Nursing Burnout Summary

According to a study, 10-78% of nurses are experiencing burnout, and as the nursing shortage worsens, the amount of workplace stressors is set to increase (Welp, Meier, & Manser, 2015). A Swiss study involving 1,425 nurses concluded that nurses experiencing burnout had higher mortality ratios and lower safety grades (Welp, Meier, & Manser, 2015). It is commonly reported that there is a positive relationship between the incidence of emotional exhaustion and patient mortality ratios. Having a shortage of nurses on staff is often referenced as a leading factor for burnout among nurses, and it has been related to an increase in the patient’s stay time (Welp, Meier, & Manser, 2015). In addition, nurses are placed in increasingly stressful situations

A weakness of the article was the fact that a convenience sample comprised of 61 oncology nurses from a university-affiliated hospital was used (Russell, 2016). Because it provides little opportunity for bias, it is seen as a weak approach (Grove, Gray, & Burns, 2015, p. 264). Although this approach is seen as weak, it was appropriate for this particular study because the researchers had limited access to patients who meet study sample criteria (Grove, Gray, & Burns, 2015, p. 264). A strength of the article is that a Bonferroni correction was conducted on the data. The Bonferroni procedure, which controls for the escalation of significance, may be used when multiple t-tests must be performed on different aspects of the same data (Grove, Gray, & Burns, 2015, p. 349). There is a higher chance for a false positive result (Type 1 error) when conducting multiple tests on a single data set, so this was used to protect from type 1 error (Russell, 2016). This correction also identified a statistically significant association when the p value was less than 0.006 (Russell, 2016). Usually the hypothesis is rejected when a p value is that small indicating strong evidence against the hypothesis but when an experimenter performs enough tests, eventually a result will show statistical significance, even if there is