AI vs human? Will patients trust AI doctors as much as they trust human doctors? An empirical study from China

Purpose The interaction between humans and artificial intelligence (AI) is becoming increasingly common. However, whether humans trust AI more or doctors more is still not clear. The purpose of this paper is to investigate whether there are significant differences in patient trust between AI and human doctors? What are the mechanisms and boundary conditions. Design/methodology/approach Based on social support theory, using experimental methods, this study investigates the trust (competence, goodwill and integrity) differences between AI doctors and human doctors by analyzing 236 online experiment participants’ data. Findings The results indicate that compared to AI doctors, patients exhibit higher levels of trust in human doctors across all three dimensions. Furthermore, informational support and emotional support mediate the relationship between service agent types (AI vs human) and patient trust. Response length moderates the impact of service agent types on these two forms of social support. Originality/value These findings contribute to a deeper understanding of the relationship between human–AI interaction and patient trust by investigating the mediating role of informational support and emotional support, as well as the moderating role of response length. The study also provides practical implications for how to improve patient trust in AI through optimized AI design.

Authors

Institutions

Publication Details

Journal
Aslib Journal of Information Management
Published
2026-01-05
DOI
https://doi.org/10.1108/ajim-04-2025-0192
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
17.70
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI vs human? Will patients trust AI doctors as much as they trust human doctors? An empirical study from China

Feifei Hao, Ge Zhang, Shenghui Liu, Liang Ma et al.
1 citations
Aslib Journal of Information Management
Artificial Intelligence in Healthcare and Education
17.70
article

AI vs human? Will patients trust AI doctors as much as they trust human doctors? An empirical study from China

Feifei Hao, Ge Zhang, Shenghui Liu, Liang Ma, Xin Zhang
article en
1 citations

Abstract

Purpose The interaction between humans and artificial intelligence (AI) is becoming increasingly common. However, whether humans trust AI more or doctors more is still not clear. The purpose of this paper is to investigate whether there are significant differences in patient trust between AI and human doctors? What are the mechanisms and boundary conditions. Design/methodology/approach Based on social support theory, using experimental methods, this study investigates the trust (competence, goodwill and integrity) differences between AI doctors and human doctors by analyzing 236 online experiment participants’ data. Findings The results indicate that compared to AI doctors, patients exhibit higher levels of trust in human doctors across all three dimensions. Furthermore, informational support and emotional support mediate the relationship between service agent types (AI vs human) and patient trust. Response length moderates the impact of service agent types on these two forms of social support. Originality/value These findings contribute to a deeper understanding of the relationship between human–AI interaction and patient trust by investigating the mediating role of informational support and emotional support, as well as the moderating role of response length. The study also provides practical implications for how to improve patient trust in AI through optimized AI design.

Aslib Journal of Information Management
Shandong University of Traditional Chinese Medicine (CN), Shandong University of Finance and Economics (CN)
Openalex Percentile: Top 3%
Artificial Intelligence in Healthcare and Education
17.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.