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

Tools and Questionnaires in Human Factors Evaluation (82) Design and Usability of Clinical Software and EHRs (368) mHealth for Diagnosis (85) Decision Support for Health Professionals (1627) Computer-Aided Diagnosis (277) Health Services in Resource-Poor Settings and LMICs (572) mHealth in the Developing World/LMICs, Underserved Communities, and for Global Health (740)

Published on in Vol 12 (2025)

This is a member publication of Bibsam Consortium

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56300, first published .
Intention to Use Automated Diagnosis and Clinical Risk Perceptions Among First Contact Clinicians in Resource-Poor Settings: Questionnaire-Based Study Focusing on Acute Burns

Intention to Use Automated Diagnosis and Clinical Risk Perceptions Among First Contact Clinicians in Resource-Poor Settings: Questionnaire-Based Study Focusing on Acute Burns

Intention to Use Automated Diagnosis and Clinical Risk Perceptions Among First Contact Clinicians in Resource-Poor Settings: Questionnaire-Based Study Focusing on Acute Burns

Authors of this article:

Constance Boissin1, 2 Author Orcid Image ;   Lisa Blom2 Author Orcid Image ;   Zara Taha2 Author Orcid Image ;   Lee Wallis3 Author Orcid Image ;   Nikki Allorto4 Author Orcid Image ;   Lucie Laflamme2, 5 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Shi H, Xiang Y, Yang X, Zhao Q, Huang H. Identifying Measurement Dimensions of Users’ Benefit-Risk Perceptions of AI in Healthcare: A Scoping Review. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 2026;63 View