Factors Associated With the Level of Trust in Health Information Robots Among the General Population From a Socioecological Model Perspective: Network Analysis

BackgroundAlthough robots have emerged as a new means of delivering health information, with the advancement of artificial intelligence technology, individuals still face challenges in deciding whether to trust the health information provided by these robots owing to various...

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Main Authors: Jiukai Zhao, Yuqi Yang, Juanxia Miao, Xue Wang, Dianjun Qi, Shuang Zang
Format: Article
Language:English
Published: JMIR Publications 2025-06-01
Series:Journal of Medical Internet Research
Online Access:https://www.jmir.org/2025/1/e68299
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author Jiukai Zhao
Yuqi Yang
Juanxia Miao
Xue Wang
Dianjun Qi
Shuang Zang
author_facet Jiukai Zhao
Yuqi Yang
Juanxia Miao
Xue Wang
Dianjun Qi
Shuang Zang
author_sort Jiukai Zhao
collection DOAJ
description BackgroundAlthough robots have emerged as a new means of delivering health information, with the advancement of artificial intelligence technology, individuals still face challenges in deciding whether to trust the health information provided by these robots owing to various trust-related factors. ObjectiveThis study aimed to investigate the factors associated with the level of trust in health information robots among the general population in China from a socioecological model perspective and identify the central indicators based on network analysis. MethodsA nationwide survey in China was conducted from June 20, 2023, to August 31, 2023, involving 30,054 participants. The level of trust in health information robots was measured using a self-developed questionnaire. Univariate and multivariate generalized linear model analyses were conducted to investigate the factors associated with the level of trust in health information robots. Network analyses were conducted to examine the network structure of trust levels in health information robots and the associated factors. ResultsThe results of the multivariate generalized linear model analysis revealed that participants who were diagnosed with chronic diseases; exhibited personality traits of higher agreeableness and openness; had an education level of junior college or higher; reported higher self-rated health status, health literacy, anxiety symptoms, family health, number of house properties, average monthly household income, and perceived social support; and had higher medical insurance coverage showed a positive association with the level of trust in health information robots compared to individuals without these characteristics. However, compared to individuals without these characteristics, being older, having the personality trait of neuroticism, and living in an urban area were negatively associated with the level of trust in health information robots. In addition, using a network approach, central indicators were identified in the network of the level of trust in health information robots and its associated factors, including family health and perceived social support. Finally, agreeableness and educational level appeared upstream of the entire directed acyclic graph, directly influencing the level of trust in health information robots. ConclusionsOur findings offer a novel perspective on the association between health information robots and trust and contribute to the application and development of artificial intelligence IT. Individuals’ acceptance of and adherence to health information may be enhanced if the factors associated with the level of trust in health information robots are considered.
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spelling doaj-art-306c896b4e87431eabd5d8016bb17f9d2025-08-20T03:25:59ZengJMIR PublicationsJournal of Medical Internet Research1438-88712025-06-0127e6829910.2196/68299Factors Associated With the Level of Trust in Health Information Robots Among the General Population From a Socioecological Model Perspective: Network AnalysisJiukai Zhaohttps://orcid.org/0009-0000-7286-0155Yuqi Yanghttps://orcid.org/0009-0002-7959-5475Juanxia Miaohttps://orcid.org/0000-0002-0507-6034Xue Wanghttps://orcid.org/0000-0002-0371-4004Dianjun Qihttps://orcid.org/0000-0003-0468-1651Shuang Zanghttps://orcid.org/0000-0001-7814-8011 BackgroundAlthough robots have emerged as a new means of delivering health information, with the advancement of artificial intelligence technology, individuals still face challenges in deciding whether to trust the health information provided by these robots owing to various trust-related factors. ObjectiveThis study aimed to investigate the factors associated with the level of trust in health information robots among the general population in China from a socioecological model perspective and identify the central indicators based on network analysis. MethodsA nationwide survey in China was conducted from June 20, 2023, to August 31, 2023, involving 30,054 participants. The level of trust in health information robots was measured using a self-developed questionnaire. Univariate and multivariate generalized linear model analyses were conducted to investigate the factors associated with the level of trust in health information robots. Network analyses were conducted to examine the network structure of trust levels in health information robots and the associated factors. ResultsThe results of the multivariate generalized linear model analysis revealed that participants who were diagnosed with chronic diseases; exhibited personality traits of higher agreeableness and openness; had an education level of junior college or higher; reported higher self-rated health status, health literacy, anxiety symptoms, family health, number of house properties, average monthly household income, and perceived social support; and had higher medical insurance coverage showed a positive association with the level of trust in health information robots compared to individuals without these characteristics. However, compared to individuals without these characteristics, being older, having the personality trait of neuroticism, and living in an urban area were negatively associated with the level of trust in health information robots. In addition, using a network approach, central indicators were identified in the network of the level of trust in health information robots and its associated factors, including family health and perceived social support. Finally, agreeableness and educational level appeared upstream of the entire directed acyclic graph, directly influencing the level of trust in health information robots. ConclusionsOur findings offer a novel perspective on the association between health information robots and trust and contribute to the application and development of artificial intelligence IT. Individuals’ acceptance of and adherence to health information may be enhanced if the factors associated with the level of trust in health information robots are considered.https://www.jmir.org/2025/1/e68299
spellingShingle Jiukai Zhao
Yuqi Yang
Juanxia Miao
Xue Wang
Dianjun Qi
Shuang Zang
Factors Associated With the Level of Trust in Health Information Robots Among the General Population From a Socioecological Model Perspective: Network Analysis
Journal of Medical Internet Research
title Factors Associated With the Level of Trust in Health Information Robots Among the General Population From a Socioecological Model Perspective: Network Analysis
title_full Factors Associated With the Level of Trust in Health Information Robots Among the General Population From a Socioecological Model Perspective: Network Analysis
title_fullStr Factors Associated With the Level of Trust in Health Information Robots Among the General Population From a Socioecological Model Perspective: Network Analysis
title_full_unstemmed Factors Associated With the Level of Trust in Health Information Robots Among the General Population From a Socioecological Model Perspective: Network Analysis
title_short Factors Associated With the Level of Trust in Health Information Robots Among the General Population From a Socioecological Model Perspective: Network Analysis
title_sort factors associated with the level of trust in health information robots among the general population from a socioecological model perspective network analysis
url https://www.jmir.org/2025/1/e68299
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