Respond to
the four colleagues in one or more of the following ways and include 2 references per colleague response:
· 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.
Precious:
Statistical Analysis in Nursing
Yeon Hee Kim, Ja Min, Soon Hee Kim, and Sujin Shin’s research aims to evaluate how well a program for work-based critical reflection for novice nurses works. The study’s main objective is to find out how this training enhances novice nurses’ clinical critical-thinking abilities, communication competency, and job performance while working at the most advanced general hospital in South Korea. The research aims to provide empirical evidence about the efficaciousness of critical reflection instruction for novice nurses, specifically during their shift from classroom to clinical environments. Additionally, the study aims to offer strategic recommendations for creating and enhancing critical reflection training programs, stressing the significance of these initiatives in addressing the particular problems encountered by novice nurses in their early careers.
Yeon Hee Kim and team used straightforward tests to understand data from new nurses in a job-based deep thinking program. They used the Wilcoxon rank sum test and Mann-Whitney U-test. These checked for any differences in averages and if the middle values were equal for the test and control groups (Vierra et al., 2023). They looked at the boosts in practical thinking in new nurses who took part in this deep thinking program. The results showed that the nurses’ abilities in the test group were much better (p = 0.003). The program’s effectiveness is evident as it resulted in the improvement of the participants. Furthermore, the Wilcoxon rank sum test was utilized to compare the average communication skill rankings between the experimental and control groups. The results showed a statistically significant difference in communication capacity (p = 0.028), indicating that the critical reflection training impacted novice nurses’ communication competency.
According to Kim (2015), parametric methods such as t-tests and ANOVA assume that the analyzed data follow a normal distribution. In the research study by Yeon Hee Kim et al., the Kolmogorov-Smirnov test revealed that the data did not meet the assumption of normality (p = 0.039), making the use of parametric methods inappropriate. The data collected for clinical critical-thinking skills, communication competency, and job performance were likely not normally distributed, and attempting to apply parametric tests in such cases could lead to inaccurate results.
For example, the Clinical Critical Thinking Skill test (CCTS) used in the study provided dichotomous data, with each question having a correct or incorrect response. These data types do not conform to parametric tests’ continuous and customarily distributed assumptions. A t-test or ANOVA in this context would not be suitable as these tests assume interval or ratio data and may not produce reliable results with dichotomous variables. An inappropriate application of parametric tests could lead to Type I errors, where statistical significance is incorrectly detected, or Type II errors, where actual effects are overlooked.
Furthermore, by using nonparametric tests—namely, the Wilcoxon rank sum test and the Mann-Whitney U-test—the researchers could ignore the normalcy assumption and still derive significant findings from the data. According to Vickers (2005), these nonparametric tests are reliable and appropriate for examining ordinal or non-normally distributed data. They offer a more accurate depiction of the statistical significance of observed differences within the study’s context.
One notable strength is the quasi-experimental design, which allows for comparing the experimental and control groups. While randomized controlled trials (RCTs) are considered the gold standard, the quasi-experimental design used in this study provides valuable insights into the effectiveness of the critical reflection program within the constraints of the setting. Additionally, incorporating a training procedure for Reflective Practitioners (RPs) contributes to the fidelity of the intervention, enhancing the consistency of program implementation. The focus on real-world applicability, with novice nurses in an advanced general hospital, adds ecological validity to the findings, making them more applicable to clinical practice.
One central area for improvement lies in the limited generalizability of the study due to its single-hospital setting in South Korea. The findings may be different from diverse healthcare settings or cultural contexts. The small sample size, though determined based on statistical power, remains a limitation, potentially affecting the study’s external validity. Additionally, the relatively low reliability of some measurement instruments, as indicated by Cronbach’s α values, raises concerns about the consistency of these tools in capturing the intended constructs. For instance, the Cronbach’s α values for the Clinical Critical Thinking Skill test at post-testing were relatively low (0.56), indicating a potential limitation in the reliability of this instrument.
By guiding educational strategies and treatments aimed at novice nurses, the research study conducted by Yeon Hee Kim et al. can make a substantial contribution to evidence-based practice in nursing. The sound effects of the work-based critical reflection program on clinical critical-thinking abilities and communication competency demonstrate the potential effectiveness of integrating reflective practices into nursing education. These findings support the main goals of evidence-based practice in nursing, which emphasize the integration of clinical judgment, patient preferences, and research findings, by suggesting that providing new nurses with structured opportunities for critical reflection may enhance their ability to make informed clinical decisions and manage complex communication scenarios in real-world healthcare settings.
The study’s recommendations include adding critical reflection programs in newcomer orientation and preceptor training programs, which can assist nurse educators and healthcare facilities. To better prepare new nurses for the demands of clinical practice, orientation programs should heavily emphasize experiential learning and critical thinking. Implementing these recommendations may assist new nurses in becoming more capable and resilient, lowering turnover rates and improving overall patient care outcomes.
Grace
Statistical Analysis in Nursing
Article Selected
Leigh, L., Taylor, C., Glassman, T., Thompson, A., & Sheu, J. J. (2020). A cross-sectional examination of the factors related to emergency nurses’ motivation to protect themselves against an Ebola infection.
Journal of Emergency Nursing, 46(6), 814–826.
Goals and Purpose of the Selected Research
According to the article by Leigh et al. (2020), this research aims to understand better and explore US emergency nurses’ motivations for safeguarding themselves from Ebola-infected patients. In investigating the variables and predictors related to emergency nurses’ desire to protect themselves when dealing with patients who have an Ebola virus at work, the study will employ a modified version of the Protection Desire Theory (PMT). The research focuses on the unique challenges faced by emergency nurses and other healthcare professionals because of the low prevalence rate of Ebola in previous outbreaks and the irregular occurrence of the disease in nations such as the United States. Nurses are frequently the first to arrive in hospital facilities, and the article underscores their lengthy and close contact with patients and their higher risk of contracting the virus. About emergency nurses in particular, the study intends to further knowledge of how they assess the danger of contracting Ebola and what motivates them to take precautions. In ensuring the safety of healthcare workers and the general public during a potential epidemic, this research is pertinent in improving healthcare professionals’ readiness and response tactics.
Nonparametric Kruskal-Wallis H Test
The Kruskal-Wallis H test is a nonparametric test used to compare three or more independent groups. This study employed it to identify significant differences among groups related to the variables of interest. The test generates χ² values. The study highlights nonparametric testing to identify connections more cautiously without depending on standard assumptions. The Bonferroni correction was used to account for the possible multiple-testing problem. The findings from these statistical studies help to clarify the variables and determinants related to US emergency nurses’ desire to shield themselves from patients who have Ebola. When the data distribution requirements of parametric tests are not satisfied, nonparametric techniques are frequently employed (Schober & Vetter, 2020). Parametric methods, such as t-tests and ANOVA, assume specific properties of the data distribution, and they may be considered inappropriate for the statistical analysis of the research study’s data.
Normality Assumptions
The data is assumed to have a normal distribution for parametric tests such as ANOVA and t-tests. It is evident in the text that nonparametric techniques were selected to find connections more cautiously without making any assumptions about normalcy. Example: If the distribution of the researched Protection Motivation Theory (PMT) components or demographic variables deviates from normality, parametric testing could yield erroneous findings.
Categorical Variables and Ordinal Data
Nonparametric tests are more appropriate when examining ordinal data or data that deviates from the parametric tests’ interval assumptions. Nonparametric methods work better when dealing with categorical variables (Vimal et al., 2022). For instance, the study looks at PMT components, which can include replies on the Likert scale. Such ordinal data are better suited for nonparametric testing.
Strengths of the Research
The research strengths include the discovery of statistically significant correlations between the modified Protection Motivation Theory (PMT) variables and the protection motivation outcome variables among emergency nurses. The discovery of relevant variables through multiple linear regression provided a thorough grasp of the elements influencing nurses’ willingness to shield themselves from probable Ebola patients. Using Principal Component Analysis (PCA) to distinguish between proactive and passive components. The study improved the analysis’s accuracy. The results support the validity of the findings, which is consistent with earlier research that used PMT as its theoretical framework. The study also covered the practical ramifications for emergency nurses, offering administrators tactics to boost staff morale and strengthen preventive measures.
Weaknesses of the Research
Among the study’s weaknesses are possible limits on generalizability because the sample was selected from Emergency Nurses Association (ENA) members, which may only accurately reflect some emergency nurses in the country. External legitimacy is in danger because of this. The poll that was carried out more than a year after the epidemic may have impacted response rates, and the timing of the Ebola outbreak may have affected nurses’ motivation. Despite a high % statistical power of 93%, the 23% response rate may raise questions regarding the findings’ generalizability. The study notes its limitations about media messaging’s impact on perceived danger and recollection bias. The ongoing COVID-19 epidemic was not addressed in the study, and although the conclusions are pertinent to Ebola, their generalizability to other infectious illnesses may differ. The study needs to address potential obstacles to these treatments. Therefore, there is a need for more research. Recommendations for ongoing training and education may take more work to apply globally.
Findings and Recommendations of the Research
The research by Leigh et al. (2020) significantly contributes to evidence-based nursing practice by revealing statistically significant relationships between modified Protection Motivation Theory (PMT) variables and outcome variables related to protection motivation among emergency nurses dealing with potential Ebola-infected patients. The research reveals positive indicators using a sophisticated analysis distinguishing between the desire for proactive and passive protection. It highlights the significance of response efficacy and self-efficacy in affecting nurses’ motivation for proactive protection. Furthermore, it finds that perceived vulnerability, reaction cost, and knowledge are all predictive factors of the desire for passive protection, providing helpful information for focused interventions. Given that COVID-19 and Ebola have comparable transmission pathways, the study’s suggestions for ongoing education, training, and demonstrations to increase nurses’ self-assurance and decrease their incentive for passive protection are even more relevant. The study acknowledges its limits and recommends more research examining the impacts of time and comprehending the actual actions of nurses, which might provide vital information for improving infection control measures in hospital environments.
Hillary
Statistical Analysis in Nursing
Goals and Purpose of the Study
Various clinical research studies employ parametric and nonparametric statistical approaches depending on the nature of the data and assumptions that can be reasonably met (Gray & Grove, 2020). In this discussion, Beaudart et al. (2023) is the selected study that employed one of these methods. The research focused on exploring the perception of nurses practicing in adult ICUs regarding the occurrence of medication administration errors during continuous infusion therapies. The research recruited a total of 300 nurses and allowed them to complete a digital web-based survey to examine their perception regarding the frequency and severity of MAEs, factors contributing to their occurrence, and the effectiveness of infusion pumps and smart infusion safety technology. The findings revealed that approaches to decrease MAEs in adult ICUs should focus on various factors, including the high patient-to-nurse ratio, problems in communication among nurses, frequent staff changes and transfers of care, and incorrect dosage on drug labels. Besides, most nurses perceived the smart infusion safety technology as an important tool to reduce MAEs.
How NonParametric Are Used In The Study
Gray and Grove (2020) defines nonparametric analysis as a statistical technique that does not make clear assumptions regarding the underlying distribution of the population from which the data is drawn. In the Beaudart et al. (2023) study, the nonparametric tests used were the Mann-Whitney U-test, Kruskal-Wallis Test, and Wilcoxon signed-rank test. Mann-Whitney U-test and Kruskal-Wallis test were used to compare the occurrence of medication administration errors between the independent groups, while the Wilcoxon Signed-Rank test compared the occurrence of medication administration errors within paired groups. The results indicated that the data on medication errors is not normally distributed, and the assumptions cannot be met.
Parametric Methods Inappropriateness for the Statistical Analysis of the Research Study’s Data
Parametric methods play a crucial role in statistical analysis since they make certain assumptions regarding the characteristics of the population distribution from which the data is drawn (Gray & Grove, 2020). In Beaudart et al. (2023), the parametric technique used was a Spearson correlation and parametric statistics for measuring mean differences. Despite this technique assisting with measuring significant differences between categories, it can be inappropriate when the data is significantly skewed or does not meet the normality assumption. Besides, they can be inappropriate when the variances are not approximately equal, leading to inaccurate results.
Strengths and Weakness of the Research Study
The strength of this study is its ability to recruit participants appropriate to address the clinical research problem. Besides, the design used was suitable to help examine the phenomenon of interest and provide estimates of the frequency of outcomes. However, the limitation present in this study is its cross-sectional nature, resulting in no causal relationship that can be inferred. Despite the sample size being adequate, no sample size calculation was performed. Besides, the researchers cannot assure whether the population included represents the targeted population.
How the Findings and Recommendations of the Research Study Contribute to Evidence-Based Practice for Nursing
Beaudart et al.’s (2023) study contributes to the body of research since it provides information regarding the occurrence of MAEs during the intravenous medication administration process. Healthcare professionals can use this study’s findings to identify strategies to decrease the prevalence of medication errors. This includes providing training to the clinical staff and identifying factors contributing to the occurrence of MAEs. Clinical staff can use the perception of other nurses in this context to understand the significance of incorporating technology to decrease the incidences of MAEs.
Vero
Main Question Post: Statistical Analysis in Nursing
Statistical analysis in nursing research is essential in determining the application of the findings. In mental health practice, both parametric and non-parametric methods could be used to evaluate the collected data. The choice of the method depends on the objectives and the nature of the data collected.
Article selected.
Kwok, Y. T., & Mah, A. P. (2023). A qualitative study on the experience of healthcare staff who have undergone a hybrid root cause analysis training program.
BMJ Open Quality,
12(2), e002153. The selected study is by Kwok & Mah (2023), which investigated the experience of healthcare workers after they had undertaken a root cause analysis training.
Goals and purpose of the research study
The goal of this study was to determine whether the training positively impacted the experience of the healthcare practitioners in terms of solving the challenges that exist. The scholars used a qualitative approach to evaluate the gathered evidence. First, they employed synchronous focus group interviews to collect data. They then integrated purposive sampling to select participants. The data analysis integrated the use of audio recording, transcribed verbatim, and anonymized transformation. The analysis resulted in five themes associated with the objective of the study. The contents of the training, the challenges of the model, the perceptions characterizing the model, the nature of the training, and future considerations were depicted in the analysis. Based on the nature of the study, parametric methods could not be used for analysis. This is because the focus of the study was to evaluate the experiences and perceptions of the staff after undertaking the training. In this case, the focus was the narrative of the participants in line with their individualized experiences and attitudes.
Strengths and weaknesses of the research study
The strengths of the method used include the capacity to integrate experiences, perceptions, and attitudes in analysis. On the other hand, the weaknesses include the lack of numerical appeal and measurement of the correlation among variables. The application of the findings revolves around optimizing quality improvement, which is also depicted in other similar studies (Martin-Delgado et al., 2020; Driesen et al., 2020).