Background: With global aging, robots are considered a promising solution for handling the shortage of aged care and companionships. However, these technologies would serve little purpose if their intended users do not accept them. While the socioemotional selectivity theory predicts that older adults would accept robots that offer emotionally meaningful relationships, selective optimization with compensation model predicts that older adults would accept robots that compensate for their functional losses. Objective: The present study aims to understand older adults’ expectations for robots and to compare older adults’ acceptance ratings for 2 existing robots: one of them is a more human-like and more service-oriented robot and the other one is a more animal-like and more companion-oriented robot. Methods: A mixed methods study was conducted with 33 healthy, community-dwelling Taiwanese older adults (age range: 59–82 years). Participants first completed a semi-structured interview regarding their ideal robot. After receiving information about the 2 existing robots, they then completed the Unified Theory of Acceptance and Use of Technology questionnaires to report their pre-implementation acceptance of the 2 robots. Results: Interviews were transcribed for conventional content analysis with satisfactory inter-rater reliability. From the interview data, a collection of older adults’ ideal robot characteristics emerged with highlights of humanlike qualities. From the questionnaire data, respondents showed a higher level of acceptance toward the more service-oriented robot than the more companion-oriented robot in terms of attitude, perceived adaptiveness, and perceived usefulness. From the mixed methods analyses, the finding that older adults had a higher level of positive attitude towards the more service-oriented robot than the more companion-oriented robot was predicted by higher expectation or preference for robots with more service-related functions. Conclusion: This study identified older adults’ preference toward more functional and humanlike robots. Our findings provide practical suggestions for future robot designs that target the older population.
Most Chinese characters are compounds consisting of a semantic radical indicating semantic category and a phonetic radical cuing the pronunciation of the character. Controversy surrounds whether radicals also go through the same lexical processing as characters and, critically, whether phonetic radicals involve semantic activation since they can also be characters when standing alone. Here we examined these issues using the Stroop task whereby participants responded to the ink color of the character. The key finding was that Stroop effects were found when the character itself had a meaning unrelated to color, but contained a color name phonetic radical (e.g., “guess”, with the phonetic radical “cyan”, on the right) or had a meaning associated with color (e.g., “pity”, with the phonetic radical “blood” on the right which has a meaning related to “red”). Such Stroop effects from the phonetic radical within a character unrelated to color support that Chinese character recognition involves decomposition of characters into their constituent radicals; with each of their meanings including phonetic radicals activated independently, even though it would inevitably interfere with that of the whole character. Compared with the morphological decomposition in English whereby the semantics of the morphemes are not necessarily activated, the unavoidable semantic activation of phonetic radicals represents a unique feature in Chinese character processing.
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