Assessing psychometric challenges and fatigue during the COVID-19 pandemic.

Environmental hazards and/or pandemics may push humans to use different protective methods to maintain their well-being. This study aimed to identify populations vulnerable to psychometric challenges and fatigue during the Coronavirus Disease (COVID-19) pandemic in Kazakhstan. A total of 1,592 participants were recruited and asked to complete the Multidimensional Fatigue Inventory-20 (MFI-20). Participants were classified according to gender and age. Data were analyzed using the Chi-square test (x2) and MedCalc to detect the odds of MFI-scales with a score ≥12 in women compared to men. Young women had significantly higher odds (OR) of reduced activity (OR 2.4, p<0.0001), physical (OR 2.5, p<0.0001), and mental fatigue (OR 3.4, p<0.0001) than young men. Middle-aged women had significantly higher odds of general fatigue (OR 2.1; p<0.0001), reduced motivation (OR 2.1, p<0.0001), physical (OR 2.1, p<0.0001), and mental fatigue (OR 1.9, p<0.0001) than did middle-aged men. Elderly women had significantly higher odds of general fatigue (OR 3.6, p<0.0001), reduced motivation (OR 3.5, p<0.0001), and physical fatigue (OR 3.5, p<0.0001) than men in the same age category. The study highlights that women were more susceptible, with significantly increased odds of experiencing various aspects of fatigue syndrome compared to men during the COVID-19 pandemic in Kazakhstan. Therefore, it is necessary to investigate individual behavioral changes to help identify vulnerable populations and provide relevant evidence for developing protocols and guidelines during pandemics and/or outbreaks.

The physical and mental health of the medical staff in Wuhan Huoshenshan Hospital during COVID-19 epidemic: A Structural Equation Modeling approach.

INTRODUCTION: Early in the epidemic of coronavirus disease 2019, the Chinese government recruited a proportion of healthcare workers to support the designated hospital (Huoshenshan Hospital) in Wuhan, China. The majority of front-line medical staff suffered from adverse effects, but their real health status during COVID-19 epidemic was still unknown. The aim of the study was to explore the latent relationship of the physical and mental health of front-line medical staff during this special period. METHODS: A total of 115 military medical staff were recruited between February 17th and February 29th, 2020 and asked to complete questionnaires assessing socio-demographic and clinical characteristics, self-reported sleep status, fatigue, resilience and anxiety. RESULTS: 55 medical staff worked within Intensive Care and 60 worked in Non-intensive Care, the two groups were significantly different in reported general fatigue, physical fatigue and tenacity (P<0.05). Gender, duration working in Wuhan, current perceived stress level and health status were associated with significant differences in fatigue scores (P<0.05), the current perceived health status (P<0.05) and impacted on the resilience and anxiety of participants. The structural equation modeling analysis revealed resilience was negatively associated with fatigue (ß=-0.52, P<0.01) and anxiety (ß=-0.24, P<0.01), and fatigue had a direct association with the physical burden (ß=0.65, P<0.01); Fatigue mediated the relationship between resilience and anxiety (ß=-0.305, P=0.039) as well as resilience and physical burden (ß=-0.276, P=0.02). CONCLUSION: During an explosive pandemic situation, motivating the effect of protective resilience and taking tailored interventions against fatigue are promising ways to protect the physical and mental health of the front-line medical staff.

High fatigue and its associations with health and work related factors among female medical personnel at 54 hospitals in Zhuhai, China.

The present study aimed to investigate the prevalence of fatigue and determine factors associated with fatigue in female medical personnel. Based on a cross-sectional study, a total of 1608 female medical personnel at 54 hospitals in Zhuhai, China were recruited by a multistage stratified cluster sampling method. The Symptoms Checklist-90-Revised and Chalder Fatigue Scale were used to assess psychiatric symptoms and fatigue, respectively. Data regarding demographic, health, and work related variables were also collected. Multivariate logistic regression model was constructed to determine the influencing factors of fatigue. Approximately 83% of participants had experienced fatigue in the past week. The risk of fatigue was higher in aged 30-39 years old than older or younger participants; Longer sleeping time predicted a lower prevalence of fatigue (OR = .35), while tense physician-patient relationship predicted a higher prevalence of fatigue (OR = 1.77). Depression (OR = 1.76) and anxiety (OR = 1.96) were found related to fatigue. Additionally, fatigue was associated with marital status, occupation, health related factors (exercise, regular diet, and health status), and work related factors (hospital rank and turnover intention). These study findings might facilitate development and implementation of targeted interventions and preventive measures.