Pedro Pablo Gomez

A Comparison of Teaching Modalities and Fidelity of Simulation Levels in Teaching Resuscitation Scenarios

INTRODUCTION The purpose of our study was to examine the ability of novices to learn selected aspects of Advanced Cardiac Life Support (ACLS) in training conditions that did not incorporate simulation compared to those that contained low- and high-fidelity simulation activities. We sought to determine at what level additional educational opportunities and simulation fidelity become superfluous with respect to learning outcomes. METHODS Totally 39 medical students and physician assistant students were randomly assigned to 4 training conditions: control (lecture only), video-based didactic instruction, low-, and high-fidelity simulation activities. Participants were assessed using a baseline written pretest of ACLS knowledge. Following this, all participants received a lecture outlining ACLS science and algorithm interpretation. Participants were then trained in specific aspects of ACLS according to their assigned instructional condition. After training, each participant was assessed via a Megacode performance examination and a written posttest. RESULTS All groups performed significantly better on the written posttest compared with the pretest (p < 0.001); however, no groups outperformed any other groups. On the Megacode performance test, the video-based, low-, and high-fidelity groups performed significantly better than the control group (p = 0.028, p < 0.001, p = 0.019). Equivalence testing revealed that the high-fidelity simulation condition was statistically equivalent to the video-based and low-fidelity simulation conditions. CONCLUSION Video-based and simulation-based training is associated with better learning outcomes when compared with traditional didactic lectures only. Video-based, low-fidelity, and high-fidelity simulation training yield equivalent outcomes, which may indicate that high-fidelity simulation is superfluous for the novice trainee.

Virtual Reality Simulators: Valuable Surgical Skills Trainers or Video Games?

BACKGROUND Virtual reality (VR) and physical model (PM) simulators differ in terms of whether the trainee is manipulating actual 3-dimensional objects (PM) or computer-generated 3-dimensional objects (VR). Much like video games (VG), VR simulators utilize computer-generated graphics. These differences may have profound effects on the utility of VR and PM training platforms. In this study, we aimed to determine whether a relationship exists between VR, PM, and VG platforms. METHODS VR and PM simulators for laparoscopic camera navigation ([LCN], experiment 1) and flexible endoscopy ([FE] experiment 2) were used in this study. In experiment 1, 20 laparoscopic novices played VG and performed 0° and 30° LCN exercises on VR and PM simulators. In experiment 2, 20 FE novices played VG and performed colonoscopy exercises on VR and PM simulators. RESULTS In both experiments, VG performance was correlated with VR performance but not with PM performance. Performance on VR simulators did not correlate with performance on respective PM models. CONCLUSIONS VR environments may be more like VG than previously thought.

Predicting and enhancing American Board of Surgery In-Training Examination performance: does writing questions really help?

BACKGROUND The generative learning model posits that individuals remember content they have generated better than materials created by others. The goals of this study were to evaluate question generation as a study method for the American Board of Surgery In-Training Examination (ABSITE) and determine whether practice test scores and other data predict ABSITE performance. METHODS Residents (n = 206) from 6 general surgery programs were randomly assigned to one of the two study conditions. One group wrote questions for practice examinations. All residents took 2 practice examinations. RESULTS There was not a significant effect of writing questions on ABSITE score. Practice test scores, United States Medical Licensing Examination Step 1 scores, and previous ABSITE scores were significantly correlated with ABSITE performance. CONCLUSIONS The generative learning model was not supported. Performance on practice tests and other data can be used for early identification of residents at risk of performing poorly on the ABSITE.