Frontiers in Psychology (Aug 2023)

Prevalence, correlates, and network analysis of depression and its associated quality of life among ophthalmology nurses during the COVID-19 pandemic

  • Zi-Han Liu,
  • Yue Li,
  • Zi-Rong Tian,
  • Yan-Jie Zhao,
  • Teris Cheung,
  • Zhaohui Su,
  • Pan Chen,
  • Pan Chen,
  • Chee H. Ng,
  • Feng-Rong An,
  • Yu-Tao Xiang,
  • Yu-Tao Xiang

DOI
https://doi.org/10.3389/fpsyg.2023.1218747
Journal volume & issue
Vol. 14

Abstract

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BackgroundNurses in Ophthalmology Department (OD) had a high risk of infection during the novel coronavirus disease 2019 (COVID-19) pandemic. This study examined the prevalence, correlates, and network structure of depression, and explored its association with quality of life (QOL) in Chinese OD nurses.MethodsBased on a cross-sectional survey, demographic and clinical data were collected. Depression was measured with the 9-item Self-reported Patient Health Questionnaire (PHQ-9), and QOL was measured using the World Health Organization Quality of Life Questionnaire-brief version (WHOQOL-BREF). Univariate analyses, multivariate logistic regression analyses, and network analyses were performed.ResultsAltogether, 2,155 OD nurses were included. The overall prevalence of depression among OD nurses was 32.71% (95%CI: 30.73–34.70%). Multiple logistic regression analysis revealed that having family or friends or colleagues who were infected (OR = 1.760, p = 0.003) was significantly associated with higher risk of depression. After controlling for covariates, nurses with depression reported lower QOL (F(1, 2,155) = 596.784, p < 0.001) than those without depression. Network analyses revealed that ‘Sad Mood’, ‘Energy Loss’ and ‘Worthlessness’ were the key central symptoms.ConclusionDepression was common among OD nurses during the COVID-19 pandemic. Considering the negative impact of depression on QOL and daily life, regular screening for depression, timely counselling service, and psychiatric treatment should be provided for OD nurses, especially those who had infected family/friends or colleagues. Central symptoms identified in network analysis should be targeted in the treatment of depression.

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