In the context of a DNP project, the Knowledge to Action Framework can provide a systematic and evidence-based approach to translate knowledge into practice and promote positive outcomes for patients. This framework helps to identify the barriers and facilitators to implementing evidence-based interventions and supports the process of knowledge translation in a particular setting.
In this case, the organizational setting is a primary care clinic for adult patients with common chronic conditions, where approximately 30 patients are seen per day and about 1500 patients over a year. The population for the DNP project is described as adults aged 18 and older with a BMI of over 25. To calculate the sample size of 30 adult patients, several factors need to be considered, such as the level of statistical power desired, the expected effect size, and the desired level of significance. Typically, statistical power of 0.80, effect size of 0.5, and a significance level of 0.05 are commonly used in sample size calculations. However, without further information, it is difficult to determine exactly how the sample size was calculated for this particular project.
The proposed data analysis plan consists of a paired t-test to compare pre-intervention and post-intervention patients’ weight. This test will help determine if there is a significant difference in weight before and after the intervention. The sample will be recruited at the clinic based on the inclusion and exclusion criteria, and strategies to mitigate patient barriers have been identified.
In terms of the expected results, the t-test will provide information on whether the intervention had a statistically significant effect on patients’ weight. The null hypothesis is that there is no significant difference in weight before and after the intervention. An alternative hypothesis is that there is a significant difference in weight before and after the intervention. A significant finding would suggest that the intervention had an impact on patients’ weight, whereas a non-significant finding would suggest that the intervention did not have a significant effect.
Descriptive statistics will be used to summarize and describe the data collected for the DNP project. The specific descriptive statistics that will be used will depend on the nature of the data and the research questions or objectives of the project. Common descriptive statistics include measures of central tendency (e.g., mean, median) and measures of dispersion (e.g., standard deviation, range). These statistics can provide information about the distribution and variability of the data.
It is important to note that while the above information provides a general overview, the full details of the DNP project are necessary to provide a more comprehensive understanding of the study design, methods, and analysis. Additionally, it is important to consider ethical considerations, limitations, and practical implications related to the DNP project, as these factors can influence the interpretation and generalizability of the results.
In conducting research for a DNP project, it is important to use scholarly and evidence-based sources that provide current and relevant information. These sources should be within the last five years to ensure that the information is up-to-date and reflective of the current state of knowledge in the field. When citing or referencing information from these sources, it is important to adhere to the appropriate citation and referencing standards according to the chosen citation style, such as APA or AMA.
References:
1. Graham ID, Logan J, Harrison MB, et al. Lost in knowledge translation: time for a map? J Contin Educ Health Prof. 2006;26(1):13-24. doi:10.1002/chp.47
2. Burnet DL, Plaut AJ, Wolf SA, Huo D, Solomon MC, Dekayie G. Reach-out: a family-based diabetes prevention program for African American youth. J Natl Med Assoc. 2010;102(3):269-277.
3. Polit DF, Beck CT. Nursing research: generating and assessing evidence for nursing practice. 10th ed. Wolters Kluwer Health; 2016.
