A randomized controlled trial on 2 simulation-based training methods in radiology: effects on radiologic technology student skill in assessing image quality

Simul Healthc. 2013 Dec;8(6):382-7. doi: 10.1097/SIH.0b013e3182a60a48.

Abstract

Introduction: A simulator for virtual radiographic examinations was developed. In the virtual environment, the user can perform and analyze radiographic examinations of patient models without the use of ionizing radiation. We investigated if this simulation technique could improve education of radiology technology students. We compared student performance in the assessment of radiographic image quality after training with a conventional manikin or with the virtual radiography simulator.

Methods: A randomized controlled experimental study involving 31 first-year radiology technology students was performed. It was organized in 4 phases as follows: (I) randomization to control or experimental group based on the results of an anatomy examination; (II) proficiency testing before training; (III) intervention (control group, exposure and analysis of radiographic images of the cervical spine of a manikin; experimental group, exposure and analysis of the cervical spine images in the virtual radiography simulator); and (IV) proficiency testing after training.

Results: The experimental group showed significantly higher scores after training compared with those before training (P < 0.01). A linear mixed-effect analysis revealed a significant difference between the control and experimental groups regarding proficiency change (P = 0.01).

Conclusions: Virtual radiographic simulation is an effective tool for learning image quality assessment. Simulation can therefore be a valuable adjunct to traditional educational methods and reduce exposure to x-rays and tutoring time.

Publication types

  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Clinical Competence / standards*
  • Computer Simulation
  • Education, Medical, Undergraduate / methods*
  • Educational Measurement
  • Humans
  • Manikins
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Radiographic Image Interpretation, Computer-Assisted / standards
  • Sweden
  • Technology, Radiologic / education*