Effective communication between patients and AI doctors: the role of the affection expression of AI doctors

Purpose The study aims to explore how the affection expression of AI doctors (language, voice, image) affects the effective communication between patients and AI doctors, thereby improving the acceptance of AI doctors by patients. Design/methodology/approach This study used a 2 × 2 × 2 experimental design (N = 505) to test how affection expression in language, voice, and image in the AI diagnosis system affects effective communication. Findings The study found that affection expression in language, voice, and image significantly improved effective communication perceptions, which in turn increased patients’ willingness to use AI doctors. Effective communication partially mediated the relationship between affection expression and willingness. Originality/value This study contributes to theories on the affection design of AI doctors and AI–human interaction. It provides new insights into how affection expression can enhance communication and increase patient acceptance, offering valuable guidance for designing more effective AID systems.

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Publication Details

Journal
Industrial Management & Data Systems
Published
2026-05-14
DOI
https://doi.org/10.1108/imds-03-2025-0332
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Effective communication between patients and AI doctors: the role of the affection expression of AI doctors

Shihui Hu, Aihui Chen, Xinyi Wang
Industrial Management & Data Systems
Artificial Intelligence in Healthcare and Education
article

Effective communication between patients and AI doctors: the role of the affection expression of AI doctors

Shihui Hu, Aihui Chen, Xinyi Wang
article en

Abstract

Purpose The study aims to explore how the affection expression of AI doctors (language, voice, image) affects the effective communication between patients and AI doctors, thereby improving the acceptance of AI doctors by patients. Design/methodology/approach This study used a 2 × 2 × 2 experimental design (N = 505) to test how affection expression in language, voice, and image in the AI diagnosis system affects effective communication. Findings The study found that affection expression in language, voice, and image significantly improved effective communication perceptions, which in turn increased patients’ willingness to use AI doctors. Effective communication partially mediated the relationship between affection expression and willingness. Originality/value This study contributes to theories on the affection design of AI doctors and AI–human interaction. It provides new insights into how affection expression can enhance communication and increase patient acceptance, offering valuable guidance for designing more effective AID systems.

Industrial Management & Data Systems
Tianjin University of Finance and Economics (CN), Fudan University (CN), University Town of Shenzhen (CN), Systems Analytics (United States) (US)
Openalex Percentile: Top 6%
Artificial Intelligence in Healthcare and Education
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