Date of Award

May 2021

Document Type


Degree Name

Master of Science (MS)


Applied Psychology

Committee Member

Marissa L Shuffler

Committee Member

Thomas Britt

Committee Member

Emily L Hirsh


Burnout—a phenomenon characterized by emotional exhaustion, cynicism, and negative self-evaluations—is a very concerning and prevalent issue among clinicians, especially those in emergency medicine. Preliminary research conducted at the start of COVID-19 has noted that frontline clinicians are experiencing elevated rates of depression, anxiety, and fatigue, making them susceptible to burnout. In an effort to understand more about clinician burnout during COVID-19, the present study used Latent Profile Analysis (LPA) to examine what profiles containing combinations of job demands and job resources exist within emergency medicine clinicians and which profiles—if any—are predictive of emergency medicine clinician burnout during COVID-19. An employee survey of emergency medicine clinicians was used to conduct the exploratory LPA and find a best-fitting solution. Results revealed five unique JD-R profiles: Meaningful Work-Low Job Demands (MW-LJD), Autopilot, Burnout Risk, Sufficient Resources, and Meaningful Work-High Job Demands (MW-HJD). Using mean burnout scores and the BCH method, patterns of job demands and resources arose that revealed what JD-R combinations may lead to clinicians being more or less susceptible to burnout. Overall, the latent profiles differed on burnout scores, with Burnout Risk having the highest and Sufficient Resources having the lowest average burnout score. These differences in burnout scores, particularly between the extreme ends previously mentioned, indicates that the profiles could be used to predict clinician burnout. The findings of this study add to the limited understanding of how burnout can manifest in emergency medicine clinicians during a pandemic. This information could be used by organizations to identify clinicians who are at risk of burnout as well to design and implement interventions that are data-driven, in order to more accurately prevent burnout and reduce the strain that results from job stressors.



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.