Literature DB >> 29395237

Learning preferences of surgery residents: a multi-institutional study.

Roger H Kim1, Rebecca K Viscusi2, Ashley N Collier3, Marie A Hunsinger4, Mohsen M Shabahang4, George M Fuhrman5, James R Korndorffer6.   

Abstract

BACKGROUND: The VARK model categorizes learners by preferences for 4 modalities: visual, aural, read/write, and kinesthetic. Previous single-institution studies found that VARK preferences are associated with academic performance. This multi-institutional study was conducted to test the hypothesis that the VARK learning preferences of residents differ from the general population and that they are associated with performance on the American Board of Surgery In-Training Examination (ABSITE).
METHODS: The VARK inventory was administered to residents at 5 general surgery programs. The distribution of the VARK preferences of residents was compared with the general population. ABSITE results were analyzed for associations with VARK preferences. χ2, Analysis of variance, and multiple linear regression were used for statistical analysis.
RESULTS: A total of 132 residents completed the VARK inventory. The distribution of the VARK preferences of residents was different than the general population (P < .001). The number of aural responses on the VARK inventory was an independent predictor of ABSITE percentile rank (P = .03), percent of questions correct (P = .01), and standard score (P = .01).
CONCLUSION: This study represents the first multi-institutional study to examine VARK preferences among surgery residents. The distribution of preferences among residents was different than that of the general population. Residents with a greater number of aural responses on VARK had greater ABSITE scores. The VARK model may have potential to improve learning efficiency among residents.
Copyright © 2017 Elsevier Inc. All rights reserved.

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Year:  2018        PMID: 29395237     DOI: 10.1016/j.surg.2017.10.031

Source DB:  PubMed          Journal:  Surgery        ISSN: 0039-6060            Impact factor:   3.982


  3 in total

1.  Computer-Aided Design, 3-D-Printed Manufacturing, and Expert Validation of a High-fidelity Facial Flap Surgical Simulator.

Authors:  Allison R Powell; Sudharsan Srinivasan; Glenn Green; Jennifer Kim; David A Zopf
Journal:  JAMA Facial Plast Surg       Date:  2019-07-01       Impact factor: 4.611

2.  The RITE of Passage: Learning Styles and Residency In-Service Training Examination (RITE) Scores.

Authors:  Brenda G Fahy; Jean E Cibula; Lou Ann Cooper; Samsun Lampotang; Nikolaus Gravenstein; Terrie Vasilopoulos
Journal:  Cureus       Date:  2021-01-03

3.  Impact of the COVID-19 pandemic on the training of general surgery residents: Surgical training and the COVID-19 pandemic.

Authors:  Călin Popa; Diana Schlanger; Florin Zaharie; Nadim Al Hajjar
Journal:  Eur Surg       Date:  2022-09-09       Impact factor: 0.796

  3 in total

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