Critical Appraisal: Fatigue, Burnout, Work Environment

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The selected article by Yu et al. (2020) seeks to explore the impact of 12-hour shifts on nursing fatigue in intensive care units (ICU). The purpose of the study is to investigate the real-world application of literature on nurse fatigue, with information being useful on developing a support environment to reduce nurse fatigue considering that nursing burnout is commonly associated with long working hours. The study follows a cross-sectional survey design. The appropriate cohort studies critical appraisal checklist will be utilized to consider the validity, reliability, and applicability of the study.

The study design is a cross-sectional survey with ICU nurses from two hospitals in different cities. The questionnaire survey is appropriate since fatigue levels have to be evaluated by the subjects themselves and it is a subjective individual measure. The survey utilized the Likert scale which helps to quantify the data and collect a wide range of response measurements (Taherdoost, 2019). The sample had to meet similar requirements of full-time ICU RNs and working 12-hour shifts regularly. After clearing for criteria, only 67 out of 112 responses, and the small sample size was discussed in limitations as reducing statistical significance and generalizability, particularly in areas outside of the ICU. The self-reporting factors create potential for bias due to nurses personal interests. The study utilized a well-established Occupational Fatigue Exhaustion/Recovery (OFER) scale instrument to measure subjects fatigue (Yu et al., 2020).

The results found that 85% of participants showed low and moderate chronic fatigue levels, while 15% demonstrated moderate and high levels. 54% nurses reported low/moderate acute fatigue, and 69% low/moderate inter-shift fatigue. T-tests and chi-square used to compare hospital results and independent variables. Spearmans correlation sought to establish a relationship between demographic factors and types of fatigue. The ANOVA test analysis found statistical significance for any demographic factors, including age, nursing experience, and exercise frequency to fatigue. The following results meet general reliability requirements and statistical tests are standard for this type of research (Vaske, 2019).

Nurse fatigue is directly associated with factors of burnout, turnover, and patient safety, which makes it critical to consistently study the subject to ensure a better and safer work environment (Al Mamari et al., 2020). These are valid results that can be applied to the nursing population at major hospitals, suggesting that shift scheduling has minor impact on fatigue levels. Yu et al. (2020) note that the majority of nurses cope well with 12-hour shifts, and actually shorter 8-hour shifts had a more detrimental effect on rest due to the necessity to travel to work more frequently. However, the statistical significance of certain demographic factors suggests the support should be established for inexperienced nurses or those who are less adaptable, overall encouraging collaboration between managers and nurses to provide improved shift schedules.

The article by Yu et al. (2020) explores the impact of 12-hour shifts on various types and levels of nursing fatigue, also investigating the involvement of demographic factors. The research uses strong methods and highly tuned instruments but maintains certain weaknesses such as sample size and lack of generalizability of results. Generally, the study can be considered valid and reliable but requires further research due to its small sample. However, the recommendations for applicability are useful in terms of supporting individual nursing staff in managing fatigue levels.

References

Al Mamari, Q., Sharour, L. A., & Al Omari, O. (2020). British Journal of Nursing, 29(1), 28-34. Web.

Taherdoost, H. (2019).International Journal of Academic Research in Management, 8(1), 1-10. Web.

Vaske, J. J. (2019). Survey research and analysis (2nd ed.). Sagamore Publishing.

Yu, F., Somerville, D., & King, A. (2019).Applied Nursing Research, 50, 1-7. Web.

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