Discussion: Data Analysis and Results Prevention Programs

Discussion: Data Analysis and Results Prevention Programs ORDER NOW FOR CUSTOMIZED AND ORIGINAL ESSAY PAPERS ON Discussion: Data Analysis and Results Prevention Programs This is a continuous chapter writing for a research project. This chapter will present “Data Analysis and Results”. Please follow the detailed instructions as attached! and the Attached previous chapters can be used as reference. Discussion: Data Analysis and Results Prevention Programs Additional references must be scholarly articles published within last 5 years. There’s no specific word count or pages required but it must covered all as instructed from the attachment. chapter_4_instruction.docx dpi_project_proposal_draft_chpater1_3_.docx Chapter 4: Data Analysis and Results The purpose of this chapter is to summarize the collected data, how it was analyzed and then to present the results. This section of Chapter 4 briefly restates the problem statement, the methodology, the clinical question(s) or phenomena, and then offers a statement about what will be covered in this chapter. Chapter 4 should present the results of the project as clearly as possible, leaving the interpretation of the results for Chapter 5. Make sure this chapter is written in PRESENT tense since the project has not actually conducted. This chapter typically contains the analyzed data, often presented in both text and tabular or figure format. To ensure readability and clarity of findings, structure is of the utmost importance in this chapter. Sufficient guidance in the narrative should be provided to highlight the findings of greatest importance for the reader. Most investigators begin with a description of the sample and the relevant demographic characteristics presented in text or tabular format. Ask the following general questions before starting this chapter: 1. Is there sufficient data to answer each of the clinical question(s) asked in the project? 2. Is there sufficient data to support the conclusions you will make in Chapter 5? 3. Is the project written in the third person? Never use the first person. 4. Is the data clearly explained using a table, graph, chart, or text? Visual organizers, including tables and figures, must always be introduced, presented and discussed within the text first. Never insert them without these three steps. It is often best to develop all of the tables, graphs, charts, etc. before writing any text to further clarify how to proceed. Point out the salient results and present those results by table, graph, chart, or other form of collected data.Discussion: Data Analysis and Results Prevention Programs Criterion Learner Score (0, 1, 2, or 3) Chairperson Score (0, 1, 2, or 3) Comments or Feedback INTRODUCTION (TOTHE CHAPTER) This section of Chapter 4 briefly restates the problem statement, the methodology, the clinical question(s) or phenomena, and offers a statement about what will be covered in this chapter. Re-introduces the purpose of the practice project. Briefly describes the project methodology and/or clinical question(s) tested. Provides an orienting statement about what will be covered in the chapter. Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document. Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present, but needs some editing); 3 (publication ready). Descriptive Data This section of Chapter 4 provides a narrative summary of the population or sample characteristics and demographics of the participants in the project. It establishes the number of subjects, gender, age, organization, or setting (if appropriate), and other appropriate sample characteristics (e.g. education level, program of project, employee classification etc.). The use of graphic organizers, such as tables, charts, histograms and graphs to provide further clarification and promote readability, is encouraged to organize and present coded data.Discussion: Data Analysis and Results Prevention Programs Ensure this data cannot lead to anyone identifying individual participants in this section or identifying the data for individual participants in the data summary and data analysis that follows. For numbers, equations, and statistics, spell out any number that begins a sentence, title, or heading – or reword the sentence to place the number later in the narrative. In general, use Arabic numerals (10, 11, 12) when referring to whole numbers 10 and above, and spell out whole numbers below 10. There are some exceptions to this rule: • If small numbers are grouped with large numbers in a comparison, use numerals (e.g., 7, 8, 10, and 13 trials); but, do not do this when numbers are used for different purposes (e.g., 10 items on each of four surveys). • Numbers in a measurement with units (e.g., 6 cm, 5-mg dose, 2%). • Numbers that represent time, dates, ages, sample or population size, scores, or exact sums of money. • Numbers that represent a specific item in a numbered series (e.g., Table 1). A sample table in APA style is presented in Table 1. Be mindful that all tables fit within the required margins, and are clean, easy to read, and formatted properly using the guidelines found in Chapter 5 (Displaying Results) of the APA Publication Manual 6.0. Table 1 A Sample Data Table Showing Correct Formatting Column A M (SD) Column B M (SD) Column C M (SD) Row 1 10.1 (1.11) 20.2 (2.22) 30.3 (3.33) Row 2 20.2 (2.22) 30.3 ( 3.33) 20.2 (2.22) Row 3 30.3 (3.33) 10.1 (1.11) 10.1 (1.11) Note. Adapted from “Sampling and Recruitment in Studies of Doctoral Students,” by I.M. Investigator, 2010, Journal of Perspicuity, 25, p 100. Criterion Learner Score (0, 1, 2, or 3) Chairperson Score (0, 1, 2, or 3) Comments or Feedback DESCRIPTIVE DATA This section of Chapter 4 provides a narrative summary of the population or sample characteristics and demographics of the participants in the project. It establishes the number of subjects, gender, age, level (if appropriate), organization, or setting (if appropriate). Discussion: Data Analysis and Results Prevention Programs The use of graphic organizers, such as tables, charts and graphs to provide further clarification and promote readability, is encouraged. Provides a narrative summary of the population or sample characteristics and demographics. Graphic organizers are used as appropriate to organize and present coded data, as well as descriptive data such as tables, histograms, graphs, and/or charts. Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document. Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present, but needs some editing); 3 (publication ready). Data Analysis Procedures This section presents a description of the process that was used to analyze the data. If clinical question(s) guided the project, data analysis procedures can be framed relative to each clinical question. Data can also be organized by chronology of phenomena, by themes and patterns, or by other approaches as deemed appropriate according for a qualitative project. The key components included in this section are: • A detailed description of the data analysis procedures. • An explanation of how the raw data relates to the clinical questions(s) asked in the project for a quantitative project. • A discussion of the identification of sources of error and their effect on the data. • An explanation and justification of any differences in why the data analysis section does not match what was approved in Chapter 3 (if appropriate). • An analysis of the reliability and validity of the data in statistical terms, for quantitative projects. •Discussion: Data Analysis and Results Prevention Programs A description of the approaches used to ensure validity and reliability, for qualitative projects. Results This section, which is the primary section of this chapter, presents a summary and analysis of the data in a non-evaluative, unbiased, organized manner that relates to the clinical question. List the clinical question as you are discussing them in order to ensure that the readers see that the question has been addressed. Answer the clinical question in the order that they are listed for quantitative studies. You can organize your data in several different ways for qualitative studies including: by clinical question, by chronology of variables, by themes and patterns, or by other approaches deemed appropriate for the project. The key components included in this section are: • The data and the analysis of that data should be presented in a narrative, nonevaluative, unbiased, organized manner by clinical question(s). • The section should also include appropriate graphic organizers, such as tables, charts, graphs, and figures. • The amount and quality of the data or information is sufficient to answer the clinical question(s) is well presented, and is intelligently interpreted. • Qualitative: Findings are coded by major themes and subthemes using section titles if thematic analysis was used. They are presented in order of significance, if appropriate. The method of qualitative analysis will inform how the data will be displayed. • Quantitative: Findings are presented by clinical question using section titles. They are presented in order of significance, if appropriate. • Quantitative: Results of each statistical test are presented in appropriate statistical format with tables, graphs, and charts. • Quantitative: For inferential statistics, p-value and test statistics are reported. • Quantitative: Control variables (if part of the design) are reported and discussed. Outliers, if found, were reported. The results must be presented without implication, speculation, assessment, evaluation, or interpretation. Discussion of results and conclusions are left for Chapter 5. In quantitative practice improvement projects, it is not required for all data analyzed to be presented; however, it is important to provide descriptive statistics and the results of the applicable statistic tests used in conducting the analysis of the data.Discussion: Data Analysis and Results Prevention Programs It is also important that there are descriptive statistics provided on all variables. Nevertheless, it is also acceptable to put most of this in the Appendix if the chapter becomes too lengthy. Required components include descriptive and inferential statistics. Descriptive statistics describe or summarize data sets using frequency distributions (e.g., to describe the distribution for the IQ scores in your class of 30 pupils) or graphical displays such as bar graphs (e.g., to display increases in a school district’s budget each year for the past five years), as well as histograms (e.g., to show spending per child in school and display mean, median, modes, and frequencies), line graphs (e.g., to display peak scores for the classroom group), and scatter plots (e.g., to display the relationship between two variables). Descriptive statistics also include numerical indexes such as averages, percentile ranks, measures of central tendency, correlations, measures of variability and standard deviation, and measures of relative standing. Inferential statistics describe the numerical characteristics of data, and then go beyond the data to make inferences about the population based on the sample data. Inferential statistics also estimate the characteristics of populations about population parameters using sampling distributions, or estimation. Table 2 presents example results of an independent t test comparing Emotional Intelligence (EI) mean scores by gender. Table 2 t Test for Equality of Emotional Intelligence Mean Scores by Gender t test for equality of means EI t df p 1.908 34 .065 Chapter 4 can be challenging with regard to mathematical equations and statistical symbols or variables. When including an equation in the narrative, space the equation as you would words in a sentence: x + 5 = a. Punctuate equations that are in the paragraph, as you would a sentence. Remember to italicize statistical and mathematical variables, except Greek letters, and if the equation is long or complicated, set it off on its own line. Basic guidelines include: • Statistical symbols are italicized (t, F, N, n) • Greek letters, abbreviations that are not variables and subscripts that function as identifiers use standard typeface, no bolding or italicization • Use parentheses to enclose statistical values (p = .026) and degrees of freedom t(36) = 3.85 or F(2, 52) = 3.85 •Discussion: Data Analysis and Results Prevention Programs Use brackets to enclose limits of confidence intervals 95% CIs [- 5.25, 4.95] Make sure to include appropriate graphics to present the results. Always introduce, present, and discuss the visual organizers in narrative form. Never insert a visual organizer without these three steps. A figure is a graph, chart, map, drawing, or photograph. Below is an example of a figure labeled per APA style. Do not include a figure unless it adds substantively to the understanding of the results or it duplicates other elements in the narrative. If a figure is used, a label must be placed under the figure. As with tables, refer to the figure by number in the narrative preceding the placement of the figure. Make sure a table or figure is not split between pages. Below is another example of a table for you to review. It describes the characteristics of a servant leader. Table 3 The Servant Leader Trait Descriptors Values People By believing in people By serving other’s needs before his or her own By receptive, non-judgmental listening Develops People By providing opportunities for learning and growth By modeling appropriate behavior By building up others through encouragement and affirmation Builds Community By building strong personal relationships By working collaboratively with others By valuing the differences of others Displays Authenticity By being open and accountable to others By a willingness to learn from others By maintaining integrity and trust Provides Leadership By envisioning the future By taking initiative By clarifying goals Shares Leadership By facilitating a shared vision By sharing power and releasing control By sharing status and promoting others Note. Derived from Laub, J. (1999). Assessing the servant organization: Development of the servant organizational leadership assessment (SOLA) instrument (Doctoral Practice improvement project). Available from ProQuest Practice improvement project and Theses Database. (UMI No. 9921922) Figure 1. An example of a strong negative correlation for SAT composite score and time spent on Facebook for 11th grade high school students enrolled in IMSmart SAT Prep Course. Summary This section provides a concise summary of what was found in the project. It briefly restates essential data and data analysis presented in this chapter, and it helps the reader see and understand the relevance of the data and analysis to the clinical question. Discussion: Data Analysis and Results Prevention Programs Finally, it provides a lead or transition into Chapter 5, where the implications of the data and data analysis relative to the clinical question will be discussed. The summary of the data must be logically and clearly presented, with the factual information separated from interpretation. For qualitative studies, summarize the data and data analysis results in relation to the clinical question. For quantitative studies, summarize the statistical data and results of statistical tests in relation to the clinical question. Finally, provide a concluding section and transition to Chapter 5. Running head: FALL PREVENTION New Fall Preventive Program for Stroke Population in Rehabilitation Facility 1 FALL PREVENTION 2 Chapter 1: Introduction to the Project Hospital falls are some of the most devastating events that patients can experience. Not only do they exacerbate already existing health complications but may also give rise to new complications to the patients. Statistics indicate that patient falls happen to more than one million patients in medical facilities across the country (Bouldin et al., 2012). Among the cases of unassisted falls, stroke patients made up the most significant aspect of this population. Stroke patients are susceptible to a wide range of complications (Leone & Adams, 2016). One of these complications is hospital falls. The number of falls recorded annually is on the rise and the trend is expected to continue as there exists a gap between the knowledge of the intervention used in reducing these accidents and the willingness of the healthcare staff to implement the aforementioned measures (Leone & Adams, 2016). Some nurses fail to comply with strategies of minimizing fall rate even in the worst cases involving a Schmid fall score of greater than three (Leone & Adams, 2016). Some staff members also fail to utilize fall risk armbands, exit alarms, seatbelts, and other tools of minimizing fall rate. In a desire to improve the provision of care services to this group, it is essential to develop effective strategies that would reduce falls among stroke patients receiving care in various facilities. When stroke patients experience falls, most of them are alone and not capable of receiving immediate help, such as when they are trying to use the toilets without calling for assistance, and this has an effect on rehabilitation process and recovery (Brady, et al., 2016). This project is therefore worth conducting because it will provide the development and implementation of evidence-based methods as an effective way of reducing hospital falls among stroke patients.Discussion: Data Analysis and Results Prevention Programs FALL PREVENTION 3 In this chapter, therefore, the background of the problem will be extensively discussed, explaining the history of hospital falls among ischemic stroke patients, as well as the current state of the problem. The focus of the problem will be defined in the problem statement section including the affected population and how the project will contribute to solving the problem. The purpose statement will be reflected upon, and an insight into how the project will be accomplished. The clinical question will be formulated, and the advancing scientific knowledge in hospital falls management described where the theoretical foundation of the project will be mentioned. The potential contribution of the project within the literature will also be addressed and the rationale of the methodology for the project provided. The specific project design will be discussed, and the various terms used within the project defined. Finally, the assumptions, limitations, and delimitations analyzed. The last part of this chapter provides a summary of the project. Background of the Project Hospital falls are not new phenomena in healthcare settings, however, the extent to which falls occur among ischemic stroke patients and the ramifications of the damages has become a major concern to the health organizations. Current records indicate that there are over one million cases of hospital falls in the United States of America alone (Brady, et al., 2016). Out of this population, patients being treated for stroke form the vast majority, approximately 85% of all hospital-acquired conditions (Brady et al., 2016; (Cuttler, Barr-Walker, & Cuttler, 2017). It is important to note that stroke patients have a plethora of challenges among them being a loss of function from one side of the body cause the inability to maintain balance. Patients suffering from stroke need constant FALL PREVENTION 4 assistance, and failure to assist may pose far-reaching ramifications to them. Discussion: Data Analysis and Results Prevention Programs Literature reports that in most cases, stroke patients who experienced fall attempted to help themselves to the toilet and accidentally experienced the fall (Panfili, Metcalf, & Griebling, 2017). The fact that stroke patients represented the largest diagnostic group experiencing falls calls for the attention of care providers to develop approaches that may be helpful in quality and safety improvement as well as reducing the health impact of the falls. The fact that patients being treated for stroke are the most vulnerable hospital falls, indicates that there are adverse complications among this group of patients need to be addressed. Implementing evidence-based care practices is one of the most effective ways of addressing this problem among patient … Get a 10 % discount on an order above $ 100 Use the following coupon code : NURSING10

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