NURS 8200 Discussion 1: Levels of Measurement

Research Question

In sleep apnea patients (P), how does the treatment of OSA with CPAP (I) compared with no treatments (C) reduce the risk of cardiovascular diseases (O)?

Independent and Dependent Variables

Independent variable: Treatment of OSA with CPAP. It does not vary. It is not dependent upon other variables

Dependent variable: Cardiovascular disease. Cardiovascular disease is the dependent variable because not everyone has this disease. Its value depends on changes in the independent  

Level of Measurement of Both the Independent and Dependent variables

Measurement involves assigning numbers to qualities of people or objects to designate the quantity of the attribute. There are four different levels of measurement: nominal, ordinal, interval, and ratio (Polit & Beck, 2020).

Ordinal measurement will be used for my independent variable. Rationale: This will be the best measurement to rate patients’ improvement using CPAP from 1 to 10. The ordinal measurement will be a great tool when evaluating the Epworth Sleepiness Scale ( ESS) for my sleep apnea patients to compare the ESS score before the use of CPAP and while using Something measured on an ordinal scale does have an evaluative connotation (Bond C.M, 2019).

Interval measurement will be used for my dependent variable. I will use the interval measurement to get greater analytic flexibility, more robust statistical options, and a more significant amount of information than at the lower levels (Polit & Beck, 2020).

Discuss considerations of analyzing data related to each variable based on its level of measurement. What are the advantages, or disadvantages, of the levels of the variables of measurements?

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When analyzing information from a quantitative study, we are often dealing with numbers; therefore, it is essential to understand the

source of the numbers. The term variable defines a specific item of information collected in a study. Examples of variables include age, sex or gender, ethnicity, exercise frequency, weight, treatment group, and blood glucose. Each variable will have a group of categories, which are referred to as values, to help describe the character of an individual study participant. For example, the variable “sex” would have values of “male.” and “female” (Bond C.M, 2019).

An ordinal variable implies that the categories can be placed in a meaningful order, as would be the case for exercise frequency (never, sometimes, often, or permanently). Nominal-level Furthermore, ordinal-level variables are also referred to as categorical variables because each category in the variable can be separated from the others. The categories for an interval variable can be placed in a meaningful order, with the interval between consecutive types also having meaning. Age, weight, and blood glucose can be considered interval variables and ratio variables because the ratio between values has meaning (e.g., a 15-year-old is half the age of a 30-year-old). Interval-level and ratio-level variables are also referred to as continuous variables because of the underlying continuity among categories (Simpson, 2018).

As we progress through the levels of measurement from nominal to ratio variables, we gather more information about the study participant. The amount of information that a variable provides will become important in the analysis stage because we lose information when variables are reduced or aggregated, a common practice that is not recommended. For example, if age is lowered from a ratio-level variable (measured in years) to an ordinal variable (categories of < 65 and ≥ 65 years), we lose the ability to make comparisons across the entire age range and introduce error into the data analysis (Simpson, 2018).

References

Bond C.M. ( 2019). The research jigsaw: how to get started. Can J Hosp Pharm., 67(1):28–30.

Simpson S. H. (2018). Creating a Data Analysis Plan: What to Consider When Choosing Statistics for a Study. The Canadian journal of hospital pharmacy, 68(4), 311–317. https://doi.org/10.4212/cjhp.v68i4.1471

Polit, D. F., & Beck, C. T. (2020). Essentials of nursing research: Appraising evidence for nursing practice. Lippincott Williams & Wilkins.

Sample Answer 3 for NURS 8200 Discussion 1: Levels of Measurement

I liked the formulation of your research question as it contains the question, the topic, the population and the variables, all of which are crucial parts of a good research question. It is commendable that your research question focuses on one of the main challenges affecting population health which is overdose from substance use. The country is currently grappling with the adverse effects of the opioid epidemic that has affected the way of life for millions of affected individuals and families.

An independent variable in a research process indicates the cause while the dependent variable indicates the effect. The independent variable is one which the experimenter or researcher is in control of while the dependent variable is the variable that is expected to change in response to any changes in the independent variable (Flannelly et al., 2020). The dependent variable from your research question would be overdosing while the independent variables would be the various causes of overdosing. As you have indicated, there are various causes of overdosing such as heroin, cocaine, fentanyl and synthetic opioids among others.

The ratio level of measurement would be appropriate for assessing the independent variable (causes of overdosing, in this case fentanyl). The ratio level of measurement measures data along a numerical scale that has equal distances between adjacent and a true zero (Allanson & Notar, 2020). In this case, the frequency of usage could be assessed, starting with those who do not use fentanyl at all (true zero) and upwards regarding the frequency of abuse in a numerical scale.

 

References

Allanson, P. E., & Notar, C. E. (2020). Statistics as measurement: 4 scales/levels of measurement. Education Quarterly Reviews, 3(3).

Flannelly, L. T., Flannelly, K. J., & Jankowski, K. R. (2020). Independent, dependent, and other variables in healthcare and chaplaincy research. In Quantitative Research for Chaplains and Health Care Professionals (pp. 34-43). Routledge.

Sample Answer 4 for NURS 8200 Discussion 1: 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

Your research question, “Can an improvement in ethical and compassionate practices from healthcare workers reduce relapse and death for dual diagnosis patients in addiction treatment centers?” is well-thought-out and addresses a crucial aspect of mental health and substance abuse treatment. You’ve correctly identified the independent variable (improvement of ethical and compassionate practices) and the dependent variable (reduction in relapse and death). Your approach to making the independent variable measurable through specific actions like one-to-one attention and assurance of patient rights is commendable. This specificity level will help in accurately assessing the impact of these practices.

You’re right in emphasizing the importance of accurate and reliable data collection. Ensuring the validity and reliability of the measurements and considering the potential challenges in data recording are essential steps in research. Your insight into the need to stay focused on specific variables to obtain valid results is astute and shows a deep understanding of the research process.

A follow-up question: How do you plan to address potential confounding factors that could influence the outcomes of dual-diagnosis patients, such as socioeconomic status or access to healthcare resources?

Sample Answer 5 for NURS 8200 Discussion 1: 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