Predictors of Technology Use among Older Adults: Evidence Ranging from Non-Users to Elite Users

TitlePredictors of Technology Use among Older Adults: Evidence Ranging from Non-Users to Elite Users
Publication TypeThesis
Year of Publication2022
AuthorsWan, X
DegreePh.D.
UniversityUniversity of Central Florida
CityOrlando, FL
KeywordsCognition, Machine learning, socioeconomic, Technology
Abstract

Older adults tend to under-utilize digital technology and online services that can yield
substantial benefits to their health and wellbeing. Addressing this problem requires
determining robust and consistent predictors of older adults’ technology use. Also, few
studies have examined older adults who are elite users of digital technology, who may
provide insights into how individuals can prepare to become competent users of future
technologies as they age. To address these gaps in the technology and aging literature,
this dissertation offers (1) large-scale machine learning analyses, (2) longitudinal
perspectives, (3) age group comparisons across the adult life span, (4) the novel
recruitment of elite, older users of digital technology, and (5) the development and
validation of a technology use scale focused on current innovations. In Study 1, data from
the Health and Retirement Study were used. Machine learning classified Internet users
versus non-users with an accuracy of ~80%. Across a 14-year span, results largely
supported current models of aging and technology use. Age, cognition, and
socioeconomics emerged as the most robust and consistent predictors of Internet use from
competition with hundreds of variables. In Study 2, the outcome variable was expanded
to include nine domains of technology use. Elite, older users exhibited many markers of
successful aging, including higher levels of cognition, socioeconomics, and self-efficacy.
Across studies, results suggested that skills needed to engage with technology at a basic
level differ slightly from those needed to reach higher levels of technology use.
Specifically, poor episodic long-term memory may pose a barrier to basic technology use
among older adults (e.g., assessing the Internet), while better short-term memory is
required to achieve elite-level technology use. These results highlight the potential value
of exposure to new technology at a younger age – when there are fewer barriers of entry
(e.g., cognitive limitations) and a foundation of technology use principles can be
developed and built upon across adulthood.

URLhttps://stars.library.ucf.edu/cgi/viewcontent.cgi?article=2110&context=etd2020
Citation Key12436