NURS 412 Research Critique Paper Guidelines Spring 2019 The Research Critique Paper is worth 50 points and is due Monday, April 15th at 800am. The purpose of this assignment is to help you find comple

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NURS 412

Research Critique Paper Guidelines Spring 2019

The Research Critique Paper is worth 50 points and is due Monday, April 15th at 800am.

The purpose of this assignment is to help you find complex information from a nursing research

study for analysis and critique that will then help you select and evaluate nursing research studies

to support your evidence-based practice.

1. Use APA format and complete sentences and your own words. The paper should be no

shorter than 8 pages and no longer than 10 pages in length.

2. Do not include the definitions of research terms in your paper.

3. You may only use direct quotations from the article to state the purpose/aim and

questions/hypotheses. Use appropriate citations with author, year, and page.

4. Validity and Reliability refer to the instruments used to collect data. Do not confuse the

instruments used to collect data with the statistical tests used to analyze the data.

5. SPSS is NOT a statistical test; it is the Statistical Package for the Social Sciences; data is

entered into SPSS to run the statistical tests used to analyze the data and to determine statistical

significance. Remember to report statistically significant findings and to include p values for the

statistically significant findings.

6. Use the bolded titles in the grading rubric as the levels of headings in your Critique Paper.

7. Remember to start with an introductory paragraph that states what the purpose of the paper is

and to end with a concluding summary paragraph.

8. Review the Mediasite video.

%Sample Research Critique Papers, Research Critique Paper Guidelines and Research Critique

Paper Rubric are posted in the Rubrics and Guidelines link.

9. Post your assignment in Blackboard in the Assignments link.

Assigned article for critique:

Bredesen, I.M., Bjoro, K., Gunningberg, L., & Hofoss, D. (2016). Effect of e-learning program

on risk assessment and pressure ulcer classification: A randomized study. Nurse

Education Today, 40, 191-197.

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CAN SOMEONE PLEASE COMPLETE THIS SHORT ONE PAGE RESPONSE PAPER?

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CAN SOMEONE PLEASE COMPLETE THIS SHORT ONE PAGE RESPONSE PAPER?

CAN SOMEONE PLEASE COMPLETE THIS SHORT ONE PAGE RESPONSE PAPER?
Watch the following video: Being Mortal:www.youtube.com/watch?v=lQhI3Jb7vMg (Links to an external site.) In approximately one page (with normal font and margins), reflect on which patient encountered in the video had the best outcome.  What role did the physician play in encouraging this outcome?  Which patient had, on the other hand, the worst outcome, and how might the physician have contributed to that outcome?  What could have been done better?  Make sure to appeal to the content of the video in your answer.  You will be graded not only on the quality of your writing, but also the originality, interest, and coherence of your answer and the evidence that it provides that you have engaged with the material.   Your answer will be subjected to a review for plagiarism.

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I need a 1350 word assignment on a case study to submit within 12 hours. I attached the case study here and the only question to be answered is listed underneath potential #3 on the attachment. The sc

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I need a 1350 word assignment on a case study to submit within 12 hours. I attached the case study here and the only question to be answered is listed underneath potential #3 on the attachment. The scenario is to be used to answer this along with references to support the decision. I am on eastern time and I need to submit before 3/2 12 noon.

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You have just been hired as a new leader within your department. The department currently has low employee morale and engagement. There is currently a lack of trust due to several business changes wit

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You have just been hired as a new leader within your department. The department currently has low employee morale and engagement. There is currently a lack of trust due to several business changes within your department, including letting go of several nurses and replacing their positions with LPN’s. Additionally, the volume within your department is below budget, impacting employee’s work schedules, which has also led to decreased engagement.

There have been several leadership changes over the past couple of years within your department and the employees feel as though these changes have led to reduced communication.

Your task as the new leader within your department is to come up with an action plan to address the aforementioned concerns, rebuild trust, and increase employee engagement and morale.

Please be specific with your action items and include pertinent details & timelines that you would use to address the above.

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A phenomenon is the term used to describe a perception or responses to an event. Examples of phenomena in nursing include caring and responses to stress. Assumptions are the ideas that we take for gra

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A phenomenon is the term used to describe a perception or responses to an event. Examples of phenomena in nursing include caring and responses to stress. Assumptions are the ideas that we take for granted. They explain the nature of the concepts in the theory, giving it structure.

Choose a middle-range theory or grand theory that, in your opinion, can be applied to research.

  • What is the phenomenon of concern in this theory?
  • What are the assumptions underpinning this theory?

Submission Details

  • In your discussion question response, provide a substantive response that illustrates a well-reasoned and thoughtful response; is factually correct with relevant scholarly citations, references, and examples; and demonstrates a clear connection to the readings.

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Find an article, website, or blog that uses graphs to communicate information on a health-related topic. Select two different resources to discuss in your initial post: an effective graph and a poorly

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  1. Find an article, website, or blog that uses graphs to communicate information on a health-related topic. Select two different resources to discuss in your initial post: an effective graph and a poorly designed graph.
  2. Embed each graph in your initial post or provide the link with specific information on which graph is being evaluated. Be sure to reference your sources.

Using Graphs and Charts to Illustrate Quantitative Data. (2018). U.S. Department of Health and Human Services. Retrieved from https://www.cdc.gov/healthyYouth/evaluation/pdf/brief12.pdf

Good and Bad Graphs. Retrieved from https://iase-web.org/islp/apps/gov_stats_graphing/GoodBad/GoodBadGraphs.pdfRubrics

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***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme

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***seems large-  (mostly describing the data) assignment is to analyzing data (attached files) to put in paper ***

Part 1:

Using the data in the “Comparison Table of the Variable’s Level of Measurement” ( attached) display the dependent variables and the level of measurement in a comparison table. You will attach the comparison table as an appendix to your paper.

Provide a conclusive result of the data analyses based on the guidelines below for statistical significance.



Mock Data: this has already been done!!!

  1. PAIRED SAMPLE T-TEST: Identify the variables BaselineWeight and InterventionWeight. Using the Analysis menu in SPSS, go to Compare Means, Go to the Paired Sample t-test. Add the BaselineWeight and InterventionWeight in the Pair 1 fields. Click OK. Report the mean weights, standard deviations, t-statistic, degrees of freedom, and p level. Report as t(df)=value, p = value. Report the p level out three digits.
  2. INDEPENDENT SAMPLE T-TEST: Identify the variables InterventionGroups and PatientWeight. Go to the Analysis Menu, go to Compare Means, Go to Independent Samples t T-test. Add InterventionGroups to the Grouping Factor. Define the groups according to codings in the variable view (1=Intervention, 2 =Baseline). Add PatientWeight to the test variable field. Click OK. Report the mean weights, standard deviations, t-statistic, degrees of freedom, and p level. Report t(df)=value, p = value. Report the p level out three digits
  3. CHI-SQUARE (Independent): Identify the variables BaselineReadmission and InterventionReadmission. Go to the Analysis Menu, go to Descriptive Statistics, go to Crosstabs. Add BaselineReadmission to the row and InterventionReadmission to the column. Click the Statistics button and choose Chi-Square. Select eta to report the Effect Size. Click suppress tables. Click OK. Report the frequencies of the total events, the chi-square statistic, degrees of freedom, and p Report ꭓ2 (df) =value, p =value. Report the p level out three digits.
  4. MCNEMAR (Paired): Identify the variables BaselineCompliance and Go to the Analysis Menu, go to Descriptive Statistics, go to Crosstabs. Add BaselineCompliance to the row and InterventionCompliance to the column. Click the Statistics button and choose Chi-Square and McNemars. Select eta to report the Effect Size. Click suppress tables. Click OK. Report the frequencies of the events, the Chi-square, and the McNemar’s p level. Report (p =value). Report the p level out three digits.
  5. MANN WHITNEY U: Identify the variables InterventionGroups and Using the Analysis Menu, go to Nonparametric Statistics, go to LegacyDialogs, go to 2 Independent samples. Add InterventionGroups to the Grouping Variable and PatientSatisfaction to the Test Variable. Check Mann Whitney U. Click OK. Report the Medians or Means, the Mann Whitney U statistic, and the p level. Report (U =value, p =value). Report the p level out three digits.
  6. WILCOXON Z: Identify the variables BaselineWeight and InterventionWeight. Go to the Analysis Menu, go to Nonparametric Statistics, go to LegacyDialogs, go to 2 Related samples. Add the BaselineWeight and InterventionWeight in the Pair 1 fields. Click OK. Report the Mean or Median weights, standard deviations, Z-statistic, and p Report as (Z =value, p =value). Report the p level out three digits.    Part 2 see below –

****Write a 1,000-1,250-word data analysis paper outlining the procedures used to analyze the parametric and nonparametric variables in the


mock data (above),


the statistics reported, and a conclusion of the results. Include the following in your paper:

  1. Discussion of the types of statistical tests used and why they have been chosen.
  2. Discussion of the differences between parametric and nonparametric tests.
  3. Description of the reported results of the statistical tests above.
  4. Summary of the conclusive results of the data analyses.


  5. Attach the SPSS outputs from the statistical analysis as an appendix to the paper.


  6. Attach the “Comparison Table of the Variable’s Level of Measurement” as an appendix to the paper


    .

Use the following guidelines to report the test results for your paper:

  • Statistically Significant Difference: When reporting exact p values, state early in the data analysis and results section, the alpha level used for the significance criterion for all tests in the project. Example: An alpha or significance level of < .05 was used for all statistical tests in the project. Then if the p-level is less than this value identified, the result is considered statistically significant. A statistically significant difference was noted between the scores before compared to after the intervention t(24) = 2.37, p = .007.
  • Marginally Significant Difference: If the results are found in the predicted direction but are not statistically significant, indicate that results were marginally Example: Scores indicated a marginally significant preference for the intervention group (M = 3.54, SD = 1.20) compared to the baseline (M= 3.10, SD = .90), t(24) = 1.37, p = .07. Or there was a marginal difference in readmissions before (15) compared to after (10) the intervention ꭓ2(1) = 4.75, p = .06.
  • Nonsignificant Trend: If the p-value is over .10, report results revealed a non-significant trend in the predicted direction. Example: Results indicated a non-significant trend for the intervention group (14) over the baseline (12), ꭓ2(1) = 1.75, p = .26.

The results of the inferential analysis are used for decision-making and not hypothesis testing. It is important to look at the real results and establish what criterion is necessary for further implementation of the project’s findings. These conclusions are a start.

***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Appendix Table 1 Characteristics and Examples of Variables Level of Measurement Definition of Variable Example of Variable from SPSS Database Nominal Ordinal Interval Ratio Note. Add notes here = (Provide any reference, 2020). Table 2 Types of Inferential Statistical Tests Performed According to the Level of the Measurement of the Outcome Variable Level of Measurement Type of Comparison Recommended Statistical Test Nominal Independent Groups Paired Groups Ordinal Independent Groups Paired Groups Interval Independent Groups Paired Groups Ratio Independent Groups Paired Groups Note. Add notes here = (Provide any reference, 2020). © 2022. Grand Canyon University. All Rights Reserved.
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Paired Samples Test Paired Differences t Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 Baseline Weight -This Column would contain the values for the baseline measure – Intervention Weight-This Column would contain the values for the intervention measure 39.16667 29.85838 5.45137 28.01736 50.31597 7.185 Paired Samples Test df Significance One-Sided p Two-Sided p Pair 1 Baseline Weight -This Column would contain the values for the baseline measure – Intervention Weight-This Column would contain the values for the intervention measure 29 <.001 <.001
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Independent Samples Test Levene’s Test for Equality of Variances t-test for Equality of Means F Sig. t df Significance One-Sided p Patient Weight in Pounds Equal variances assumed .019 .890 .084 28 .467 Equal variances not assumed .084 27.991 .467 Independent Samples Test t-test for Equality of Means Significance Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Two-Sided p Lower Patient Weight in Pounds Equal variances assumed .934 1.66667 19.84063 -38.97503 Equal variances not assumed .934 1.66667 19.84063 -38.97563 Independent Samples Test t-test for Equality of Means 95% Confidence Interval of the Difference Upper Patient Weight in Pounds Equal variances assumed 42.30836 Equal variances not assumed 42.30897
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Baseline Readmission Rate 0 = No 1 = Yes * Intervention Readmission Rate 0 = No 1 = Yes 30 100.0% 0 0.0% 30 100.0%
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Chi-Square Tests Value df Asymptotic Significance (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square 6.982a 1 .008 Continuity Correctionb 4.870 1 .027 Likelihood Ratio 9.562 1 .002 Fisher’s Exact Test .010 .010 Linear-by-Linear Association 6.749 1 .009 N of Valid Cases 30 a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 3.03. b. Computed only for a 2×2 table
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Directional Measures Value Nominal by Interval Eta Baseline Readmission Rate 0 = No 1 = Yes Dependent .482 Intervention Readmission Rate 0 = No 1 = Yes Dependent .482
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Baseline Non-Compliance 0 = No 1 = Yes * Intervention Non-Compliance 0 = No 1 = Yes 30 100.0% 0 0.0% 30 100.0%
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Chi-Square Tests Value df Asymptotic Significance (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square 1.639a 1 .201 Continuity Correctionb .293 1 .588 Likelihood Ratio 2.381 1 .123 Fisher’s Exact Test .492 .313 Linear-by-Linear Association 1.584 1 .208 McNemar Test .007c N of Valid Cases 30 a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is .87. b. Computed only for a 2×2 table c. Binomial distribution used.
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Directional Measures Value Nominal by Interval Eta Baseline Non-Compliance 0 = No 1 = Yes Dependent .234 Intervention Non-Compliance 0 = No 1 = Yes Dependent .234
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Paired Samples Test Paired Differences t Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 Baseline Weight -This Column would contain the values for the baseline measure – Intervention Weight-This Column would contain the values for the intervention measure 39.16667 29.85838 5.45137 28.01736 50.31597 7.185 Paired Samples Test df Significance One-Sided p Two-Sided p Pair 1 Baseline Weight -This Column would contain the values for the baseline measure – Intervention Weight-This Column would contain the values for the intervention measure 29 <.001 <.001
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Independent Samples Test Levene’s Test for Equality of Variances t-test for Equality of Means F Sig. t df Significance One-Sided p Patient Weight in Pounds Equal variances assumed .019 .890 .084 28 .467 Equal variances not assumed .084 27.991 .467 Independent Samples Test t-test for Equality of Means Significance Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Two-Sided p Lower Patient Weight in Pounds Equal variances assumed .934 1.66667 19.84063 -38.97503 Equal variances not assumed .934 1.66667 19.84063 -38.97563 Independent Samples Test t-test for Equality of Means 95% Confidence Interval of the Difference Upper Patient Weight in Pounds Equal variances assumed 42.30836 Equal variances not assumed 42.30897
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Baseline Readmission Rate 0 = No 1 = Yes * Intervention Readmission Rate 0 = No 1 = Yes 30 100.0% 0 0.0% 30 100.0% Chi-Square Tests Value df Asymptotic Significance (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square 6.982a 1 .008 Continuity Correctionb 4.870 1 .027 Likelihood Ratio 9.562 1 .002 Fisher’s Exact Test .010 .010 Linear-by-Linear Association 6.749 1 .009 N of Valid Cases 30 a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 3.03. b. Computed only for a 2×2 table Directional Measures Value Nominal by Interval Eta Baseline Readmission Rate 0 = No 1 = Yes Dependent .482 Intervention Readmission Rate 0 = No 1 = Yes Dependent .482
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Baseline Non-Compliance 0 = No 1 = Yes * Intervention Non-Compliance 0 = No 1 = Yes 30 100.0% 0 0.0% 30 100.0% Chi-Square Tests Value df Asymptotic Significance (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square 1.639a 1 .201 Continuity Correctionb .293 1 .588 Likelihood Ratio 2.381 1 .123 Fisher’s Exact Test .492 .313 Linear-by-Linear Association 1.584 1 .208 McNemar Test .007c N of Valid Cases 30 a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is .87. b. Computed only for a 2×2 table c. Binomial distribution used. Directional Measures Value Nominal by Interval Eta Baseline Non-Compliance 0 = No 1 = Yes Dependent .234 Intervention Non-Compliance 0 = No 1 = Yes Dependent .234
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Ranks Intervention Groups – Baseline & Intervention N Mean Rank Sum of Ranks Patient Satisfaction 0 = Not satisfied, 1 = Satisfied, 2 = Very Satisfied Intervention Group 15 12.20 183.00 Baseline Group 15 18.80 282.00 Total 30 Test Statisticsa Patient Satisfaction 0 = Not satisfied, 1 = Satisfied, 2 = Very Satisfied Mann-Whitney U 63.000 Wilcoxon W 183.000 Z -2.110 Asymp. Sig. (2-tailed) .035 Exact Sig. [2*(1-tailed Sig.)] .041b a. Grouping Variable: Intervention Groups – Baseline & Intervention b. Not corrected for ties.
***seems large- (mostly describing the data) assignment is to analyzing data (attached files) to put in paper *** Part 1: Using the data in the “Comparison Table of the Variable’s Level of Measureme
Ranks N Mean Rank Sum of Ranks Intervention Weight-This Column would contain the values for the intervention measure – Baseline Weight -This Column would contain the values for the baseline measure Negative Ranks 22a 11.50 253.00 Positive Ranks 0b .00 .00 Ties 8c Total 30 a. Intervention Weight-This Column would contain the values for the intervention measure < Baseline Weight -This Column would contain the values for the baseline measure b. Intervention Weight-This Column would contain the values for the intervention measure > Baseline Weight -This Column would contain the values for the baseline measure c. Intervention Weight-This Column would contain the values for the intervention measure = Baseline Weight -This Column would contain the values for the baseline measure Test Statisticsa Intervention Weight-This Column would contain the values for the intervention measure – Baseline Weight -This Column would contain the values for the baseline measure Z -4.307b Asymp. Sig. (2-tailed) <.001 a. Wilcoxon Signed Ranks Test b. Based on positive ranks.

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According to the Council on Education for Public Health, public health practitioners ought to be competent in the following areas of health policy: Discuss multiple dimensions of the policy-making pro

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According to the Council on Education for Public Health, public health practitioners ought to be competent in the following areas of health policy:

Discuss multiple dimensions of the policy-making process, including the roles of ethics and evidencePropose strategies to identify stakeholders and build coalitions and partnerships for influencing public health outcomesAdvocate for political, social or economic policies and programs that will improve health in diverse populationsEvaluate policies for their impact on public health and health equity

Given your experience in this course, why are these competency areas important? Which competency areas have we addressed in this course? How do you plan to supplement your learning in this course in order to address these competency areas? Which resources or learning opportunities would you recommend to other emerging public health practitioners in order to gain competency in the areas listed above. Please support your recommendations with ample evidence.3 APA  reference no more than 5 years old

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The interpretation of research in health care is essential to decision making. By understanding research, health care providers can identify risk factors, trends, outcomes for treatment, health care c

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The interpretation of research in health care is essential to decision making. By understanding research, health care providers can identify risk factors, trends, outcomes for treatment, health care costs and best practices. To be effective in evaluating and interpreting research, the reader must first understand how to interpret the findings. You will practice article analysis in Topics 2, 3, and 5.


For this assignment:

Search the GCU Library and find three different health care articles that use quantitative research. Do not use articles that appear in the Topic Materials or textbook. Complete an article analysis for each using the “Article Analysis 1” template.

Refer to the “Patient Preference and Satisfaction in Hospital-at-Home and Usual Hospital Care for COPD Exacerbations: Results of a Randomised Controlled Trial,” in conjunction with the “Article Analysis Example 1,” for an example of an article analysis.

While APA style is not required for the body of this assignment, solid academic writing is expected, and documentation of sources should be presented using APA formatting guidelines, which can be found in the APA Style Guide, located in the Student Success Center.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

The interpretation of research in health care is essential to decision making. By understanding research, health care providers can identify risk factors, trends, outcomes for treatment, health care c
Article Analysis 1 Article Citation and Permalink (APA format) Article 1 Article 2 Article 3 Point Description Description Description Broad Topic Area/Title Identify Independent and Dependent Variables and Type of Data for the Variables Population of Interest for the Study Sample Sampling Method Descriptive Statistics (Mean, Median, Mode; Standard Deviation) Identify examples of descriptive statistics in the article. Inferential Statistics Identify examples of inferential statistics in the article. © 2019. Grand Canyon University. All Rights Reserved.
The interpretation of research in health care is essential to decision making. By understanding research, health care providers can identify risk factors, trends, outcomes for treatment, health care c
Article Analysis: Example 1 Article Citation Utens, C. M. A., Goossens, L. M. A., van Schayck, O. C. P., Rutten-van Mölken, M. P. M. H., van Litsenburg, W., Janssen, A., … Smeenk, F. W. J. M. (2013). Patient preference and satisfaction in hospital-at-home and usual hospital care for COPD exacerbations: Results of a randomised controlled trial. International Journal of Nursing Studies, 50, 1537–1549. doi.org/10.1016/j.ijnurstu.2013.03.006 Link: https://www.ncbi.nlm.nih.gov/pubmed/23582671 (Include permalink for articles from GCU Library.) Category Description Broad Topic Area/Title The differences in preference and satisfaction based upon hospital care location for COPD exacerbations Variables and Type of Data for the Variables Treatment Location-categorical -“home treatment” and “hospital treatment” Satisfaction – Ordinal Scale (1-5) Preference – categorical “home treatment” and “hospital treatment” Population of Interest for the Study COPD exacerbation patients from five hospitals and three home care organizations Sample 139 patients 69 from the usual hospital care group 70 from the early assisted discharge care group Sampling Method A randomized sampling method was used to select the patients who met the criteria for the study (p. 1540) Descriptive Statistics (mean, median, mode; standard deviation) Identify examples of descriptive statistics in the article. Example descriptive statistics: Usual hospital Age: Mean: 67.8 Standard deviation: 11.30 Early assisted discharge Age: Mean: 68.31 Standard deviation: 10.34 (p. 1540) Inferential Statistics Identify examples of inferential statistics in the article. Example of inferential statistics: Overall satisfaction score: Tested difference between HC and EAD p-value .863 (p. 1543) © 2019. Grand Canyon University. All Rights Reserved.

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Assignment file is attached.

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Assignment file is attached.

Assignment file is attached.
Please create a Power Point to answer the following: Case study Ann, a community nurse, made an afternoon home visit with Susan and her father. After the death of her mother, Susan had growing concerns about her father living alone. “I worry about my father all the time. He is becoming more forgetful and he has trouble seeing. Mom used to take care of him. I am not sleeping and I am irritable around him. Yesterday I shouted at him because he wouldn’t let me help him with his laundry. I felt terrible! I am at my wits’ end! My brothers and sisters do not want to put dad in a nursing home but they are not willing to help out. As usual, they have left me with all the responsibility. I work part time and have two small children to care for.” Susan’s father, Sam, sat quietly with tears filling his eyes. He was well nourished and well-groomed but would not make eye contact. Nurse Ann noticed that the house was clean and orderly. A tray in front of the TV had the remains of a ham sandwich and glass of ice tea. Mail was piled up, unopened on a small table near the front door. There was only one car in the driveway and the yard was in need of attention. What questions does Orlando’s theory guide the nurse to consider in caring for Susan and Sam? Develop a family plan of care from the perspective of Orlando. Explore the 1950 and 60’s in the United States: Explore was happening in the United States during this time (culture, social, economics, struggles) What did nursing look like during this time (what were their jobs like, responsibilities, dress, autonomy, respect) What is the most influential accomplishment in nursing theory from the 1950’s and 1960’s? Power Point should include at least 4 outside references and the textbook. It should include title and reference slides and be 14-20 slides. Textbook Smith, M. C., &  Parker, M. E. (2015). Nursing Theories and Nursing Practice (4th ed.).  Philadelphia, PA: F.A. Davis. ISBN  978-0-8036-3312-4

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