How the gender of a victim character in a virtual scenario created to learn CPR protocol affects student nurses' performance

Comput Methods Programs Biomed. 2018 Aug:162:233-241. doi: 10.1016/j.cmpb.2018.05.019. Epub 2018 May 22.

Abstract

Background and objective: Virtual simulations recreate scenarios where student nurses can practice procedures in a safe and supervised manner and with no risk to the patient. Virtual scenarios include digital characters that reproduce human actions. Generally, these characters are modeled as males and restricted roles are assigned to females. Our objective is to evaluate how the character gender of a victim in a scenario created to practice the cardiopulmonary resuscitation protocol (CPR) affects performance of student nurses.

Methods: Three virtual scenarios with cardiac arrest victims modeled as males or females were assigned to 41 students of the Nursing Faculty to practice the CPR protocol. We evaluated student performance with respect to the time to remove clothes, the time to perform the CPR maneuver, and the hands position for CPR. Chi-square, Fisher exact, and Mann-Whitney U were used to test primary outcome measures in the experimental design of victim character sex (male vs. female) and student sex (men vs. women).

Results: The analysis performed did not find statistically differences in time to remove clothes or in time to start CPR. With respect to hands placement we also did not find significant difference in any of the cases.

Conclusion: Nurse student actions are not influenced by the character gender of the victim. Excellent results with respect to hands placement to start CPR are obtained. Virtual scenarios can be a suitable strategy to reduce gender differences in gender sensitive situations such as CPR performance.

Keywords: Cardiopulmonary resuscitation; Character gender; Nursing informatics; Virtual environments.

MeSH terms

  • Cardiopulmonary Resuscitation / education*
  • Computer Simulation
  • Faculty, Nursing*
  • Female
  • Heart Arrest
  • Humans
  • Learning
  • Male
  • Patient Simulation*
  • Sex*
  • Software
  • Students, Nursing*