Dataset Information

Association of healthcare worker behaviors with coronavirus disease 2019 (COVID-19) risk during four pandemic periods and characteristics associated with high-risk behaviors.

ABSTRACT: In a large healthcare worker cohort, we quantified the association between behaviors and risk of coronavirus disease 2019 (COVID-19) during different pandemic phases, adjusting for prior infection and vaccination. Individual characteristics, including personal concerns, were associated with these behaviors. Public health messaging should target high-risk populations and behaviors as the pandemic evolves.

SUBMITTER: Egbert ER

PROVIDER: S-EPMC9879855 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association of healthcare worker behaviors with coronavirus disease 2019 (COVID-19) risk during four pandemic periods and characteristics associated with high-risk behaviors.

Egbert Emily R ER Xiao Shaoming S Prochaska Erica E Ali S Omar SO Colantuoni Elizabeth E Gadala Avi A Koontz Danielle D Zhong Diana D Schumacher Christina M CM Sick-Samuels Anna C AC Debes Amanda K AK Milstone Aaron M AM

Antimicrobial stewardship & healthcare epidemiology : ASHE 20230117 1

In a large healthcare worker cohort, we quantified the association between behaviors and risk of coronavirus disease 2019 (COVID-19) during different pandemic phases, adjusting for prior infection and vaccination. Individual characteristics, including personal concerns, were associated with these behaviors. Public health messaging should target high-risk populations and behaviors as the pandemic evolves. ...[more]

PMID: 36714294

Similar Datasets

Project description:Background: Healthcare workers in the front line of diagnosis, treatment, and care of patients with coronavirus disease 2019 (COVID-19) are at great risk of both infection and developing mental health symptoms. This study aimed to investigate the following: (1) whether healthcare workers in general hospitals experience higher mental distress than those in psychiatric hospitals; (2) the role played by religion and alexithymic trait in influencing the mental health condition and perceived level of happiness of healthcare workers amidst the stress of the COVID-19 pandemic; and (3) factors that influence the resilience of healthcare workers at 6 weeks' follow-up. Methods: Four-hundred and fifty-eight healthcare workers were recruited from general and psychiatric hospitals, and 419 were followed-up after 6 weeks. All participants filled out the 20-item Toronto Alexithymia Scale, five-item Brief-Symptom Rating Scale, and the Chinese Oxford Happiness Questionnaire. Results: Under the stress of the COVID-19 pandemic, 12.3% of frontline healthcare workers in general hospitals reported having mental distress and perceived lower social adaptation status compared with those working in psychiatric hospitals. Christians/Catholics perceived better psychological well-being, and Buddhists/Taoists were less likely to experience mental distress. The results at 6 weeks of follow-up showed that the perceived lower social adaptation status of general hospital healthcare workers was temporary and improved with time. Christian/Catholic religion and time had independent positive effects on psychological well-being; however, the interaction of Christian/Catholic religion and time had a negative effect. Conclusions: Collectivism and individualism in the cultural context are discussed with regard to alexithymic trait and Buddhist/Taoist and Christian/Catholic religious faiths. Early identification of mental distress and interventions should be implemented to ensure a healthy and robust clinical workforce for the treatment and control of the COVID-19 pandemic.

Dataset Information

Association of healthcare worker behaviors with coronavirus disease 2019 (COVID-19) risk during four pandemic periods and characteristics associated with high-risk behaviors.

Publications

Association of healthcare worker behaviors with coronavirus disease 2019 (COVID-19) risk during four pandemic periods and characteristics associated with high-risk behaviors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets