• *Ting Li and Xichenhui Qiu contributed equally for this manuscript
Introduction and objective:
From March 2022, China has been in the rapid progressing stage of the Omicron outbreak. However, the mental status of clinical nurses against infection by the Omicron variant of COVID-19 has been not explored. Therefore, a nationwide online investigation with a larger sample size was conducted to explore the mental status of Chinese frontline clinical nurses, and its influencing factors using sound validated and reliable measurements.

Material and methods:
A cross-sectional study was conducted, and 1,204 clinical nurses fighting the Omicron outbreak were recruited across various provinces of China.

The mean age of the nurses was 30.43 (SD=6.59) years. The majority were female. The rates of these nurses with depression, anxiety, stress, and insomnia symptoms were 29.2%, 37.2%, 19.1%, and 48.8%, respectively. The variables of department, insomnia, fear with COVID-19, turnover intention, job burnout, work coping style, and public recognition of nursing, were significant factors influencing the mental status of clinical nurses.

The Chinese clinical nurses fighting the Omicron variant of COVID-19 had a similar level of depression and anxiety, a higher level of insomnia, and a lower level of stress, in comparison with nurses globally who experienced the initial period of the pandemic. Targeted investigation and interventions are urgently needed for Chinese frontline clinical nurses with high levels of anxiety, depression and insomnia, who fought against infection by Omicron. Much more professional advocacy is strongly recommended during control of the pandemic and recovery to consolidate the role and influence of nurses. The contribution and visibility of nursing should be recognized not only by the medical professionals, but by the public in general.

Xujuan Zheng was supported by the General Program of Stable Support Plan for Universities in Shenzhen City (Grant No. 20200804101756002); Xichenhui Qiu was supported by the Shenzhen Natural Science Fund (the Stable Support Plan Program), China (Grant No: 8940206-0221).
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