Psychological responses among nurses caring for patients with COVID-19: a comparative study in China

Abstract

Frontline healthcare nurses devoted themselves to deal with the outbreak of COVID-19, saving many lives. However, they are under incredible unknown psychological pressures with a considerable risk of infection. In this study, a self-administered questionnaire was used to survey 593 frontline nurses in Wuhan City and non-Hubei provinces for psychological responses from March 1 to March 10, 2020. Compared with nurses outside Hubei Province, those working in Wuhan were more likely to feel physically and mentally exhausted. Their probable depression and anxiety were significantly higher than those of nurses outside Hubei province (31.2%, 18.3% vs. 13.8%, 5.9%). Correspondingly, the depressive symptoms were more often reported in the Wuhan group (70.8% vs. 41.4%). Although Wuhan received wishes, concerns, and abundant psychological and material resources from all of the world, the survey-based study found that frontline nurses in Wuhan still had higher depression and anxiety with less social support compared with nurses from non-Hubei provinces. Unexpectedly, only 4.0% of nurses have sought psychological assistance. These findings suggested that the short-term psychological impact of frontline nurses in Wuhan during the COVID-19 outbreak was extremely high compared with nurses outside Hubei Province. This research enlightened the efficient integration of psychological resources, the optimization of the nurse emergency psychological assistance system, and the mental health care of medical staff during the outbreak of epidemics.

RETRACTED: Mental Health Identification of Children and Young Adults in a Pandemic Using Machine Learning Classifiers

“…The effect of COVID-19 as well as its limitation rules on the researched group has been investigated in a number of studies (McKune et al, 2021;Qin et al, 2021;Błaszczyk et al, 2022). Multivariable logistic regression models were used in many research to: (i) examine the possible risk factors defined as selfemotional problems (Ren H. et al, 2021) and (ii) compare the impact of COVID-19 assessments (Gomathi et al, 2021).…”

An Explainable Machine Learning Approach for COVID-19’s Impact on Mood States of Children and Adolescents during the First Lockdown in Greece

“…A plethora of studies have been conducted to examine the impact of COVID-19 and its restriction policies on the studied population [ 6 , 7 , 8 ]. Specifically, multivariable logistic regression analyses were adopted in various studies to: (i) identify the correlations of mental health with other factors [ 9 , 10 , 11 ], such as sociodemographic features [ 4 , 12 , 13 , 14 ] and/or school aspects [ 14 ] or health behaviors [ 15 ], mostly on university students [ 16 , 17 , 18 ]; (ii) assess the prevalence and the risk factors associated with self-reported psychological distress [ 19 ]; and (iii) evaluate the effects of COVID-19 measures upon the mental health of children and adolescents, with or without pre-existing diagnoses [ 20 ]. Binomial or binary logistic regression analysis was used to: (i) identify sleeping problems of adolescents and young adults (12–29 years) during the pandemic [ 21 , 22 ]; (ii) assess depression and anxiety amongst university students [ 23 ]; and (iii) examine the prevalence of anxiety among children and the possible association to COVID-19 [ 24 ].…”

Negative and positive psychological experience of frontline nurses in combatting COVID‐19: A qualitative study

“…In this study, loss of appetite was observed. Previous study showed that nurses in Wuhan city had higher score in poor appetite or overeating than nurses in other cities (Ren et al, 2021 ). These health issues were associated with the negative psychological experiences and might further the conditions.…”