Research for Evidence Based Practice

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Research for Evidence Based Practice 

DISCUSSION: LEVELS OF MEASUREMENT INITIAL POST

Analyzing Quantitative Data:

My research aims to examine the efficacy of online mindfulness-based interventions (MBIs) in reducing anxiety levels among adult patients with anxiety disorder. The following question will guide the research; What techniques within online mindfulness-based interventions are most effective in reducing anxiety levels among adults with anxiety disorders, and does their efficacy compared to in-person interventions?

Independent and Dependent Variables

In research, variables refer to any features that can take on various values, such as age and height (Schutt, 2019). Researchers usually measure independent and dependent variables in studies to examine cause-and-effect relationships. An independent variable is a variable that can be manipulated during a study (Schutt, 2019). For this research, independent variables include mindfulness techniques, frequency of engaging in mindfulness-based interventions, and accessibility of materials that facilitate online mindfulness interventions.

On the other hand, a dependent variable is a variable that changes due to the manipulation of an independent variable (Gray & Grove, 2020). It is the outcome researchers are usually interested in measuring and is reliant on the independent variable. By recording the independent variable, researchers can measure the extent to which they influence the dependent variable. For my research, the dependent variable is anxiety levels among patients with anxiety disorder. Anxiety levels will be measured through standardized scales or self-reported measures.

Levels of Measurement for the Variables

When researchers gather data, they collect various types of information based on what they hope to investigate or explore. Levels of measurement involve the mathematical feature of the values given to each variable (Xuan et al., 2020). The level of measurement determines the appropriate type of analysis to carry out. There are four major levels of measurement: nominal, ordinal, interval, and ratio. The following are the levels of measurement for my research variables and the rationale for each.

· Mindfulness techniques: The level of measurement for mindfulness techniques is nominal. The nominal scale classifies variables based on qualitative labels (Xuan et al., 2020). The labels do not have any order or hierarchy. They also do not convey any numerical value.

· Frequency of engaging in mindfulness-based interventions: The level of measurement here is ordinal. The ordinal scale classifies variables that have an order (Xuan et al., 2020). Frequency of engaging in mindfulness-based interventions can be daily, weekly, or monthly.

· Accessibility of materials that facilitate online mindfulness interventions: This variable's measurement level is nominal since there is no inherent order.

· Anxiety levels: The level of measurement for anxiety levels is ordinal. The levels will be measured using standardized scales and can be low, medium, or high.

Considerations of Analyzing Data Related to Each Variable Based on Its Level of Measurement

· Mindfulness techniques (nominal): Although nominal data cannot be measured using mathematical operators, analysis can be done through hypothesis testing. Hypothesis testing involves nonparametric tests such as the chi-squared test, which can be used to test how various techniques impact anxiety levels (Schutt, 2019).

· Frequency of engaging in mindfulness-based interventions (ordinal): To analyze ordinal data, visualization tools would be appropriate. For example, data may be presented in three rows with every row representing a distinct category (low, medium, and high frequency).

· Accessibility of materials that facilitate online mindfulness interventions (nominal): A chi-squared test can be used to test how the variable relates to anxiety levels.

· Anxiety levels (ordinal): Analysis of variance may be used to determine differences between research results in pre-and post-intervention.

Potential Advantages and Challenges in Statistical Analysis of Each Variable

Statistical analysis of the impact of mindfulness techniques and accessibility of materials is easier when chi-square technique is employed. Chi-square is perfect for data measured on a nominal scale and is simpler to compute (Schutt, 2019). While analysis of variance may be appropriate for analyzing anxiety levels, according to Schutt (2019), assuming equal intervals may impact interpretation.

References

Gray, J. R., & Grove, S. K. (2020).  Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.

Schutt, R. K. (2019). Quantitative methods.  The Wiley Blackwell Companion to Sociology, 39-56.

Xuan, W., Williams, K., & Peat, J. K. (2020).  Health science research: A handbook of quantitative methods. Routledge.

Research for Evidence Based Practice 

QUANTITATIVE METHODS: ANALYZING QUANTITATIVE DATA

  

INTRODUCTION

Research allows us to learn more. It allows us to go beyond simple questioning and curiosity. It provides us the opportunity to dig deeper, search for outcomes, and explore meaning. Throughout your practice, you will experience the need for research. Whether it is in your educational journey or within your career, research is an integral skill set for your role as a DNP-prepared nurse. 

Research begins as a question which leads to the study and collection of data. Through understanding and examining variables, determining levels of measurement, and analyzing outcomes, the question presented comes into clearer focus. This week, you consider the role of research in the field of nursing. You will explore variables in research and analyze data to develop understanding and meaning.

· Analyze independent and dependent variables for research questions

· Identify levels of measurement for independent and dependent variables

· Analyze approaches for addressing advantages and challenges in the data analysis for variables and levels of measurement

· Evaluate frequency and descriptive statistics

· Summarize descriptive statistics

 DISCUSSION: LEVELS OF MEASUREMENT

What is the incidence of blood clots from COVID-19 in females over the age of 35?

The above question is an example of a research question. A research question consists of three parts and guides the methods and approaches in which you will study the question to find answers. The research question includes: the question, the topic, and the population or variables. In the example provided above, the question is examining the prevalence of blood clots from severe COVID-19 in a selected population. From this question, the variables can be assessed, considerations can be analyzed, and populations can be sampled in order to guide the research.

During Week 2, you developed a research problem statement based on a topic of interest to you or your specific area of practice. Using this research problem statement, you will develop a research question. “A research question is a concise, interrogative statement that is worded in the present tense and includes one or more of a study’s principal concepts or variables” (Gray & Grove, 2020). These questions typically point to the type of study that will be conducted and serves as a guide for the research.

For this Discussion, reflect on your research problem statement. Consider the independent and dependent variables of your research problem through the construction of a research question. Reflect on the potential levels of measurement for your variables and the rationale for the labels, as well as consider the advantages and challenges that you might experience in the statistical analysis of your proposed variables. 

 

Reference: Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.

Required Readings

· Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.

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· Chapter 21, “Introduction to Statistical Analysis” (pp. 635–651)

· Chapter 22, “Using Statistics to Describe Variables” (pp. 652–662)

· Chapter 26, “Interpreting Research Outcomes” (pp. 699–716)

· Gholami, S., Mojen, L. K., Rassouli, M., Pahlavanzade, B., & Farahani, A. S. (2020).  The predictors of postoperative pain among children based on the theory of unpleasant symptoms: A descriptive-correlational study Links to an external site. . Journal of Pediatric Nursing, 55, 141–146. doi:10.1016/j.pedn.2020.08.006

· Huang, J., Qi, H., Lv, K., Chen, X., Zhuang, Y., & Yang, L. (2020).  Emergence delirium in elderly patients as a potential predictor of subsequent postoperative delirium: A descriptive correlational study Links to an external site. . Journal of PeriAnesthesia Nursing, 35(5), 478–483. doi:10.1016/j.jopan.2019.11.009

· Document:  Week 4 Descriptive Statistics SPSS Output  Download Week 4 Descriptive Statistics SPSS Output(PDF)

· Document:  CITI Program Learner Registration Guide  Download CITI Program Learner Registration Guide(PDF)