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 

ASSIGNMENT: FREQUENCY AND DESCRIPTIVE STATISTICS

Imagine that you have collected data from 100 patients. You have carefully compiled vitals, pain scores, and medications for each of the patients. However, what does all of this data mean? Is your work now done?

How do we make data meaningful? Why must we move beyond the raw data to ensure that data is purposeful?    Descriptive analysis is the analysis of the data to develop meaning. Descriptive analysis provides meaning through showing, describing, and summarizing the data compiled to “reveal characteristics of the sample and to describe study variables” (Gray & Grove, 2020). This allows the researcher to present data in a more meaningful and simplified way.

For this Assignment, summarize your interpretation of the descriptive statistics provided to you in the Week 4 Descriptive Statistics SPSS Output document. You will evaluate each variable in your analysis.

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.

RESOURCES

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)

TO PREPARE:

· Review the Week 4 Descriptive Statistics SPSS Output provided in this week’s Learning Resources.

· Review the Learning Resources on how to interpret descriptive statistics, including how to interpret research outcomes.

· Consider the results presented in the SPSS output and reflect on how you might interpret the frequency distributions and the descriptive statistics presented.

THE ASSIGNMENT: (2–3 PAGES)

· Summarize your interpretation of the frequency data provided in the output for respondent’s age, highest school grade completed, and family income from prior month.  

· Note: A frequency analysis is way of summarizing data by depicting the number of times a data value occurs in the data table or output. It is used to analyze the data set including where the data are concentrated or clustered, the range of values, observation of extreme values, and to determine intervals for analysis that could make sense in categorizing your variable values.

· Summarize your interpretation of the descriptive statistics provided in the output for respondent’s age, highest school grade completed, race and ethnicity, currently employed, and family income from prior month.

· Note: The descriptive analysis includes N (size of your sample), the mean, the median, the standard deviation, the size and spread of your data to determine the variability/variance in your data. 

Reminder: The College of Nursing requires that all papers submitted include a title page, introduction, summary, and references.