JMIR Publications

ABSTRACT

Background:

Remote Monitoring of Cancer Treatment-Related Skin Toxicities Using an AI-Enabled Digital Health Solution: Qualitative Development and Validation

Objective:

To describe the development and qualitative content validation of a digital health solution to support remote monitoring of cancer-treatment–related skin toxicities

Methods:

Published literature review and clinical expertise informed the content of the digital product. Behavioral psychology, measurement, and data science drove the design of interfaces and functionalities with a focus on user-engagement and diversity. Patients (n=15) receiving anticancer therapies participated in the first round of content validation for the symptom tracker and patients (n=20) and clinicians (oncologists and nurses, n=8) participated in the second round of qualitative user testing of the overall content and design.

Results:

The digital solution enabled structured patient reporting of symptom occurrence, severity, anatomic distribution, and visual documentation. In the first round of content validation (n=15), dryness was reported by 13/15 participants (87%), rash by 10/15 (67%), skin sensitivity by 9/15 (60%), and itching by 8/15 (53%). During subsequent patient user testing (n=20), 14/20 participants (70%) appreciated skin-tone personalization, 16/20 (80%) considered it inclusive, and 11/20 (55%) preferred a simple body avatar without skin-tone customization. Clinicians (n=8) also evaluated the prototype. Qualitative feedback indicated that the content was generally easy to understand and that symptom tracking could facilitate more precise discussions with clinicians.

Conclusions:

The digital solution features several innovative components for reliable and sustained data capture of the onset and evolution of skin symptoms, providing relevant insight for the remote monitoring of patients at risk of STs. Empirical evidence of clinical utility is needed.