Evidence map›Paper›PMID 42780716›Full record

ArticleFrontiers in public health2026

Trusting and staying with AI doctors: cognitive and emotional pathways driving continuance intention toward AI healthcare chatbots.

Zhanyou Wang, Haoran Han, Dongmei Han, Liang Ma, Feifei Hao

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
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.

Zhanyou WangSchool of Business Administration, Shandong Management University, Jinan, China.
Haoran HanSchool of Business Administration, Shandong Management University, Jinan, China.
Dongmei HanSchool of Information Engineering, Shandong Management University, Jinan, China.
Liang MaSchool of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, China.
Feifei HaoCollege of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: AI-powered medical chatbots are increasingly used in healthcare, yet the mechanisms underlying users' continued engagement remain unclear. This study examines how AI use influences continuance intention through cognitive trust and emotional attachment and whether technology anxiety differentially moderates these pathways. Methods: Data were collected from 233 users of AI medical services in China. The proposed model was tested using partial least squares structural equation modeling (PLS-SEM) and bootstrapping in SmartPLS 4.0. Results: AI use positively influences both cognitive trust and emotional attachment, which in turn enhance continuance intention. Both mechanisms significantly mediate the relationship between AI use and continuance intention, with emotional attachment showing a stronger mediating effect. Technology anxiety significantly moderates the AI use-cognitive trust relationship but not the AI use-emotional attachment relationship, revealing an asymmetric moderating pattern. Discussion: This study extends cognitive-affective processing theory by revealing dual cognitive and emotional pathways linking AI use to continuance intention. It further identifies technology anxiety as a boundary condition that selectively shapes the cognitive pathway while leaving the emotional pathway relatively unaffected. The findings offer implications for designing anxiety-sensitive AI healthcare services and differentiated user engagement strategies.

Indexed as

Artificial IntelligenceCognitionEmotionsIntentionPhysician-Patient RelationsTrustAdultAnxietyChinaFemaleHumansMaleMiddle AgedAI doctor usecognitive trustcontinuance intentionemotional attachmenttechnology anxiety

Identifiers

PMID42780716
PMCPMC13597734

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.