期刊
COMPUTERS IN HUMAN BEHAVIOR
卷 128, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chb.2021.107128
关键词
Human-robot interaction; Best-worst scaling; Healthcare; Anthropomorphism; Design features
资金
- German Federal Ministry of Education and Research (BMBF) [16SV8436]
The application of lifelike design features to promote acceptance and use of social robots has been established as a promising design principle. Research shows that communication is the key determinant of robot preference, with an overall preference for anthropomorphic features and matched features leading to improved ratings. Findings from an online survey with two different samples can serve as a basis for the implementation of concrete design principles for social robotics in healthcare.
To promote acceptance and use of social robots, the application of lifelike design features has been established as a promising design principle. The majority of research to date emphasizes a high degree of anthropomorphism with respect to robot appearance and communication to support positive perceptions of robots. However, these features are often examined separately. As a result, there has been little evidence of possible interaction effects when implementing different design principles with a particular focus on matched features. An online survey with two different samples (sample 1: random; sample 2: healthcare professionals and trainees) is reported that investigate whether certain feature combinations are preferred for care robots. The attributes appearance (human-like, animal-like, technical), size (small, large), and communication (speech, sound, text) were combined. Results suggest that communication is the key determinant of robot preference. With regard to feature combinations the survey showed an overall preference for anthropomorphic features. Furthermore, the occurrence of matched features led to an additional improvement of preference ratings. Both samples provide similar results with high correlations. The obtained findings can therefore serve as a basis for the implementation of concrete design principles for social robotics in healthcare.
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