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Predictive factors of anxiety and depression among nurses fighting coronavirus disease 2019 in China.
Pang, Yongli; Fang, Hengying; Li, Lili; Chen, Minhua; Chen, Yuanli; Chen, Miaoxia.
  • Pang Y; Department of Nursing, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Fang H; Department of Nursing, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Li L; Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Chen M; Department of Psychology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Chen Y; Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Chen M; Department of Nursing, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Int J Ment Health Nurs ; 30(2): 524-532, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1045710
ABSTRACT
Anxiety and depression are common mental illnesses among nurses fighting coronavirus disease 2019 (COVID-19). However, the precise factors that affect anxiety and depression in this population require further evaluation. This study aimed to explore factors associated with anxiety and depression among nurses fighting COVID-19 in China. We used convenience sampling to recruit 282 nurses fighting COVID-19 in three hospitals. Participants were questioned about demographic characteristics, daily working time, daily sleep duration, sleep quality, anxiety, depression, resilience, and coping styles. Linear regression analysis indicated that resilience (ß = -0.217, P < 0.001), positive coping style (ß = -0.281, P < 0.001), negative coping style (ß = 0.395, P < 0.001), and sleep quality (ß = 0.153, P = 0.010) were predictive factors for anxiety, and the model explained 44.20% (P < 0.001) of variability. Resilience (ß = -0.239, P < 0.001), positive coping style (ß = -0.222, P < 0.001), negative coping style (ß = 0.152, P < 0.001), and sleep quality (ß = 0.104, P = 0.003) were identified as explanatory factors for depression, and the model explained 34.50% (P < 0.001) of variability. The present study suggested that resilience, coping styles, and sleep quality could account for an individual's levels of anxiety and depression.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Anxiety / Depression / COVID-19 / Nursing Staff, Hospital / Occupational Diseases Type of study: Experimental Studies / Observational study / Prognostic study / Qualitative research / Randomized controlled trials Limits: Adult / Humans / Middle aged / Young adult Country/Region as subject: Asia Language: English Journal: Int J Ment Health Nurs Journal subject: Nursing / Psychology Year: 2021 Document Type: Article Affiliation country: Inm.12817

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Anxiety / Depression / COVID-19 / Nursing Staff, Hospital / Occupational Diseases Type of study: Experimental Studies / Observational study / Prognostic study / Qualitative research / Randomized controlled trials Limits: Adult / Humans / Middle aged / Young adult Country/Region as subject: Asia Language: English Journal: Int J Ment Health Nurs Journal subject: Nursing / Psychology Year: 2021 Document Type: Article Affiliation country: Inm.12817