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This study evaluated post traumatic stress disorder (PTSD) among frontline USphysicians (treating COVID-19 patients) in comparison with second-linephysicians (not treating COVID-19 patients), and identified the significanceand patterns of factors associated with higher PTSD risk. A cross-sectional,web-based survey was deployed during August and September, 2020, to practicingphysicians in the 18 states with the largest COVID-19 cases. Among 1,478responding physicians, 1,017 completed the PTSD Checklist (PCL-5). First, thePCL-5 was used to compare symptom endorsement between the two physician groups.A greater percentage of frontline than second-line physicians had clinicallysignificant endorsement of PCL-5 symptoms and higher PCL-5 scores. Second,logistic regression and seven nonlinear machine learning (ML) algorithms wereleveraged to identify potential predictors of PTSD risk by analyzing variableimportance and partial dependence plots. Predictors of PTSD risk includedcognitive/psychological measures, occupational characteristics, workexperiences, social support, demographics, and workplace characteristics.Importantly, the final ML model random forest, identified patterns of bothdamaging and protective predictors of PTSD risk among frontline physicians. Keydamaging factors included depression, burnout, negative coping, fears ofcontracting/transmitting COVID-19, perceived stigma, and insufficient resourcesto treat COVID-19 patients. Protective factors included resilience and supportfrom employers/friends/family/significant others. This study underscores thevalue of ML algorithms to uncover nonlinear relationships amongprotective/damaging risk factors for PTSD in frontline physicians, which maybetter inform interventions to prepare healthcare systems for futureepidemics/pandemics.

The Invisible COVID-19 Crisis: Post-Traumatic Stress Disorder Risk Among Frontline Physicians Treating COVID-19 Patients