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This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (5310) Quality/Credibility of eHealth Information and Trust Issues (965) Design and Usability of Medical Devices (241) Robotics in Rehabilitation (113) Machine Learning (3343) Robots in Healthcare (272) Artificial Intelligence (5027)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68299, first published .
Elderly woman in wheelchair smiles at a healthcare robot holding a tablet.

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

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

Authors of this article:

Jiukai Zhao1 Author Orcid Image ;   Yuqi Yang2 Author Orcid Image ;   Juanxia Miao1 Author Orcid Image ;   Xue Wang1 Author Orcid Image ;   Dianjun Qi3 Author Orcid Image ;   Shuang Zang1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Jiang Y, Zhang J, Wu J. Online health information seeking, healthcare utilization, and exercise-related self-management among patients with long-term conditions in China during COVID-19. DIGITAL HEALTH 2026;12 View
  2. Beauchamp J, Savitz S, Sharrief A, Reininger B, Acierno R, Suchting R, Burnett J, Rosales L, Albaqali J, Rajan R, Choi N. Behavioural activation for the prevention of poststroke depression in low-income older stroke survivors (LIVE WEL): protocol for a randomised controlled trial. BMJ Open 2026;16(6):e120452 View
  3. Annisa , Darmi Arda . Determinants of compliance with contribution payment of JKN mandiri participants in the bantimurung health center working area. JAKESPOL Journal of Health Policy Analysis 2026;1(4):152 View