Literature DB >> 30656675

Smartphone wallpapers for dermoscopy training in medical students and residents.

Fang-Ying Wang1,2, Ren-Feng Liu1,2, Gary Chuang3, Chih-Hsun Yang1,2, Yao-Yu Chang1,2.   

Abstract

BACKGROUND: Several dermoscopy training programs have found the accuracy of dermoscopy examination depends on adequate training of practitioners. Smartphones are readily available and time-efficient tools for dermoscopy training. AIM: To evaluate the learning efficacy of utilizing dermoscopy smartphone wallpapers to train medical students, PGY (postgraduate year)-1 trainees, and junior dermatological residents without prior dermoscopy training.
METHODS: We designed smartphone wallpapers with dermoscopy pictures and features of several common melanocytic and nonmelanocytic conditions. Pretests and posttests were performed before and after a 10-day-long smartphone wallpaper training program to evaluate their diagnostic accuracy using dermoscopy images.
RESULTS: Significant progressions were noted between the pretest and posttest scores both in the nonmelanocytic (P < 0.001) and the melanocytic (P = 0.003) sections. Medical students and PGY-1 trainees demonstrated more significant improvement in nonmelanocytic lesions, compared to dermatology residents. Residents of dermatology showed more progression in the melanocytic section than nonresidents. LIMITATIONS: There were limited participants. The frequency and time allotted by each participant in perusing the wallpapers were variable. Further study of the application on clinical practice is still needed.
CONCLUSION: Smartphone wallpapers training improves dermoscopic interpretation significantly in medical students, PGY-1 trainees, and dermatological residents. The background knowledge of dermatology has an effect on the degree of improvement in the training course.
© 2019 The International Society of Dermatology.

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Mesh:

Year:  2019        PMID: 30656675     DOI: 10.1111/ijd.14338

Source DB:  PubMed          Journal:  Int J Dermatol        ISSN: 0011-9059            Impact factor:   2.736


  1 in total

1.  Teaching Skin Cancer Detection to Medical Students Using a Dermoscopic Algorithm.

Authors:  Peggy R Cyr; Wendy Craig; Hadjh Ahrns; Kathryn Stevens; Caroline Wight; Elizabeth Seiverling
Journal:  PRiMER       Date:  2021-02-08
  1 in total

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