Currently submitted to: JMIR Dermatology
Date Submitted: Apr 3, 2025
Open Peer Review Period: Apr 10, 2025 - Jun 5, 2025
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Patient Perceptions of Artificial Intelligence and Telemedicine in Dermatology: A Narrative Review
ABSTRACT
Background:
Artificial intelligence (AI) and telemedicine have great potential to transform dermatology care delivery, but patient perspectives on these technologies have not been systematically compared.
Objective:
To examine patient perspectives on AI and telemedicine in dermatology to inform implementation strategies as these technologies increasingly converge in clinical practice.
Methods:
A comprehensive literature search was conducted using PubMed, Scopus, and Embase databases between August 2024 and October 2024. We identified 48 articles addressing patient perspectives on AI and telemedicine in dermatology, with none directly comparing views on both technologies.
Results:
Several distinct themes emerged regarding patient perspectives on these technologies: willingness to use, perceived benefits and risks, barriers to implementation, and conditions necessary for successful integration. Findings revealed that patients express hesitancy towards AI-based diagnoses that lack dermatologist involvement, while preferences for teledermatology varied by appointment reason, age, and prior technology exposure. Patients' motivations for AI implementation are connected to AI's potential for quicker diagnoses and improved triage efficiency, while telemedicine addresses logistical challenges such as reduced travel time and improved appointment availability. Both technologies were perceived to improve accessibility and diagnostic efficiency, though patients expressed concerns about AI's limited communication abilities and teledermatology's limits in performing physical examinations. Primary adoption barriers for these modalities included technological limitations and trust concerns, with patients emphasizing the need for dermatologist oversight, transparency, and adequate educational resources for successful integration.
Conclusions:
The complementary strengths of AI and teledermatology suggest they could mitigate each other's limitations when integrated—AI potentially enhancing teledermatology's diagnostic accuracy while teledermatology addresses AI's lack of human connection. By thoroughly examining these perspectives, this review may serve as a guide for patient-centered technological integration in the future landscape of accessible dermatologic care.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.