Emotional labour and turnover intention among nurses in China: Mediating effects of nurse-patient relationship and self-rated health.

AIM: This study tested the mediating role of the nurse-patient relationship and self-rated health in the effect of emotional labour on turnover intention among nurses in China. BACKGROUND: The underlying mechanism behind the effect of emotional labour on turnover intention remains inadequately understood. INTRODUCTION: Nurses with a high level of emotional labour are predisposed to experiencing poor health and tension in their relationships with patients, which may increase turnover intention. METHODS: A cross-sectional survey of 527 nurses in a public tertiary hospital in Qiqihar, located in China's Heilongjiang province, was conducted. Emotional labour and turnover intention were assessed using existing validated scales containing multiple items, while the nurse-patient relationship and self-rated health were assessed using single items, respectively. Baron and Kenny's causal steps and the Karlson/Holm/Breen method were adopted to test the mediating effects of the nurse-patient relationship and self-rated health in the association between emotional labour and turnover intention after adjusting for variations in sociodemographic and job characteristics. RESULTS: Emotional labour was positively associated with turnover intention. Self-rated poor health and a disharmonious nurse-patient relationship partially mediated the positive effect of emotional labour on turnover intention. CONCLUSIONS: Emotional labour significantly affects the turnover intention of nurses working in public tertiary hospitals in China, and this effect is partially mediated by self-rated health and the nurse-patient relationship. IMPLICATIONS FOR NURSING PRACTICE AND NURSING POLICY: Giving more attention to nurses' negative emotions and work attitudes is crucial. Developing comprehensive strategies for enhancing nurses' emotional management ability, promoting their physical and psychological well-being, and improving nurse-patient relationship to reduce nurses' turnover.

The Role of Subjective Wellbeing in Mediating Social Trust to the Mental Health of Health Workers.

Mental health problems of health workers are attracting increasing concerns in China and the world. A trustful relationship between health workers and patients is the foundation of quality patient care, which is currently under serious threat. This study aimed to determine the associations of social trust on subjective wellbeing and mental health of health workers. Using the survey data of 262 health workers extracted from the 2018 Chinese Family Panel Studies, a structural equation model with partial least square approach was established. The results showed that social trust was linked to both subjective wellbeing (ß = 0.251, p < 0.01) and mental health (ß = -0.210, p < 0.01). The effect of social trust on mental health was partially mediated by subjective wellbeing (51.87%). The association between social trust and subjective wellbeing was moderated by socioeconomic status: social trust has a stronger effect on subjective wellbeing in those with higher socioeconomic status. Erosion of social trust may present a serious risk to mental health and subjective wellbeing of health workers. High socioeconomic status can amplify the effect of social trust.

Anxiety and Insomnia Mediate the Association of Fear of Infection and Fatigue: A Cross-Sectional Survey of Nurses Deployed to a COVID-19 Epicenter in China.

Background: This study aimed to test the mediating role of anxiety and insomnia in the association between fear of infection and fatigue. Methods: A cross-sectional questionnaire survey was conducted on the nurses deployed to Heihe. A serial multiple mediation model was established to determine the role of anxiety and insomnia in the association between fear of infection and fatigue. Findings: Over half (53.0%) of the study participants reported experiencing fear of infection despite stringent personal protection measures. The scores of anxiety (11.87±5.19), insomnia (16.33±5.95), and fatigue (45.94±12.93) were moderately correlated, with a Pearson correlation coefficient ranging from 0.501 to 0.579. Anxiety, either alone or in combination with insomnia, mediated the association between fear of infection and fatigue. Conclusion: The findings suggest that anxiety and insomnia play a mediating role in the relationship between fear of infection and fatigue. These results emphasize the importance of implementing targeted mental health interventions and work arrangements to address the well-being of healthcare professionals.

Identifying Antibiotic Prescribing Patterns Through Multi-Level Latent Profile Analyses: A Cross-Sectional Survey of Primary Care Physicians.

Background: Overuse of antibiotics significantly fuels the development of Antimicrobial resistance, which threating the global population health. Great variations existed in antibiotic prescribing practices among physicians, indicating improvement potential for rational use of antibiotics. This study aims to identify antibiotic prescribing patterns of primary care physicians and potential determinants. Methods: A cross-sectional survey was conducted on 551 physicians from 67 primary care facilities in Hubei selected through random cluster sampling, tapping into their knowledge, attitudes and prescribing practices toward antibiotics. Prescriptions (n = 501,072) made by the participants from 1 January to March 31, 2018 were extracted from the medical records system. Seven indicators were calculated for each prescriber: average number of medicines per prescription, average number of antibiotics per prescription, percentage of prescriptions containing antibiotics, percentage of antibiotic prescriptions containing broad-spectrum antibiotics, percentage of antibiotic prescriptions containing parenteral administered antibiotics, percentage of antibiotic prescriptions containing restricted antibiotics, and percentage of antibiotic prescriptions containing antibiotics included in the WHO "Watch and Reserve" list. Two-level latent profile analyses were performed to identify the antibiotic prescribing patterns of physicians based on those indicators. Multi-nominal logistic regression models were established to identify determinants with the antibiotic prescribing patterns. Results: On average, each primary care physician issued 909 (ranging from 100 to 11,941 with a median of 474) prescriptions over the study period. The mean percentage of prescriptions containing antibiotics issued by the physicians reached 52.19% (SD = 17.20%). Of those antibiotic prescriptions, an average of 82.29% (SD = 15.83%) contained broad-spectrum antibiotics; 71.92% (SD = 21.42%) contained parenteral administered antibiotics; 23.52% (SD = 19.12%) contained antibiotics restricted by the regional government; and 67.74% (SD = 20.98%) contained antibiotics listed in the WHO "Watch and Reserve" list. About 28.49% of the prescribers were identified as low antibiotic users, compared with 51.18% medium users and 20.33% high users. Higher use of antibiotics was associated with insufficient knowledge, indifference to changes, complacency with satisfied patients, low household income and rural location of the prescribers. Conclusion: Great variation in antibiotic prescribing patterns exists among primary care physicians in Hubei of China. High use of antibiotics is not only associated with knowledge shortfalls but also low socioeconomic status of prescribers.