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NR439 Week 6: Data Results and Analysis

This is a graded discussion: 50 points possible

Week 6: Data Results and Analysis

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?
    • Professor and Class,

      The second basic rule for understanding results in a research study is identifying the variables. In order to determine if the study is producing fruitful data, the variables are important to record and define at the start of a study (Houser, 2018). Variables are either independent or dependent. The independent variable is what is being introduced to cause changes or effects. The dependent variable is the effect of an independent variable or the outcome. The measurement of variables is important to the research study since the researchers are studying how the independent variable affects the dependent variable, or how it is not affected at all.

      While statistical significance is how likely the effects of an intervention is due to chance, clinical significance relates to how the effects of an intervention could affect future patient care (Skelly, 2011). I believe clinical significance would be more meaningful in my practice. Since I would study the effects of postpartum depression education and screening of new mothers immediately after birth, positive outcomes of the mothers seeking treatment if they feel they are exhibiting the symptoms of postpartum depression could change how postpartum depression is dealt with in the labor and delivery process.

      Descriptive statistics are used to give readers a description of the study sample (Giuliano & Polanowicz, 2008). For my clinical issue, descriptive statistics would include age and whether the subjects have been diagnosed with a mental disorder in the past, and if they received PPD education after the birth of their child/children. Inferential statistics use the information collected about the study sample to make conclusions about the larger population (Giuliano & Polanowicz, 2008). In my clinical issue, inferential statistics would include a conclusion of how many new mothers in the facility received education of PPD.

      Giuliano, K. K., & Polanowicz, M. (2008). Interpretation and use of statistics in nursing research. AACN Advanced Critical Care19(2), 211-222. doi:10.1097/01.AACN.0000318124.33889.6e

      Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones & Bartlett.

      Skelly, Andrea C. “Probability, Proof, and Clinical Significance.” Evidence-Based Spine-Care Journal 2.4 (2011): 9–11. PMC. Web. 29 Nov. 2017.

      Dear Kimberly and Class,

      Can you explain how the purpose of qualitative and quantitative research would be different?

      Thanks,

      Dr. Taulbee

      Dr. Taulbee and Class,

      The difference between the purpose of qualitative and quantitative research is what the researchers are looking for when conducting their study. Since qualitative research is used to understand the meaning of an experience (Houser, 2018), then the researcher’s purpose could be to understand how an intervention influences a condition or how the study subjects feel the intervention helped their condition. Using my PICOT as an example (PPD education and screening post-delivery), a qualitative purpose would be to determine how the mothers in the study sample felt about seeking help for PPD as opposed to those that received no PPD education or screening. According to Houser (2018), quantitative research uses the measuring and identification of variables to gain statistics and generalize the results. Using my PICOT again, a quantitative purpose would be for a researcher to determine how many women sought treatment for PPD symptoms after post-delivery education and screening as opposed to those that did not receive the education. Just a side note, the words qualitative and quantitative are sometimes so hard to remember which means what, lol.

      Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones & Bartlett.

      Class,

      Quantitative research is information that can be measured and written down with numbers. Qualitative research is information about qualities and can’t be measured. Quantitative focus on how many of something that you have and qualitative focus on the characteristics of what you have. Whether you use quantitative or qualitative data depends on the type of research study you are doing and what your ultimate goal is.

      Tyangala

      Hello Kimberly,

      I also observed the second rule to be most critical due to the exploration and distinguishing the variable within. This kind of research prompts a portion of the most grounded investigations with regards to exhibiting proof for training (Houser, 2018).  Quantitative tests are proper to survey the nature and bearing of connections between subjects or variables, including the ability to foresee a result given an arrangement of qualities or occasions.

       

      Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones & Bartlett.

      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.

      Dr. Taulbee and Class,

      Rule number 1 is understanding the Purpose of the Study. It is a statement that helps to assess the importance of the study relative to individual standards.  The statement should include not only the immediate purpose of the study, but also any larger, subsequent purpose. It describes the goals and objectives that are the targets for research investigation.

      Statistical significance is just one of the important measures that determine whether research is truly applicable to practice. It is the measurement that that tells us if there is a higher chance that a change has occurred or if there is more of a probability for error. “The largest a p value can be, and still be considered significant, is 0.05, or 5%. If the p value is very large (greater than 0.05 or 5%), then the probability that the results were due to error is very large, and the researcher cannot conclude that the intervention had an effect greater than would be expected from random variations. When the p value is very small, indicating that the probability the results were due to chance is also very small, then the test is said to have statistical significance. It is the comparison of differences to standard error and the calculation of the probability of error that give inferential analysis its strength”. (Houser, 2018).

      Clinical significance is relating more to how much an intervention can affects patients’ lives. Clinicians are more interested in this fact versus if something was due to a chance occurrence was due to chance. As our text states, “However, while well-established means are available to assess statistical significance, no single measure can identify a result’s clinical significance”. (Houser, 2018). This would prove more meaningful when applied to my practice.

      Descriptive statistics describes the main properties of a data set quantitatively. To represent the properties of a data set as accurately as possible, the data are summarized using either graphical or numerical tools. Graphical involves tabulating, grouping, and graphing the values of the variables of interest. Frequency distribution and relative frequency distribution histograms are such representations. They portray the distribution of the values throughout the population. The numerical summarization involves measures such as average, mode, and mean (Difference between.com) An example would be to give a histogram depicting the results of the latest Medication Reconciliation audits over the past quarter.

      Inferential statistics derives results that are obtained from a random sample of the population and the conclusions derived from the sample are then generalized to represent the whole population. Inferential statistics focus on how to generalize the statistics obtained from a sample as accurately as possible to represent the population.an example would be taking a survey of 25 patients from each of the field staff’s team and polling the results from the audits to see if there is a correlation between any particular staff, facilities, discharge planning and the lack of medication reconciliations.

      Germaine

      References

      (2012, November 18). Difference Between Descriptive and Inferential Statistics. Retrieved November 29, 2017, from http://www.differencebetween.com/difference-between-descriptive-and-vs-inferential-statistics

      Houser, J. (2015). Nursing research: Reading, using and creating evidence (3rd ed.). Denver, C.O.: Jones & Bartlett Publishers.

      Dear Germaine and Class,

      You have done an excellent job with this post. I noticed that many students have a tough time with sample size between quantitative and qualitative research designs. How does the sample size differ between qualitative and quantitative studies?

       How does the sample size differ between qualitative and quantitative studies? Dr. Taulbee and Class,

      Quantitative design studies rely on numbers to measure and quantify variables. It studies objective characteristics and responses that can be measured and compares groups of subjects in some way. The aim is to determine the effects of an intervention through a high level of control. Quantitative studies typically have higher samples of participants, Quantitative research in almost all cases requires a large-scale study.

      “In many ways, qualitative research is the polar opposite of quantitative research. Designs are not preplanned; the details of a particular study are “emergent”, meaning the specifics of the study adapt to the emerging characteristics of the data. Qualitative research seeks to understand the meaning of an event, rather than measure effects, so issues of internal validity, control, and avoidance of bias are not central concerns. Instead, trustworthiness is the key issue when appraising the validity of a qualitative study (Thomas & Magilvy, 2011; Whitting & Sines, 2012)” (Houser,2018). Qualitative methods tend to use smaller sample sizes, only needing enough data to represent in detail whatever concept they’re examining.

      Germaine

      Reference

      Houser, J. (2015). Nursing research: Reading, using and creating evidence (3rd ed.). Denver, C.O.: Jones & Bartlett Publishers

      Hi Germaine,

      You do not have to write a specific number of pages. However, you need to address all areas of the rubric. Write until this is done.

      Thanks,

      Dr. Taulbee

      Good evening Professor

      Quantitative studies focus on measuring relationships between variables.The rules are 1) understand the purpose of the study,2) identify the variable dependent and independent,3) identify how the variables are measured,4) look at he measures of central tendency and the measure of variability for the study variables.With the second rule the variables are classified as either independent or dependent.The independent is the intervention and the dependent is the outcome

      Thanks

      Referneces

      Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones & Bartlett.

       Dr. Taulbee & class,

      In this week’s lesson, we learned about the four basic rules for understanding results in a research study. I would like to discuss rule #2 because I think it is very important. Rule #2 is to identify the variables. According to Houser (2018), both variables need to be defined in a quantifiable way before the experiment begins. The first variable will be the independent, which is the intervention, or the “cause” of “cause and effect”. The dependent variable is the outcome of interest or the “effect” of “cause and effect”. If you can not effectively define these roles, the research study will be aimless, and the researcher will not get the desired results.

      Clinical significance reflects how the intervention will affect the patient. Statistical significance measures the accuracy or probability of the intervention. Traditionally, statistical significance proves if the intervention should be accepted or rejected (Page, 2014). I believe both are meaningful when applying evidence to your practice. I do feel when applying evidence to my practice, I would lean toward clinical significance being more meaningful because if I can’t use the results of the study in my practice, is there a point for me to do the research? It wouldn’t matter if there was a small or large statistical significance if I couldn’t apply the findings to my practice.

      Descriptive statistics describe the population under study in a meaningful way. Inferential statistics define the population based on analysis and observation (Surbhi, 2017). My clinical issue is using teach-back method to educate patients with heart failure to reduce 30-day readmission. The descriptive statistic that can be collected during my study would be, age, diagnosis, and frequency of readmissions for each patient in the study prior to and after integrating teach-back method of teaching. The inferential statistics that would be formulated is the change in readmissions after patients received teach-back method. For example, I could make the statement, readmissions will decrease in 6 months after receiving teach-back method when compared to previous forms of education.

      Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones & Bartlett.

      Page, P. (2014). Page P. Beyond statistical significance: Clinical interpretation of rehabilitation research literature. International Journal of Sports Physical Therapy, 9(5), 726-736. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4197528/ (Links to an external site.).

      Surbhi, S. (2017, September 09). Difference Between Descriptive and Inferential Statistics (with Comparison Chart). Retrieved from http://keydifferences.com/difference-between-descriptive-and-inferential-statistics.html

      Dear Shannon and Class,

      You did a great job describing the statistics of research. Can you show some more examples of descriptive statistics? Why does a researcher need to describe their statistics?

      Thanks,

      Dr. Taulbee

      Shannon and Class,

      Descriptive statistics are a way to manage the quantitative data in a research study. I can understand the difference between descriptive statistics and inferential statistics by saying that descriptive statistics organize and describe collected data and inferential statistics predict the outcomes of the data or help to conclude what the data might mean. Houser (2018) describes descriptive designs as statistics in which follow this rule: “No variables are manipulated in the study of descriptive statistics.” It is simply a collection of what already exists, such as numbers (quantitative) and words (qualitative). Examples of descriptive statistics can be the mean, median, mode, range, standard deviation, the coefficient of variation and percentages, these examples can be displayed in graphs or tables to help understand the data (Farber, 2015). These examples are meaningful ways to describe the collection of data for which we can then use to make decisions or predictions in inferential statistics. A researcher needs to describe their statistics to allow the reader to know what already exists on the topic or subject of study. Without understanding the data first, it is difficult to analyze or gain insight on what the data can actually mean and how it will affect current practices.

      Yvette Salas

      Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones & Bartlett.

      Farber, B. (2015). Elementary statistics: Picturing the world (6th ed.). Boston, MA: Pearson Learning Solutions

      Yvette and class,

          Your definitions on the descriptive and inferential statistic are easily understood. In the abstract the reader is looking for both of these in the abbreviated version such as the results in percentages. In the research study, the reader would be looking for more details of the measurements. ” Tables and graphs are helpful in visually understanding the data and condensing large amounts of information into smaller sections” (Houser,2015,p.315).

      Audrey

      Houser, J. (2015). Nursing research: Reading, using and creating evidence (3rd ed.). Burlington, MA: Jones& Bartlett.

      Audrey and Yvette,

      I agree with Audrey, Yvette your examples are so detailed It makes it a lot easier to understand. I had a hard time trying to figure these out and actually coming up with something good to post. I really enjoyed your post-Yvette great job.

      Jennifer

      Professor and class,

      Descriptive statistics summarize the collection of research data. It is used to summarize a sample, or a population that is being researched.  “Once the data is collected, statistical analysis begins by calculating descriptive statistics.” (Larson 2006)  Descriptive statistics use tables or graphs that may use the demographic information like sex, age and comorbidities. The researcher needs to describe their statistics to communicate their research findings and give credibility to research methods and conclusions. It also provides how the variables are similar and different. This also enhances the understanding of the research and its findings. (Houser 2018)

      Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones & Bartlett

      Circulation. Descriptive Statistics and Graphical Displays. AHA Journal. (2006) Retrieved from http://circ.ahajournals.org/content/114/1/76.full (Links to an external site.). November 28,2017

      Good evening professor and class,

      Statistics are used in nursing for many reasons.  One is to analyze a trend in the vital statistics of a particular patient.  For example, if a patient’s blood pressure deviates too far from the norm, that is a sign that a nurse should let the attending know.  Another is in research in nursing processes and procedures.  Someone might perform a statistical analysis of patient outcomes based upon how many patients a nurse cares for or based upon how many hours a nurse works.  If nurses are doing wound care, there has probably been research using statistics on patient outcomes for different kinds of procedures for wound care.  Your need to wash thoroughly when you leave one patient and go to the next is based upon research that used statistics showing that this procedure significantly reduces infections.  There are statistics that tell us about trends in nursing, that there is supposed to be a shortage of nurses in coming years. Statistics in nursing are very important!  Much of what a nurse does every day is based upon statistics.

      -Armando

      Good evening Armando

      I enjoyed reading your post and agree that statistics ares a big part of nursing and could effect  patient care.The use of statistics can also aid in changing policies for instance at my facility we have implemented that we do a meet and greet with a new patient and their families within 48 hrs of admission,this has shown a better understanding of the plan of care and a better outcome for the patients and their care givers.This has become a policy at the facility.

      Thanks

      Dr. Taulbee & class,

      Descriptive statistics are used to describe the basics features of a study through numbers placed into graphs and tables (Web Center for Social Research Methods, 2006). This is super helpful in nursing because it pulls all the useful information from a study and condenses it to a graph or table. Which, for me, is easier to read, absorb and remember. Some examples of descriptive statistics are graphing the demographics of nurses in a New York State. Another, studying the fall pattern on a unit and collecting data about each event (fall) and placing that information on a graph to get a better picture of trends. Descriptive statistics offer insight into complex information.  My classmates have given wonderful examples of descriptive statistics.

      Shannon

      Web Center for Social Research Methods. (2006). Descriptive Statistics. Retrieved from https://www.socialresearchmethods.net/kb/statdesc.php

      Shannon, excellent post.  Your post went into great detail and taught me more on this subject. Research is a systematic and organized process as noted in Brown (2013). It is about collecting information that answers a question.  Information gathered must be cross-checked by using other sources and references, even when the researcher is convinced that the information already obtained provides a good answer to the question asked (Brown, 2013). Accurate data collection will be essential to maintain the integrity and rigor of research.  I think one challenge of evidence based practice is that after being satisfied that the results of a study justify making a change, how is this implemented? As nurses, we are not free to “just do it.”  Grove, Burns, and Gray (2014) state that change is supposed to be done base on the evidence suggested by the latest research studies in the field.

      References

      Brown, S. J. (2013). Evidence-based nursing: The research-practice connection. Burlington, MA: Jones & Bartlett Learning.

      Grove, S. K., Burns, N., & Gray, J. R. (2014). Understanding nursing research: Building an evidence-based practice. New York: Elsevier Health Sciences.

      Excellent post Yenisleydi!

      Dr. Taulbee

      Hello Shannon

      I enjoyed reading your discussion and I agree with your clinical issue regarding the  use of tech back method to educate patients with chf. It is to help reduce 30 days admission back to the hospital. I know that in my hospital chf readmission is a big thing and we.are trying to find ways to decrease reaadmiasion.I would like to know more about the tech back method.

      Uche Fernes

      Professor Taulbee and class,

           There are four basic rules when we look at a research report. There are many research articles to choose from. First, the research criteria are put into the search engines. We select an individual article which may be pertinent to our inquiry. ” To follow Rule #1, We must understand the purpose of the study” ( Chamberlain, 2017, week 6 lesson). One must ask themselves, is this study’s purpose the same as ours, the design of the study? Does the research question or objective the same as mine? What is the study’s group of people, age and selection process for their groups? How strong are the variables and are they pertinent to my question?

      Clinical significance sounds like it would be more meaningful to nurses compared to statistical significance. ” In the work of clinical practice, whether or not a result is significant is based on its importance to, and implications for, practice; that is, the practical value of any particular result”  (Fethney, 2010, pg. 94). Statistics are significant to research and nursing. Measurements are significant in the reporting when they are likely to not have happened by an error or a change. Statistical significance is important to the interpreting of the results of the study and it’s validity. I would like to know that I was providing the most optimal care for my patient’s which statistical significance and clinical significant both being important.

      “Inferential statistics yield numbers that are helpful in two ways: they allow for the researcher to determine the probability that random error is responsible for the outcome, and they give the reader of the study write-up information about the size of the effect” (Houser,2015, pg328). A clinical trial would be an example as it is testing the intervention between two groups. A descriptive statistics are used to describe the traits or characteristics of the group or population in the study. These two statistics are used in quantitative analysis.

      My research topic was the timing of breast feeding education to successfulness of exclusively breast feeding for the first six months of an infant’s life. The descriptive statistics would be the characteristics of the study groups, those who successfully exclusively breast feed for six months, those who left the hospital breast feeding exclusively, those who were exclusively breast feeding at three months; then the education they had in one or more combinations- prenatally, in the hospital, the community, or no education. The inferential statistics would look if this data could be used on the whole population of pregnant women.

      Thank you, Audrey

      Chamberlain College of Nursing. (2017). week 6: Reading literature-results. [on-line lesson]. Retrieved from http://nursingonline.chamberlain.edu (Links to an external site.)

      Fethney, J. (2010). Statistics paper: Statistical and clinical significance, and how to use confidence interval to help interpret both. Australian Critical Care, 2393-97. doi:10.1016/j.aucc.2010.03.001

      Houser, J. (2015).  Reading, using and creating evidence (3rd ed.). Burlington, MA: Jones & Bartlett.

      Audrey,

           Yes!  When we are talking about nursing care we all would like to know we are providing them the most optimal care.  So we would like our research to be statistically significant and clinically important but you could also end up with results that is not statistically significant but it is clinically important, which is what could happen if the sample size is not large enough.  Then you could always have results that is statistically significant but Not clinically important, which could happen with a large group of samples ( Students, 2017).  I think both statistical significance and clinical significance could mean a lot to any research that would effect our patients.

      Kim Evans

      References:  Students 4 Best Evidence, (2017).  Statistical significance vs. clinical significance. Retrieved from: https://www.students4bestevidence.net (Links to an external si

      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

      This week, we will learn to read the Results section of a research report. If all the hard work that goes into a research study is to have meaning and purpose for nursing practice, the data collected must be analyzed so that nurses can understand (with a high level of confidence) what the researcher learned.

      Remember that statistics are only a tool for organizing data in order to make it meaningful. For nurses, knowing what the statistics are really saying as we review the results of a study will give us better evidence for improving nursing practice.

      Please remember that research is an orderly process with defined steps.

      Have a Great Week!

      Dr. Taulbee

      Instructor and class,

                 Without understanding the purpose of a study none of the other steps can start fall into place. Understanding the purpose of the study is the first basic rule to looking at data in the results section of a study (Parahoo, 2014). Clinical significance is more meaningful to my workplace because it “is generally expected to reflect the extent to which an intervention can make a real difference in patient lives” as opposed to statistical significance being the probability of an error occurring (Houser, 2015, p. 290). Clinical significance plays the key role in preventing the readmission through the education on interventions provided to patients assisting them in managing their care. “Descriptive statistics use numbers or graphic displays to organize and describe the characteristics of a sample and inferential statistics concludes from the sample data what the population might think” (Houser, 2015, p. 304). While descriptive statistics are usually quantitative, being expressed in the form of graphs or charts, inferential statistics are expressed as informed assumptions or supposed predictions. Houser (2015) states, “inferential analyses are used to determine if results found in a sample can be applied to a population—a condition for confidently generalizing research as a basis for evidence for nursing practice” (p. 353). An example of descriptive statistics would be during this year’s second quarter the care transitions programed had fewer 30 day readmissions. There was a decrease in Medicare readmission of about 10% compared to the last year’s second quarter. An example of the inferential statistics would be to enroll the Medicare members that are flagged as high-risk for readmissions, and those noted with several readmissions during the calendar year.

    References

    Houser, J. (2015). Nursing research: Reading, using and creating evidence (3rd ed.). Denver, C.O.: Jones & Bartlett Publishers.

    Dr. Taulbee and class 

    Statistical analysis is the evaluation of data collection about theory in order to draw a conclusion according to Data Analysis Australia (2017).  In nursing research it would beneficial to verify theories/EBP, or disprove it prior to implementation.  There are various examples we can relate to on a daily basis – using hand sanitizers in between patients and the number of times it is effective before having to use the standard soap and water method.  Prior to having each room and hallway installed with the sanitizers, data collection would need to be done and reviewed prior to the expense of going through the trouble.  Once the idea is obtained and explained, and the relationship between uses and decreasing nosocomial infections is correlated, developing a diagram proving or disproving the idea ensure validity either way.  Statistical data is relevant to identify trends to improve something or, in business, increase sales. 

    Thanks, Sharon 

    Applied Statistical Analysis: Data Analysis Australia. (2017). Retrieved from www.dau.com.au 

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