Evidence map›Paper›PMID 36416885›Full record

ArticleJMIR aging2022

The Factors Influencing Older Adults' Decisions Surrounding Adoption of Technology: Quantitative Experimental Study.

Jerad Moxley, Joseph Sharit, Sara J Czaja

Abstract read
In one paragraph

Article in JMIR aging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

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  9. Beyond the Digital Divide: Factors Associated With Adoption of Technologies Related to Aging in Place.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2025
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  13. Enabling Older Adults to Provide High-quality Activity Labels: Unpacking Accuracy, Precision, and Granularity in Activity Labeling.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2025
    Article
  14. Article
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  16. A Tablet-Based Application to Enhance Social Connectedness for Individuals With a Cognitive Impairment: Results From the PRISM-CI Pilot Study.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jerad Moxley *Division of Geriatrics and Palliative Medicine, Center on Aging and Behavioral Research, Weill Cornell Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0002-4362-9963
Joseph SharitDepartment of Industrial and Systems Engineering, University of Miami, Miami, FL, United States.ORCID https://orcid.org/0000-0001-9549-7109
Sara J CzajaDivision of Geriatrics and Palliative Medicine, Center on Aging and Behavioral Research, Weill Cornell Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0002-8096-5413

Funding

Understanding Issues Surrounding Technology Uptake and the Influence of Technology and Decision Making in Older AdultsP01AG017211 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI CZAJA, SARA J · 1999 to 2019
$26.6M
NIA NIH HHS P01 AG017211
6 · The paper itself

Abstract

backgroundThe rapid diffusion of technology apps may support older adults' independence and improve the quality of their lives. Models for predicting technology acceptance in older adults are sparse, based on broad questions related to general technology acceptance, and largely not grounded in theories of aging.

objectiveThis study aimed to use a mixed methods approach involving 5 technologies to comprehensively assess the causal relationships among factors that influence older adults' willingness to adopt the technologies.

methodsIn total, 187 men and women aged 65 to 92 years participated in the study. Participants were given presentations on 5 different technologies spanning domains that included transportation, leisure, health, and new learning and provided ratings of each technology on various measures hypothesized to influence adoption. They were also administered other instruments to collect data on their actual and self-assessed cognitive abilities, rates of discounting of the technologies with respect to willingness to invest time to attain higher skills in the technologies, general technology experience, and attitudes toward technology. We used the machine learning technique of k-fold cross-validated regressions to select variables that predicted participants' willingness to adopt the technologies.

resultsWillingness to adopt technologies was most impacted by 3 variables: perceived value of the technologies (β=.54), perceived improvement in quality of life attainable from the technologies (β=.24), and confidence in being able to use the technologies (β=.15). These variables, in turn, were mostly facilitated or inhibited by the perceived effort required to learn to use the technologies, a positive attitude toward technology as reflected in the optimism component of the technology readiness scale, the degree to which technologies were discounted, and the perceived help needed to learn to use the technologies.

conclusionsOur findings demonstrate that participants' willingness to adopt technologies is mainly determined by perceptions of 3 aspects of the technologies; these aspects possibly mediate many relationships with willingness to adopt. We discuss the implications of these findings for the design and marketing of technology products for older consumers.

Indexed as

adoptadoptionagingapplicationcognitioncognitiveconsumerdesignhealthindependencelearningleisuremarketingmobile phoneolder adultrelationshiptechnologytransportationwillingness

Identifiers

PMID36416885
PMCPMC9730211

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.