NR716 Week 5 Discussion | Analyzing Descriptive Statistics
NR716 Week 5 Discussion | Analyzing Descriptive Statistics – Step-by-Step Guide With Example Solution
The first step before starting to write the NR716 Week 5 Discussion | Analyzing Descriptive Statistics is to understand the requirements of the assignment. The first step is to read the assignment prompt carefully to identify the topic, the length and format requirements. You should go through the rubric provided so that you can understand what is needed to score the maximum points for each part of the assignment.
It is also important to identify the paper’s audience and purpose, as this will help you determine the tone and style to use throughout. You can then create a timeline to help you complete each stage of the paper, such as conducting research, writing the paper, and revising it to avoid last-minute stress before the deadline. After identifying the formatting style to be applied to the paper, such as APA, review its use, including writing citations and referencing the resources used. You should also review the formatting requirements for the title page and headings in the paper, as outlined by Chamberlain University.
How to Research and Prepare for NR716 Week 5 Discussion | Analyzing Descriptive Statistics
The next step in preparing for your paper is to conduct research and identify the best sources to use to support your arguments. Identify a list of keywords related to your topic using various combinations. The first step is to visit the Chamberlain University library and search through its database using the important keywords related to your topic. You can also find books, peer-reviewed articles, and credible sources for your topic from the Chamberlain University Library, PubMed, JSTOR, ScienceDirect, SpringerLink, and Google Scholar. Ensure that you select the references that have been published in the last 5 years and go through each to check for credibility. Ensure that you obtain the references in the required format, such as APA, so that you can save time when creating the final reference list.
You can also group the references according to their themes that align with the outline of the paper. Go through each reference for its content and summarize the key concepts, arguments and findings for each source. You can write down your reflections on how each reference connects to the topic you are researching. After the above steps, you can develop a strong thesis that is clear, concise and arguable. Next, create a detailed outline of the paper to help you develop headings and subheadings for the content. Ensure that you plan what point will go into each paragraph.
How to Write the Introduction for NR716 Week 5 Discussion | Analyzing Descriptive Statistics
The introduction of the paper is the most crucial part, as it helps provide the context of your work and determines whether the reader will be interested in reading through to the end. Begin with a hook, which will help capture the reader’s attention. You should contextualize the topic by offering the reader a concise overview of the topic you are writing about so that they may understand its importance. You should state what you aim to achieve with the paper. The last part of the introduction should be your thesis statement, which provides the main argument of the paper.
How to Write the Body for NR716 Week 5 Discussion | Analyzing Descriptive Statistics
The body of the paper helps you to present your arguments and evidence to support your claims. You can use headings and subheadings developed in the paper’s outline to guide you on how to organize the body. Start each paragraph with a topic sentence to help the reader know what point you will be discussing in that paragraph. Support your claims using the evidence collected from the research, and ensure that you cite each source properly using in-text citations. You should analyze the evidence presented and explain its significance, as well as how it relates to the thesis statement. You should maintain a logical flow between paragraphs by using transition words and a flow of ideas.
How to Write the In-text Citations for NR716 Week 5 Discussion | Analyzing Descriptive Statistics
In-text citations help readers give credit to the authors of the references they have used in their work. All ideas that have been borrowed from references, any statistics and direct quotes must be referenced properly. The name and date of publication of the paper should be included when writing an in-text citation. For example, in APA, after stating the information, you can put an in-text citation after the end of the sentence, such as (Smith, 2021). If you are quoting directly from a source, include the page number in the citation, for example (Smith, 2021, p. 15). Remember to also include a corresponding reference list at the end of your paper that provides full details of each source cited in your text. An example paragraph highlighting the use of in-text citations is as below:
“The integration of technology in nursing practice has significantly transformed patient care and improved health outcomes. According to Morelli et al. (2024), the use of electronic health records (EHRs) has streamlined communication among healthcare providers, allowing for more coordinated and efficient care delivery. Furthermore, Alawiye (2024) highlights that telehealth services have expanded access to care, particularly for patients in rural areas, thereby reducing barriers to treatment.”
How to Write the Conclusion for NR716 Week 5 Discussion | Analyzing Descriptive Statistics
When writing the conclusion of the paper, start by restating your thesis, which helps remind the reader what your paper is about. Summarize the key points of the paper by restating them. Discuss the implications of your findings and your arguments. Conclude with a call to action that leaves a lasting impression on the reader or offers recommendations.
How to Format the Reference List for NR716 Week 5 Discussion | Analyzing Descriptive Statistics
The reference helps provide the reader with the complete details of the sources you cited in the paper. The reference list should start with the title “References” on a new page. It should be aligned center and bolded. The references should be organized in an ascending order alphabetically, and each should have a hanging indent. If a source has no author, it should be alphabetized by the title of the work, ignoring any initial articles such as “A,” “An,” or “The.” If you have multiple works by the same author, list them in chronological order, starting with the earliest publication.
Each reference entry should include specific elements depending on the type of source. For books, include the author’s last name, first initial, publication year in parentheses, the title of the book in italics, the edition (if applicable), and the publisher’s name. For journal articles, include the author’s last name, first initial, publication year in parentheses, the title of the article (not italicized), the title of the journal in italics, the volume number in italics, the issue number in parentheses (if applicable), and the page range of the article. For online sources, include the DOI (Digital Object Identifier) or the URL at the end of the reference. An example reference list is as follows:
References
Morelli, S., Daniele, C., D’Avenio, G., Grigioni, M., & Giansanti, D. (2024). Optimizing telehealth: Leveraging Key Performance Indicators for enhanced telehealth and digital healthcare outcomes (Telemechron Study). Healthcare, 12(13), 1319. https://doi.org/10.3390/healthcare12131319
Alawiye, T. (2024). The impact of digital technology on healthcare delivery and patient outcomes. E-Health Telecommunication Systems and Networks, 13, 13-22. 10.4236/etsn.2024.132002.
NR716 Week 5 Discussion | Analyzing Descriptive Statistics Instructions
Purpose
The purpose of this discussion is for you to demonstrate an understanding of the DNP-prepared nurse’s role in the work of both appraising statistical tests in quantitative research studies and application of statistical tests to a practice change project. Have a look at NR716 Week 6 Discussion | Using Non-parametric Statistical Tests.
Instructions
Consider the following scenario:
As a DNP-prepared nurse working in a rural clinic, you have a large population of patients with type 2 diabetes whose HbA1c levels are greater than 7% and body mass index (BMI) is over 30. You design a 9-month practice change project to impact these values.
Based on an exhaustive search and appraisal of research studies, you select an evidence-based intervention—diabetic self-management education (DSME)—to translate to your local rural clinic.
The evidence-based intervention includes exercise, healthy eating, and understanding the importance of regular blood glucose monitoring.
Before implementing the intervention, you retrieve aggregate data from 3, 6, and 9 months from medical records prior to the intervention being implemented. Data included HbA1c levels, BMIs, and numbers of patients with uncontrolled HbA1c. You also collected demographic data.
You collect the same data at 3, 6, and 9 months after implementation of the evidence-based intervention (DSME).
Pre-implementation and post-implementation data include the following.
| Patient | Column A HbA1c Pre-implementation | Column B HbA1c > 7 | Column C HbA1c Post-implementation | Column D HbA1c > 7 |
| 1 | 7.4 | Y | 6.9 | N |
| 2 | 7.8 | Y | 7.1 | Y |
| 3 | 7.1 | Y | 6.7 | N |
| 4 | 6.8 | N | 6.4 | N |
| 5 | 7.4 | Y | 6.8 | N |
| 6 | 7.8 | Y | 7.7 | Y |
| 7 | 7.8 | Y | 7.4 | Y |
| 8 | 8.2 | Y | 8 | Y |
| 9 | 7.5 | Y | 6.7 | N |
| 10 | 11.8 | Y | 11.3 | Y |
As a DNP-prepared nurse, you will analyze descriptive statistics, such as measures of central tendency and variability, to describe outcomes of a practice change project. Reflect upon this scenario and the data presented. What conclusions would you make at the end of this practice change project? What recommendations would you make to stakeholders for continuing the diabetes self-management education (DSME) program based on these results?
In order to respond to this discussion question, you will first need to complete the following calculations and consider responses to your analysis of the descriptive statistics.
- Perform the following calculations:
- Based on the data set provided, calculate the average percentage of patients with uncontrolled diabetes (HbA1c>7) both pre-implementation and post-implementation.
- Next, calculate the mean pre-implementation and post-implementation HbA1c values for patients involved in this practice change project.
- Now calculate the pre-implementation and post-implementation median score of HbA1c levels.
- Next, calculate the pre-implementation and post-implementation standard deviation of HbA1c levels of patients involved in the practice change project. The standard deviation will determine the spread of increase or decrease in HbA1c levels.
- Finally, calculate the pre-implementation and post-implementation range of HbA1c levels. If no outliers exist, the range will determine how close together HbA1c levels are in the patients involved.
- Based on your analysis of the descriptive statistics, what determinations related to the mean HbA1c levels following implementation of the evidence-based intervention can be made?
- As you reflect upon HbA1c levels, you observe that patient #10 HbA1c levels are an outlier. What does this do to your understanding of the data?
Please click on the following link to review the DNP Discussion Guidelines on the Student Resource Center program page:
- Link (webpage): DNP Discussion GuidelinesLinks to an external site.
Course Outcomes
This discussion enables the student to meet the following course outcome(s):
- Evaluate selected statistical methods for the purposes of critiquing research to complement the critical appraisal of evidence. (PO 3, 5, 9)
- Analyze research and non-research data for the purposes of critical appraisal and judgment of evidence for translation into practice. (PO 1, 3, 5, 7, 9)
NR716 Week 5 Discussion | Analyzing Descriptive Statistics Example
Analyzing Descriptive Statistics
- Percentage of pre-and post-implementation of uncontrolled diabetes.
The percentage of pre-implementation of uncontrolled diabetes: 90%
The percentage of post-implementation of uncontrolled diabetes: 50%
The total uncontrolled diabetes in the pre-implementation data was 9 out of 10 since patient 4 was below 7 HbA1c. While the post-implementation was 5 out of ten, we then multiplied it by 100 to come up with 90% pre-implementation and 50% post-implementation.
- Calculate the mean pre-implementation and post-implementation of the HbA1c value.
The mean of the pre-implementation HbA1c value:
79.6 (Total of HbA1c)/10 = 7.96
The mean of post-implementation HbA1c value:
75 (Total of HbA1c)/10 = 7.5
The mean is computed by dividing the total value by the number of values. The mean is also known as the arithmetic mean, which describes all the responses (Guetterman, 2019).
- Calculate the pre-implementation and post-implementation median scores of HbA1c.
The median for pre-implementations HbA1c = 7.65
The median for post-implementation HbA1c = 7.0
Arranging data from the smallest to the largest amount and ensuring the number in the middle is less than the highest number and higher than the lowest number. Sometimes, data is counted in an even number; then, we add the two values and divide them into two, which is how we obtain the median.
- Calculate the standard deviation of HbA1c of pre- and post-implementation.
Pre-Implementation: 1.4
Post-Implementation: 1.4
The standard deviation is obtained when investigators or, in our case, doctoral-prepared nurses want to identify the spread on how it differs from the mean (Guetterman, 2019). The computation is the square root of the sum of the data minus the mean, squared, then subtracted from the total data.
- Calculate the range of HbA1c pre-and post-implementation.
Pre-Implementation Range: 5
Post-Implementation Range: 4.9
The range is obtained by subtracting the highest value from the lowest value. Investigators utilize this to determine the difference between the highest and lowest values.
What determinations related to the mean HbA1c levels following the implementation of the evidence-based intervention can be made?
As DNP-prepared nurses, we are tasked to describe our data and give these numbers meaning. The data above noted that the DSME intervention improved outcomes of HBA1c. The percentage of those who have HbA1c pre-implementation decreased from post-implementation, with 90% to 50%, respectively. The deviation between the mean is low; therefore, most of the collected data is closer to the mean pre- and post-implementation.
DSME intervention is an effective way to decrease the HbA1c of patients. The intervention also improves patient satisfaction in managing diabetes (McLendon et al., 2019). The impact of the intervention also enhances adherence to dietary and footcare recommendations (Hailu et al., 2019). A study by McLendon et al. (2019) identified a decrease in emergency department costs by 51.4% and inpatient costs by 96%.
As you reflect upon HbA1c levels, you observe that patient #10 HbA1c levels are an outlier. What does this do to your understanding of the data?
Patient 10 is considered an outlier since, compared to other values is higher. This outlier should be considered in the analysis of data, since this may create a negative skew, which is defined as being far away from the mean, and hence not provide accurate data from the intervention.
Reference:
Guetterman T. C. (2019). Basics of statistics for primary care research. Family medicine and community health, 7(2), e000067. https://doi.org/10.1136/fmch-2018-000067.
Hailu, B.F., Moen, A. & Hjortdahl, P. (2019). Diabetes Self-Management Education (DSME) – Effect on Knowledge, Self-Care Behavior, and Self-Efficacy Among Type 2 Diabetes Patients in Ethiopia: A Controlled Clinical Trial, Diabetes, Metabolic Syndrome and Obesity, 12:, 2489-2499, DOI: 10.2147/DMSO.S223123.
McLendon, SF, Wood, FG, Stanley, N. (2019). Enhancing diabetes care through care coordination, telemedicine, and education: Evaluation of a rural pilot program. Public Health Nurs. 2019; 36: 310– 320. https://doi.org/10.1111/phn.12601.
