6 comments to my peers – Nursing Research and Evidence Based practice
Comment 1:
The p-value is a crucial statistical measure that plays a significant role in hypothesis testing. It determines the significance of the results obtained from a study and represents the probability of obtaining results as extreme as the observed results, assuming that the null hypothesis is true. It is important to note that a commonly used threshold for statistical significance is a p-value of 0.05 or lower. When the p-value is less than 0.05, it suggests that the results are unlikely to have occurred by random chance alone, leading to the rejection of the null hypothesis in favor of the alternative hypothesis. Conversely, if the p-value is greater than 0.05, it indicates that the results are not statistically significant, meaning there’s insufficient evidence to reject the null hypothesis (Andrade ,2019). It is crucial to understand that even if the p-value is not statistically significant (greater than 0.05), it does not mean that the findings are meaningless. Instead, it suggests that the observed results could occur due to chance, rather than the effects of the variables being studied. Moreover, the generalizability of research is affected by sample characteristics, study design, and contextual factors. Sample characteristics refer to the demographics and characteristics of the participants involved in the study. Study design encompasses the methods used to collect data, including the experimental setup, measures, and procedures. Contextual factors include the setting in which the study was conducted and any unique circumstances that may influence the findings. (Guetterman ,2019). Therefore, while assessing the generalizability of a research article on pain to a nursing problem, it is essential to carefully consider these factors. If the study involved a diverse sample of patients with diverse types of pain and was conducted in a clinical setting relevant to the nursing problem, it may be more applicable. However, if the study had limitations in its sample size, design, or context that limit its relevance to the nursing problem under consideration, its generalizability would be reduced. It is crucial to critically evaluate these factors when determining the applicability of research findings to specific nursing contexts (Kamper ,2020).
Comment 2:
This study looks at varied factors comparing opioid free anesthesia (OFA) to the control group of standard anesthesia practices. The surgical procedure in this study is an anterior approach total hip arthroplasty (THA). The statistical significance of the results is measured in p-value, or probability value. A P value that is less than or equal to 0.05 is considered statistically significant in that the effect is real rather than chance. This study found that OFA showed both statistically significant and insignificant effects. Time to extubating, morphine required in PACU, and time to discharge home were statistically significant with a p values all greater than 0.05. Time to PACU discharge was not statistically significant with a p-value of p=0.45.
Certain results have higher clinical significance. These results decrease patient stay, length of intubation, patient safety, and costs. The most clinically significant result noted is patients discharge earlier with a p<0.001 and decreased oxygen requirements in PACU p=0.003. Working in PACU these are real world improvements.
These results should be generalized and applicable to other surgeries. Aspects that affect generalizability include population details, a large random sampling, and analysis or control of all variables. Detailed population and large random sampling both lead to generalizability by eliminating biases, statistical outliers and accurately representing the population in question. Analyzing or controlling all factors leads to higher accuracy and more information that may be applicable to specific populations.
The research in this paper is generalizable in that the technique was specific and accurate. The sample size was small, and all data came from 1 facility. To improve generalizability, a higher sample size and data from multiple locations in multiple regions. The data is also only applicable to anterior THR. Data from different total joint replacement procedures, or many diverse types of surgery would make this study generalized to OFA as an alternative to traditional anesthesia.
Comment 3:
The p-value is a measurement used in research testing to determine the strength of the evidence against the null hypothesis. It indicates the probability of obtaining the observed results if the null hypothesis were true. Clinical significance refers to the practical importance or relevance of the study results in real-world settings. Even if the p-value is not statistically significant, the results may still be clinically meaningful if they have a meaningful impact on patient outcomes or practice.
According to the article “Honey for Wound Management: A Review of Clinical Effectiveness and Guidelines,” the null hypothesis would be that there is no difference in wound healing between honey and standard wound care. The alternative hypothesis would be that there is a difference, with honey being either more effective or less effective than standard care. Any observed differences in wound healing between honey and standard care could be due to random chance rather than a true difference in effectiveness. However, according to the article, there was a statistical difference between those treated with honey and those treated with standard wound management. The P value would be great in strength and therefore counteract the null hypothesis making it void. The P value holds clinical strength in the notion that honey therapies are substantial in treating wounds. Honey has been proven clinically effective and applicable to similar clinical settings and patient populations.
The study on honey for wound healing had a sample that closely resembles the population of hospitalized patients with wounds, and the findings are more generalizable to the presented nursing problem. The setting is similar and configures to the nursing study at hand. The study had no methodological flaws, such as bias or confounding variables, and therefore the generalizability is valid.
Comment 4:
The article chosen by the student was the article published by Han et al. (2021) on effects of a four-year intervention on hand hygiene compliance and incidences of healthcare-associated infections. In this study, the p value was set at 0.01. The p-value is a statistical measure that helps to determine the significance of a hypothesis test. It is the probability of obtaining a test statistic at least as extreme as the one that was actually observed, assuming that the null hypothesis is true. The smaller the p-value, the stronger the evidence against the null hypothesis and the greater the confidence we have in rejecting it. The study found out that The HH compliance increased from 68.90% in 2017 to 91.76% in 2020 and the incidence of HAIs decreased from 1.10 to 0.91% (P?<?0.01) (Han et al., 2021). This p-value is statistically significant. This means that there is strong evidence against the null hypothesis, which is the hypothesis that there is no difference between groups or no relationship between variables.
Generalizability is the degree to which research findings can be applied to a broader context (Andrew et al., 2022). There are several factors that determine the generalizability of a study, including the randomness of the sample, how representative the sample is of the population, and the size of the sample. The outcomes of the research are generalizable. The sample size is adequate, and thus well representative of the population. There was also adequate randomization. Therefore, these outcomes can be applied to a broader context.
Comment 5:
Levels of evidence play a crucial role in guiding practice changes by providing a hierarchy of research designs based on their methodological rigor and reliability. Healthcare professionals use levels of evidence to evaluate the strength of research findings and determine the confidence they can place in the results when making clinical decisions or implementing changes in practice (AACN Levels of Evidence – AACN, n.d.).
The most reliable level of evidence is typically systematic reviews and meta-analyses of randomized controlled trials (RCTs), as they synthesize findings from multiple high-quality studies to provide the highest level of evidence. These studies undergo rigorous methodological processes, including comprehensive literature searches, critical appraisal of included studies, and statistical analysis to pool data across studies (Research Guides: Nursing Resources: Levels of Evidence (I-VII), n.d.).
An example of a practice change resulting from this level of evidence could be the adoption of a new treatment protocol for a specific medical condition. For instance, suppose a systematic review and meta-analysis of RCTs consistently demonstrate that a particular medication is more effective than standard treatment in managing a certain disease with minimal adverse effects. In that case, healthcare providers may update clinical guidelines or treatment protocols to recommend the use of this medication as a first-line therapy for patients with that condition. This practice change is based on robust evidence derived from the highest level of evidence, ensuring that patients receive the most effective and evidence-based care.
Comment 6:
Levels of evidence play a crucial role in guiding practice changes in healthcare. These levels are used to categorize the strength of evidence supporting a particular intervention or practice, with higher levels indicating stronger evidence. Professional organizations and healthcare institutions use levels of evidence to develop clinical practice guidelines and remain up to date in accordance to evidenced based practices. Levels of evidence are used to educate healthcare providers about the strength of evidence supporting different practices. Higher levels of evidence are given more weight in the development of guidelines, leading to practical changes that align with these recommendations.
Research has shown that the most reliable level of evidence is often considered systematic reviews and analyses of randomized control trials. These studies provide a comprehensive summary of the existing evidence on a particular intervention or practice, making them reliable for guiding practice changes. An example of a practice change that could result from this level of evidence is the adoption of a new treatment protocol for a specific condition based on the findings of a systematic review and meta-analysis demonstrating its effectiveness compared to standard care, such as my ongoing example of using honey-based therapies in the treatment of wounds compared to standard wound management.
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