NURS 8201 Week 4 Levels of Measurement
Walden University NURS 8201 Week 4 Levels of Measurement-Step-By-Step Guide
This guide will demonstrate how to complete the Walden University NURS 8201 Week 4 Levels of Measurement 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 4 Levels of Measurement
Whether one passes or fails an academic assignment such as the Walden University NURS 8201 Week 4 Levels of Measurement 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 4 Levels of Measurement
The introduction for the Walden University NURS 8201 Week 4 Levels of Measurement 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 4 Levels of Measurement
After the introduction, move into the main part of the NURS 8201 Week 4 Levels of Measurement 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 4 Levels of Measurement
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 4 Levels of Measurement
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 4 Levels of Measurement
In the previous discussions, the practice problem in nursing identified that needed further intervention was based on limited use of health information technology to support mental healthcare services (Snyder et al., 2011). The discussion proposed that digital informatics technology can be implement to support mental healthcare service by enhancing access to the services, reduce waiting time, increase capacity to provide services to many people and support timely appointed, Consequently, the research question was developed as “What impacts will the implementation of digital informatics technology in the mental health services have on waiting time, capacity, access to services and preferred appointment times?. In this discussion, the paper focuses on the above proposed research question to describe independent and dependent variables, the level of measurement, and consideration that need to be taken when analyzing data related to the identified variable. The discussion also identifies some of the advantages and challenges that may be experienced in the statistical analysis of each variable.
The Independent and Dependent Variables
In research/project, variables can be defined as the properties or kinds of attributes of certain events or objects and can be divided into dependent and independent variable. The two variables are different. First, independent variables are those characteristics/attributes that can be changed or manipulated in the study and their effects are measured and compared (Gray, Grove & Sutherland, 2021). The independent variables predict the values of the dependent variable in given model. On the other hand, dependent variables measure the impact of the independent variable(s) on the test unit (Gray, Grove & Sutherland, 2021).
In the proposed research question “What impacts will the implementation of digital informatics technology in the mental health services have on waiting time, capacity, access to services and preferred appointment times?, the independent variable is digital informatics technology. On the other hand, dependent variable are the effects that would result from the implementation of digital informatics technology in the mental health services and include waiting time, capacity, access to services and preferred appointment times.
The Level of Measurement of Variables
The independent variable is digital informatics technology whose implementation would result into improved or reduced outcome in mental healthcare setting. Therefore, the level of measurement is nominal. The normal level that would be used to label the outcome of digital informatics technology on mental healthcare service is either improved no effect or reduced outcome. When it comes to statistical analysis, nominal data will not be utilized to perform many statistical computations.
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When it comes to dependent variable, the level of measurement for waiting time is interval scale in which a rating scale will be used to represent the range of average time take by patient before meeting the doctor. The level of measurement for access to services and preferred appointment times will also be ordinal because it will be used to depict order of satisfaction (Granberg-Rademacker, 2010).
A consideration that needs to be taken when analyzing wait time, access to services and preferred appointment times as the dependent variable is the scale to use. For instance, the level of satisfaction with access to services and preferred appointment times can be measured using Likert Scales. Likert scales can be designed to include ordinal measure ranging from 1 to 5 to strongly disagree (1) to strong agree (5). The statistical analysis for access to services and preferred appointment times can include logistic regression. The advantage of logistic regression is that will be able to show direction of association (positive or negative) between dependent and independent variable. However, if the result is non-linear, it can be difficult to solve using logistic regression because it has a linear decision surface (Lee, & S, George, 2012). Finally, waiting time can be measured on interval scale and a possible statistical analysis if t-tests. The advantage of t-test is that values obtained from Likert scales are quantitative and therefore, easy to analyze (Liang, Fu & Wang, 2019).
References
Granberg-Rademacker, J. S. (2010). An algorithm for converting ordinal scale measurement data to interval/ratio scale. Educational & Psychological Measurement, 70(1), 74–90.
Gray, J.R., Grove, S.K., & Sutherland, S. (2021). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Saunders Elsevier.
Lee, A. J. J., & George A.F.A.F. (2012). Linear Regression Analysis. Wiley.
Liang, G., Fu, W., & Wang, K. (2019). Analysis of t-test misuses and SPSS operations in medical research papers. Burns & Trauma, 7.
Snyder, C. F., Wu, A. W., Miller, R. S., Jensen, R. E., Bantug, E. T., & Wolff, A. C. (2011). The Role of Informatics in Promoting Patient-Centered Care. The Cancer Journal, 17, 4, 211-218.
Sample Answer 2 for NURS 8201 Week 4 Levels of Measurement
Alternatives in Levels of Measurement
Beginning with your variables, I would agree that your independent variable is the use of a Smart Dose blister pack medication distribution system, and your dependent variables are both adherence and compliance. You could use the nominal or ordinal level of measurement for your independent variable. Because the distribution system represents a specific category and does not involve any systematic ordering or ranking, it can be at the nominal level. If you were to assess the patients’ preferences through a survey based on their satisfaction ranking from “very satisfied” to “least satisfied,” you could use the ordinal level of measurement (Faisal et al., 2022).
For your dependent variable, you could use the interval or ratio level of measurement in measuring adherence and/or compliance. At the interval level, you can use an interval scale to quantify medication adherence by emphasizing the percentage of prescribed doses taken or to quantify compliance by emphasizing the correctness of dosing time (Izzah et al., 2022).
Alternative Statistical Analysis Method
You have a few good options methods to use for your research data. First, you could use descriptive statistics which would require you to summarize the adherence data into Smart Dose blister pack users and non-users. Then, you would calculate the mean, median, standard deviation, and percentiles of your data to receive an overview of adherence levels from both groups. Since you are measuring data continuously over a 6-month period, a t-test or a Mann-Whitney U test are also acceptable methods. Similar to the descriptive statistics method, the t-test and Mann-Whitney U test compare the means and medication of Smart Dose blister pack users and non-users.
References
Faisal, S., Ivo, J., Tennant, R., Prior, K.-A., Grindrod, K., McMillan, C., & Patel, T. (2022). Integration of a smart multidose blister package for medication intake: A mixed method ethnographic informed study of older adults with chronic diseases. PLOS ONE, 17(1), e0262012. https://doi.org/10.1371/journal.pone.0262012Links to an external site.
Izzah, Z., Zijp, T. R., Åberg, C., Touw, D. J., & van Boven, J. F. (2022). Electronic Smart Blister Packages to Monitor and Support Medication Adherence: A Usability Study. Patient Preference and Adherence, Volume 16, 2543–2558. https://doi.org/10.2147/ppa.s374685
Sample Answer 3 for NURS 8201 Week 4 Levels of Measurement
Post your research question and describe the independent and dependent variables.
Would better communication between surgical personnel regarding patients’ pre-operative pain, anxiety, and discomfort reduce negative effects in the postoperative period?
Hospitalized patients exhibit discomfort and anxiety rates ranging from 10%-30%, according to Murat Kurul et al. (2023). In addition to addressing preoperative anxiety and discomfort, patients who received analgesics before surgery required less morphine equivalents during the first 24 hours, had decreased pain scores, and ambulated sooner during the postoperative period (Haffner et al., 2019).
Independent variable: communication tool between the anesthesia provider and the surgical nurse, such as a communication sheet about the surgical patients’ preoperative pain and discomfort decreases the patients’ pain postoperatively (dependent variable).
Identify the level of measurement of both your independent and dependent variables.
For the dependent variable of being able to assess the patient’s pain, an ordinal level of measurement can be used. According to Gray and Grove (p.455, 2021), can be assigned to categories of an attribute that can be ranked, for example, one could rank the intensity of pain.
As for the independent variable of utilizing a communication tool between surgical staff rating and relaying patients’ anxiety and discomfort, the use of an interval scale, such as the Spielberger State-Trait Anxiety Inventory (STAI), can be used as a measurement method. The STAI has been widely used to measure the state and trait components of anxiety (Zsido et al., 2020). This questionnaire can be used in research as well as in clinical practice. This type of scale is considered a Likert scale, which is a rating scale used to measure opinions, attitudes, or behaviors, and is used to measure a select concept and is considered by most researchers to be an interval-level measurement (Gray & Grove, 2021).
Provide a brief rationale for your classification of each variable. Be specific.
In a study performed by Gurler et al. (2022), it showed that a majority (70.8%) of surgical patients had fears associated with surgery and anesthesia and nearly half of them had a moderate/high level of preoperative anxiety.
The ordinal level of measurement can rank the intensity of pain on an ordinal scale. For example, the preoperative patient can rank either their pain, discomfort, or anxiety on a scale such as 0=no pain, 1=slight pain or anxiety, 2=moderate pain, discomfort, or anxiety, 3=high anxiety and/or pain. This type of scale is an example of a metric ordinal scale because the different levels for measuring pre-operative pain and anxiety are numbered in order from a low of 0 to a high of 3, as demonstrated by Gray and Grove (2021).
The rationale for the use of an interval level of measurement, such as the STAI or Likert scale is that it has been shown to be the most widely used test to determine preoperative anxiety level, which is accepted as the gold standard (Gurler et al., 2022). Additionally, the STAI scale was found to have a positive correlation with the Surgical Anxiety Questionnaire (ASSQ) and can be used interchangeably to determine preoperative anxiety and discomfort levels.
Explain considerations of analyzing data related to each variable based on its level of measurement.
Considerations of analyzing data related to the ordinal level of measurement are that ordinal data requires people to select from a scale, which may not offer respondents freedom of expression. Additionally, with ordinal variables, respondents are restricted to a set of predefined options.
On the other hand, considerations that may need to be taken when analyzing data related to utilizing an interval level of measurement is that an interval scale does not have a true zero that represents a total absence of the variable, such as only a ratio scale can have. According to Bhandari (2020), interval data have equal intervals between scores, but they do not have true zeros because they cannot measure “zero feelings” or “zero emotions.” With a normal distribution of interval data, both parametric and non-parametric tests are possible.
Include any advantages or challenges that you might encounter in your statistical analysis of each variable and explain why.
With the independent variable, if the surgical nurse does not visibly see that the preoperative patient is in visible distress due to anxiety or discomfort, that subjective information could be construed that the patient is not experiencing any pain, anxiety, or discomfort. This poses a challenge of a Type II error, which occurs when the researcher concludes no significant effect when an effect actually exists (Gray & Grove, 2021). One primary advantage of using ordinal scale is the ease of collation, categorization, and comparison between variables. Furthermore, statistical analysis is applied to the responses once they are collected to place the people who took the survey into the various categories.
Conversely, the main advantage of using interval variables is that they allow for meaningful comparisons between variables. Interval variables measure the distance between two variables, so it is possible to compare the differences between them (Young et al., 2020). This is particularly useful when looking at trends over time or comparing differences between groups.
References
Bhandari, P. (2020, August 28). Interval Data and How to Analyze It | Definitions & Examples. Scribbr. https://www.scribbr.com/statistics/interval-data/
Gray, J. R., & Grove, S. K. (2021). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence. (9th ed.). Elsevier – Health Science.
Gürler, H., Yılmaz, M., & Türk, K. E. (2022). Preoperative Anxiety Levels in Surgical Patients: A Comparison of Three Different Scale Scores. Journal of PeriAnesthesia Nursing, 37(1), 69–74. https://doi.org/10.1016/j.jopan.2021.05.013
Haffner, M., Saiz, A. M., Nathe, R., Hwang, J., Migdal, C., Klineberg, E., & Roberto, R. (2019). Preoperative multimodal analgesia decreases 24-hour postoperative narcotic consumption in elective spinal fusion patients. The Spine Journal: Official Journal of the North American Spine Society, 19(11), 1753–1763. https://doi.org/10.1016/j.spinee.2019.07.005
Murat Kurul, Aydin, N., & Sen, O. (2023). Effect of Preoperative Anxiety Level on Postoperative Analgesia Requirement in Patients Undergoing Laparoscopic Cholecystectomy. 61(3), 167–171. https://doi.org/10.4274/haseki.galenos.2023.9005
Young, C. A., Mills, R., Al-Chalabi, A., Burke, G., Chandran, S., Dick, D. J., Ealing, J., Hanemann, C. O., Harrower, T., Mcdermott, C. J., Majeed, T., Pinto, A., Talbot, K., Walsh, J., Williams, T. L., Tennant, A., & TONiC study group. (2020). Measuring quality of life in ALS/MND: validation of the WHOQOL-BREF. Amyotrophic Lateral Sclerosis & Frontotemporal Degeneration, 1–9. https://doi.org/10.1080/21678421.2020.1752244
Zsido, A. N., Teleki, S. A., Csokasi, K., Rozsa, S., & Bandi, S. A. (2020). Development of the short version of the spielberger state—trait anxiety inventory. Psychiatry Research, 291(1), 113223. https://doi.org/10.1016/j.psychres.2020.113223
Sample Answer 4 for NURS 8201 Week 4 Levels of Measurement
Thank you for your interesting post. Your research question is well crafted and responds to a challenge in patient care. Addressing pain post operatively as well as anxiety is critical to the patient’s experience as well as outcomes. The variables you highlighted do not indicate what the dependent variable would be for your study. The independent variable you indicated is the tool used by the surgical nurse and anesthetist. I would propose to perhaps consider the independent variable that can be measurable to be able to relate it to the dependent variable. For the dependent variable, pain level on a pain scale of 0-10 or an anxiety score can be utilized to measure and relate the level of pain and anxiety to the patients’ outcomes or input of the surgical team (Schober et al., 2019).
The consideration for the level of measurement on pain is an ordinal level of measurement. The other level of measurement for the tool is difficult to determine as it does not explicitly provide the specific measure we would be aiming at. The classification for the level of measurement is sound. An ordinal scale enables categorization depending on the pain levels that the clients’ experiences.
In the analysis for the data for your study using descriptive statistics would be essential to help you in comparing outcomes across different patient outcomes of care. Mean, variance and median can be key. Pearson correlation scores are important in providing the correlation between the data sets and establishing relationships between the tool use and post-operative pained anxiety (Adeboye et al., 2021).
References:
Adeboye, A., Hart, R., Senapathi, S., Ali, N., Holman, L., & Thomas, H. W. (2021). Assessment of functional pain score by comparing to traditional pain scores. Cureus. https://doi.org/10.7759/cureus.16847Links to an external site.
Schober, P., Boer, C., & Schwarte, L. A. (2019). Correlation coefficients: Appropriate use and interpretation. Anesthesia & Analgesia, 126(5), 1763-1768. https://doi.org/10.1213/ane.0000000000002864Links to an external site.