Moral injury and psychosocial functioning in health care workers during the COVID-19 pandemic.

Studies of moral injury among nonmilitary samples are scarce despite repeated calls to examine the prevalence and outcomes of moral injury among civilian frontline workers. The purpose of this study was to describe the prevalence of moral injury and to examine its association with psychosocial functioning among health care workers during the COVID-19 pandemic. We surveyed health care workers (N = 480), assessing exposure to potentially morally injurious events (PMIEs) and psychosocial functioning. Data were analyzed using latent class analysis (LCA) to explore patterns of PMIE exposure (i.e., classes) and corresponding psychosocial functioning. The minimal exposure class, who denied PMIE exposure, accounted for 22% of health care workers. The moral injury-other class included those who had witnessed PMIEs for which others were responsible and felt betrayed (26%). The moral injury-self class comprised those who felt they transgressed their own values in addition to witnessing others' transgressions and feeling betrayed (11%). The betrayal-only class included those who felt betrayed by government and community members but otherwise denied PMIE exposure (41%). Those assigned to the moral injury-self class were the most impaired on a psychosocial functioning composite, followed by those assigned to the moral injury-other and betrayal-only classes, and finally the minimal exposure class. Moral injury is prevalent and impairing for health care workers, which establishes a need for interventions with health care workers in organized care settings. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Identification of county-level health factors associated with COVID-19 mortality in the United States.

Many studies have investigated causes of COVID-19 and explored safety measures for preventing COVID-19 infections. Unfortunately, these studies fell short to address disparities in health status and resources among decentralized communities in the United States. In this study, we utilized an advanced modeling technique to examine complex associations of county-level health factors with COVID-19 mortality for all 3141 counties in the United States. Our results indicated that counties with more uninsured people, more housing problems, more urbanized areas, and longer commute are more likely to have higher COVID-19 mortality. Based on the nationwide population-based data, this study also echoed prior research that used local data, and confirmed that county-level sociodemographic factors, such as more Black, Hispanic, and older subpopulations, are attributed to high risk of COVID-19 mortality. We hope that these findings will help set up priorities on high risk communities and subpopulations in future for fighting the novel virus.