Data Results and Analysis, health and medicine homework help

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After the data are collected, it is time to analyze the results!

  1. Discuss one of the four basic rules for understanding results in a research study.
  2. Compare clinical significance and statistical significance. Which one is more meaningful when considering applying evidence to your practice?
  3. Compare descriptive statistics and inferential statistics in research. Please give an example of each type that could be collected in a study that would be done on your nursing clinical issue you identified in previous weeks.

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Hello class, After the data are collected, it is time to analyze the results! Discuss one of the four basic rules for understanding results in a research study. Compare clinical significance and statistical significance. Which one is more meaningful when considering applying evidence to your practice? Compare descriptive statistics and inferential statistics in research. Please give an example of each type that could be collected in a study that would be done on your nursing clinical issue you identified in previous weeks. You can begin posting in this TD on Sunday, August 6, 2017 There are four basic rules described in this week's lesson. They help the clinicians understand and interpret the research study's results in a systematic way. Understanding results does not mean reading the conclusion made by the investigators in their publication, but evaluating the results based on the intent of the study, its research question, specific aims (if applicable), and actual results reported in the results section. As you learned over the last few weeks, results from a research study refer to statistical significance and the magnitude of the effect from an applied intervention. Prospective research studies often refer to a power analysis to demonstrate the effectiveness of their results (Houser, 2018). It is very important to recognize that statistical analysis in research is used to demonstrate that the effects and resulting outcomes are not likely due to chance. It means that replication of the study in another facility with similar group of participants will produce the same results. This also refers to generalizability of results and how others would be able to apply these findings to their practice. Often times, researchers gather data from multiple studies and perform additional statistical analyses on a much larger sample (Chamberlain College of Nursing, 2017). This type of comprehensive analysis is called a meta-analysis and many of these publications are found in Cochrane or Joanna Briggs databases. While reviewing and critiquing research articles as part of an evidence-based practice approach, you would question whether or not the results were statistically significant. Some research studies demonstrate strong statistical significance in their results; however, they lack clinical relevance. A good example would be a randomized study with an excessively large sample size that was powered to detect a minute difference to produce statistically significant results. Perhaps a study found 10% difference between an active drug and placebo with an excessively large sample. This means results are statistically significant, but they have very little clinical relevance. Often times, investigators report p-values in their results to demonstrate statistical significance. This statistical measure should not be a single determinant of clinical relevance. As a clinician, you should consider whether or not statistically significant results will make any difference in your patient population. As we discuss the difference between statistical and clinical significance this week, we will identify key elements that will help us as clinicians determine the true effectiveness of the intervention in a research study. We discussed the research questions in week 2 and it is a great way to refer back to the question and make decision regarding data collection methods. The research question I discussed in week 2 was regarding perioperative hypothermia. In order to execute this project, I have to consider availability of resources. If prewarming is not currently utilized preoperatively, then I need to determine if additional equipment needs to be purchased. This is why it is important to review literature and identify strong evidence to support the request for purchase of additional equipment. Data collection will involve consistent measurement of patients’ temperature during the entire perioperative period. If I were to add patient satisfaction component and thermal comfort to my study, then I would need to use questionnaires with Likert scale to generate numerical values. In terms of study outcomes, I would need to collect information about patient’s length of PACU stay, length of hospital stay, incidence of postoperative bleeding, incidence of postoperative surgical site infection, operating room temperature, preoperative and recovery room area temperature. These are some basic elements that would be considered when investigators decide on data collection methods. It is also very important to consider the person responsible for data collection, a need for additional training on how to collect data and use specific instruments. As you evaluate your PICOT question and work through identifying variables, you can see if data can be retrieved from secondary sources or you need to begin prospective data collection (Chamberlain College of Nursing, 2017). Chamberlain College of Nursing. (2017). NR-439 Week 6: Reading research literature - Results [Online Lesson]. Downers Grove, IL: DeVry Education Group. Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.) Sudbury, MA: Jones and Bartlett. ...
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School: New York University

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Running head: DATA RESULTS AND ANALYSIS

Data Results and Analysis
Institution Affiliation
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DATA RESULTS AND ANALYSIS
Introduction
Once data has been collected, it needs to be documented in a manner that is easily
understandable, precise and clear. This is usually done by the process of analysis. This is

basically narrowing in on the important issues of a research and leaving out non-important
surplus information.
One of the Basic Rules for Understanding Research Results
There are several rules that should be followed while trying to understand research
results. These are like, identifying the purpose of the research, singling out the variables,
pinpointing how the variables were measured and also considering...

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