Cognitive Components Predict Virtual Reality-Induced Analgesia: Repeated Measures in Healthy Subjects

Research output: Contribution to journalArticlepeer-review

Abstract

Virtual reality (VR) is an advanced and useful technology in the distraction from pain. The efficacy of VR for reducing pain is well established. Yet, the literature analyzing the unique attributes of VR which impact pain reduction is scarce. The present study evaluated the effect of two VR environments on experimental pain levels. Both VR environments are games used with an EyeToy application which is part of the video capture VR family. The VR environments were analyzed by expert occupational therapists using a method of activity analysis, allowing for a thorough evaluation of the VR activity performance requirements. The VR environments were found to differ in the cognitive load (CL) demands they apply upon subjects. Sixty-two healthy students underwent psychophysical thermal pain tests, followed by exposure to tonic heat stimulation under one of three conditions: Low CL (LCL) VR, high CL (HCL) VR, and control. In addition, following participation in VR, the subjects completed a self-feedback inventory evaluating their experience in VR. The results showed significantly greater pain reduction during both VR conditions compared to the control condition (p = 0.001). Hierarchical regression revealed cognitive components which were evaluated in the self-feedback inventory to be predictive factors for pain reduction only during the high cognitive load (HCL) VR environment (20.2%). CL involved in VR may predict the extent of pain decrease, a finding that should be considered in future clinical and laboratory research.

Original languageEnglish
Article number70
JournalFrontiers in Robotics and AI
Volume4
DOIs
StatePublished - 4 Jan 2018

Bibliographical note

Publisher Copyright:
© Copyright © 2018 Demeter, Pud and Josman.

Keywords

  • activity analysis
  • cognitive load
  • environments
  • experimental pain
  • virtual reality

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence

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