Objective To describe the condition of depression of the undergraduate nursing students in practice,and compare the differences of depression between male and female nursing students.Methods Using the Beck Depression Inventory (BDI) to investigate the undergraduate nursing students who were practicing in the Affiliated Hospital of Sun Yat-sen University from July 2011 to June 2012 and analyze the condition and gender-related differences of depression.Results The occurrence of depression was high in the undergraduate practical nurses(37.2％).The occurrence of depression in the male (41.2％)undergraduate practical nurses was higher than that in the female (34.6％) undergraduate practical nurses.The occurrence of depression was mostly light depression(16.3％) and middle depression (20.9％),no serious depression occurred.Conclusions The higher occurrence of depression in the undergraduate practical nurses and the gender-related differences signify the importance of psychological problems.

Objective To analyze the related factors of nursing risk in department of nephrology and to explore strategies of risk management.Methods Risk management was implemented to 39 nurses in department of nephrology of our hospital.The KAP scores,the incidence of nursing risk events,nursing complaints and patients' satisfaction degree before and after the implementation of nursing risk management were compared.Results After the implementation of nursing risk management,nurses' KAP score was significantly higher; the incidence of nursing risk events and complaints significantly reduced; patients' satisfaction degree to nursing were significantly higher compared with those before the implementation.Conclusions The implementation of nursing risk management can effectively improve the quality of nursing and reduce the incidence of nursing risk events.

Objective:To explore the mediating effect of resilience between perceived stress and insomnia in medical staff.Methods:A questionnaire survey was conducted among 1 163 medical staff. All subjects were assessed with the insomnia severity index (ISI), simplified Chinese version of Connor-Davidson resilience scale (CD-RISC-10) and perceived stress scale (PSS-10). SPSS 20.0 software was used for common method biases test, descriptive statistics, difference analysis, correlation analysis, hierarchical regression analysis, and SPSS PROCESS V3.4 was used for Bootstrap mediating effect.Results:①The perceived stress (16.28±6.35) was positively correlated with insomnia (6.14±5.80)( r=0.404, P<0.01), and psychological resilience was negatively correlated with insomnia and perceived stress in medical staff ( r=-0.279, P<0.01, r=-0.399, P<0.01). ②Psychological resilience played a partial mediating role between perceived stress and insomnia in medical staff, with the mediating effect as 0.051, accounting of 13.82% of the total effect. Conclusion:Psychological resilience can reduce the negative effects of perceived stress on sleep and is a protective factor for insomnia in medical staff. Clinically, reducing perceived stress and improving psychological resilience can reduce insomnia in medical staff.

【Objective:】 To explore the network characteristics of sleep quality and anxiety in first-line medical staff fighting against COVID-19, further understand the relationship between sleep quality and anxiety, and provide basis for intervention. 【Methods:】 Using the convenient sampling method, this paper used the Pittsburgh Sleep Quality Index (PSQI) and Self Rating Anxiety Scale (SAS) to conduct a questionnaire survey on the front-line medical staff who fought against the epidemic during the COVID-19. Network analysis was used to construct sleep quality and anxiety network, and R language was used for statistical analysis and visualization. 【Results:】 In the network of sleep quality and anxiety of first-line medical staff fighting against COVID-19, "sleep disorder" and "sleep quality", "unfortunate premonition" and "inability to sit still", "syncope" and "hand and foot tingling" were highly related. "Fatigue", "dizziness" and "panic" had the highest expected influence. "Sleep quality", "sleep disorder" and "fatigue" had the highest bridge expected influence. The average predictability value of all nodes was 0.778. 【Conclusion:】 This paper used network analysis to explore the sleep quality and anxiety of first-line medical staff fighting against COVID-19 and found that there was a unique correlation path between them. Intervention against core symptoms can ameliorate anxiety and sleep problems to the great extent, and provide guidance for improving the physical and mental health.