Methods
This is a cross-sectional, survey-based, national study conducted during
the COVID-19 pandemic from April 14, 2020 to April 25, 2020. The
self-administered, anonymous online survey collected demographic data
and mental health measurements from otolaryngology physicians from
academic institutions throughout the United States. Participation was
voluntary, and participants were allowed to terminate the survey at any
time. A REDCap (Research Electronic Data Capture) database was developed
specifically for this project and used to capture survey data. It was
accessible only to study personnel. This project was reviewed and
determined to qualify as quality improvement by the University of
Pennsylvania’s Institutional Review Board.
We contacted otolaryngology program directors via e-mail from all 109
allopathic academic programs in the US to disperse the survey to their
residents, fellows, and attendings. Demographic data were self-reported
by the participants, including sex (male or female), age, occupation
(attending physicians, fellows, resident physicians), and geographic
location. Date of projected peak resource utilization for each state was
obtained from the Institute for Health Metrics and Evaluation’sCOVID-19 Projections in order to categorize participants based on
the “Surge status” of their state.24 States reaching
their date of projected peak resource use during our study period were
in the “Surge”, while states that had not reached that date were “Pre
Surge,” and states that were already past that date were “Post
Surge.” Numbers of positive COVID-19 cases and numbers of COVID-19
deaths per state were obtained from the COVID Tracking Projectfrom date April 19, 2020, the midpoint of our study
period.25
We focused on symptoms of burnout, anxiety, distress, and depression for
all participants, using validated measurement
tools.26-30 The single-item Mini-Z burnout assessment
(range, 1-5) was used to assess burnout, with burnout defined as> 3.27,28 The 7-item Generalized
Anxiety Disorder (GAD-7) scale (range, 0-21) was used to assess symptoms
of anxiety over the past two weeks, with a scale of normal (0-4), mild
(5-9), moderate (10-14), and severe (15-21) anxiety.26A score of 10 has been reported to be a cut-off point for identifying
cases of GAD. The GAD-7 included a final question assessing the
“difficulty [these problems] made it for you to do your work, take
care of things at home, or get along with other people” (range, 0-3).
The 15-item Impact of Event Scale (IES; range, 0-75) was used to assess
symptoms of distress over the past seven days, with a scale of
subclinical (0-8), mild (9-25), moderate (26-43), and severe (44-75)
distress.29 A score of 27 has been reported as a
cut-off for risk of post-traumatic stress disorder
(PTSD).31 The IES total score was also divided into
two sub-scores: intrusion (range, 0-35) and avoidance (range, 0-40). Per
Horowitz et al., the intrusion sub-scores assessed symptoms of
“unbidden thoughts and images, troubled dreams, strong pangs or waves
of feelings, and repetitive behavior.”29 The
avoidance sub-score measured “ideational constriction, behavioral
inhibition and counterphobic activity, and awareness of emotional
numbness.”29 The 2-item Patient Health Questionnaire
(PHQ-2; range, 0-6), was used to assess symptoms of depression over the
past two weeks, with a score of 3 as the cut-off for a positive
depression screening requiring further evaluation with the more in-depth
PHQ-9.30 These categories were based on values
established in the literature.26-30
Data analysis was performed using R software version 3.6.3. The
difference in distribution of symptoms across multiple groups is tested
by the chi-square independence test (Table 2 ) and by the
nonparametric Wilcoxon rank sum test and Kruskal-Wallis test
(Table 3 ). To determine risk factors for severity of burnout,
anxiety, distress, and depression, multiple logistic regression models
were used (Table 4 ). The binary outcome variables were created
for anxiety (normal vs other categories) and for distress (subclinical
vs other categories). Type of physician, sex, age, surge status, and
number of positive cases were included in the model, while location and
number of deaths were found to be highly correlated with the number of
positive cases and therefore excluded to alleviate the issue of
collinearity. All tests were two-sided and the significance level α=0.05
was applied. 95% confidence intervals were constructed, where
applicable.