8201 wk 5 Discussion: t-Tests and ANOVA in Clinical Practice 1 response

Read a selection of your colleagues’ responses and respond  in one or more of the following ways:  Ask a probing question, substantiated with additional background information, evidence, or research. Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives. Offer and support an alternative perspective using readings from the classroom or from your own research in the Walden Library.Validate an idea with your own experience and additional research. Suggest an alternative perspective based on additional evidence drawn from readings or after synthesizing multiple postings.Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.                                                                                                                                           COLLAPSEt-Tests and ANOVA in Clinical PracticeA common issue in the nursing practice is nurse burnout (Dall’Ora et al., 2020). Nurse burnout is an outcome characterized by emotional and physical exhaustion secondary to work-related stress (Dall’Ora et al., 2020). Nurses that experience burnout often experience constant fatigue, anxiety, lack of enthusiasm to work, feeling overworked and feeling ill (Dall’Ora et al., 2020). As a result, nurse burnout greatly affects the quality of care that in turn affects patient outcomes and safety negatively (Dall’Ora et al., 2020).Bellanti et al. (2021) in their study used a cross-sectional study to evaluate the factors related to nurses’ burnout during the first wave of corona virus disease-19 (COVID-19) in a University Hospital in Italy. The study was conducted using a sample of 293 nurses working at the University Hospital in Foggia, Italy (Bellanti et al., 2021). The data was collected using an online questionnaire surveying on the demographics, True/False statements on the impact of COCID-19 outbreak, the Maslach Burnout Inventory–Humans Service Survey (MBI-HSS), and the Oldenburg Burnout Inventory (OBI) (Bellanti et al., 2021). Statistical analysis of data was conducted using the Kolgomorov–Smirnov test to evaluate the Gaussian distribution of the samples, the Pearson’s correlation coefficient to correlate the MBI and OBI scores (Bellanti et al., 2021). To analyze the significance if the differences between the groups, the independent t-tests was used for continuous variables between two groups, ANOVA for one-way analysis of variance, Tukey as a post-hoc test for continuous variables in more than two groups or the Pearson’s chi-square test and Fisher exact test in contingency tables for categorical variables (Bellanti et al., 2021). The findings of the study pointed out an increase in psychological problems such as anxiety, depression, insomnia and burnout in healthcare workers (Bellanti et al., 2021). Almost 90% of the 293 participants met the criteria for medium to high burnout, while 70% of the participants exhibited emotional exhaustion (Bellanti et al., 2021). The study was relevant to the topic of nurses’ burnout because it provides an understanding of the impact of health pandemics on the emotional and physical wellbeing of nurses. As a result, the findings can be used to promote preparedness to reduce nurses’ burnout during pandemics.The use of inferential statistics strengthened the study’s application to evidence-based practice. The researchers can generalize the findings of the study to make conclusions and predictions in regards to the factors associated to nurse burnout (Gray & Grove, 2020; Lee, & Kim, 2022). As a result, the findings can be used to predict nurse burnout and develop evidence-based interventions to reduce the nurse burnout.                                                                                                                  References  Bellanti, F., Lo Buglio, A., Capuano, E., Dobrakowski, M., Kasperczyk, A., Kasperczyk, S., … & Vendemiale, G. (2021). Factors related to nurses’ burnout during the first wave of Coronavirus Disease-19 in a University Hospital in Italy. International Journal of Environmental Research and Public Health, 18(10), 5051.Dall’Ora, C., Ball, J., Reinius, M., & Griffiths, P. (2020). Burnout in nursing: a theoretical review. Human resources for health, 18(1), 1-17.Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.Lee, S. H., & Kim, E. (2022). Inferential Statistics. In Scholarly Research in Music (pp. 165-182). Routledge.