Accepted for/Published in: JMIR Dermatology
Date Submitted: Apr 21, 2023
Date Accepted: Jul 3, 2023
Date Submitted to PubMed: Aug 25, 2023
Improving skin cancer diagnostics through mobile application with a large interactive image repository: a randomized controlled study
ABSTRACT
Background:
Skin cancer diagnostics is challenging, and mastery requires extended periods of dedicated practice.
Objective:
The aim of the study was to determine if self-paced pattern recognition training in skin cancer diagnostics with clinical and dermoscopic images of skin lesions using a large-scale interactive image repository (LIIR) with patient cases improves primary care physicians’ (PCPs) diagnostic skills and confidence.
Methods:
115 PCPs were randomized (allocation ratio 3:1) to receive or not receive self-paced pattern recognition training in skin cancer diagnostics using a LIIR with patient cases through a quiz-based smartphone application during an eight-day period. The participants’ ability to diagnose skin cancer was evaluated using a 12-item multiple choice questionnaire (MCQ) prior to and eight days after the educational intervention period. Their thoughts on the use of dermoscopy were assessed using a study-specific questionnaire. A learning curve was calculated through analysis of data from the mobile application.
Results:
On average, participants in the intervention group spent 2 hours and 26 minutes quizzing digital patient cases and 41 minutes reading the educational material. They had an average preintervention MCQ score of 52.0% correct answers, which increased to 66.4% on the postintervention test; a statistically significant improvement of 14.3 percentage points [p<.001, 95% CI 9.8-18.9] with Intention-To-Treat analysis. Analysis of participants who received the intervention as per protocol (500 patient cases in 8 days) showed an average increase of 16.7 percentage points [p<.001, 95%CI 11.3 - 22.0] from 53.9% to 70.5%. Their overall ability to correctly recognize malignant lesions in the LIIR patient cases improved over the intervention period by 6.6 percentage points from 67.1% [95l% CI 65.2-69.3] to 73.7% [95% CI 72.5-75.0] and their ability to set the correct diagnosis improved by 10.5 percentage points from 42.5% [95% CI 40.2-44.8%] to 53.0% [95% CI 51.3-54.9]. The diagnostic confidence of participants in the intervention group increased on a scale from 1 to 4 by 32.9% from 1.6 to 2.1 (p<.001). Participants in the control group did not increase their postintervention score nor their diagnostic confidence during the same period.
Conclusions:
Self-paced pattern recognition training in skin cancer diagnostics through the use of a digital large-scale interactive image repository with patient cases delivered by a quiz-based mobile application improves the diagnostic accuracy of primary care physicians. Clinical Trial: ClinicalTrials.Gov NCT05661370
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