Nurses' mental workload and public health emergency response capacity in COVID-19 pandemic: A cross-sectional study.

AIMS: The aim of this study was to assess the level of mental workload of Chinese nurses through a latent profile analysis and to explore its relationship with public health emergency response capacity. DESIGN: A cross-sectional design with a convenience sample. METHODS: A convenience sample of nurses from five tertiary hospitals in Chengdu between May and December 2022. Demographic, work-related information, Nurse's version of NASA's Task Load Index Scale and Nurse's Public Health Emergency Response Capacity Scale were used in this study. RESULTS: The mean scores for mental workload and emergency response capacity for nurses were (57.19 ± 15.67) and (3.58 ± 0.77) respectively. We found that the mental workload of nurses fell into three potential categories. In addition, there were differences in psychological training and supply of epidemic prevention materials in the department among nurses with different mental workload subtypes. There was a moderate negative correlation between nurses' mental workload and public health emergency response capacity. CONCLUSION: Our results show that there is still a strong mental workload on a proportion of nurses, and enhanced psychological training and material supply support are beneficial in relieving nurses' mental workload. The better the nurses' capacity to cope with public health emergencies, the lower their mental workload. IMPACT: Nursing managers should pay ongoing attention to the mental workload status of nurses in the latter stages of a pandemic and individual differences in nurses' mental workload. In addition, nursing managers should be aware of the impact of public health emergency response capacity on nurses' mental workload. They can intervene in nurses mental workload from a new perspective. PATIENT OR PUBLIC CONTRIBUTION: 560 registered nurses participated in this study.

Effects of compassion satisfaction and compassion fatigue on posttraumatic growth of psychiatric nurses: A cross-sectional study.

AIMS: This study aimed to explore the effects of compassion satisfaction and compassion fatigue on the posttraumatic growth of psychiatric nurses. BACKGROUND: Psychiatric nurses' prolonged and repeated exposure to trauma and complex situations in the work environment can lead to negative emotions such as compassion fatigue, but they also experience positive consequences such as posttraumatic growth, and the relationship between compassion fatigue and posttraumatic growth is not unclear. METHODS: A total of 336 nurses from psychiatry departments of seven tertiary hospitals in Sichuan Province, China, were administered an online questionnaire. Participants were recruited through convenience sampling. The posttraumatic growth level was measured with the Simplified Chinese version of the Posttraumatic Growth Inventory. The Professional Quality of Life Scale-Chinese version was used to assess compassion satisfaction, burnout and secondary traumatic stress. T-test and one-way variance analysis, Pearson correlation analysis and hierarchical linear regression were used for data analysis. A STROBE checklist was used to guide the reporting of the research. RESULTS: Psychiatric nurses' posttraumatic growth is at a low level, influenced by demographic and occupational factors, whereas compassion satisfaction, burnout and secondary traumatic stress are at a moderate level. Hierarchical regression analysis suggested that compassion satisfaction and secondary traumatic stress had a positive impact on posttraumatic growth, whereas burnout had a negative impact on posttraumatic growth. CONCLUSIONS: Findings suggest that nursing managers should attach importance to the mental health of psychiatric nurses, improve compassion satisfaction, alleviate burnout and promote posttraumatic growth.

Psychological capital among clinical nurses: A latent profile analysis.

AIM: To determine the psychological capital level of nurses and explore the latent profiles of nurses regarding their psychological capital scores. BACKGROUND: The use of individual-centered analysis for the connotation of nurses' psychological capital structure is less studied and still needs to be further explored. METHODS: By the convenience sampling method, 494 clinical nurses from 7 general hospitals in Sichuan province were selected. The study was conducted from December 2022 to February 2023. Latent profile analysis was used for data analysis. We followed STROBE guidelines in this research. RESULTS: The total mean score of nurses' psychological capital is 5.17 (SD = 0.8). The following four latent profiles were identified: "poor" (4.5%), "medium" (22.9%), "well-off" (41.5%), and "rich" (31.1%). Multiple logistic regression showed that the number of hours worked per day and the number of night shifts per month were negative predictors of psychological capital, and psychological training and job satisfaction were protective factors of psychological capital. DISCUSSION: Our study found that the four profiles can be distinguished by "poor," "well-off," "medium," and "rich" levels of psychological capital. Among them, more than 70% of the nurses belonged to the well-off and rich profiles, and the number of the poor profile was the lowest. CONCLUSION: The overall psychological capital of clinical nurses is at a medium-high level. Each profile is influenced by multiple sociodemographic factors (i.e., age, working hours, monthly income, psychological training, and job satisfaction). IMPLICATIONS FOR NURSING AND HEALTH POLICY: Administrators should develop enhancement strategies to improve the mental health of nurses based on the characteristics of their psychological capital profiles.