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https://rda.sliit.lk/handle/123456789/497
Title: | Improved robot attitudes and emotions at a retirement home after meeting a robot |
Authors: | Stafford, R. Q Broadbent, E Jayawardena, C Unger, U Kuo, I. H Igic, A Wong, R Kerse, N Watson, C MacDonald, B. A |
Keywords: | Robot sensing systems Retirement Particle measurements Atmospheric measurements Medical services Education |
Issue Date: | 13-Sep-2010 |
Publisher: | IEEE |
Citation: | Cited by 94 |
Series/Report no.: | 19th international symposium in robot and human interactive communication;Pages 82-87 |
Abstract: | This study investigated whether attitudes and emotions towards robots predicted acceptance of a healthcare robot in a retirement village population. Residents (n = 32) and staff (n = 21) at a retirement village interacted with a robot for approximately 30 minutes. Prior to meeting the robot, participants had their heart rate and blood pressure measured. The robot greeted the participants, assisted them in taking their vital signs, performed a hydration reminder, told a joke, played a music video, and asked some questions about falls and medication management. Participants were given two questionnaires; one before and one after interacting with the robot. Measures included in both questionnaires were the Robot Attitude Scale (RAS) and the Positive and Negative Affect Schedule (PANAS). After using the robot, participants rated the overall quality of the robot interaction. Both residents and staff reported more favourable attitudes (p <; .05) and decreases in negative affect (p <; .05) towards the robot after meeting it, compared with before meeting it. Pre-interaction emotions and robot attitudes, combined with post-interaction changes in emotions and robot attitudes, were highly predictive of participants' robot evaluations (R = .88, p <; .05). The results suggest both pre-interaction emotions and attitudes towards robots, as well as experience with the robot, are important areas to monitor and address in influencing acceptance of healthcare robots in retirement village residents and staff. The results support an active cognition model that incorporates a feedback loop based on re-evaluation after experience. |
URI: | http://localhost:80/handle/123456789/497 |
ISSN: | 1944-9437 |
Appears in Collections: | Research Papers - SLIIT Staff Publications Research Publications -Dept of Information Technology |
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