Intention to Use Automated Diagnosis and Clinical Risk Perceptions Among First Contact Clinicians in Resource-Poor Settings: Questionnaire-Based Study Focusing on Acute Burns
Almost three-quarters of first contact clinicians were inclined to seek automated advice for burn diagnosis. The proposed model contributes to explaining the intention to use with 5 hypotheses supported. When seeking additional determinants, clinical risk perception is a dimension that should be considered in any artificial intelligence implementation process, to help ensure sustainability.
Authors
- Lisa Blom (ORCID: https://orcid.org/0000-0002-3538-7159)
- Lucie Laflamme (ORCID: https://orcid.org/0000-0002-6443-1307)
- Lee Wallis (ORCID: https://orcid.org/0000-0003-2711-3139)
- Constance Boissin (ORCID: https://orcid.org/0000-0003-4026-3190)
- Nikki Allorto (ORCID: https://orcid.org/0000-0001-9339-4640)
- Zara Taha
Institutions
- University of Cape Town (ZA)
- University of South Africa (ZA)
- Karolinska Institutet (SE)
- Umkhuseli Innovation and Research Management (ZA)
- University of KwaZulu-Natal (ZA)
Publication Details
- Journal
- JMIR Human Factors
- Published
- 2025-06-03
- DOI
- https://doi.org/10.2196/56300
- Primary Topic
- Fire Detection and Safety Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00