Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 308

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Factors Predicting Decisions About Technology Adoption Among Older Adults

Open access
Berkowsky, Ronald W, Sharit, Joseph, Czaja, Sara J·2017·Innovation in Aging

Abstract

Background and Objectives: Numerous technology applications are available that have the potential to improve the quality of life (QoL) of older adults. However, older adults are less likely to adopt new and emerging technologies and reap the potential benefits. This study examines factors that influence older adults’ decisions about the adoption of new technology. Research Design and Methods: Fifty-two older adults participated in a mixed-method procedure, which entailed: (1) observing presentations detailing nine differing technologies, (2) assessing the technologies using tailored questionnaires, and (3) participating in focus group discussions. Participants were assigned into one of seven groups separated by age (65–74, 75+) and language (English, Spanish). The outcome was willingness to adopt technology. Predictors included self-assessed abilities (e.g., numeric ability), computer/Internet skills and knowledge, technology readiness, age, language, and technology ratings (e.g., perceived value). Analyses included Spearman’s ρ, t-tests, and regression analysis. Focus group discussions were examined for supportive examples. Results: Self-assessed abilities and computer/Internet skills were predictive of willingness to adopt technologies although the relationship varied according to the technology examined. Technology readiness, age, and language group showed weak associations with the outcome. Of the technology ratings, perceived value, confidence in ability to learn the technology, and the perceived impact on QoL were the most robust predictors of willingness to adopt technology. Discussion and Implications: Findings indicate that various stakeholders in technology adoption among older adults must be cognizant of a technology’s functionality and complexity as well as the characteristics and abilities of older adults. However, certain factors such as perceptions about the value of the technology and potential impact on QoL are also critically important to decisions regarding technology adoption among older people.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/geroni/igy002

Cites

39 of 39 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 39 references

Cited by

See all 308

Metadata

Authors
Berkowsky, R. W., Sharit, J., & Czaja, S. J.
Venue
Innovation in Aging
Published
2017-11-01
Volume
1
Issue
3
Pages
igy002-igy002
ISSN
2399-5300 (ISSN-L)
OpenAlex
W2791141718
Cited by
308
References
39
FWCI
25.03
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Factors Predicting Decisions About Technology Adoption Among Older Adults. https://app.cochat.ai/papers/10.1093/geroni/igy002
The paper
Berkowsky, R. W., Sharit, J., & Czaja, S. J. (2017). Factors Predicting Decisions About Technology Adoption Among Older Adults. Innovation in Aging. https://doi.org/10.1093/geroni/igy002

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.