Tapping into Efficient Learning: An Exploration of the Impact of Sequential Learning on Skill Gains and Learning Curves in Central Venous Catheterization Simulator Training.

Objective: Medical residents learn how to perform many complex procedures in a short amount of time. Sequential learning, or learning in stages, is a method applied to complex motor skills to increase skill acquisition and retention but has not been widely applied in simulation-based training (SBT). Central venous catheterization (CVC) training could benefit from the implementation of sequential learning.

Competence over confidence: uncovering lower self-efficacy for women residents during central venous catheterization training.

Background: While women make up over 50% of students enrolled in medical school, disparities in self-efficacy of medical skills between men and women have been observed throughout medical education. This difference is significant because low self-efficacy can impact learning, achievement, and performance, and thus create gender-confidence gaps. Simulation-based training (SBT) employs assessments of self-efficacy, however, the Dunning-Kruger effect in self-assessment posits that trainees often struggle to recognize their skill level.

Evaluating the effects of comprehensive simulation on central venous catheterization training: a comparative observational study.

Background: Simulation-based training (SBT) is vital to complex medical procedures such as ultrasound guided central venous catheterization (US-IJCVC), where the experience level of the physician impacts the likelihood of incurring complications. The Dynamic Haptic Robotic Trainer (DHRT) was developed to train residents in CVC as an improvement over manikin trainers, however, the DHRT and manikin trainer both only provide training on one specific portion of CVC, needle insertion. As such, CVC SBT would benefit from more comprehensive training.

Shifting Perspectives: A proposed framework for analyzing head-mounted eye-tracking data with dynamic areas of interest and dynamic scenes.

Eye-tracking is a valuable research method for understanding human cognition and is readily employed in human factors research, including human factors in healthcare. While wearable mobile eye trackers have become more readily available, there are no existing analysis methods for accurately and efficiently mapping dynamic gaze data on dynamic areas of interest (AOIs), which limits their utility in human factors research. The purpose of this paper was to outline a proposed framework for automating the analysis of dynamic areas of interest by integrating computer vision and machine learning (CVML).

Preparing for the lasting effects of COVID-19 on medical training: The design and pilot study of a low-fidelity virtual reality prototype for Central Venous Catheterization training.

Over the last several decades we have seen a shift from in-person to online training that has been exasperated by the COVID-19 pandemic. Researchers believe that many of these effects will be lasting which makes it even more important that the Human Factors community seek to step back and understand how to best train complex skills in a virtual world. The current paper is focused on understanding the utility of Virtual Reality (VR) in medical education for a hands-on procedural heavy procedure - ultrasound-guided Internal Jugular Central Venous Catheterization.

LEARNING FROM FAILURE: A CASE STUDY OF HUMAN DRIVEN RISK ASSESSMENT IN MEDICAL SIMULATOR DESIGN.

Failure Modes and Effects Analysis (FMEA) is a qualitative and quantitative approach to measuring and analyzing risk that compiles and ranks failure modes, their effects, and their corrective actions. Though widely used, traditional FMEA has been criticized for the lack of a scientific basis behind the Risk Priority Number calculation. To combat this, researchers have argued that Multiple Criteria Decision Making (MCDM) methods should be used to rank failure modes instead.

Slow and Steady: Examining the impact of hands-on instructions on learnability of a training simulator to enhance development of core skills in Central Venous Catheterization.

Instructional design is the theory surrounding how learners perceive information and is prevalent in simulation-based medical education. Simulation is used for a variety of medical procedures including central venous catheterization (CVC). The dynamic haptic robotic trainer (DHRT) is a CVC teaching simulator developed to specifically focus on training the needle insertion portion of CVC.

Evaluating the Impact of Assessment Metrics for Simulated Central Venous Catheterization Training.

Introduction: Performance assessment and feedback are critical factors in successful medical simulation-based training. The Dynamic Haptic Robotic Trainer (DHRT) allows residents to practice ultrasound-guided needle insertions during simulated central venous catheterization (CVC) procedures while providing detailed feedback and assessment. A study was performed to examine the effectiveness of the DHRT in training the important skills of needle tip tracking and aspiration and how these skills impact procedural complications in simulated CVC.

FUN AND GAMES: DESIGNING A GAMIFIED CENTRAL VENOUS CATHETERIZATION TRAINING SIMULATOR.

Gamification, or adding elements of games to training systems, has the potential to increase learner engagement and information retention. However, the use of gamification has yet to be explored in Central Venous Catheterization (CVC) trainers which teach a commonly performed medical procedure with high incidence rates. In order to combat these errors, a Dynamic Haptic Robotic Trainer (DHRT) was developed, which focuses on vessel identification and access.

Going the (social) distance: Comparing the effectiveness of online versus in-person Internal Jugular Central Venous Catheterization procedural training.

Background: This study compares surgical residents' knowledge acquisition of ultrasound-guided Internal Jugular Central Venous Catheterization (US-IJCVC) between in-person and online procedural training cohorts before receiving independent in-person Dynamic Haptic Robotic Simulation training.

Methods: Three surgical residency procedural training cohorts, two in-person (N = 26) and one online (N = 14), were compared based on their performance on a 24-item US-IJCVC evaluation checklist completed by an expert physician completed after training. Pre- and post-training US-IJCVC knowledge was also compared for the online cohort.