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Testing the Efficacy of an Artificial Intelligence Real-Time Coaching SystemSystemSimulatioTraining of Medical Students

NCT05168150 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 98

Last updated 2022-08-08

No results posted yet for this study

Summary

Background:

Trainees learn surgical technical skills through apprenticeship model working closely with surgeons and given increased responsibility in patient cases under expert supervision. However, factors such as surgeons' busy schedule, number of available patient cases, patient safety and lack of objectivity and standardization in training pose strong limitations. Virtual reality surgical simulators integrated with artificial intelligence (AI) systems provide a standardized realistic simulation environment and detailed performance data that allows accurate quantitation of surgical skills and tailored feedback. These platforms make repetitive practice of surgical skills possible in a risk-free environment.

The Intelligent Continuous Monitoring System (ICEMS), a deep learning application integrated in NeuroVR simulation platform, was developed to assess surgical performance continuously in 0.2 second intervals and provide coaching and risk detection. Although a predictive validity for assessment module was provided previously, the effectiveness of real-time coaching and risk detection ability with this AI system remains to be explored.

The objective of this study is to compare the error-oriented intelligent feedback provided by the ICEMS to in-person expert instruction in surgical simulation training by monitoring the improvement of medical student technical skills on a series of virtual reality tumor resection tasks.

Conditions

  • Surgical Education

Interventions

BEHAVIORAL

Experimental: Experimental Group - Intelligent Continuous Expertise Monitoring System group

During each of the practice task they will receive real-time auditory feedback instructed by the intelligent system. After each attempt, a student takes a 5-minute break. They will be shown the errors they made during the task regarding five performance metrics. After seeing each error, they will be shown video demonstration to learn how to expertly perform at each performance metrics. On their 6th attempt they will perform on the realistic scenario without any feedback given.

BEHAVIORAL

Experimental Group In-person expert-mediated instruction group

During each of the practice task, students will receive verbal feedback from the expert instructor present in the room. After each task, experts will summarize their performance and outline the errors the student made. Based on the student's performance, expert will demonstrate how to expertly perform the task in the simulation, and how to improve their performance in the next attempt. Students will perform the 6th attempt on the realistic scenario without any instruction given.

Sponsors & Collaborators

Principal Investigators

  • Rolando Del Maestro, MD · McGill

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
DOUBLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-01-05
Primary Completion
2022-05-03
Completion
2022-05-03

Countries

  • Canada

Study Locations

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Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05168150 on ClinicalTrials.gov