Loading...
Acceptance of artificial intelligence among older adults
Hutton, Abbie M.
Hutton, Abbie M.
Citations
Altmetric:
Files
Loading...
Ph.D. thesis
Adobe PDF, 1.83 MB
Authors
Other Names
Location
Time Period
Advisors
Original Date
Digitization Date
Issue Date
2024-12
Type
Dissertation
Genre
Keywords
Subjects (LCSH)
Electronic dissertations
Citation
Abstract
Emerging technologies, such as artificial intelligence (AI), show promise in addressing the challenges of aging by promoting independence and well-being among older adults (Czaja & Ceruso, 2022; Padhan et al., 2023). These applications include health monitoring (Fear & Gleber, 2023; Iqbal, 2023; Shiwani et al., 2023), social interaction (Getson & Nejat, 2021; Padhan et al., 2023), cognitive stimulation (Gasteiger et al., 2021), and assistance with daily tasks (Padhan et al., 2023; Shandilya & Fan, 2022). Research on AI for older adults typically focuses on its application and development. However, despite the significance of acceptance, limited research exists regarding the aging community. Acceptance is crucial to identify adoption patterns and inform user-friendly designs. This dissertation strived to comprehensively investigate the acceptance of AI among older adults using quantitative and qualitative methods. A scoping review identified eight categories of potential factors of acceptance. Next, a focus group study tested these themes using more advanced AI and divided these themes into two categories (e.g., the individual and the system). Based on these findings, the Aging Acceptance Artificial Intelligence Model $(A_3IM; aim)$ was developed. The model included perceived ease of use, perceived usefulness, attitude toward intention to use, behavioral intention to use, actual use, perceived cognitive ability, perceived trust, perceived intelligence, perceived health benefit, environmental influence, perceived enjoyment, perceived social interaction, AI literacy, and AI anxiety. A Confirmatory Factor Analysis was used to validate the items, and Partial Least Squares Structural Equation Modeling was used to test the hypothesized relationships. Overall, $A_3IM$ is one of the few that comprehensively investigates the acceptance of AI among older adults. The continued validation of $A_3IM$ could have important implications for researchers investigating AI acceptance among older adults.
Table of Contents
Description
Thesis (Ph.D.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Psychology
Publisher
Wichita State University
Journal
Book Title
Series
Digital Collection
Finding Aid URL
Use and Reproduction
© Copyright 2024 by Abbie Hutton
All Rights Reserved