“Nurse Burnout in China” the Article by Lu, M., Ruan, H., Xing, W., & Hu, Y.

Introduction

Nurse burnout is one of the most present problems to exist in hospitals across the world. Due to the very labor-intensive as well as mentally and emotionally exhausting nature of medical work, burnout levels among nurses and physicians are very high. This results in high turnover rates, which, in turn, affects the overall quality of care. In addition, this tendency is further exacerbated by forcing additional expenses on hospitals, associated with training new staff.

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A research article by Lu, Ruan, Xing, and Hu (2013) sought to estimate various correlations and interdependencies between burnout, staffing, job satisfaction, and quality of care in Chinese hospitals. In order to do so, they analyzed numerous variables, such as patient-to-nurse ratios, levels of burnout, and levels of job satisfaction. The hypothesis, although not explicitly stated, was that nurse staffing was directly connected to burnout and affected job satisfaction and quality of care (Lu et al., 2013). The purpose of this paper is to analyze the article and its key components in order to evaluate its accuracy and significance to nursing practice.

The Problem: Burnout in Nursing Staff

The problem of nursing burnout in relation to medical practice is clearly stated and frequently repeated throughout the entire paper. Burnout causes nurses to leave and directly affects the quality of provided care (Lu et al., 2013). This issue is especially prominent in China, as the country’s population is numerous while its number of medical personnel is limited, making every nurse and physician count. Learning more about correlations between different variables is important, as it enables creating evidence-based interventions in order to address the highlighted issues.

The aims and purposes of the study are stated on the first page of the article. The investigators sought to discover how nurse staffing affected job satisfaction and quality of care. The implicit hypothesis is that high patient-to-nurse ratios affect both of these parameters in a negative way. The key terms defined in the article are as follows: burnout, intent to leave, job dissatisfaction, nurse staffing, and quality of care (Lu et al., 2013).

Literature Review

The article presents a literature review in order to provide an overview of the subject as well as several findings made by other researchers in the same area. The materials cited were published between the years 2000 and 2009, making them relatively recent in academic terms. The situation did not improve since, as the researchers claim, stating that large-scale studies on the subject are lacking. One of the purposes of this article is to fill the academic void on this matter and provide quantitative data pertaining to the situation in China.

The literature review is neither too broad nor too narrow. As it is a quantitative study, the role of literature in it is reduced to providing a framework and academic background for the study, which it does. There is no evidence of bias in the literature section, as the information provided in it is doubled by several peer-reviewed and academic sources. The citations are pertinent to the study and are not taken out of context.

Design and Procedures

This original study follows a cross-sectional methodology based on the use of questionnaires as primary data collection tools. In terms of design, it followed a framework appropriate for large-scale studies. The sample included 873 Chinese nurses, who were asked to complete several questionnaires (Lu et al., 2013). Sampling locations included 20 hospitals located in Shanghai; therefore, the results of the research could be extrapolated to other large cities in China, as hospital conditions there would be similar. No pilot study was performed.

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Some of the tools used to measure burnout and collect data about the participants included a customized survey, which contained questions about nurse-to-patient ratios, as well as an emotional exhaustion scale from the Maslach Burnout Inventory-Human Service Survey (Lu et al., 2013). Nurses were asked to fill out the test every day rating their exhaustion levels on the scale of zero through six. Lastly, the researchers asked the participants to rate satisfaction with their job using a single-item scale of one to four.

The main dependent variables in this study were nursing burnout, intent to leave, job dissatisfaction, and the provided quality of care. Independent variables that were impossible to isolate from the rest were hospital-related characteristics (technological levels, financial and sanitary conditions, etc.), and nurse demographics, both of which were accounted for during data analysis procedures (Lu et al., 2013).

Data Analysis and Presentation

Data collected with questionnaires and item scales were analyzed using SPSS 15.0 in order to ensure accuracy and eliminate the factor of human error during statistical calculations (Lu et al., 2013). Descriptive statistics were used to analyze and evaluate the effects of independent variables (demographics, hospital conditions) and any interconnections between dependent variables (nurse burnout, job dissatisfaction, quality of care, and intent to leave the profession). Statistical tools and tests included a multinomial logistical regression analysis.

The results give a unified picture of nursing ratios, demographics, burnout, and work satisfaction. The average age for all nurses is 28.8 years. The average patient-to-nurse ratio was 7.71 (Lu et al., 2013). 92.7% of nurses did not intend to leave their profession within the next year, though it is possible for these results to be motivated by nurses fearing retribution from their superiors, even though the information was acquired anonymously (Lu et al., 2013). In total, 45% of nurses reported high burnout rates, and over a half were dissatisfied with their jobs (Lu et al., 2013). Nurses with the average patient-to-nurse ratio below four reported significantly less burnout than the rest. Thus, the results support the hypothesis regarding the correlation between nurse staffing, burnout, and job dissatisfaction. The weaknesses and limitations of the research were discussed.

Conclusions and Implications

The main conclusion of the article is that nearly half of all nurses in Shanghai reports high burnout and dissatisfaction with the profession. Considering that the data regarding the intent to leave the profession is subjective to criticism, the situation is even worse than anticipated. Around 30% of nurses reported suboptimal quality of care, which is related to stress, burnout, and unsatisfactory working conditions (Lu et al., 2013). The evidence suggests that nurse understaffing plays a key role in influencing high levels of burnout as well as other variables used in this research.

The conclusions of the study answer the inquiry announced at the beginning of the article. The researchers offer several implications and recommendations in order to improve healthcare in Chinese hospitals. The main implications for the profession are as follows (Lu et al., 2013):

  • Nurses are suffering from high levels of stress and burnout in every hospital setting.
  • Burnout results in 30% of all nursing care being suboptimal.
  • The organization of the nursing process state-wide requires re-examination.

The most obvious recommendation is to increase the number of nurses, thus effectively reducing the patient-to-nurse ratio, which is associated with lower levels of burnout and stress. The findings are similar to other researchers conducted in a similar scale and scope. In those studies, the shortage of nurses forces others to take on larger workloads, work overtime, and utilize 12-hour shift schedules (Lu et al., 2013). These schedules are increasingly tiring and cause long-term burnout and compassion fatigue, which affects the quality of care.

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Another strategy proposed by the researchers involves increasing job satisfaction to act as a counterweight to mounting stress and burnout. Clear career opportunities, reduced orientation times, and increased recognition are stated to be effective in increasing nurse satisfaction, thus lowering levels of burnout and reinforcing their desire to remain in the profession. Leadership is stated to be an important part of the nursing process (Lu et al., 2013). Adopting progressive models of leadership (transitional leadership, servant leadership, etc.) is associated with increases in agency and job satisfaction. Open relationships, mutual trust, encouragement of nurse-centered initiatives are also likely to improve job satisfaction.

Overall, the article provides important quantitative data regarding the state of nursing in hospitals in Shanghai. Although the results can be directly related to major cities in China, they reflect a situation similar to that in other hospitals of the world. American hospitals, for example, are also suffering from high turnover rates because of burnout. Some of the solutions proposed in this article are universally applicable to other locations. The article helps fill the research gap in the academic literature, as the number and quality of large-scale studies such as this one are thoroughly lacking. Additional researches of similar designs in other large Chinese cities would likely provide a more accurate picture of the situation. Hospitals with lower rates of burnout and job dissatisfaction should be analyzed and set as examples of proper conduct.

Reference

Lu, M., Ruan, H., Xing, W., & Hu, Y. (2013). Nurse burnout in China: a questionnaire survey on staffing, job satisfaction, and quality of care. Journal of Nursing Management, 23(4), 440-447.

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StudyCorgi. (2021, July 20). "Nurse Burnout in China" the Article by Lu, M., Ruan, H., Xing, W., & Hu, Y. Retrieved from https://studycorgi.com/nurse-burnout-in-china-the-article-by-lu-m-ruan-h-xing-w-and-amp-hu-y/

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""Nurse Burnout in China" the Article by Lu, M., Ruan, H., Xing, W., & Hu, Y." StudyCorgi, 20 July 2021, studycorgi.com/nurse-burnout-in-china-the-article-by-lu-m-ruan-h-xing-w-and-amp-hu-y/.

1. StudyCorgi. ""Nurse Burnout in China" the Article by Lu, M., Ruan, H., Xing, W., & Hu, Y." July 20, 2021. https://studycorgi.com/nurse-burnout-in-china-the-article-by-lu-m-ruan-h-xing-w-and-amp-hu-y/.


Bibliography


StudyCorgi. ""Nurse Burnout in China" the Article by Lu, M., Ruan, H., Xing, W., & Hu, Y." July 20, 2021. https://studycorgi.com/nurse-burnout-in-china-the-article-by-lu-m-ruan-h-xing-w-and-amp-hu-y/.

References

StudyCorgi. 2021. ""Nurse Burnout in China" the Article by Lu, M., Ruan, H., Xing, W., & Hu, Y." July 20, 2021. https://studycorgi.com/nurse-burnout-in-china-the-article-by-lu-m-ruan-h-xing-w-and-amp-hu-y/.

References

StudyCorgi. (2021) '"Nurse Burnout in China" the Article by Lu, M., Ruan, H., Xing, W., & Hu, Y'. 20 July.

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