NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING

Walden University NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING– Step-By-Step Guide

This guide will demonstrate how to complete the Walden University NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.

How to Research and Prepare for NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING

Whether one passes or fails an academic assignment such as the Walden University NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.

After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.

How to Write the Introduction for NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING

The introduction for the Walden University NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.

How to Write the Body for NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING

After the introduction, move into the main part of the NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.

Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.

How to Write the Conclusion for NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING

After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.

How to Format the References List for NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING

The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.

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Sample Answer for NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING

Leigh, L., Taylor, C., Glassman, T., Thompson, A., & Sheu, J-. J. (2020)

Introduction

The selected article outlines a research study with the stated goal of determining what drives American emergency nurses to adopt protective measures against working with Ebola patients. A modified version of the Protection Motivation Theory (PMT) was employed in this study to examine the associations and predictors of the nurses’ motivation to adopt Ebola precautions based on multiple psychological traits (Leigh et al., 2020). The purpose of this study is to investigate the relationship between emergency nurses’ anxiety of treating Ebola patients and the psychological elements that encourage them to adopt preventative measures during outbreaks.

Utilizing statistics

The group uses nonparametric testing in their statistical analysis. Because the data in this study do not meet the normalcy assumptions of parametric testing, nonparametric tests are used. Whereas Fisher’s exact and chi-square tests are used to compare categorical variables, the Wilcoxon rank-sum test is used to compare continuous variables between groups. Empirical research indicates a strong correlation between emergency nurses’ psychological traits and their inclination to stop the spread of Ebola. Nonparametric tests such as the post hoc Dunn-Bonferroni and Kruskal-Wallis H tests are used to assess the demographic and PMT construct data. The nonparametric Kruskal-Wallis H test was used to determine whether there was a statistically significant difference between the sexes. According to Dunn-Bonferroni post hoc tests, respondents who were male showed higher levels of self-efficacy; nevertheless, the response cost for female nurses was higher. In terms of perceived vulnerability, response cost, and passive protection motivation, the results also differ significantly throughout the age range that was studied. For this study’s statistical analysis, non-normal data means that nonparametric procedures (tests and ANOVA) are out of place. The study utilized nonparametric tests such as Kruskal-Wallis and Spearman’s rho correlation, which are chosen because they conservatively identify relationships without presuming normalcy. Given that some of the study’s variables are ordinal, parametric tests are likewise improper. While tests like the Wilcoxon rank-sum test are used to compare continuous variables across groups, chi-square, and Fisher’s exact tests are used to analyze the significance of a relationship between categorical variables(Gray, Grove, & Sutherland, 2020)

Strength and Weaknesses

The study’s various aspects include its use of a modified version of the partial-merit theory (PMT) model to analyze the psychological elements that affect emergency nurses’ desire to take precautions during outbreaks. A high sample size helps this research since it can more precisely represent the population. One drawback of the study is that it is cross-sectional, which makes inferring causal relationships challenging. Since the study exclusively examined 2015 enrollees in the Emergency Nurses Association, its conclusions may not be generalizable to the profession as a whole (ENA). Ten demographic and construct-specific components make up the survey, which is validated by subject-matter specialists and a focus group. Furthermore, a three-phase mailing approach is employed in the study to enhance the quantity of replies. The likelihood that the sample of nurses in this study is not representative of all emergency nurses in the US is one of the study’s shortcomings, which would limit how broadly the results can be applied. Given the date of the Ebola epidemic, nurses may have been more careful when treating patients, which could have contributed to the slower-than-usual response time.

Utilizing Statistical Method/Conclusion

The findings and recommendations of the study offer insight into the psychological elements that influence nurses’ motivation to defend themselves against Ebola patients, potentially advancing evidence-based nursing practice. Proactive protection motivation was revealed to be affected by nurses’ self-efficacy and response efficacy, but passive protection motivation was found to be affected more by nurses’ perceived vulnerability, response cost, and knowledge. According to the study’s authors, hospitals and clinics should establish protocols for admitting Ebola patients, train and observe nurses, stockpile respirators, impermeable disposable gowns and coveralls, extended cuff disposable examination gloves, boot covers, disposable aprons, and more.

Reference

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. Chapter 25,”Using Statistics to Determine Differences” (pp. 687-698)

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.

Sample Answer 2 for NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING

Article:  Nonparametric Statistical Methods in Medical Research

What are the goals and purpose of the research study described by the article you selected?

This article by Schober & Vetter (2020) has the intention of utilizing the non-parametric test Mann-Whitney U, to compare the pain scores between the effects of preoperative gum chewing on sore throat after anesthesia with a supraglottic device and those who do not chew gum preoperatively. Schober & Vetter (2020) explain that their null hypothesis is that both groups have the same distribution and come from the same population, more precisely if one group is more likely to be higher. Gray & Grove (2020) explain that these nonparametric tests are available when the assumptions do not need to be as in parametric statistics. 

How are nonparametric tests used in the research study? What are the results of their use? Be specific.

This study uses a nonparametric test called the Mann-Whitney U to test two independent groups. The result shows data from a chart of self-reported pain scores between the patients chewing gum and those who did not. The pain score is reported 2 hrs, 6 hrs, and 24 hours after surgery for 69 people. The G group are those that are chewing gum and the C group is the control group. The p value for 2 hours and 6 hours is 0.48. The p value for 24 hours is .011. 

Why are parametric methods ( tests and ANOVA) inappropriate for the statistical analysis of the research study’s data? Be specific and provide examples.

Parametric methods are not appropriate for the statistical analysis of this research study because there are no specific assumptions to be met. Gray & Grove state that parametric statistics are known for a specific set of assumptions and it becomes the formula. This study does not have those assumptions. It is comparing 2 independent groups. 

What are the strengths and weaknesses of the research study (e.g., study design, sampling, and measurement)?

This particular study’s weaknesses could be that it is less efficient than a parametric test. The potential strengths are that these tests are less sensitive to data that is not within the normal range and apply to a much broader population. 

How could the findings and recommendations of the research study contribute to evidence-based practice for nursing?

It is endless how the Mann-Whitney U can contribute to evidence for nursing practice. This test is an excellent option to compare two populations such as behavior and mood or such as a comparison between emotional lability and detox patients. 

References

Schober, P., & Vetter, T. R. (2020). Nonparametric Statistical Methods in Medical Research. Anesthesia and analgesia, 131(6), 1862–1863. https://doi.org/10.1213/ANE.0000000000005101

Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevi

Sample Answer 3 for NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING

Ask a probing question, substantiated with additional background information, evidence, or research.

I enjoyed reading your highlighted research study. It was interesting to me that the more experience a charge nurse had, the better able they were to recognize an unsafe situation meaning that their perception of safety decreased. What factors outside of competence training and ongoing education may be establishing a correlation between charge nurse experience and perception of safety? From personal experience, nursing judgment, one of the core tools nurses utilize to determine patient safety, increases with nursing experience. This may be a factor that is helping more experienced charge nurses be able to recognize unsafe situations. A different research study suggests that nurses perception of patient safety culture may be influenced by hospital accreditation programs (Kwan, 2021). If a hospital was accredited, nurses felt that patient safety culture was positively influenced. This shows that another factor in determining patient safety may be the level of credentials a hospital has. If a hospital has more credentials, this may mean the hospital is more qualified to care for patients therefore increasing patient safety.

Validate an idea with your own experience and additional research.

I would have to raise awareness to the fact you list implications that nurses’ perceptions are negatively affected by having charge responsibilities. This, as I stated above, may be due to more experience. With experience, you are able to better recognize an unsafe situation and a safe situation. I don’t think this is a bad thing. Being able to recognize an unsafe situation is crucial in nursing. Research performed by Biresaw supports the idea that more experience lead to an increase in patient safety (2020). Nurses who were more educated were better able to provide patient safety. This research study was able to use correlational analysis to identify that there was a relationship between level of education and perception of patient safety. As stated by Gray and Grove, the purpose of correlational analysis is to understand the relationship among different concepts (2020).

References

Biresaw, H., Asfaw, N., & Zewdu, F. (2020). Knowledge and attitude of nurses towards patient safety and its associated factors. International Journal of Africa Nursing Sciences 13. https://doi.org/101016/j.ijans.2020.100229Links to an external site..

Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research:

Appraisal, synthesis, and generation of evidence (9^th ed.). Elsevier.

Kwan, M. R., Seo, H. J., & Lee, S. J. (2021). The association between experience of hospital accreditation and nurses’ perception of patient safety culture in South Korean general hospitals: a cross-sectional study. BMC Nurs 20, 195. https://doi.org/10.1186/s12912-021-00708-x.

Sample Answer 4 for NURS 8201 WEEK 8 DISCUSSION: STATISTICAL ANALYSIS IN NURSING

Article chosen:

Wilson, D., Redman, R., Talsma, A., & Aebersold, M. (2012). Differences in perceptions of patient safety culture between charge and noncharged nurses: Implications for effectiveness outcome. Nursing Research and Practice, 2012, 1–7. doi:10.1155/2012/847626

What are the goals and purpose of the research study described by the article you selected?

The research study described in the article aims to explore and compare the perceptions of patient safety culture between two distinct groups of nurses: charge nurses and staff nurses (non-charge nurses). The primary goal is to determine if there are significant differences in how these two groups perceive the safety culture within nursing units. This investigation is crucial because charge nurses, who are often frontline unit leaders making shift-by-shift decisions, and staff nurses, who mainly provide direct patient care, play pivotal roles in the implementation of safety guidelines and the utilization of research evidence in clinical settings.

The purpose of the study is highlighted as follows:

To Compare Perceptions of Safety Culture: The study specifically seeks to understand how charge nurses and staff nurses perceive aspects of the patient safety culture differently within their work environments. This includes their overall perceptions of safety, the frequency of event reporting, teamwork dynamics within units, and their personal safety grading of the work area.

To Examine the Impact of Charge Nurse Experience: By differentiating between nurses with various levels of charge responsibilities (e.g., permanent charge nurses, relief charge nurses, and those without any charge nurse experience), the study intends to assess how the extent of responsibility and leadership experience might influence perceptions of safety.

To Inform Effective Implementation of Practice Guidelines: Understanding these perceptions can aid healthcare organizations in tailoring interventions that promote the effective implementation of evidence-based practice guidelines. Charge nurses, often utilized as change champions, could be better supported through targeted strategies that consider their unique insights and challenges related to patient safety culture.

Overall, the study focuses on identifying and addressing potential disparities in safety culture perceptions which could impact the practical application of safety protocols and guidelines across different nursing roles within acute care settings. This could ultimately contribute to enhancing patient care outcomes by refining the roles of charge and non-charge nurses in safety and practice guideline implementation.

 How are nonparametric tests used in the research study? What are the results of their use? Be specific.

 In the research study described, nonparametric tests are utilized to analyze differences in perceptions of patient safety culture among charge and non charged nurses. Specifically, the Pearson’s chi-square test and the t-test for independent samples are used as part of the study’s statistical approach to handling the data collected through surveys.

Use of Nonparametric Tests:

Pearson’s Chi-square Test:

• Purpose: This test is used to examine the relationship between categorical variables, specifically looking at the percentage of shifts nurses are in charge and the number of events reported.
• Application: It tests the independence between two categories such as the percentage of shifts worked in charge (less than 25% vs. more than 25% of shifts in charge) and the frequency of events reported (no event, 1-2 events, 3–21 events).

Two-tailed t-test for Independent Groups:

• Purpose: Although technically a parametric test, it is used here assuming non-normal distribution could be tolerated given large sample sizes or robustness of the t-test. It aims to compare means between two independent groups who do not share charge experience.
• Application: The test compares the mean scores for perceptions of safety between nurses with charge experience and those without.

Results of Their Use:

Results from Pearson’s Chi-square Test:

• Findings: Significant variations were observed in the reporting of events among nurses with different levels of charge responsibilities. Nurses with more than 25% shifts in charge reported a higher number of safety incidents (3 to 21 events) compared to those with less than 25% of shifts in charge or no charge experience. This suggests that charge nurses may be more aware or more diligent in reporting potential safety issues or incidents.
• Statistical Output: Chi-square value was 13.240 with a p-value of .010, indicating statistical significance in the differences observed among the groups.

Results from Two-tailed t-test:

• Findings:
  • Nurses with no charge experiencehad a higher overall perception of safety (mean = 3.46) compared to those with some charge experience (mean = 3.27); t(374) = 2.86, P = .005.
  • The number of events reported was higher among nurses with some charge experience(mean = 2.31) than those without (mean = 2.06); t(368) = -3.35, P = .001.
• Implication: These results suggest that having charge responsibilities may influence nurses’ perceptions negatively, possibly because charge nurses are more exposed to the complexities and risks inherent in their roles which might lower their overall safety perception.

The nonparametric tests used in the study effectively highlighted significant differences in safety perceptions and reporting behaviors between charge and non charged nurses. These results are critical as they suggest that the role and experience level in charge positions can significantly impact how safety culture is perceived and reported in healthcare settings. This understanding can help tailor interventions and support mechanisms for charge nurses to enhance patient safety outcomes (Turhan 2020).

 Parametric methods like t-tests and ANOVA are generally favored for their statistical power and ability to handle complex designs (Yu, et al. 2022). However, their appropriateness hinges on several key assumptions about the data they are applied to. When these assumptions are violated, the reliability and validity of the test results are compromised. Here’s why these methods might be inappropriate for the research study’s data involving charge and non charged nurses’ perceptions of patient safety culture:

Assumptions of Parametric Tests

Parametric tests, including t-tests and ANOVA, rely on the following assumptions:

Normality: Data should be normally distributed within groups. This assumption is crucial because parametric tests are based on the distribution of the means and heavily rely on the mean and standard deviation as measures of central tendency and dispersion.

Homogeneity of Variances: The variance among the groups should be equal. When comparing group means, as in ANOVA or t-tests, the assumption is that all groups have the same variance. If variances are unequal, the probability estimates about the means may be off.

Interval or Ratio Level Data: The data should be on an interval scale (where numerical distances between values are meaningful) or a ratio scale (which has a meaningful zero).

Independence: Observations must be independent of each other, which is typically satisfied by proper random sampling and assignment in experimental designs.

Specific Concerns in the Study

Normality:

• Example: Nurse perceptions of safety might not be normally distributed. For instance, it’s common in survey data for responses to skew towards more positive or more negative ends, especially in fields like healthcare where respondent bias towards socially desirable answers (e.g., overrating safety) can skew distributions.
• Impact: Using t-tests or ANOVA without normal distribution can lead to incorrect conclusions about significant differences due to the effect of outliers or skewed data. This can either inflate type I errors (false positives) or increase type II errors (false negatives).

Homogeneity of Variances:

• Example: Variance in the number of events reported could differ significantly between nurses with different charge responsibilities — perhaps less experienced nurses report fewer events due to less familiarity with protocols, resulting in unequal variances across groups.
• Impact: If variances are unequal (a condition known as heteroscedasticity), standard parametric tests can yield erroneous results because these tests assume equal variability among the groups.

Sample Size and Distribution Shape:

• Example: The study’s groups (charge vs. noncharged nurses) might have different sample sizes, which can exacerbate the effects of non-normality in data, particularly if the smaller group is highly skewed.
• Impact: Non-normality is particularly problematic in smaller samples. Parametric tests might then misrepresent the actual p-values, affecting the study’s findings and conclusions.

Alternative Approaches

Given these potential issues, nonparametric tests might be more suitable because they do not assume normality or equal variances:

• Mann-Whitney U Test(instead of t-tests): This test is used for comparing two independent samples, especially beneficial when the data are ordinal or not normally distributed (Sundjaja, et al. 2023).
• Kruskal-Wallis Test(instead of ANOVA): This test compares more than two groups and is used when the assumption of normality is not met. It is a generalization of the Mann-Whitney U test to more than two groups (UVA 2020).

 While parametric tests provide powerful means for statistical analysis under correct conditions, their use in the context of the described research might lead to misleading results due to the violation of assumptions like normality and homogeneity of variances. Employing nonparametric tests, which are less sensitive to these assumptions, would likely offer more reliable insights into the differences in safety culture perceptions among nurses with varying levels of charge responsibility. This approach ensures that the findings are robust and reflective of true underlying patterns in the data, rather than artifacts of assumption violations (Vrbin 2022).

 What are the strengths and weaknesses of the research study (e.g., study design, sampling, and measurement)?

The research study examining differences in perceptions of patient safety culture between charge and noncharged nurses within a healthcare setting presents various strengths and weaknesses associated with its design, sampling, and measurement methodologies. Analyzing these aspects can help assess the robustness of the study’s findings and suggest areas for improvement in future research.

Strengths:

Study Design:

• Descriptive, Correlational, and Cross-Sectional: This design allows for the examination of relationships between variables (charge status and perceptions of safety culture) at a single point in time, which is practical for assessing current conditions and identifying existing associations without requiring long-term follow-up.
• Clearly Defined Variables: The study defines its primary variables, including the roles of charge and noncharged nurses and various dimensions of patient safety culture, which aids in precise data collection and analysis.

Sampling:

• Large Sample Size: The sample includes 375 nurses, which provides sufficient data for statistical analysis and helps ensure that the findings are stable and reliable.
• Inclusion and Exclusion Criteria: By setting clear criteria (e.g., nurses with at least six months of experience, excluding LPNs and nurse managers), the study targets a specific population of interest and controls for potential confounding variables.

Measurement:

• Use of Established Survey Instrument: Utilizing the AHRQ Hospital Survey on Patient Safety Culture, which has been validated in previous research, lends credibility to the measurement process and enables comparison with other studies.
• Reliability Indicators Provided: Reporting Cronbach’s alpha for the scales used (e.g., .70 for overall perceptions of safety) provides transparency about the reliability of the measures.

Weaknesses:

Study Design:

• Cross-Sectional Nature: While practical, the cross-sectional design limits the ability to infer causality between charge nurse status and safety culture perceptions. Longitudinal designs would be needed to establish causal relationships and track changes over time.
• Single Institution Study: Conducting the study in a single academic medical center may limit the generalizability of the findings to other settings, such as community hospitals or clinics in different geographic areas.

Sampling:

• Potential Selection Bias: The use of a convenience sample may introduce bias, as participants who are available or willing to respond might differ systematically from those who do not participate. This could affect the representativeness of the sample.
• Lack of Randomization: Without random selection of participants, it’s challenging to ensure that the sample accurately reflects the broader population of nurses, potentially limiting the external validity of the findings.

Measurement:

• Subjective Self-report Data: Relying on nurses’ self-reported perceptions can introduce response biases (social desirability or recall biases), where participants might overrate their safety practices or underreport negative incidents.
• Single Source Data: Collecting all data from the same source (nurse respondents) without triangulation (e.g., patient outcomes, peer reports) may affect the depth of understanding and reliability of the findings related to patient safety culture.

Statistical Analysis:

• Assumption Violations for Parametric Tests: The potential non-normality of the data and unequal variances across groups suggest that parametric tests (t-tests, ANOVA) may not be the most appropriate methods, risking type I and type II errors. The use of nonparametric tests could have been a better choice given the data characteristics.

How could the findings and recommendations of the research study contribute to evidence-based practice for nursing?

 The findings and recommendations from the research study examining the perceptions of patient safety culture between charge nurses and non charged nurses provide critical insights that can be instrumental in shaping evidence-based practice (EBP) in nursing. Here’s how these contributions could manifest:

 Improving Patient Safety Interventions

Findings: The study revealed that charge nurses report more safety incidents than noncharged nurses, possibly due to their heightened awareness and leadership responsibilities.

Contributions to EBP:

• Targeted Safety Training: Insights from the study can guide the development of tailored safety training programs that address specific needs of charge and non charged nurses. This could include situational awareness, risk identification, and error reporting.
• Leadership Development Programs: Enhance leadership skills among charge nurses, focusing on effective communication, problem-solving, and crisis management to further foster a proactive safety culture.

Enhancing Implementation of Practice Guidelines

Findings: Differences in safety culture perceptions between nurse categories suggest that uniform strategies might not be effective across all nursing roles.

Contributions to EBP:

• Customized Implementation Strategies: Use the findings to design role-specific approaches for implementing practice guidelines. For instance, charge nurses could benefit from strategies that leverage their influence and leadership, while staff nurses might need more supportive and instructional approaches.
• Incorporate Frontline Input: Charge nurses, given their critical role and unique perspective, should be involved in the planning stages of new safety practices or guidelines to ensure the strategies are realistic and applicable.

 Policy Development and Organizational Change

Findings: The study highlights the importance of organizational context in shaping perceptions of safety culture.

Contributions to EBP:

• Policy Revisions: Recommendations could inform policy changes that support an organizational structure conducive to effective safety practices, such as clear role definitions and responsibilities for charge nurses.
• Change Management: Utilize charge nurses as champions for change who can effectively communicate and implement safety initiatives among their peers.

 Strengthening Safety Culture

Findings: Positive safety culture perceptions correlate with lower adverse events, emphasizing the role of cultural factors in patient outcomes.

Contributions to EBP:

• Cultural Competence Training: Develop and integrate cultural competence training into ongoing education for nurses to enhance understanding and execution of safety practices.
• Continuous Feedback Mechanisms: Establish systems that enable continuous feedback from all nursing levels to monitor and improve the safety culture dynamically.

 Research and Continuous Improvement

Findings: The cross-sectional study design points to the need for more dynamic research approaches to fully understand temporal and causal relationships.

Contributions to EBP:

Longitudinal Research: Advocate for longitudinal studies that can track changes in safety culture over time and assess the impact of specific interventions.

Data-Driven Decisions: Encourage the use of data analytics in nursing practice to identify trends, predict outcomes, and tailor interventions based on real-time data.

The research study’s findings on the differential perceptions of patient safety culture among charge and noncharged nurses serve as a valuable resource for developing, refining, and implementing evidence-based practices. By recognizing and addressing the unique contributions and needs of different nursing roles, healthcare institutions can better design interventions that not only enhance patient safety but also improve nurse satisfaction and effectiveness. These adaptations ensure that evidence-based practices in nursing are not only theoretical ideals but are practically applicable, leading to measurable improvements in healthcare outcomes (Eylul 2020).

 Conclusion:

 The research study investigating the differences in perceptions of patient safety culture between charge nurses and noncharged nurses provides crucial insights that can significantly influence evidence-based practices in nursing. By identifying how perceptions vary by role, the study underscores the need for tailored approaches in training, policy development, and practice implementation that consider the unique perspectives and responsibilities of different nurse categories. Specifically, the findings suggest that integrating charge nurses in the planning and execution of safety protocols can leverage their leadership roles to enhance overall safety culture. Additionally, the study highlights the importance of adapting safety interventions to match the specific context and needs of staff nurses, thereby improving the effectiveness of these measures. Ultimately, the research calls for continuous improvement through role-specific strategies, longitudinal studies, and a proactive involvement of nurses at all levels in fostering a robust patient safety environment. This focused approach not only promises to improve patient care but also to enhance the work environment for nurses by aligning safety culture with the realities of their daily practices (Breedlove, et al. 2022).

References:

Breedlove, D., Amiri, A., Arris, L. (2022). Evaluating the Efficacy of an Evidence-Based Charge Nurse Professional Development Activity at a Highly Complex Veterans Affairs Medical Center. Journal of Nursing Professional Development. 38(2). 19-24. doi: 10.1097/NND.00000000000824.

Eylul, D. (2020). The relationship between Charge nurses and Clinical nurse’s perceptions of patient safety culture and leadership practices. ResearchGate. 14(1) 333-339. doi: 10.46483/deuhfed.743446.

Sundjaja, J., Shrestha, R., Krishan, K. (2023). McNemar and Mann-Whitney U Tests. StatPearls. July 2023. https://www.ncbi.nlm.nih.gov/books/NBK560699/.

Turhan, N. (2020). Karl Pearson’s chi-square tests. Academic Journals. 15(9) 575-580. doi: 10.5897/ERR2019.3817.

University of Virginia Library. (2021). Getting Started with the Kruskal-Wallis Test. https://library.virginia.edu/data/articles/getting-started-with-the-kruskal-wallis-testLinks to an external site.

 Vrbin, C. (2022). Parametric or nonparametric statistical tests: Considerations when choosinf the most appropriate option for your data. Cytopathology. 33(6) 663-667. doi: 10.1111/cyt.13174.

Wilson, D., Redman, R., Talsma, A., & Aebersold, M. (2012). Differences in perceptions of patient safety culture between charge and noncharged nurses: Implications for effectiveness outcome. Nursing Research and Practice, 2012, 1–7. doi:10.1155/2012/847626

Yu, Z., Guindani, M., Grieco, S., Chen, L., Holmes, T., Xu, X. (2022). Beyond t-test and ANOVA: Applications of mixed-effects models for more rigorous statistical analysis in neuroscience research. ScienceDirect. 1(5) 21-35. doi: 10.1016/j.neuron.2021.10.030.