Effect of Music on Surgical Performance During Artificial Intelligence-Based Simulation Training

NCT07111481 | Completed

• 1 other identifier: 2010-270, NEU-09-042-Trial 6
• Study Type: interventional
• Target: 97
• Locations: 1 country
• Sites: 1

Brief Summary

At the Neurosurgical Simulation and Artificial Intelligence Learning Centre, we seek to provide surgical trainees with innovative technologies that allow them to improve their surgical technical skills in risk-free environments, potentially improving patient operative outcomes. The Intelligent Continuous Expertise Monitoring System (ICEMS), a deep learning application that assesses and trains neurosurgical technical skill and provides continuous intraoperative feedback, is one such technology that may improve surgical education. Previous research has found that music can impact cognitive performance and learning outcomes. However, the effects of music on neurosurgical simulation performance-along with the associated affective-cognitive responses-remain largely unexplored. In this randomized controlled trial, medical students from four Quebec universities will be blinded and randomized to one of two groups. The control group will undergo a simulation training session without music, while the intervention arm will listen to a Mozart piano sonata during their session. The aim of this study is to determine how listening to Mozart music during surgical simulation training influences learner technical skill acquisition and transfer, as well as their emotions and cognitive load.

Conditions

Surgical Education

Keywords

Neurosurgery; Virtual Reality; Surgical Simulation; Music; Mozart Effect; Artificial Intelligence; Intelligent Tutoring Systems

Outcome Measures

Primary Outcomes (2)

• Intelligent Continuous Expertise Monitoring System (ICEMS) expertise score - Technical skill acquisition across practice tasks on NeuroVR simulator

  The ICEMS will continuously evaluate the trainee's performance during each practice task and calculate average expertise scores on a scale of -1.00 (novice) to 1.00 (expert). This will allow us to assess learner technical skill acquisition from the first through fifth repetitions of the practice task.

  1 day of study

• Intelligent Continuous Expertise Monitoring System (ICEMS) expertise score - Technical skill transfer during complex realistic task on NeuroVR simulator

  The ICEMS will continuously evaluate the trainee's performance during the realistic task and calculate an average expertise score on a scale of -1.00 (novice) to 1.00 (expert). This will allow us to assess learner technical skill transfer from the practice tasks to a more complex realistic scenario.

  1 day of study

Secondary Outcomes (2)

• Strength of emotions elicited

  1 day of study

• Levels of cognitive load

  1 day of study

Study Arms (2)

No music group

NO INTERVENTION

20 participants allocated. Participants perform a simulated subpial brain tumor resection on the NeuroVR simulator without music while receiving verbal feedback from the ICEMS tutor.

Mozart music group

EXPERIMENTAL

20 participants allocated. Participants will listen to Mozart music while performing a simulated subpial brain tumor resection on the NeuroVR simulator and receiving verbal feedback from the ICEMS tutor.

Behavioral: Mozart music

Interventions

Mozart music BEHAVIORAL

Participants will be played Mozart's Sonata for Two Pianos in D Major, K. 448 during their surgical simulation training session with an AI tutor.

Mozart music group

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may not qualify if:

• Prior use of the NeuroVR (CAE Healthcare) simulator.

Sponsors & Collaborators

• McGill University: lead

Study Sites (1)

Neurosurgical Simulation and Artificial Intelligence Learning Centre

Montreal, Quebec, H2X 4B3, Canada

Location

Related Publications (9)

• Duffy MC, Lajoie SP, Pekrun R, Lachapelle K. Emotions in medical education: Examining the validity of the Medical Emotion Scale (MES) across authentic medical learning environments. Learn Instr. 2020;70:101150. doi:10.1016/j.learninstruc.2018.07.001

  BACKGROUND

• R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2025. https://www.R-project.org/

  BACKGROUND

• Leppink J, Paas F, Van der Vleuten CP, Van Gog T, Van Merrienboer JJ. Development of an instrument for measuring different types of cognitive load. Behav Res Methods. 2013 Dec;45(4):1058-72. doi: 10.3758/s13428-013-0334-1.

  PMID: 23572251 BACKGROUND

• Winkler-Schwartz A, Bissonnette V, Mirchi N, Ponnudurai N, Yilmaz R, Ledwos N, Siyar S, Azarnoush H, Karlik B, Del Maestro RF. Artificial Intelligence in Medical Education: Best Practices Using Machine Learning to Assess Surgical Expertise in Virtual Reality Simulation. J Surg Educ. 2019 Nov-Dec;76(6):1681-1690. doi: 10.1016/j.jsurg.2019.05.015. Epub 2019 Jun 13.

  PMID: 31202633 BACKGROUND

• Liu X, Cruz Rivera S, Moher D, Calvert MJ, Denniston AK; SPIRIT-AI and CONSORT-AI Working Group. Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension. Lancet Digit Health. 2020 Oct;2(10):e537-e548. doi: 10.1016/S2589-7500(20)30218-1. Epub 2020 Sep 9.

  PMID: 33328048 BACKGROUND

• Wiseman MC. The Mozart effect on task performance in a laparoscopic surgical simulator. Surg Innov. 2013 Oct;20(5):444-53. doi: 10.1177/1553350612462482. Epub 2012 Nov 14.

  PMID: 23154636 BACKGROUND

• Nees LK, Grozinger P, Orthmann N, Rippinger N, Hennigs A, Sohn C, Domschke C, Wallwiener M, Rom J, Riedel F. The Influence of Different Genres of Music on the Performance of Medical Students on Standardized Laparoscopic Exercises. J Surg Educ. 2021 Sep-Oct;78(5):1709-1716. doi: 10.1016/j.jsurg.2021.03.008. Epub 2021 Mar 31.

  PMID: 33812805 BACKGROUND

• Rauscher FH, Shaw GL, Ky KN. Listening to Mozart enhances spatial-temporal reasoning: towards a neurophysiological basis. Neurosci Lett. 1995 Feb 6;185(1):44-7. doi: 10.1016/0304-3940(94)11221-4.

  PMID: 7731551 BACKGROUND

• Yilmaz R, Winkler-Schwartz A, Mirchi N, Reich A, Christie S, Tran DH, Ledwos N, Fazlollahi AM, Santaguida C, Sabbagh AJ, Bajunaid K, Del Maestro R. Continuous monitoring of surgical bimanual expertise using deep neural networks in virtual reality simulation. NPJ Digit Med. 2022 Apr 26;5(1):54. doi: 10.1038/s41746-022-00596-8.

  PMID: 35473961 BACKGROUND

Study Officials

• Rolando F. Del Maestro, MD, PhD

  Neurosurgical Simulation and Artificial Intelligence Learning Centre

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Masking Details: Study participants are blinded to group assignments and study outcomes.
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director, Neurosurgical Simulation and Artificial Intelligence Learning Centre

Model Details: Parallel Assignment

Study Record Dates

• First Submitted: August 1, 2025
• First Posted: August 8, 2025
• Study Start: August 5, 2025
• Primary Completion: March 14, 2026
• Study Completion: March 14, 2026
• Last Updated: May 6, 2026

Record last verified: 2026-05

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE
• Time Frame: Data will be available for 5 years following the completion of the trial.
• Access Criteria: Researchers who wish to access the data must contact the principal investigator of the trial, Dr. Rolando F. Del Maestro.

Locations

CA (1)