CCE Theses and Dissertations
Medical Decision Making Under Stress-Evaluating the Role of Computerized Medical Simulation Education
Date of Award
2005
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Information Systems (DISS)
Department
Graduate School of Computer and Information Sciences
Advisor
Getrude W. Abramson
Committee Member
Maxine S. Cohen
Committee Member
Helen St. Aubin
Abstract
In an emergency, cognitive ability, skill performance, and decision making skills of medical personnel are often impaired due to the physical and psychological effects of stress created by the emergency event itself. Computerized human patient simulators hold the potential of enabling personnel to recreate the cognitive, psychomotor, and affective demands of a real life medical emergency without putting patients or personnel at risk. While previous research has demonstrated the potential of simulation-based instruction to improve cognitive and psychomotor learning outcomes, there has been no attention focused on affective learning domains and performance outcomes. Repeated practice in a realistic simulation training environment has the potential to decrease the stress response of personnel in an emergency, blunt the effects of skill degradation due to stress, and increase the performance capacity of medical personnel in an actual emergency.
In this study, senior anesthesiology nursing residents participated in a series of computerized patient simulation scenarios in which overall medical performance and physiological and psychological indicators of stress were assessed. Physiological measures included noninvasive measures of heart rate, blood pressure, and salivary cortisol level. Psychological measurements included the State-Trait Anxiety Inventory (STAT) and two Likert-scale responses to the subject's perceived level of stress and level of confidence. Because of the individual variation in response to stress, each subject served as their own control. Fifty-four subjects participated in the study. A random sample of 16 subjects participated in a baseline nonemergency simulation scenario. All 54 subjects then participated in a pre- and post-intervention simulated emergency scenario. Between the two scenarios, each subject received 16 hours of simulation-based instruction in the management of anesthesia emergencies and stress inoculation training. Subjects showed a significant increase in all parameters in the pre-intervention emergency scenario when compared to the nonemergency baseline scenario. Equally, all subjects showed a significant increase in parameters during the pre-intervention scenario when compared to that during post-intervention scenario. However, all of the parameters during the post-intervention scenario showed significantly less response to stress than during the pre-intervention scenario. Additionally, ratings for performance showed a significant increase in the post-intervention scenario when compared to performance during the pre-intervention scenario. The research demonstrates that computerized human patient simulation is capable of replicating the demands of a real emergency. The study was able to validate an improvement in medical performance and decrease in responsiveness to stress. The research appears to be the first to confirm the utility of simulation-based instruction in mitigating the physical and psychological effects of stress, created by an emergency event itself. Equally important, the participants reported a decreased perception of stress and an increased level of confidence following the intervention. The combination of stress inoculation training and simulation-based instruction appears to an effective strategy for improving cognitive, psychomotor and affective learning and performance outcomes. Further study in a wider population and evaluation of the duration of the intervention is warranted.
NSUWorks Citation
Jeffrey A. Groom. 2005. Medical Decision Making Under Stress-Evaluating the Role of Computerized Medical Simulation Education. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, Graduate School of Computer and Information Sciences. (552)
https://nsuworks.nova.edu/gscis_etd/552.