Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Aug 14, 2024
Open Peer Review Period: Aug 16, 2024 - Oct 11, 2024
Date Accepted: Feb 25, 2025
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Understanding Acceptance of Healthcare Technology Among Older Adults Through TAM and UTAUT: Systematic Review and Meta-Analysis
ABSTRACT
Background:
To understand the acceptance of healthcare technology for older adults, the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) is commonly used. However, the divergence in the current literature makes it difficult to predict acceptance and understand how various factors affect older adults’ behavior.
Objective:
This study aims to 1) determine the influence of perceived usefulness (PU), perceived ease of use (PEOU), and social influence (SI) on the behavioral intention (BI) to use healthcare technology among older adults and 2) and assess the moderating effects of age, gender, geographic region, type of healthcare technology, and the presence of visual demonstrations on these three pairwise relationships.
Methods:
Google Scholar, Web of Science, Scopus, IEEE Xplore, and ProQuest electronic databases were searched from inception to February 2024. Two independent reviewers screened the titles, abstracts, full texts, and performed data extraction and risk of bias assessments with the Newcastle-Ottawa Quality Assessment Scale. The "meta" package in R was used for data synthesis, conducting random-effects meta-analyses, meta-regression and subgroup analysis.
Results:
41 studies with a total of 11,574 participants were included. Random-effects meta-analyses showed significant positive correlations for PU-BI (r = 0.607, 95% CI 0.543 - 0.665, P < .001), PEOU-BI (r = 0.525, 95% CI 0.462 - 0.583, P < .001), and SI-BI (r = 0.551, 95% CI 0.468 - 0.624, P < .001). Moderator analyses indicated significant differences in effect sizes based on geographic region for PEOU-BI (Q-test, P = .04), type of technology for PU-BI (Q-test, P = .04) and SI-BI (Q-test, P = .002), and presence of visual demonstrations for PU-BI (Q-test, P = .03) and SI-BI (Q-test, P = .04).
Conclusions:
The findings indicate that PU, PEOU, SI significantly impact the acceptance of healthcare technology among older adults, with heterogeneity influenced by geographic region, type of technology, and presence of visual demonstrations. Researchers should account for these variables when interpreting previous research and embarking on new studies with the TAM or UTAUT model for older adults. Clinical Trial: Current paper is not RCT
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