Investigating socially assistive systems from system design and evaluation: a systematic review

Developing a model to explain users' ethical perceptions regarding the use of care robots in home care: A cross-sectional study in Ireland, Finland, and Japan

To date, research on ethical issues regarding care robots for older adults, family caregivers, and care workers has not progressed sufficiently. This study aimed to build a model that universally explains the relationship between the use of care robots and ethical awareness, such as regarding personal information and privacy protection in home care. We examined data obtained from cross-sectional surveys conducted in Japan (n=528), Ireland (n=296), and Finland (n=180). We performed a confirmatory factor analysis by using responses to 11 items related to the ethical use of care robots. We evaluated the model based on the chi-square to degrees of freedom ratio, the comparative fit index, and the root mean square error of approximation. Subsequently, we compared the model with the Akaike's information criterion. Ten items were adopted in the final model. There were 4 factors in the model: 'acquisition of personal information', 'use of personal information for medical and long-term care', 'secondary use of personal information', and 'participation in research and development'. All factor loadings of the final model ranged between 0.63 and 0.92, which were greater than 0.6, showing that the factors had a high influence on the model. The final model was applied to each country; the fit was relatively good in Finland and poor in Ireland. Although the three countries have different geographies, cultures, demographics, and systems, this study showed that the impact of ethical issues regarding the use of care robots in home care can be universally explained by the same model.

A Review of Data Gathering Methods for Evaluating Socially Assistive Systems

Social interactions significantly impact the quality of life for people with special needs (e.g., older adults with dementia and children with autism). They may suffer loneliness and social isolation more often than people without disabilities. There is a growing demand for technologies to satisfy the social needs of such user groups. However, evaluating these systems can be challenging due to the extra difficulty of gathering data from people with special needs (e.g., communication barriers involving older adults with dementia and children with autism). Thus, in this systematic review, we focus on studying data gathering methods for evaluating socially assistive systems (SAS). Six academic databases (i.e., Scopus, Web of Science, ACM, Science Direct, PubMed, and IEEE Xplore) were searched, covering articles published from January 2000 to July 2021. A total of 65 articles met the inclusion criteria for this systematic review. The results showed that existing SASs most often targeted people with visual impairments, older adults, and children with autism. For instance, a common type of SASs aimed to help blind people perceive social signals (e.g., facial expressions). SASs were most commonly assessed with interviews, questionnaires, and observation data. Around half of the interview studies only involved target users, while the other half also included secondary users or stakeholders. Questionnaires were mostly used with older adults and people with visual impairments to measure their social interaction, emotional state, and system usability. A great majority of observational studies were carried out with users in special age groups, especially older adults and children with autism. We thereby contribute an overview of how different data gathering methods were used with various target users of SASs. Relevant insights are extracted to inform future development and research.