Aims: This scoping review aims to examine the level and outcomes of emotional labor in nurses. Background: Nursing is a highly emotional profession that requires nurses to experience a wide range of emotions and control their emotional expressions in nursing practice. Chronic emotional labor and emotional burden not only impact nurses’ individual well‐being and professional performance but also their job satisfaction and turnover intention. Evaluation: This scoping review was guided by a five‐stage scoping review framework and the PRISMA‐ScR checklist. Eight databases were searched and 41 studies were reviewed. Key Issues: The Emotional Labor Scale and the Emotional Labor Scale for Nurses were the most commonly used instruments. Significant associations were found between emotional labor and 52 outcomes, which were categorized into two main themes: nurses’ personal well‐being and organizational well‐being. There were 19 mediators and 12 moderators between nurses’ emotional labor and 26 different outcomes. Conclusions: While the level of emotional labor among nurses remains uncertain, its consequences are plentiful and intricate. Studies have shown an important relationship between nurses’ emotional labor and individual and organizational well‐being, which is crucial for nurse managers. There is a need to explore the positive effects of nurses’ emotional labor and its impact on patients. Additionally, validation studies of the instruments used to measure nurses’ emotional labor are necessary. Implications for Nursing Management: The insights gained from this scoping review provided a more comprehensive understanding of emotional labor for nurse managers. This knowledge can be utilized to design training programs on emotional management and to explore different interventions aimed at alleviating the adverse impacts of nurses’ emotional labor. 

The Level and Outcomes of Emotional Labor in Nurses: A Scoping Review

Previous studies have thoroughly evaluated the association between long-term exposure to PM2.5 and mortality, but the effect of socioeconomic status on the association remains controversial. We utilized the data of all-cause mortality per year, concentration of PM2.5, socioeconomic and demographic characteristics for 345 cities in China from 2000-2019. We applied the Poisson generalized estimating equations (Poisson GEE) model to explore the association between PM2.5 and mortality in cities with different quartiles of demographic and socioeconomic characteristics. Overall, every 10 µg/m ³ increase in PM2.5, the RR was 1.082 (95% CI:1.058-1.106) for all-cause mortality, with residents of the Northeast and Southwest regions having a higher risk of death. Cities with the highest quartiles of gender ratio, age, dependency rate, and migration rate had relative risks of 1.110 (95% CI: 1.020-1.208), 1.075 (95% CI: 1.018-1.135), 1.101 (95% CI: 1.068-1.135), and 1.108 (95% CI: 1.053-1.165), respectively. Stratified analyses showed that the exposure-mortality associations were strongest in cities with both the lowest and highest socioeconomic status (SES) quartiles. The association between PM2.5 and mortality varied by socioeconomic status, demonstrating a U-shaped pattern with the highest mortality risk observed among residents in cities with both the lowest and highest socioeconomic levels.

pdf/study-of-socioeconomic-differences-of-long-term-pm2-5-oio6qg2vumwn.pdf

Study of socioeconomic differences of long-term PM2.5 exposure and population mortality risk - based on 345 cities from 2000 to 2019 in China

We aimed to examine the relationships among nurses' career compromise, job satisfaction, and turnover intention and the mediating role of job satisfaction in the relationship between career compromise and turnover intention. 

The effect of career compromise on nurses’ turnover intention: the mediating role of job satisfaction

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.

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

Abstract Background Poor nurse-patient relationship poses an obstacle to care delivery, jeopardizing patient experience and patient care outcomes. Measuring nurse-patient relationship is challenging given its multi-dimensional nature and a lack of well-established scales. Purpose This study aimed to develop a multi-dimensional scale measuring nurse-patient relationship in China. Methods A preliminary scale was constructed based on the existing literature and Delphi consultations with 12 nursing experts. The face validity of the scale was tested through a survey of 45 clinical nurses. This was followed by a validation study on 620 clinical nurses. Cronbach’s α, content validity and known-group validity of the scale were assessed. The study sample was further divided into two for Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA), respectively, to assess the construct validity of the scale. Results The Nurse-Patient Relationship Scale (NPRS) containing 23 items was developed and validated, measuring five dimensions: nursing behavior, nurse understanding and respect for patient, patient misunderstanding and mistrust in nurse, communication with patient, and interaction with patient. The Cronbach’s α of the NPRS ranged from 0.725 to 0.932, indicating high internal consistency. The CFA showed excellent fitness of data into the five-factor structure: χ 2 /df = 2.431, GFI = 0.933, TLI = 0.923, CFI = 0.939, IFI = 0.923, RMSEA = 0.070. Good content and construct validity are demonstrated through expert consensus and psychometric tests. Conclusion The NPRS is a valid tool measuring nurse-patient relationship in China. 

Developing and validating the nurse-patient relationship scale (NPRS) in China

Abstract Background Local environmental factors are associated with health and healthcare-seeking behaviors. However, there is a paucity in the literature documenting the link between air pollution and healthcare-seeking behaviors. This study aimed to address the gap in the literature through a cross-sectional study of domestic migrants in China. Methods Data were extracted from the 2017 China Migrants Dynamic Survey ( n = 10,051) and linked to the official air pollution indicators measured by particulate matter (PM 2.5 and PM 10 ) and air quality index (AQI) in the residential municipalities ( n = 310) of the study participants over the survey period. Probit regression models were established to determine the association between air pollution and refraining from visiting health facilities after adjustment for variations in the predisposing, enabling and needs factors. Thermal inversion intensity was adopted as an instrumental variable to overcome potential endogeneity. Results One unit (µg/m 3 ) increase in monthly average PM 2.5 was associated with 1.8% increase in the probability of refraining from visiting health facilities. The direction and significance of the link remained unchanged when PM 2.5 was replaced by AQI or PM 10 . Higher probability of refraining from visiting health facilities was also associated with overwork (β = 0.066, p = 0.041) and good self-related health (β = 0.171, p = 0.006); whereas, lower probability of refraining from visiting health facilities was associated with short-distance (inter-county) migration (β=-0.085, p = 0.048), exposure to health education (β=-0.142, p &lt; 0.001), a high sense of local belonging (β=-0.082, p = 0.018), and having hypertension/diabetes (β=-0.169, p = 0.005). Conclusion Air pollution is a significant predictor of refraining from visiting health facilities in domestic migrants in China. 

/pdf/air-pollution-and-refraining-from-visiting-health-facilities-2rzwkb3k.pdf

Air pollution and refraining from visiting health facilities: a cross-sectional study of domestic migrants in China

Developing a scale measuring the doctor-patient relationship in China from the perspective of doctors.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Chen Wang

Author Tools

Chat about Author

Papers

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

Developing and validating the nurse-patient relationship scale (NPRS) in China

Air pollution and refraining from visiting health facilities: a cross-sectional study of domestic migrants in China

Developing a scale measuring the doctor-patient relationship in China from the perspective of doctors.