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NURS 8201 Week 5 Discussion: t-Tests and ANOVA in Clinical Practice

Thank you for sharing this research with us! The study’s results demonstrate the potential of weight loss interventions in improving arterial stiffness, a key marker of cardiovascular health, among children with obesity. The researchers’ incorporation of comprehensive assessments, including both clinical and biochemical parameters, strengthens the validity of their findings. By measuring various markers such as lipid profile, insulin resistance, and inflammatory markers, the study provides a comprehensive evaluation of the overall impact of the intervention on cardiovascular health (Genoni et al., 2021). While the study presents promising results, it is important to acknowledge certain limitations. The sample size of the study was relatively small, which may limit the generalizability of the findings. Additionally, the follow-up period was relatively short, and it would be beneficial to assess the long-term sustainability and durability of the observed improvements (Gray & Grove, 2020). The study underscores the potential effectiveness of a healthy lifestyle intervention program, including weight loss, in improving cardiovascular dysfunction among children with obesity. The findings support the importance of early intervention and comprehensive approaches to address this pressing public health concern. Further research with larger sample sizes and longer follow-up periods is needed to expand upon these findings. Overall, this study contributes to the significance of promoting healthy lifestyles in combating obesity-related cardiovascular complications among children. Thank you for an interesting research topic!

NURS 8201 Week 5 Discussion: t-Tests and ANOVA in Clinical Practice

NURS 8201 Week 5 Discussion: t-Tests and ANOVA in Clinical Practice

Discussion: t-Tests and ANOVA in Clinical Practice

Student t-test is often applied in the statistical analysis to test hypothesis. In the SPSS output, the results of t-test can be translated in different ways. In other words confidence interval can be applied as well as the significant values obtained. T-test is a form of inferential statistics that is always applied to determine if there is a significant different between the means of two variables or two groups in a dataset (Kim, 2015). The two variables may be related in certain features. While performing t-test, there are always assumptions that have to be made. For example, there is always assumption of equality of variance. Some other assumptions that are always made include normality of data distribution, adequacy of sample size, the data is also assumed to be randomly sampled. The independent sample t-test or two sample t-test is always performed when one variable being considered is categorical while the other is continuous. The continuous variable must have a normal distribution (Delacre et al., 2017).

When determining what evidence to use in practice, I hold the opinion that clinical significance is more important. This is because you will find that statistical significance may be prone to biases. Statistical significance basically indicates that the outcomes did not happen by chance. However, when a researcher fails to account for outliers and confounding variables, then this is bound to bring about questions on the significance of the relationship established by the research (Frank et al., 2021). It is therefore imperative that when deciding on a treatment or intervention that there is evidence of its clinical significance. This is because clinical significance will be evidence that the intervention will bear positive implications on the intended populations.

T-distribution is always considered to be a continuous probability distribution that often arise from the estimation of the mean of a given population with a normal distribution. In most cases t-test is applied in proving hypothesis (Champely et al., 2017). There are different approaches that can be applied in either rejecting or accepting null hypothesis (Test et al., 2018). In t-test, there is always the testing of the difference between the two samples under consideration when the variances of the two variables are unknown. Assumptions of normality are essential in ensuring accurate or effective processes in the statistical analysis. There is always the need to consider the scale of measurement in the process of undertaking t-test. In most cases, the scale of measurement applied to the data under analysis should always follow an ordinal or continuous scale. Homogeneity of variance is another assumption that is always made regarding t-test (Kim & Park, 2019). In other words, the variance of data under each variable should be equal to ensure that there is effective outcomes in the process of comparing the means using t-test.

Two sample t-test or the independent sample t-test is often used in data analysis to compare the means of two independent groups to test whether there is a statistical evidence that the associated population means have a significant difference. Just like any other t-test, the independent t-test is a parametric test. The independent sample t-test is always recommended when one variable is categorical while the other variable is continuous and normally distributed. In this case, weight is a continuous variable while sex is a categorical variable (Jeanmougin et al., 2018). The independent sample t-test is most commonly applied in testing the statistical difference between the means of the given two groups. It can also be applied in the determination of the statistical difference between the means of two interventions. Finally, independent sample t-test can be applied in the determination of statistical difference between the means of two change scores. The independent sample t-test can only be applied in comparing the means for two and only two groups (Kruschke, 2018).

You are the DNP-prepared nurse responsible for overseeing staffing for the telehealth services provided at your practice. To determine the number of nurses that you might need for these services, you must determine how many patients might be interested in using the telehealth services versus the traditional clinical practice setting. For a week, you ask each patient visiting the practice his or her interest in setting up a visit via telehealth services. At the conclusion of the week, you use this data and reasoning to develop a statistic of the population interested in telehealth services. You have successfully used inferential statistics to help guide your decision-making for your practice.

The scenario outlined provides a random sampling and assumptions to develop a conclusion. With assumptions, and in this case, a small random sampling, this scenario is ripe with the possibility of error. However, how might inferential statistics be used in a valid and credible way?

The design of a study determines the validity of the results, and if done following appropriate techniques, inferential statistics can determine clear differences and help researchers to form conclusions. In your Discussion, you will focus on two forms of identifying differences in groups: t-tests and analysis of variance (ANOVA).

For this Discussion, review the Learning Resources and reflect on a healthcare issue of interest to find a research article in which to analyze the use of inferential statistical analysis. Reflect on how the study was comprised, the validity of the findings, and whether or not it increased the study’s application to EBP

To Prepare:

  • Consider some of the important issues in healthcare delivery or nursing practice today. Bring to mind the topics to which you have been exposed through previous courses in your program of study, as well as any news items that have caught your attention recently. Select one topic to focus on for this Discussion.
  • Review journal, newspaper, and/or internet articles that may provide credible information on your selected topic. Then, select one research article to focus on for this Discussion that used inferential statistical analysis (either a t-test or ANOVA) to study the topic.
  • With information from the Learning Resources in mind, evaluate the purpose and value of the research study discussed in your selected article and consider the following questions:
  • Ask yourself: How did using an inferential statistic bring value to the research study? Did it increase the study’s application to evidence-based practice?

By Day 3 of Week 5

Post a brief description of the topic that you selected for this Discussion. Summarize the study discussed in your selected research article and provide a complete APA citation. Be sure to include a summary of the sample studied, data sources, inferential statistic(s) used, and associated findings. Then, evaluate the purpose and value of this particular research study to the topic. Did using inferential statistics strengthen or weaken the study’s application to evidence-based practice? Why or why not? Be specific and provide examples.

NURS 8201 Week 5 Discussion: t-Tests and ANOVA in Clinical Practice

By Day 6 of Week 5

Read a selection of your colleagues’ responses and respond to at least two of your colleagues on two different days in one or more of the following ways:

  • Ask a probing question, substantiated with additional background information, evidence, or research.
  • Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.

    NURS 8201 Week 5 Discussion t-Tests and ANOVA in Clinical Practice
    NURS 8201 Week 5 Discussion t-Tests and ANOVA in Clinical Practice
  • Offer and support an alternative perspective using readings from the classroom or from your own research in the Walden Library.
  • Validate an idea with your own experience and additional research.
  • Suggest an alternative perspective based on additional evidence drawn from readings or after synthesizing multiple postings.
  • Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.

Submission and Grading Information

Grading Criteria

Also Read:  NURS 8201 Week 4 Discussion: Levels of Measurement

To access your rubric:

Week 5 Discussion Rubric

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Post by Day 3 of Week 5 and Respond by Day 6 of Week 5

To Participate in this Discussion:

Week 5 Discussion

Statistics play an important role in analyzing the primary data collected to examine a problem in clinical practice. Despite its complexity, it allows the researcher to deduce the meaning of the data to support evidence-based practice (Weaver et al., 2017). The precision required in nursing studies has led to a demanding task among nursing scholars. These demands have compelled them to use inferential statistical analysis to achieve the accuracy and dependability of the results.

My topic of interest is to examine the prevalence of obesity among children. The increase in cases of childhood obesity has been drawing more attention from scholars because of its negative effect on health outcomes among children (Smith et al., 2021). The number of children with obesity has doubled in the last two decades, calling for effective intervention that would counter this menace. The increased rate of children with obesity calls for accurate studies that would reveal the underlying problem and propose an effective EBP practice that would act as an effective intervention for the problem.

Article Summary

The study authored by Katzmarzyk et al. (2019) focuses on the effect of lifestyle behavior and environment on childhood obesity. The study’s primary objective was to examine the relationship between lifestyle behaviors and obesity. The study termed as ISCOLE was a multi-national study carried out on children aged 9-11 years from 12 countries across the continent. The primary focus of the study was on the result gained from the primary data collected for this study. 7372 children aged between 9-11 years participated in the study. The study used ISCOLE design and methods, which was a multi-national study done in 12 countries.

Inferential statistics separated the data from countries where the reading on the Human Development Index (HDI) produced a range of 0.509 in Kenya to 0.929 in Australia (Katzmarzyk et al., 2019). The descriptive statistics effectively organized data from each country and showed how the variables considered in the study changed in each country. The study also went further to correlate obesity and lifestyles behavior at different levels, where it found that children with active school transport had lower chances of becoming obese. For instance, the odds ratio was 0.72 at a 95% confidence interval. In essence, inferential statistics was important in breaking down the data from the 12 countries into meaningful pieces that readers could easily understand.

This study was important in revealing how various factors such as average income in a country affect the lifestyle behaviors in families that further relay more information on childhood obesity. The analysis of the big sampled data from the countries resulted in reliable information that could be applied to all the countries included in the study (Katzmarzyk et al., 2019). Inferential statistics in the study strengthened the results by revealing the relationship between dependent variables and multiple independent variables considered in the study. The analysis used in the study strengthened the application of the evidence-based practice as it showed the effect that lifestyle changes had on childhood obesity. For example, the study proved that increasing physical activity among children during school hours and at home reduces their chances of becoming obese. Therefore, if children and parents in the selected countries with high childhood obesity could adopt the EBP practice of increasing physical activity, then the prevalence rates in those countries could decrease drastically.

The importance of inferential statistics could also be evident in the correlation of the variables that had a greater effect on childhood obesity and those variables that had a comparatively lower impact on obesity. For example, the study found a high correlation between physical activity and obesity. On the other hand, the study found that school transport and obesity did not differ by country or sex.

Reference

Katzmarzyk, P. T., Chaput, J. P., Fogelholm, M., Hu, G., Maher, C., Maia, J., … & Tudor-Locke, C. (2019). International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE): contributions to understanding the global obesity epidemic. Nutrients11(4), 848. https://dx.doi.org/10.3390%2Fnu11040848

Smith, H. J., Piotrowski, J. I., & Zaza, S. (2021). Ethics of implementing US Preventive Services Task Force recommendations for childhood obesity. Pediatrics148(1). https://doi.org/10.1542/peds.2020-048009.

Weaver, K. F., Morales, V. C., Dunn, S. L., Godde, K., & Weaver, P. F. (2017). An introduction to statistical analysis in research: with applications in the biological and life sciences. John Wiley & Sons.

Name: NURS_8201_Week5_Discussion_Rubric

  Excellent

90–100

Good

80–89

Fair

70–79

Poor

0–69

Main Posting:

Response to the Discussion question is reflective with critical analysis and synthesis representative of knowledge gained from the course readings for the module and current credible sources.

40 (40%) – 44 (44%)

Thoroughly responds to the Discussion question(s).

Is reflective with critical analysis and synthesis representative of knowledge gained from the course readings for the module and current credible sources.

No less than 75% of post has exceptional depth and breadth.

Supported by at least three current credible sources.

35 (35%) – 39 (39%)

Responds to most of the Discussion question(s).

Is somewhat reflective with critical analysis and synthesis representative of knowledge gained from the course readings for the module.

50% of the post has exceptional depth and breadth.

Supported by at least three credible references.

31 (31%) – 34 (34%)

Responds to some of the Discussion question(s).

One to two criteria are not addressed or are superficially addressed.

Is somewhat lacking reflection and critical analysis and synthesis.

Somewhat represents knowledge gained from the course readings for the module.

Cited with fewer than two credible references.

0 (0%) – 30 (30%)

Does not respond to the Discussion question(s).

Lacks depth or superficially addresses criteria.

Lacks reflection and critical analysis and synthesis.

Does not represent knowledge gained from the course readings for the module.

Contains only one or no credible references.

Main Posting:

Writing

6 (6%) – 6 (6%)

Written clearly and concisely.

Contains no grammatical or spelling errors.

Adheres to current APA manual writing rules and style.

5 (5%) – 5 (5%)

Written concisely.

May contain one to two grammatical or spelling errors.

Adheres to current APA manual writing rules and style.

4 (4%) – 4 (4%)

Written somewhat concisely.

May contain more than two spelling or grammatical errors.

Contains some APA formatting errors.

0 (0%) – 3 (3%)

Not written clearly or concisely.

Contains more than two spelling or grammatical errors.

Does not adhere to current APA manual writing rules and style.

Main Posting:

Timely and full participation

9 (9%) – 10 (10%)

Meets requirements for timely, full, and active participation.

Posts main Discussion by due date.

8 (8%) – 8 (8%)

Meets requirements for full participation.

Posts main Discussion by due date.

7 (7%) – 7 (7%)

Posts main Discussion by due date.

0 (0%) – 6 (6%)

Does not meet requirements for full participation.

Does not post main Discussion by due date.

First Response:

Post to colleague’s main post that is reflective and justified with credible sources.

9 (9%) – 9 (9%)

Response exhibits critical thinking and application to practice settings.

Responds to questions posed by faculty.

The use of scholarly sources to support ideas demonstrates synthesis and understanding of learning objectives.

8 (8%) – 8 (8%)

Response has some depth and may exhibit critical thinking or application to practice setting.

7 (7%) – 7 (7%)

Response is on topic and may have some depth.

0 (0%) – 6 (6%)

Response may not be on topic and lacks depth.

First Response:

Writing

6 (6%) – 6 (6%)

Communication is professional and respectful to colleagues.

Response to faculty questions are fully answered, if posed.

Provides clear, concise opinions and ideas that are supported by two or more credible sources.

Response is effectively written in standard, edited English.

5 (5%) – 5 (5%)

Communication is mostly professional and respectful to colleagues.

Response to faculty questions are mostly answered, if posed.

Provides opinions and ideas that are supported by few credible sources.

Response is written in standard, edited English.

4 (4%) – 4 (4%)

Response posed in the Discussion may lack effective professional communication.

Response to faculty questions are somewhat answered, if posed.

Few or no credible sources are cited.

0 (0%) – 3 (3%)

Responses posted in the Discussion lack effective communication.

Response to faculty questions are missing.

No credible sources are cited.

First Response:

Timely and full participation

5 (5%) – 5 (5%)

Meets requirements for timely, full, and active participation.

Posts by due date.

4 (4%) – 4 (4%)

Meets requirements for full participation.

Posts by due date.

3 (3%) – 3 (3%)

Posts by due date.

0 (0%) – 2 (2%)

Does not meet requirements for full participation.

Does not post by due date.

Second Response:
Post to colleague’s main post that is reflective and justified with credible sources.
9 (9%) – 9 (9%)

Response exhibits critical thinking and application to practice settings.

Responds to questions posed by faculty.

The use of scholarly sources to support ideas demonstrates synthesis and understanding of learning objectives.

8 (8%) – 8 (8%)

Response has some depth and may exhibit critical thinking or application to practice setting.

7 (7%) – 7 (7%)

Response is on topic and may have some depth.

0 (0%) – 6 (6%)

Response may not be on topic and lacks depth.

Second Response:
Writing
6 (6%) – 6 (6%)

Communication is professional and respectful to colleagues.

Response to faculty questions are fully answered, if posed.

Provides clear, concise opinions and ideas that are supported by two or more credible sources.

Response is effectively written in standard, edited English.

5 (5%) – 5 (5%)

Communication is mostly professional and respectful to colleagues.

Response to faculty questions are mostly answered, if posed.

Provides opinions and ideas that are supported by few credible sources.

Response is written in standard, edited English.

4 (4%) – 4 (4%)

Response posed in the Discussion may lack effective professional communication.

Response to faculty questions are somewhat answered, if posed.

Few or no credible sources are cited.

0 (0%) – 3 (3%)

Responses posted in the Discussion lack effective communication.

Response to faculty questions are missing.

No credible sources are cited.

Second Response:
Timely and full participation
5 (5%) – 5 (5%)

Meets requirements for timely, full, and active participation.

Posts by due date.

4 (4%) – 4 (4%)

Meets requirements for full participation.

Posts by due date.

3 (3%) – 3 (3%)

Posts by due date.

0 (0%) – 2 (2%)

Does not meet requirements for full participation.

Does not post by due date.

Total Points: 100

Name: NURS_8201_Week5_Discussion_Rubric