Evidence map›Paper›PMID 41315393›Full record

ArticleScientific reports2025

Matching embodied conversational agent appearance to message emotion enhances persuasion in eHealth.

Chengkun Tang, Li Wang, Duanwei Pan, Hui Zhang, Ying Fang

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

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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

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.

Chengkun TangCollege of Humanities, Donghua University, Shanghai, China.
Li WangSchool of Journalism, Communication University of China, Beijing, China.
Duanwei PanThe School of Basic Education, Shanghai Institute of Visual Arts, Shanghai, China. 87194931@qq.com.
Hui ZhangDepartment of Physical Education, Donghua University, Shanghai, China.
Ying FangCollege of Humanities and Social Sciences, University of Science and Technology of China, Hefei, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examines how matching Embodied Conversational Agents' (ECAs) appearance to message emotional tone enhances eHealth persuasion through the lens of Elaboration Likelihood Model (ELM) and Social Cues Theory. Using Event-Related Potential (ERP) measurements with 42 participants, we found professional ECAs delivering neutral messages elicited neural signatures of reduced cognitive conflict (smaller N400) and increased attention (larger LPP), demonstrating central route processing through credible source cues. Conversely, positive messages paired with casual appearances leveraged peripheral route persuasion via social rapport. Behavioral data confirmed these patterns, showing highest persuasion when professional appearance aligned with neutral tone - a congruence effect explained by both theories. Results provide actionable insights for designing persuasive ECAs in healthcare contexts by strategically combining visual and textual cues to optimize either credibility or approachability based on communication goals. The integration of neural and behavioral measures offers novel evidence for how multimodal cue matching operates in digital health interventions.

Indexed as

EmotionsPersuasive CommunicationTelemedicineAdultCommunicationCuesEvoked PotentialsFemaleHumansMaleYoung AdultElaboration likelihood model (ELM)Embodied conversational agent (ECA)Event-related potential (ERP)Healthcare communicationSocial cues theory

Identifiers

PMID41315393
PMCPMC12663181

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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.