Evidence map›Paper›PMID 42840137›Full record

ReviewFrontiers in psychology2026

From digital companionship to capability building: reframing conversational artificial intelligence and older adults' psychological wellbeing in active aging.

Chong Zhou, Hongyu Wu, Gaohang Li, Yuanxin Chen

Abstract readReview
In one paragraph

Review in Frontiers in psychology, 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

4 authors.

Chong Zhou *Economy & Management School, Wuhan Sports University, Wuhan, China.
Hongyu Wu *Economy & Management School, Wuhan Sports University, Wuhan, China.
Gaohang LiPhysical Education and Sports College, Central China Normal University, Wuhan, China.
Yuanxin ChenEconomy & Management School, Wuhan Sports University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid diffusion of conversational artificial intelligence (AI) has reshaped the landscape of digital interaction in later life, with growing attention to its implications for older adults' mental health and wellbeing. Existing research has predominantly interpreted conversational AI through the lens of digital companionship, emphasizing its capacity to simulate social presence, reduce loneliness, and provide emotional support. While this perspective captures important affective outcomes, it offers a limited account of the developmental processes through which AI engagement may influence psychological wellbeing in aging populations. This conceptual analysis proposes a shift from a companionship-oriented paradigm to a capability-building perspective grounded in the Capability Approach. It argues that the primary value of conversational AI lies not in its ability to substitute social interaction, but in its potential to expand older adults' cognitive, emotional, social, and digital capabilities. Building on this argument, this paper develops an AI-Augmented Active Aging Framework that explains how conversational AI affordances, responsiveness, personalization, accessibility, and availability, interact with personal, social, environmental, and system-level conversion factors. Under supportive conditions, these affordances may facilitate cognitive, emotional, social, and digital capability formation, thereby supporting autonomy, competence, social integration, and active aging. Under adverse conditions, however, conversational AI may contribute to capability erosion through over-reliance, cognitive offloading, reduced human contact, or diminished autonomous judgment. The framework therefore emphasizes heterogeneous and conditional outcomes rather than assuming uniform benefits across older adults.

Indexed as

active agingconversational artificial intelligencedigital companionshiphuman-AI interactionolder adultspsychological wellbeing

Identifiers

PMID42840137
PMCPMC13638658

What OpenQuestion holds

Textmetadata
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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.