Perceptions of Risk, Work, and Lifestyle Changes on Mental Health of Healthcare Workers Amidst the COVID-19 Pandemic.
Awatef ErgaiLeeAnna SpivaLin LiRyan BreshearsGinny ZhanPublished in: International journal of environmental research and public health (2022)
The COVID-19 outbreak is significantly affecting the mental health of healthcare workers worldwide. This study aims to investigate the mental health outcomes of healthcare workers in a health system located in southeastern US during the first peak of the pandemic and examine the association of specific factors on the mental well-being of healthcare workers. A cross-sectional survey of 388 healthcare workers was conducted. Data were collected using a 79-item questionnaire, which included the Patient Health Questionnaire (PHQ-9) instrument, the 7-item Generalized Anxiety Disorder (GAD-7) instrument, and the 22-item Impact of Event Scale-Revised (IES-R), to assess symptoms of depression, anxiety, and general distress, respectively. Data were analyzed using descriptive, bivariate, and multivariate statistics. Accordingly, 30.1%, 28.7%, and 39.4% of respondents reported depression, anxiety, and distress symptoms, respectively. Younger workers and females reported higher mental symptomologies. We identified significant, nontraditional factors associated with depression and anxiety symptoms among healthcare workers: healthcare procedure change, concern of exposing family to COVID-19, number of missed shifts, and access to psychological resources/services. These findings emphasize the importance of providing the proper training to reduce concerns of exposing family members and psychological interventions to promote mental health well-being for healthcare workers during the stressful COVID-19 pandemic.
Keyphrases
- mental health
- sleep quality
- psychometric properties
- healthcare
- physical activity
- depressive symptoms
- coronavirus disease
- sars cov
- mental illness
- cross sectional
- electronic health record
- primary care
- big data
- data analysis
- metabolic syndrome
- patient reported outcomes
- cardiovascular disease
- case report
- weight loss
- risk assessment
- machine learning
- affordable care act