Exploring predictors of technology adoption among older adults
Date
Authors
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Altmetrics
Authors
Research Projects
Organizational Units
The Department of Human Development and Family Studies focuses on the interactions among individuals, families, and their resources and environments throughout their lifespans. It consists of three majors: Child, Adult, and Family Services (preparing students to work for agencies serving children, youth, adults, and families); Family Finance, Housing, and Policy (preparing students for work as financial counselors, insurance agents, loan-officers, lobbyists, policy experts, etc); and Early Childhood Education (preparing students to teach and work with young children and their families).
History
The Department of Human Development and Family Studies was formed in 1991 from the merger of the Department of Family Environment and the Department of Child Development.
Dates of Existence
1991-present
Related Units
- College of Human Sciences (parent college)
- Department of Child Development (predecessor)
- Department of Family Environment (predecessor)
Journal Issue
Is Version Of
Versions
Series
Department
Abstract
The purpose of this study was to investigate predictors of older adult technology adoption through a mixed methods perspective. One hundred and seventy-six older adults responded to a quantitative survey assessing their technology adoption. Four participants were selected for qualitative interviews. The mean age of participants was 74.71 years old that included an age range of 65-96 year old participants. The majority of older adults lived independently, and no participants lived in care facilities. In the quantitative phase, structural equation modeling in Mplus was used to evaluate the fit of a technology adoption model using personality, self-efficacy, perceptions of technology, and attitudes of technology as predictors. Noteworthy findings indicated the model showed a good fit predicting technology adoption. Education, perceived usefulness, and attitudes toward using technology were positively associated with technology adoption. Participant age was negatively associated with technology adoption, indicating younger older adults were significantly more likely to adopt technology. Greater levels of agreeableness predicted greater levels of perceived usefulness and self-efficacy. Additionally, a significant indirect effect was obtained from perceived usefulness via attitudes toward using technology to technology adoption. This finding indicated that greater levels of perceived usefulness influenced more positive attitudes toward technology which in turn predicted greater levels of technology adoption. The qualitative phase indicated three themes specifically highlighting the importance of 1) earlier life experiences (e.g., workplace experiences), 2) personal preferences (e.g., choices regarding keeping up with technology), and 3) societal perspectives (e.g., concern for human interaction) on technology adoption. A revised theoretical model of technology adoption is suggested, tying together the quantitative and qualitative findings of this research study. Lastly, future research should consider implementing lifelong learning opportunities teaching older adults the usefulness of technology and giving them a chance to interact with technology in a supportive environment.