Factors Predicting the Mental Health Status of Registered Nurses during the COVID-19 Pandemic

Abstract

Introduction Registered nurses are frontline healthcare workers in the Covid-19 pandemic, which spread rapidly and lasted over three years, resulting in a significant increase in the number of patients. As a result, nurses experience a high risk of Covid -19. A review of the literature reveals that nurses working during the pandemic have high rates of depression and anxiety. Long working hours and close contact with patients have led to depression, anxiety, and stress among nurses, which affects their quality of life and increases the risk of Post-Traumatic Stress Disorder. This also diminishes their ability to provide effective patient care. Previous studies have found that the fear of being infected and spreading within family, coping strategies, social support, and resilience are factors that affect nurses’ mental health status. However, studies in Thailand are lacking in examining factors predicting mental health status among nurses working in a private hospital.

Objectives This study aimed to examine the predictive factors of mental health status among registered nurses during the Covid-19 pandemic, including the fear of being infected and spreading within family, coping strategies, resilience, and social support.

Design This study is a cross-sectional descriptive research. The conceptual framework of the study applies Lazarus and Folkman’s psychological stress and coping theory, which explains that stress occurs when a person interacts with the environment. Whether stress arises or not depends on how the person appraises the situation and its potential impact on them. The process begins with primary appraisal. If the situation is appraised as perceived stress, secondary appraisal is then used to identify sources of social support for coping, problem-solving, and adaptation to the situation. The person will then choose an appropriate coping strategy.

Methodology The participants consisted of 113 registered nurses working at a private hospital in Bangkok, selected through a convenience sampling based on the following inclusion criteria: 1) holding a nursing and midwifery professional license, Class 1, 2) aged between 22 and 60 years, and 3) not on maternity leave. The sample size was determined using the power analysis principle with the G*Power program, setting a power of .80 and a significance level of .05, with an effect size of .11. Data were collected between December 2022 and February 2023 through an online platform. The research instruments included: 1) a personal information questionnaire, 2) the Depression Anxiety Stress Scales (DASS 21), 3) the Anxiety Toward Covid-19 questionnaire, 4) the BRIEF COPE inventory, 5) the Connor-Davidson resilience scale, and 6) the Multidimensional scale of perceived social support (MSPSS), with Cronbach’s alpha coefficient of .93, .90, .92, .81, and .81, respectively. Data were analyzed using descriptive statistics and Multiple linear regression analysis.

Results The participants had a mean age of 35.37 years (SD = 7.35), with the majority of female (97.3%). Most participants had a bachelor’s degree (97.9%), did not have any chronic diseases (90.3%), practiced Buddhism (94.7%), were single (77.0%), worked 41-60 hours per week (91.2%), lived alone (70.8%), did not provide direct care for patients with Covid-19 (77.0%), and had received infection control training (85.0%). The participants had depression at 10.6%, anxiety at 12.4%, and stress at 9.7%. Coping strategies were found to predict depression, anxiety, and stress (β = .290, p < .05; β = .375, p < .05; β = .415, p < .05). Resilience was found to predict depression and stress (β = -.203, p < .05; β = -.214, p < .05). Fear of being infected and spreading within family, and social support, were found to predict depression (β = .211, p < .05; β = -.267, p < .05).

Recommendation The findings of this study can be used as information for nursing administrators to develop strategies for prevention of mental health problems among nurses in the future pandemics or emerging infectious diseases.