Files in this item



application/pdfBAYLES-THESIS-2021.pdf (5MB)Restricted to U of Illinois
(no description provided)PDF


Title:A holistic understanding of older adults' acceptance of domestic robots
Author(s):Bayles, Megan Ashley
Advisor(s):Rogers, Wendy A
Contributor(s):Mejia, Shannon; Hauser, Kris
Department / Program:Kinesiology & Community Health
Discipline:Community Health
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):older adults
domestic robots
aging in place
Abstract:The aging population is growing and as people age declines in their ability to perform everyday living activities can interfere with an older adult’s ability to age in place. Aging in place can allow older adults to keep their independence. However, declines can cause their everyday living tasks to become barriers. Domestic robots can be developed, integrated, and used by older adults to address these barriers. Before these technologies can be successfully integrated, users must be willing to accept and adopt domestic robots. Currently, the research in this field consistently finds discrepancies not only in the results of older adults’ preferences for robotic assistance but in how the relationship between these factors form to a conclusion. The robot appearance, the context of the interaction, and the user have all been investigated to further our knowledge in this area. However, these studies have yielded mixed results, leading to uncertainty when designing robots to support aging in place. Without consistency in this domain of research, the foundation of domestic robot design for older adults may promote robots that are unsuccessful. The complexity of human-robot interaction requires a research approach that can 1) understand the intricacies of older adults’ preferences for domestic robots, and 2) understand the whole picture of this decision-making process. To address the lack of consistency in the intricacies of older adults’ preferences in this study, we incorporated a variety of robots as well as a variety of tasks pertinent to aging in place. Further, we implemented a mixed method approach to understand potential changes in the decision-making process for an indication of method bias and/or participant inconsistency. We included six different robots varying in appearance to provide participants an understanding of the range of robot types. Further, we discussed three categories of everyday living activities that older adults engage in that the robots had potential to assist with. Finally, we investigated the older adults’ thoughts on the robots using three methods of testing: a survey, a structured interview, and a participatory design method called card sorting. Each method was chosen to supplement the weaknesses of the other two methods. Our evaluation of the older adults’ preferences of the six robots revealed that they were overwhelmingly open to robots helping with domestic activities. When the activities were divided into categories, we observed mixed preferences with little pattern to detect. Although there was one task category that had a clear indication of the favored robot generally, we found that predicting a preferred robot by older adults for a specific task would not be possible. Further, by mixing methods we were able to detect a potential for method bias in this context. We found not only a lack of corroboration between the different methods, but within a method as well. This study showed that the potential lack of corroborating findings through the literature could be the result of 1) fluid individual and group preferences when it comes to robot appearance, and 2) task or method bias. To address the first point, future research should be conducted to understand the fluid nature of older adults’ preferences for domestic robots, with the goal to understand the temporal precedence of task function and appearance. Further, to address the method bias, research should investigate reasons for within method bias and between method bias. Ultimately, determining an approach that can successfully aid in predicting acceptance of domestic robots to assist older adults aging in place. In addition to the methodological advancements from this research, the data provided valuable insights to guide robot design for older adults. By implementing multi-method studies, research can benefit by understanding where inconsistencies are when using quantified data but also why these inconsistencies are arising with qualitative data. Further, when testing one phenomenon, method bias can be seen when one method leads to divergent results from others.  
Issue Date:2021-04-23
Rights Information:Copyright 2021 Megan Bayles
Date Available in IDEALS:2021-09-17
Date Deposited:2021-05

This item appears in the following Collection(s)

Item Statistics