Date of Award
May 2021
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Applied Psychology
Committee Member
Marissa L Shuffler
Committee Member
Thomas Britt
Committee Member
Emily L Hirsh
Abstract
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.
Recommended Citation
Smith, Jordan Gail, "Protecting Our Healthcare Heroes: Using Latent JD-R Profiles to Predict Burnout in Emergency Medicine Clinicians During the COVID-19 Pandemic" (2021). All Theses. 3564.
https://open.clemson.edu/all_theses/3564