Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Production Efficiency01:01

Production Efficiency

Net production efficiency (NPE) is the efficiency at which organisms assimilate energy into biomass for the next trophic level. Due to low metabolic rates and less energy spent on thermoregulatory processes, the NPE of ectotherms (cold-blooded animals) is 10 times higher than endotherms (warm-blooded animals).
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Medical exam question difficulty prediction: An analysis of embedding representations, machine-learning approaches, and input feature impact.

Medical teacher·2025
Same author

Optimizing cost-effectiveness in remote objective structured clinical examinations through targeted double scoring methodologies.

Medical education online·2025
Same author

Developing Computerized Adaptive Testing for a National Health Professionals Exam: An Attempt from Psychometric Simulations.

Perspectives on medical education·2023
Same author

'Is it painful'? A qualitative study on experiences of patients before prostate needle biopsy.

BMJ open·2022
Same author

Cost-Effectiveness Analysis in Performance Assessments: A Case Study of the Objective Structured Clinical Examination.

Medical education online·2022
Same author

Association between systemic lupus erythematosus and disruption of gut microbiota: a meta-analysis.

Lupus science & medicine·2022

Related Experiment Video

Updated: May 13, 2026

A Computerized Functional Skills Assessment and Training Program Targeting Technology Based Everyday Functional Skills
07:31

A Computerized Functional Skills Assessment and Training Program Targeting Technology Based Everyday Functional Skills

Published on: February 13, 2020

7.0K

Methodological Innovation in Evaluating the Cost-Effectiveness of Simulation Training Combining Transfer

Zhehan Jiang1, Hao Hang2, Xinyu Wu3

  • 1Tenure-Track in Institute of Medical Education at Health Science Center of, Peking University and National Center for Health Professions Education Development of Peking University, Beijing, China.

Journal of Medical Education and Curricular Development
|August 14, 2025
PubMed
Summary
This summary is machine-generated.

This study found that 8 hours of VR simulation training optimizes medical education efficiency. Integrating cost-effectiveness metrics like TER and ITER can guide optimal training durations.

Keywords:
change-point analysiscost-effectiveisoperformance curvesimulationtransfer effectiveness ratio

More Related Videos

Creation of a High-Fidelity, Low-Cost, Intraosseous Line Placement Task Trainer via 3D Printing
11:45

Creation of a High-Fidelity, Low-Cost, Intraosseous Line Placement Task Trainer via 3D Printing

Published on: August 17, 2022

2.2K
Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training
05:04

Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training

Published on: August 9, 2024

1.1K

Related Experiment Videos

Last Updated: May 13, 2026

A Computerized Functional Skills Assessment and Training Program Targeting Technology Based Everyday Functional Skills
07:31

A Computerized Functional Skills Assessment and Training Program Targeting Technology Based Everyday Functional Skills

Published on: February 13, 2020

7.0K
Creation of a High-Fidelity, Low-Cost, Intraosseous Line Placement Task Trainer via 3D Printing
11:45

Creation of a High-Fidelity, Low-Cost, Intraosseous Line Placement Task Trainer via 3D Printing

Published on: August 17, 2022

2.2K
Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training
05:04

Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training

Published on: August 9, 2024

1.1K

Area of Science:

  • Medical Education
  • Health Informatics
  • Simulation Technology

Background:

  • Simulation-based medical education faces challenges with high costs and limited effectiveness evaluations.
  • There is a need for novel methods to assess the cost-effectiveness of simulation training.
  • This study addresses the feasibility concerns of simulation training in medicine.

Purpose of the Study:

  • To introduce a novel approach for assessing the cost-effectiveness of simulation training.
  • To determine the optimal duration of virtual reality (VR) training for medical students.
  • To maximize knowledge and skills transfer efficiency while minimizing costs.

Main Methods:

  • Utilized simulated data from 120 medical students across 6 training duration groups.
  • Employed four analytical methods: Transfer Effectiveness Ratio (TER), Incremental TER (ITER), isoperformance curves, and change-point analysis.
  • Evaluated time savings, individual gains, cost-effectiveness, and diminishing returns of VR training.

Main Results:

  • An overall TER of 0.66 indicated time savings per training unit.
  • Isoperformance curves identified a 4.5-minute minimum operative time threshold.
  • An inflection point at 8 VR training hours signaled diminishing returns on training investment.

Conclusions:

  • The integrated methodology provides a new framework for evaluating simulation training cost-effectiveness.
  • Simulation training can potentially reduce the time needed to achieve clinical competency.
  • Findings support optimizing medical simulation training strategies for better efficiency and cost-effectiveness.