Sexually Transmitted Diseases in Adolescents, Incompatibility of Intravenous Medications, Turnover Rates due to Burnout in Healthcare (24 hours)

Turnover Rates due to Burnout in Healthcare

Review of Literature

High turnover rates as a result of nurse burnout are a major issue in healthcare that needs to be resolved. Kelly et al. (2021) established that burnout can be addressed by improving resilience through mental health awareness and mindfulness-based stress reduction to address nurses’ turnover. The article provided high-quality evidence as the conclusions made were definitive and supported by the data provided. The evidence is applicable to the PICOT question as it supports improvement in mental well-being could reduce burnout and turnover. The findings are consistent with those of other studies (Kwon et al., 2021). The major difference was the methodologies used to collect data as Kelly et al. (2021) obtained patient data from health databases while Kwon et al. (2021) used anonymous online surveys. The controversy in the article is that it does rule out the contribution of other factors in improving nurses’ resilience.

In another study, Kwon et al. (2021) associated burnout with turnover intention and suggested that nurses’ turnover intention could be mitigated by improving their mental health. The article provides low-quality evidence as the sample size is insufficient for the study. The findings can be applied to the PICOT question to address nurse turnover. The evidence provided in the article is supported by other studies that associate burnout and nurses’ intention to leave (Chen et al., 2019). The similarities between the studies included the methodology as they were both cross-sectional studies and some of the variables in the studies. The difference identified included the location of the studies as one was conducted in Korea and the other in Taiwan (Chen et al., 2019; Kwon et al., 2021). There was no controversy identified in the study.

However, Tununu and Martin (2020) established that psychiatric nurses did not suffer from burnout because they had low emotional exhaustion. The article provides low-quality evidence that cannot be generalized as it was conducted in one psychiatric hospital, and the evidence varied from that of other studies (Scanlan & Still, 2019). The evidence applies to the PICOT question as it provides an alternative view of the existence of burnout among psychiatric nurses. The similarity between the articles is that they were single-site studies The differences noted include the geographical location and the participants’ response rates since one had 100% and the other 25% response rate (Scanlan & Still, 2019; Tununu & Martin, 2020). The controversy identified is the sufficiency of the sample size yet the findings were inconsistent with those of other studies.

Research indicates that there is an inter-correlation between turnover intention and burnout (Scanlan & Still, 2019). The evidence provided was of high quality as the findings were supported by data from the study. The findings are applicable to the PICOT question to provide a solution to the issue of turnover by developing strategies to reduce burnout. The evidence is similar to the findings of Chen et al. (2019). However, the major difference between the studies was that Chen et al. (2019) investigated burnout as a mediating factor influencing turnover intention among nurses with high patient-nurse ratios. The controversy that exists in the articles is the different measurements of turnover intention (Chen et al., 2019; Scanlan & Still, 2019).

Wei et al. (2022) established that burnout was prevalent among nurses in delivery and peri-operative settings. The article provided high-quality evidence as the conclusions were supported by the results of the study. The evidence is applicable to the PICOT question since the researchers recommended the need to improve burnout symptoms and nurses’ physical and mental health. The findings are consistent with the evidence in other studies that associated work-related stress and increased burnout in nurses (Karimi et al., 2022). The difference noted is the location of the study as Wei et al. (2022) was conducted at a single site and the other in two hospitals (Karimi et al., 2022). No controversy has been identified in the study.

Karimi et al. (2019) found that some elements of burnout influenced turnover intention such as a personal accomplishment. The quality of the evidence provided was affected by the small sample size, which could have influenced the results, but the study was conducted in multiple settings, which improves the generalizability of the findings. However, the evidence is related to the PICOT question as the authors recommended monitoring nurses’ mental health to prevent the effects of burnout such as turnover. Other researchers have also identified burnout as a common problem among nurses during the COVID-19 pandemic (Maunder et al., 2022). The two studies were conducted in multiple settings. The studies were conducted in two different geographical locations. The controversial information in the article is that work position was the highest predictor of the intention to leave.

In their study, Maunder et al. (2022) found that nurses experienced high levels of burnout during the COVID-19 pandemic. The findings were consistent and generalizable and can be applied to the PICOT question to address the problem of nurse turnover due to burnout by helping nurses cope with work-related stressors such as COVID-19. A similar study conducted by Karimi et al. (2019) had similar findings where data was collected through surveys. The differences identified include the setting, and the measures of burnout used. No controversies were identified in the study.

There are some other elements of burnout such as client-based and personal burnout that influence the intention to leave among nurses (Chen et al., 2019). The quality of the evidence was supported by the statistical data and the sample was sufficient. The findings provide important information for answering the PICOT question by reducing burnout to address nurses’ intention to quit their jobs. Similar findings were provided by Kwon et al. (2021). But the difference is that Chen et al. (2019) used a large sample from multiple settings and conducted the study in one setting. No controversial information was identified from the study.

Kowalczuk et al. (2020) associated burnout symptoms with working excessively, which increased nurses’ tendency to frequently take sick leave. The evidence was consistent with the data provided and was correctly interpreted. The sample size was sufficient for generalization and the study was conducted in multiple sites. The evidence can be used to answer the PICOT question since the researchers explained that burnout and excessive work affect employees’ mental health. Therefore, reducing workload could reduce burnout and prevent nurses from leaving. The similarity identified with the other articles include the research design; But differed in the data collection procedure as the authors applied paper-questionnaires Kowalczuk et al. (2020), other than online surveys (Maunder et al., 2022; Wei et al., 2022).

Rudman et al. (2020) associated nurse burnout with various mental health problems such as insomnia, depressive symptoms, and cognitive problems. The article provided high-quality evidence as the sample size was sufficient and the results were consistent and generalizable. The findings apply to the PICOT question since improving nurses’ mental health would prevent them from such problems and could be overwhelmed by the demands of their careers. The evidence is consistent with other studies that identified the association between burnout and mental health issues (Maunder et al., 2022). However, the study involved nursing students while the others mostly focused on nurses and other healthcare professionals (Kowalczuk et al., 2020; Maunder et al., 2022).

PICOT question support

Burnout is a major issue among nurses that should be addressed to prevent nurse turnover. Current research indicates a significant association between burnout and nurses’ intention to quit their jobs to seek other opportunities. Studies have suggested that addressing burnout could help reduce nurses’ intention to leave their careers or positions by improving their resilience (Kelly et al., 2021). Burnout is associated with increased psychological distress (Maunder et al., 2021), and low satisfaction with their jobs (Scanlan & Still, 2019).

It is important to note that the relationship between nurse turnover and burnout can be influenced by other factors such as workload, which may not independently affect nurse turnover. The PICOT question seeks to establish whether improving mental health and well-being could address the problem of nurse turnover. Available evidence indicates the need to create strategies to reduce burnout and improve nurses’ job satisfaction to reduce their intentions to leave (Scanlan & Still, 2019). Strategies to help nurses cope with stressors in the workplace could reduce nurses’ burnout and turnover intentions by enhancing personal accomplishment and reducing emotional exhaustion (Karimi et al., 2019).

Practice Change

To address the problem of the high turnover rate of nurses affected by burnout, implementing a mental health program to reduce burnout can help nurses to cope with job-related stress. Kelly et al. (2021) identified improving employee well-being as essential in preventing nurses from leaving their positions or units. Tununu and Martin (2020) explained that promoting open communication and resources could help reduce burnout among nurses and provide a safe working environment. It is important to identify and prevent factors that lead to nurse burnout to successfully prevent nurses from the intention to leave, especially when faced with critical situations (Karimi et al., 2019).

Objective

The project change aims to reduce the nurse turnover rate caused by burnout by providing nurses with a program that will improve their mental health. When the nurses’ mental health is improved, it would be easy to cope with stressors that arise in the workplace and prevent them from burnout and subsequently intentions to quit. The intervention will protect not only nurses from harm but also patients since burnout is associated with psychological distress which threatens patients’ safety (Maunder et al., 2022). Improving nurses’ mental health would translate to improved patient outcomes.

Problem

The problem of nurse turnover resulting from burnout is common among nurses working in busy and understaffed units. There is a relationship between a high workload and increased burnout, which is a predictor of high turnover (Chen et al., 2019). Nurses are more likely to be overwhelmed when they ate overworked Therefore, there is a need to improve nurses’ ability to cope with the stress that arises due to high workloads and help them to be more resilient. Nursing is a challenging profession that is faced with many challenges such as staffing shortages and nurses are bound to find themselves in difficult situations; thus, have to be mentally strong.

Current state of problem

Since the emergence of the COVID-19 pandemic, nurses have been faced with relentless pressure to care for many patients. The pro of the problem is the increasing demand for nurses as the opportunities for front-line workers have increased as more nurses leave the profession to seek other opportunities. However, the negative part of the problem is that many healthcare institutions still need to hire more nurses as they still struggle to properly compensate the existing workforce putting more pressure on the remaining workforce. Hospitals have been faced with the challenge of managing their costs and providing quality care (Chen et al., 2019).

Strengths and weaknesses of review of literature

The major strength of Kelly et al. (2021) was a sufficient sample size and consistent results, while the limitation was the fixed times of data collection. In Kwon et al. (2021), the main strength was the relevance of the article to the PICOT question, while the weakness was that it was a single-site study, which limited its generalizability. The main strength of Tununu and Martin (2020) was a sufficient sample size but was conducted in a single hospital. In Scanlan and Still (2019), the main strength was the consistency of the findings but lacked a random sample. Wei et al. (2022) provided consistent findings from a sufficient sample size but only focused on peri-operative units of one hospital.

Karimi et al. (2019) provided consistent findings, but the sample size was small and relied on self-reported data, which can be biased. The main strength of Maunder et al. (2022) was the study design that allowed for follow-up, but there was a high drop-out, which created an opportunity for bias. Chen et al. (2019) had a sufficient sample size for the study, but the model may not be used with other mediators. In Kowalczuk et al. (2020), the main strength was that the hypothesis was confirmed, and the major weakness was the cross-sectional study design and self-reported data, which can be biased. Lastly, Rudman et al. (2020) had a sufficient sample size from different settings, and the major weakness was the over-reliance on self-reported data.

References

Chen, Y. C., Guo, Y. L. L., Chin, W. S., Cheng, N. Y., Ho, J. J., & Shiao, J. S. C. (2019). Patient–nurse ratio is related to nurses’ intention to leave their job through mediating factors of burnout and job dissatisfaction. International journal of environmental research and public health, 16(23), 4801. https://doi.org/10.3390/ijerph16234801

Karimi, L., Raei, M., & Parandeh, A. (2022). Association between dimensions of professional burnout and turnover intention among nurses working in hospitals during coronavirus disease (COVID-19) pandemic in Iran based on structural model. Frontiers in public health, 10. https://doi.org/10.3389/fpubh.2022.86026

Kelly, L. A., Gee, P. M., & Butler, R. J. (2021). Impact of nurse burnout on organizational and position turnover. Nursing outlook, 69(1), 96-102. https://doi.org/10.1016/j.outlook.2020.06.008.

Kowalczuk, K., Krajewska-Kułak, E., & Sobolewski, M. (2020). Working excessively and burnout among nurses in the context of sick leaves. Frontiers in psychology, 11, 285. https://doi.org/10.3389/fpsyg.2020.00285

Kwon, C. Y., Lee, B., Kwon, O. J., Kim, M. S., Sim, K. L., & Choi, Y. H. (2021). Emotional labor, burnout, medical error, and turnover intention among South Korean nursing staff in a University Hospital setting. International journal of environmental research and public health, 18(19), 10111. https://doi.org/10.3390/ijerph181910111

Maunder, R. G., Heeney, N. D., Hunter, J. J., Strudwick, G., Jeffs, L. P., Ginty, L., ... & Wiesenfeld, L. A. (2022). Trends in burnout and psychological distress in hospital staff over 12 months of the COVID-19 pandemic: a prospective longitudinal survey. Journal of Occupational Medicine and Toxicology, 17(1), 1-11. https://doi.org/10.1186/s12995-022-00352-4

Scanlan, J. N., & Still, M. (2019). Relationships between burnout, turnover intention, job satisfaction, job demands and job resources for mental health personnel in an Australian mental health service. BMC health services research, 19(1), 1-11. https://doi.org/10.1186/s12913-018-3841-z

Tununu, A. F., & Martin, P. (2020). Prevalence of burnout among nurses working at a psychiatric hospital in the Western Cape. Curationis, 43(1), 1-7. https://doi.org/10.4102/curationis.v43i1.2117

Wei, H., Aucoin, J., Kuntapay, G. R., Justice, A., Jones, A., Zhang, C., ... & Hall, L. A. (2022). The prevalence of nurse burnout and its association with telomere length pre and during the COVID-19 pandemic. Plos one, 17(3), e0263603. https://doi.org/10.1371/journal.pone.0263603