Evidence map›Paper›PMID 42054346›Full record

ArticlePloS one2026

Exploring the association between personality and attitudes towards ageing in UK and Canadian older adults': Use of a novel Behavioural Artificial Intelligence solution.

Stuart W Flint, Eva Klein, Leonard Waverman, Ezra Goldberg, Mohammad Kaykanloo, Hager Ghouma, Stuart Sherman

Abstract read
In one paragraph

Article in PloS one, 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
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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

7 authors.

Stuart W FlintSchool of Psychology, University of Leeds, Leeds, United Kingdom.ORCID https://orcid.org/0000-0003-4878-3019
Eva KleinDeGroote School of Business, McMaster University, Ontario, Canada.
Leonard WavermanDeGroote School of Business, McMaster University, Ontario, Canada.
Ezra GoldbergScaled Insights, Nexus, University of Leeds, Leeds, United Kingdom.
Mohammad KaykanlooScaled Insights, Nexus, University of Leeds, Leeds, United Kingdom.
Hager GhoumaScaled Insights, Nexus, University of Leeds, Leeds, United Kingdom.
Stuart ShermanScaled Insights, Nexus, University of Leeds, Leeds, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Perceptions of ageing is an important psychosocial factor that influences health, wellbeing as well as engagement in health- promoting behaviours as people age. This study used a novel Behavioural Artificial Intelligence (AI) solution to examine the association between personality and attitudes towards ageing, and to explore how perceptions of ageing impact health promoting behaviours in UK and Canadian adults. Using a cross-sectional online survey methodology, 1011 UK and 1023 Canadian adults aged 65 years and older were recruited. Participants completed the attitudes towards ageing questionnaire short form and responded to 5 open-ended questions relating to their perceptions of ageing. Natural language computed in the open-ended responses was analysed using Scaled Insights Behavioural AI solution to examine personality attributes associated with attitudes towards ageing. Thematic analysis was also conducted to explore themes that emerged in the participants responses to the open-ended questions. Two personality clusters were identified that were associated with attitudes towards ageing.: Optimistic Ageing and Pessimistic Ageing. The Optimistic Ageing personality cluster had significantly more positive attitudes towards ageing; i.e., towards physical change, and psychosocial loss. Six significant themes emerged relating to participants perceptions of ageing, between those in the Optimistic Ageing and Pessimistic Ageing personality clusters; 1) attitudes towards physical activity and health, 2) mental and emotional health, 3) social connections and relationships, 4) independence and autonomy, 5) attitudes towards ageing and mortality, and 6) experiences of ageism. The findings highlight the important role of personality in attitudes towards ageing and the need for psychologists and other interventionists to consider personality in addressing negative attitudes towards ageing as well as actions to promote healthy behaviour. The novel Behavioural AI solution employed in this study, highlights the potential value of understanding personality both in predicting attitudes towards ageing but also in designing interventions and communications that are more personalised and target older adults based on their personality attributes.

Indexed as

AgingArtificial IntelligenceAttitudeAttitude to HealthPersonalityAgedAged, 80 and overCanadaCross-Sectional StudiesFemaleHumansMaleSurveys and QuestionnairesUnited Kingdom

Identifiers

PMID42054346
PMCPMC13127943

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.