Evidence map›Paper›PMID 36799089›Full record

ArticleJournal of applied gerontology : the official journal of the Southern Gerontological Society2023

Artificial Intelligence in Long-Term Care: Technological Promise, Aging Anxieties, and Sociotechnical Ageism.

Barbara Barbosa Neves, Alan Petersen, Mor Vered, Adrian Carter, Maho Omori

Open access · hybridAbstract read
In one paragraph

Article in Journal of applied gerontology : the official journal of the Southern Gerontological Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
40.0field-weighted citation impact, top 1% of its field
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

11 citing papers in PubMed, 46 citations in OpenAlex.

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  7. HCI and Older Adults: The Critical Turn and What Comes Next.Foundations and trends in human computer interaction · 2025
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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

5 authors at 2 institutions in 1 country.

Barbara Barbosa NevesSociology, School of Social Sciences, Faculty of Arts, Monash University, Clayton, VIC, Australia.ORCID 0000-0002-4490-4322
Alan PetersenSociology, School of Social Sciences, Faculty of Arts, Monash University, Clayton, VIC, Australia.
Mor VeredDepartment of Data Science and AI, Faculty of Information Technology, Monash University, Clayton, VIC, Australia.ORCID 0000-0001-5286-6509
Adrian CarterSchool of Psychological Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC, Australia.
Maho OmoriDepartment of Data and Design, Victoria Police, Melbourne, VIC, Australia.
Monash University · AUVictoria Police · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article explores views about older people and aging underpinning practices and perceptions of development and implementation of Artificial Intelligence (AI) in long-term care homes (LTC). Drawing on semi-structured interviews with seven AI developers, seven LTC staff, and four LTC advocates, we analyzed how AI technologies for later life are imagined, designed, deployed, and resisted. Using the concepts of "promissory discourse" and "aging anxieties", we investigated manifestations of ageism in accounts of AI applications in LTC. Despite positive intentions, both AI developers and LTC staff/advocates engaged in simplistic scripts about aging, care, and the technological capacity of older people. We further uncovered what we termed

Indexed as

AgeismLong-Term CareAgedAgingAnxietyArtificial IntelligenceHumansageismalgorithmic biasdigital ageismnursing homesolder peopletechnologytechno-solutionism

Identifiers

PMID36799089
PMCPMC10201070
OpenAlexW4321165272

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.