Tailored Domestic Social Robots and Monitoring Tech for Older Adults, Considering Socioeconomic Factors and Motor Challenges (78666)
Session Chair: Roberto Vagnetti
Wednesday, 27 March 2024 17:20
Session: Session 5
Room: Room 604
Presentation Type: Oral Presentation
Population aging carries profound implications for the economy and society, particularly in the decline of Activities of Daily Living (ADLs) among those with low socio-economic backgrounds and motor impairments. Social Assistive Robots (SARs) and monitoring technologies offer promise in enhancing the well-being of older adults by assisting with ADLs at home and monitoring ongoing activities. This mixed-method study involved 31 older adults, divided into low socio-economic, motor-impaired, and control groups. Through four focus groups, participants shared how technologies could support ADLs at home. Transcripts underwent thematic analysis. Participants also completed the 12-Item Short Form Health Survey and the Multi-dimensional Robot Attitude Scale to assess attitudes toward SARs and their association with well-being. Thematic analysis revealed specific needs across groups. The low-socioeconomic group expressed heightened concerns, while the motor-impaired group exhibited enthusiasm and interest in applications. Physical well-being correlated with familiarity (r= -.41, p= .02), interest (r= -.38, p= .03), perceived utility (r= -.59, p<.01), and control (r= -.56, p<.01), while psychological well-being linked to the need for variety (r= .55, p< .01) and a negative attitude toward SARs (r= -.40, p=.02). Significant group differences emerged in attitudes toward SARs in terms of Familiarity (ꭓ2(2)= 10.77, p < .01), Interest (ꭓ2(2)= 11.96, p < .01), Utility (ꭓ2(2)= 14.48, p < .01), and Control (ꭓ2(2)= 13.19, p < .01). Older adults perceive SARs and monitoring technologies as crucial for ADLs at home. Socio-economic status and motor limitations significantly influence acceptance, highlighting the importance of considering diverse needs and circumstances for effective implementation.
Authors:
Roberto Vagnetti, Nottingham Trent University, United Kingdom
Nicola Camp, Nottingham Trent University, United Kingdom
Matthew Story, Sheffield Hallam University, United Kingdom
Khaoula Ait-Belaid, Loughborough University, United Kingdom
Daniele Magistro, Nottingham Trent University, United Kingdom
About the Presenter(s)
Dr Roberto Vagnetti is a University Postdoctoral Fellow or Instructor at Nottingham Trent University in United Kingdom
See this presentation on the full schedule – Wednesday Schedule
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