Prevalence and correlates of depression and anxiety among nursing staff in the post-COVID-19 era: a cross-sectional study from southern Iran.

BACKGROUND

The COVID-19 pandemic had a significant negative impact on the mental health of healthcare workers globally, with some studies reporting increase in depression and anxiety rates. While the acute phase of the pandemic has subsided, concerns remain about the long-term psychological effects on frontline staff. This study aimed to assess the prevalence and correlates of depression and anxiety among nursing staff in the post-COVID-19 era.

METHODS

This cross-sectional study was conducted between January 2023 and March 2023 among nursing staff at government teaching hospitals affiliated with Shiraz University of Medical Sciences in southern Iran. All nursing staff willing to participate and provide written informed consent were included. Participants completed questionnaires assessing demographics (age, gender, marital status, education level) and using Beck's Depression and Anxiety Inventories. Nurses who had left the workplace or submitted incomplete questionnaires were excluded.

RESULTS

A total of 890 nurses participated. The mean age was 34.89 ± 7.84 years, and 88% were female. The mean depression and anxiety scores were 20.79 ± 13.69 and 22.0 ± 13.38, respectively, with 26.7% exhibiting severe depression and 38.4% experiencing severe anxiety. Stepwise regression analysis revealed significant associations between anxiety scores and psychiatric drug usage (P < 0.001), working hours per week (P < 0.001), department (P = 0.02), and gender (P = 0.028). Similarly, depression scores were significantly correlated with psychiatric drug usage (P < 0.001), working hours per week (P = 0.001), and gender (P = 0.018).

CONCLUSION

The prevalence and severity of anxiety and depression among nursing staff in this post-COVID-19 setting appear elevated compared to pre-pandemic levels/national averages. These findings highlight the need for specific organizational and policy interventions. However, interpretation should consider the crosssectional design, sampling bias, and absence of prepandemic baseline data.