Evidence map›Paper›PMID 41967012›Full record

ArticleThe journals of gerontology. Series B, Psychological sciences and social sciences2026

Characterizing middle-aged and older adults' perceptions of the cultural sensitivity and quality of generative artificial intelligence-authored text messages to promote physical activity.

Allyson Tabaczynski, Yingjia Liu, Saeed Abdullah, Lizbeth Benson, David E Conroy

Abstract read
In one paragraph

Article in The journals of gerontology. Series B, Psychological sciences and social sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Allyson TabaczynskiSchool of Kinesiology, University of Michigan, Ann Arbor, Michigan, United States.ORCID 0000-0003-2209-5103
Yingjia LiuSchool of Kinesiology, University of Michigan, Ann Arbor, Michigan, United States.ORCID 0009-0001-6515-7936
Saeed AbdullahCollege of Information Sciences and Technology, The Pennsylvania State University, University Park, Pennsylvania, United States.
Lizbeth BensonInstitute for Social Research, University of Michigan, Ann Arbor, Michigan, United States.
David E ConroySchool of Kinesiology, University of Michigan, Ann Arbor, Michigan, United States.

Funding

Roybal Center for Promoting Adherence to Behavior Change and Enhancing Cognitive FunctionP30AG086637 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DAVID E. CONROY · 2024 to 2026
$2.9M
National Institute on Aging of the National Institutes of Health P30AG086637NIA NIH HHS P30 AG086637University of Michigan Roybal Center for Promoting Adherence to Behavior Change and Enhancing Cognitive Function
6 · The paper itself

Abstract

objectivesGenerative artificial intelligence (GenAI) could be used to write text message content in physical activity behavior change interventions for middle-aged and older adults. Yet, biases in GenAI systems could lead to culturally insensitive or low-quality messages. Evaluating the acceptability of GenAI-authored messages is crucial before use in interventions. This research examined middle-aged and older adults' perceptions of the cultural sensitivity and quality of GenAI-authored messages for promoting physical activity, and the person- and message-level factors influencing these perceptions.

methodsIn a cross-sectional survey, middle-aged and older adults (≥40 years of age; N = 630; mean age = 56.8 years; SD = 10.1) read 80 text messages written by GenAI and identified those that were culturally insensitive or had other problems. Descriptive statistics identified the proportion of GenAI-authored messages labeled as having issues. Separate negative binomial regressions examined the participant (zero-inflated) and message factors associated with message issues.

resultsOf 49,859 cultural sensitivity and 49,894 quality message ratings, only 4.9% and 6.1% of the messages, respectively, were labeled as having issues. Knowledge of AI-authorship and more favorable attitudes toward AI were associated with identifying more messages as culturally insensitive. Messages generated by prompts that targeted sitting less (compared to moving more) or that described preparing for activity (compared to performing physical activity) received more labels as containing quality issues. DISCUSSION: GenAI can be prompted to write high-quality, culturally sensitive text messages for promoting physical activity for middle-aged and older adults. Message content and participants' knowledge of AI use could influence perceptions.

Indexed as

Cultural CompetencyExerciseGenerative Artificial IntelligenceHealth PromotionText MessagingAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedAcceptabilityDigital interventionHealth behavior changeLarge language modelText message intervention

Identifiers

PMID41967012
PMCPMC13134737

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.