Evidence mapPaperPMID 42145488Full record

ArticleFrontiers in public health2026

Aging with AI companionship: the role of artificial intelligence in enhancing the mental wellbeing of older adults.

Yonggang Wang, Huanchen Tang, Jingchun Zhang, Yubo Wang, Xiaodong Liu

Abstract read
In one paragraph

Article in Frontiers in public health, 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
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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

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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

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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.

Yonggang Wang *College of Fashion and Design, Donghua University, Shanghai, China.
Huanchen Tang *College of Fashion and Design, Donghua University, Shanghai, China.
Jingchun ZhangCollege of Fashion and Design, Donghua University, Shanghai, China.
Yubo WangCollege of Fashion and Design, Donghua University, Shanghai, China.
Xiaodong LiuCollege of Fashion and Design, Donghua University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: With the intensification of global population aging, mental health problems among older adults have become increasingly prominent. As an important innovative approach in smart eldercare, artificial intelligence (AI) has been gradually applied to older populations due to its advantages in emotional support, cognitive stimulation, and social interaction. However, there is still a lack of systematic empirical evidence regarding the mechanisms through which AI affects older adults' mental wellbeing. Methods: Drawing on Self-Determination Theory and the Technology Acceptance Model, this study constructs a five-dimensional analytical framework consisting of autonomy, perceived ease of use, perceived usefulness, competence, and relatedness, and combines structural equation modeling (SEM) with fuzzy-set qualitative comparative analysis (fsQCA). Using survey data from 418 Chinese older adults aged 60 and above, we systematically explore the pathways through which AI influences their mental wellbeing. Results: The findings indicate that autonomy exerts the most significant positive effect on older adults' mental wellbeing, while perceived ease of use, perceived usefulness, competence, and relatedness also have positive impacts. Discussion: By granting older adults greater choice and decision-making power, AI enhances their sense of control over life and self-efficacy, thereby effectively promoting mental wellbeing. At the same time, the ease of use and practicality of AI technologies lower the threshold for adoption, increasing older adults' intention to use and satisfaction. Furthermore, AI supports cognitive training, health management, and emotional communication, helping older adults maintain cognitive vitality, strengthen self-care abilities, and receive emotional support and social connection, which in turn further enhance their sense of wellbeing and quality of life. This study not only enriches the theoretical foundation of research on AI and mental wellbeing among older adults, but also provides empirical evidence for the optimization, design, and promotion of related technologies.

Indexed as

AgingArtificial IntelligenceMental HealthAgedAged, 80 and overChinaFemaleHumansMaleMiddle AgedPersonal AutonomyPsychological Well-BeingSelf EfficacySurveys and Questionnairesartificial intelligencemental wellbeingolder adultsself-determination theorytechnology acceptance model

Identifiers

PMID42145488
PMCPMC13176159

What Socratic holds

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LicenceCC BY
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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 Socratic graph.