experts and the elderly are required to master the reliability and validity to improve the performance of the study.…”

Section: Methodsmentioning

confidence: 99%

Acceptance and Influencing Factors of Social Virtual Reality in the Urban Elderly

Shao

Lee

2020

Sustainability

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In the stage of aging society and population aging, the social needs of the elderly are widely discussed by researchers. Especially driven by the demand of tele-medical treatment and tele-rehabilitation therapy, it is vital for the elderly to integrate into virtual communities by combining social virtual reality (VR) with different medical services and entertainment needs. In addition, affected by the COVID-19 epidemic, it is more difficult for people to have face-to-face contacts. With more remote consultation, entertainment and virtual social connectivity, the application of social VR is more urgent and valuable. However, there is little discussion on the acceptability and influencing factors of social VR among the elderly at present. Therefore, in order to get further data, we used (1) early stage semi-structured interviews and then (2) Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaires for investigation. One hundred fourteen elderly people aged 60–89 living in the metropolitan area of Taipei were taken as the subjects. To help them understand the situation and state of using social VR, these elderly people were asked to use a head-mounted display (HMD) to experience social VR games. The preliminary results showed that the elderly had obvious preference for entertainment (32.4%) and medical treatment (31.3%). The interview showed that this was related to the physiological condition or medical needs of the age range. In order to further understand how social VR would affect the social life of the elderly, we proposed the further demand structure of UTAUT Model based on the interview of both experts and the elderly. The model structures include (1) Performance Expectancy, (2) Perceived Enjoyment, (3) Social Influence, (4) User Attitude, (5) Behavioral Intention, and so on. These structures were applied to conduct interviews and questionnaires to find out the influence extent and relevance of the elderly on different structural needs, and suggestions were given accordingly. The results of the above interviews showed that (1) the elderly thought that the functions of entertaining and interacting of social VR could increase their social opportunities, and also meet medical needs (teleconference, cognitive decline, etc.), (2) the closeness of social relations (between family members, friends, doctors, and places), and also affect the relevance of Perceived Enjoyment (β = 0.77, p = 0.000 < 0.05). The results of these phenomena and interviews showed the interplay between the demand structures and their special relevance. They also indicated that as to social VR technologies, various demands and functional issues of the elderly need to be considered, and these demands would appear in the subtle usage, and different social VR interfaces and functions would emerge based on their special living ways and physical and psychological demands.

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What to Do Next? An Activity Scheduling Schema for Social Assistance Robots for Older Adults

Gollasch

Weber

2023

Lecture Notes in Computer Science

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Elderly’s acceptance of companion robots from the perspective of user factors

Cited by 10 publications

References 51 publications

Technology Acceptance in Socially Assistive Robots: Scoping Review of Models, Measurement, and Influencing Factors

Technology Acceptance in Socially Assistive Robots: Scoping Review of Models, Measurement, and Influencing Factors

Acceptance and Influencing Factors of Social Virtual Reality in the Urban Elderly

What to Do Next? An Activity Scheduling Schema for Social Assistance Robots for Older Adults

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