Predictors of anxiety and depressive symptoms among Greek nurses

Nikolaou, Ioannis, Alikari, Victoria, Tzavella, Foteini, Zyga, Sofia, Tsironi, Maria and Theofilou, Paraskevi (2020) Predictors of anxiety and depressive symptoms among Greek nurses. Journal of Health Sciences, 10 (1). pp. 90-98. ISSN 2232-7576

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Official URL: https://doi.org/10.17532/jhsci.2020.856

Abstract

Introduction: The increasing needs of an aging population and the shortage of nursing personnel have a negative impact on the workload of nurses increasing the risk of developing anxiety and depressive symptoms. This research aims to evaluate the strength of occupational and demographic characteristics in predicting anxiety and depression among nurses.

Methods: In this cross-sectional study, a sample of 164 Greek nurses from three hospitals employed full-time participated. Anxiety and depression were measured using the validated Greek versions of the State-Trait Anxiety Inventory – State and Trait Y forms and the Centre for Epidemiological Studies Depression scale, respectively. The statistical analysis of the data was performed using the statistical program SPSS version 19.0. The statistical significance level was set up at 0.05.

Results: Younger nurses, unmarried, those without children, those with less work experience, and working in the general medical units were more vulnerable. The average number of patients per nurse during the day shift may not predict anxiety or depression scores. Strong positive correlation between state and trait anxiety (r [162] = 0.77, p < 0.001), state anxiety and depression (r [162] = 0.62, p < 0.001), and trait anxiety and depression (r [162] = 0.63, p < 0.001) was revealed.

Conclusion: Anxiety and depression are prevalent among nurses. Demographic and working characteristics are strong predictors of anxiety and depression among nurses. Nursing managers should emphasize emotional interventions (cognitive behavioral therapy, training on emotional intelligence, strengthening coping skills, and development of high resilience) in supporting nurses at higher risk.


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