Improving Medication Adherence among Type II Home Healthcare Diabetic Patients

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Improving Medication Adherence among Type II Home Healthcare Diabetic Patients

Improving Medication Adherence among Type II Home Healthcare Diabetic Patients

Submitted by

Bola Odusola-Stephen

 

 

 

 

 

 

 

A Direct Practice Improvement Project Presented in Partial Fulfillment

of the Requirements for the Degree

Doctor of Nursing Practice

 

 

 

 

 

 

 

Grand Canyon University

Phoenix, Arizona

 

 

April 6, 2021

 

 

 

 

 

 

 

 

 

 

 

 

© Bola Odusola-Stephen, 2020

All rights reserved.

 

 

GRAND CANYON UNIVERSITY

Improving Medication Adherence among Type II Home Healthcare Diabetic Patients

by

Bola Odusola-Stephen

 

 

 

has been approved.

 

 

 

April 6, 2021

 

 

APPROVED:

Maria Thomas., DNP., DPI Project Chairperson

Bamidele Jokodola., DNP., DPI Project Mentor

 

 

ACCEPTED AND SIGNED:

________________________________________

Lisa Smith, PhD, RN, CNE

Dean and Professor, College of Nursing and Health Care Professions

_________________________________________

Date

Abstract

Patient medication adherence is essential in their disease management for home health Type II diabetic patients. At the project site, there was no standardized process for identifying and addressing the patient’s medication adherence. The purpose of this quantitative quasi-experimental project is to determine to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The nursing theory and change model that will guide this project is Orem’s Self-Care Deficit Theory and Diffusion of Infusion Model. Data will be collected on the medication adherence rates pre-and-post-implementation of the project. It will be analyzed utilizing an independent t-test to determine the statistical significance. The clinical significance could be found in the nurses being consistent in performing the medication adherence screenings and providing the patient-centered strategy for the patient to remain compliant. The findings should suggest that implementing the medication adherence program could improve patient compliance rates. This project’s recommendation is to conduct it using larger populations of home health patients for a longer timeframe. Comment by Author: MAP must indicate that it is driven by ISMP project Comment by Author: Remove Infusion over here.

Keywords: diabetes mellitus type II, home-based care, medication adherence, MAP resources, quantitative approach Comment by Author: Add the 2 Theories in the Kwewords

Dedication

An optional dedication may be included here. While a practice improvement project is an objective, scientific document, this is the place to use the first person and to be subjective. The dedication page is numbered with a Roman numeral, but the page number does not appear in the Table of Contents. It is only included in the final practice improvement project and is not part of the proposal. If this page is not to be included, delete the heading, the body text, and the page break below.

Acknowledgments

An optional acknowledgements page can be included here. This is another place to use the first person. If it applies, acknowledge and identify grants and other means of financial support. Also acknowledge supportive colleagues who rendered assistance. The acknowledgments page is numbered with a Roman numeral, but the page number does not appear in the Table of Contents. This page provides a formal opportunity to thank family, friends, and faculty members who have been helpful and supportive. The acknowledgements page is only included in the final practice improvement project and is not part of the proposal. If this page is not to be included, delete the heading, the body text, and the page break below. If you cannot see the page break, click on the Show/Hide button (go to the Home tab and then to the Paragraph toolbar).

Table of Contents Chapter 1: Introduction to the Project 1 Background of the Project 2 Problem Statement 4 Purpose of the Project 5 Clinical Question(s) 7 Advancing Scientific Knowledge 7 Significance of the Project 9 Rationale for Methodology 10 Nature of the Project Design 11 Definition of Terms 13 Assumptions, Limitations, Delimitations 14 Summary and Organization of the Remainder of the Project 15 Chapter 2: Literature Review 18 Theoretical Foundations 20 Review of the Literature 21 Theme 1 22 Theme 2 26 Summary 29 Chapter 3: Methodology 31 Statement of the Problem 32 Clinical Question 33 Project Methodology 34 Project Design 34 Population and Sample Selection 37 Instrumentation or Sources of Data 39 Validity 40 Reliability 40 Data Collection Procedures 41 Data Analysis Procedures 42 Potential Bias and Mitigation 43 Ethical Considerations 43 Limitations 44 Summary 45 Chapter 4: Data Analysis and Results 68 Descriptive Data 69 Data Analysis Procedures 72 Results 73 Summary 79 Chapter 5: Summary, Conclusions, and Recommendations 81 Summary of the Project 82 Summary of Findings and Conclusion 83 Implications 85 Theoretical Implications 85 Practical Implications 85 Future Implications 85 Recommendations 86 Recommendations for Future Projects 87 Recommendations for Practice 88 References 90 Appendix A 92 The Parts of a Practice Improvement Project 92 Preliminary Pages 92 Main Text 92 Supplementary Pages 93 Appendix B 94 What is my DPI project design? 94 Appendix C 96 Power Analysis Using G Power 96 Appendix D 97 Example SPSS Dataset & Variable View 97 Appendix E 98 How to Make APA Format Tables and Figures Using Microsoft Word 98 Appendix F 108 Writing up your statistical results 108

 

 

 

 

 

List of Tables

Table 1 Characteristics of Variables 42

Table 2 Type of Methodology and Rationale for Selecting It 45

Table 3 A Sample Data Table Showing Correct Formatting 71

Table 4 t  Test for Equality of Emotional Intelligence Mean Scores by Gender 75

Table 5 The Servant Leader 76

(Note: single-space table titles; use “Add a Space After Paragraph” (12pt) in Line Spacing Options between table titles)

List of Figures

Figure 1. Approaches to C ollecting the D ata to A nswer the C linical Q uestions. 43

Figure 2. Parametric S tatistics for A nalysis of R atio or I nterval L evel D ependent V ariabl e 58

Figure 3. Non- P arametric S tatistics for A nalysis of N ominal or O rdinal L evel D ependent V ariable 59

Figure 4. Scattor Plot Example – Strong Negative Correlation 78

(Note: single-space figure titles; use “Add a Space After Paragraph” (12pt) in Line Spacing Options between table titles) double-space between entries)

 

 

 

 

Chapter 1: Introduction to the Project

According to the Centers for Disease Control and Prevention (2020), diabetes impacts one in ten Americans. Furthermore, the prevalence of diabetes continues to rise and is projected to increase by 0.3% per year until 2030 (Lin et al., 2018). For individuals with Type II diabetes, proper and effective medication adherence is critical (Kvarnström et al., 2017). This is particularly significant among healthcare patients because diabetes is one of the leading diagnoses for admission into a home health care facility (Sertbas et al., 2019). The home health service is increasing due to the aging population (Sertbas et al., 2019). In this population, approximately 45% of the patients fail to maintain glycemic control (HgbA1c < 7%) (Polonsky & Henry, 2016). This is attributed to poor medication adherence (Polonsky & Henry, 2016). Poor medication adherence is linked with increased morbidity and mortality rates, increased financial expenses for the patient, hospital, and insurance companies, frequent hospitalizations, and lower quality of life (Polonsky & Henry, 2016).

Various researchers have denoted the critical role that home healthcare providers play in promoting enhanced medication adherence (Bussell et al., 2017). Healthcare providers must assess the patient’s current situation and explore all options to improve the barriers associated with poor medication adherence (Nikitara et al., 2019). Furthermore, they must understand their roles in diabetes care and what obstacles they have when performing their responsibilities (Nikitara et al., 2019). Comment by Author: Rephrase by saying According to Bussell et al.,………

At the project site, the primary investigator, in collaboration with the stakeholders, noted that the healthcare providers documented ten percent of the patients were not adhering to their medication regimen. This prompted frequent hospitalizations, infections, and other diabetic complications. In further investigation, it was found that there was not a standardized method for the healthcare providers to evaluate the patients regarding medication adherence. Hence, the introduction of the MAP resources and education intervention will be implemented.

The project is worth conducting because the primary investigator focuses on diabetic home health patients who are not the focal point of many literature reviews. Furthermore, little information is noted regarding the impact the healthcare team plays in addressing this population’s lack of medication adherence. The primary investigator aims to introduce a standardized method of addressing patient’s medication adherence using the MAP resources and education to minimize frequent hospitalizations, infections and increase their quality of life. For this project’s purpose, the primary investigator (PI) will examine the impact/role healthcare team members play in addressing patient-related factors that affect medication adherence among home healthcare diabetic patients. Comment by Author: Requires Citations

Chapter 1 introduces the project, background, and problem statements. Other segments include the purpose of the project, clinical question, advancing scientific knowledge, and project significance. The last sections consist of the rationale for using a quantitative method and quasi-experimental design, definition of operational terms, assumptions, limitations, and delimitations. The last few sentences are transitional ones providing a preview into Chapter 2.

Background of the Project

Home-based healthcare has existed since 1909 (Choi et al., 2019). Since its inception, home-based healthcare has been perceived as a more costly method of patient care than expenses associated with hospitalization (Singletary, 2019). In the early 20th century, home-based healthcare was mainly practiced due to financial disparities, specifically since many individuals could not afford hospitalized care. Furthermore, home-based healthcare was also practiced due to medical inaccessibility, which often existed in African American communities due to limited access to resources (Choi et al., 2019).

Present-day, home-based healthcare is often selected due to an individual’s personal preferences. There are some situations in which individuals prefer the comforts of their own home compared to that of a hospital or group home (Bryant, 2018). As older generations continue to age, they often prefer to remain in their home for as long as possible. Given the needs of older generations and the impact of advances in healthcare and technology, the prevalence of home-based healthcare has exponentially grown (Wong et al., 2020). While home-based healthcare is not appropriate for all patients, Szanton et al. (2016) noted that this care option is best when an individual’s condition can be managed without admission to a hospital. Patients who have diabetes or hypertension are often recipients of home-based healthcare (Wong et al., 2020).

Adhering to diabetes medication regimen requirements can be complex. A study conducted by Raoufi et al. (2018) noted that ten percent of diabetic patients did not correctly monitor their glucose levels, nor did they adhere to medication requirements. Patients with diabetes often express difficulties adhering to medication regimens, thereby reinforcing the critical role of receiving education from home healthcare providers (Wong et al., 2020). This is in part to the patients not having sufficient knowledge and education regarding diabetes and proper management of the disease (Wong et al., 2020). With diabetes being one of the leading diagnoses for patients needing home health services, healthcare agencies must educate their staff to evaluate the factors prohibiting patients from adhering to their medication regimen. Comment by Author: How did you determine the 10%? State the history and the present state of the problem Comment by Author: State the 10% of what number of how many population

Problem Statement

It is not known if or to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The population affected are home health Type II diabetic patients in an urban healthcare agency in Texas. The stakeholders have cited that medication adherence among diabetic patients is lacking. According to data obtained from the site’s electronic health record (EHR), home healthcare providers documented that ten percent of diabetic home healthcare patients are not adhering to their medication regimen. Although this percentage four to six percent lower than other percentages cited in the literature for medication non-adherence, in terms of chronic disease management, various researchers have noted the implications associated with lacking adherence to medication regimens (Camacho et al., 2020; Hamrahian, 2020; Misquitta, 2020). Comment by Author: Please state where you got the MAP from? State the article that is driving this project. Comment by Author: Who are the Stakeholders?

The lack of medication adherence can be attributed to inadequate drug-related knowledge, medication costs, poor understanding of medication regimen, etc., reinforcing the need for this quality improvement project (Heath, 2019; Sharma et al., 2020). Kvarnström et al. (2017) emphasized healthcare providers play a critical role in ensuring medication adherence. To promote medication adherence among patients of a home healthcare facility, the primary investigator will introduce a standardized method for the healthcare providers to assess the patient’s medication adherence. The staff will achieve greater insight by using MAP resources and an education intervention created by Starr and Sacks (2010). The tools utilized in this study, which are from Starr and Sacks’s (2010) MAP Toolkit and Training Guide resources, include: (1) the questions to ask poster, (2) an adherence assessment pad, and (3) my medications list.

The project contributes to solving the problem by introducing a standardized method of evaluating the patient’s medication adherence. It will improve the healthcare provider’s knowledge and awareness regarding the obstacles or factors the patient may face in maintaining a medication regimen. This would help the facility adhere to the current Centers for Disease Control and Prevention (2020) guidelines in controlling their HgbA1c levels, deter healthcare costs, frequent hospitalizations, and infections. Comment by Author: The project is 4 weeks, so you cannot measure the A1c because it takes 90 days. Comment by Author: Outcome measurement must be indicated and must show a decrease that is maintained at normal range of 70-110

Purpose of the Project

The purpose of this quantitative quasi-experimental project is to determine to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The independent variable is the MAP resources and educational intervention. The dependent variable is medication adherence rates. A quantitative methodology will be used for the project to learn about this population (home health patients) (Allen, 2017). Furthermore, it will allow the primary investigator to determine the relationship between the independent variable (MAP resources and educational intervention) and the dependent variable (medication adherence rates) within the home health patients (Allen, 2017). A quasi-experimental design will be used to establish a cause-and-effect relationship between the variables. It will also be used for practical reasons (Leedy & Ormrod, 2014). Comment by Author: Follow the Template in the problem statement. state “determine if…….” State the articles used Comment by Author: Include the glucose level

The specific population that will be addressed are home health patients ages 35 to 64 years old. The selected site serves approximately 100 patients annually, and 30 patients are diagnosed with Type II diabetes. The inclusion criteria are males and females diagnosed with Type II diabetes, oral medication or insulin, and home health patients. The exclusion criteria are individuals with language or cognitive deficits and diagnosed with Type I diabetes. Five staff nurses will help to implement the quality improvement project. They are individuals who are registered nurses, work full-time, and have been employed with the facility over one year. Comment by Author: Please state why you are using this Population Group Comment by Author: State that the staff will be trained and include the statistics (Male & Females)

The geographic location of the project is in an urban area of Houston, Texas. The County statistics show that approximately 17.6% of the population have Type II diabetes (Houston, 2021). During 2016-2018, 20.2% of the population was hospitalized due to diabetic complications (Houston, 2021). There are over 700 000 Medicare participants in a three-county radius, which is higher than the national average (Understanding Houston, 2021). Data further showed that preventable hospital stays occur in older adults 65 and above (Understanding Houston, 2021). This suggested a trend to overuse the hospitals as a primary source of care (Understanding Houston, 2021).

The project contributes to the nursing field by increasing the healthcare providers’ knowledge and awareness of the obstacles and other risk factors involved in a patient not adhering to their medication regimen. Furthermore, it would help increase dialogue between the provider and patient in sharing the details of their behavior (Bussell et al., 2017). The details of medication nonadherence are frequently hidden (Bussell et al., 2017). In a qualitative study conducted by Brown et al. (2016), they suggested that the approach used by healthcare providers asking a patient about their medication-taking behaviors is critical in discovering their medication nonadherence. Educating healthcare providers to discuss the situation using a nonjudgmental approach could uncover the obstacles (Bussell et al., 2017). This creates a positive, blame-free atmosphere allowing the patients to discuss their medication-taking behavior (Bussell et al., 2017).

Clinical Question Comment by Author: This section must be 3 Paragraphs 10 Clinical Questions Comment by Author: The Paragraphs must include 1) Clinical Questions, 2) Variables, 3) Discussion of the Clinical Questions

A well-developed clinical question must be related and relevant to patient care. This helps the primary investigator search for evidence-based answers. The clinical question that will direct this quality improvement project is: To what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The independent variable is the MAP resources and educational intervention. The dependent variable is the medication adherence rates.

Advancing Scientific Knowledge

This direct practice improvement project seeks to enhance medication adherence among diabetic home healthcare patients using the MAP resources. As previously noted, at the selected project site, medication adherence among home healthcare patients is lacking. Polonsky and Henry (2016) emphasized that of all the home healthcare patients, diabetes patients have the highest rates of medication non-adherence. According to information gathered from the home healthcare’s EHR, from 2018 to 2019, ten percent of the diabetic patients did not adhere to their prescribed medication regimen. Issues for non-adherence included worry about high medical bills for future management, limited glycemic control, and using the emergency room as a primary care source (Polonsky & Henry, 2016).

Various researchers have cited the benefits associated with patient-provider engagement and collaboration to improve medication adherence. Therefore, to answer a call by researchers, it is necessary to improve medication adherence among diabetic patients (Ong et al., 2018; Polonsky & Henry, 2016; Wong et al., 2017). The advancement of a small step forward at the clinical site is that by improving medication adherence among diabetic patients’ positive patient-related outcomes will likely occur using the MAP protocol. This DPI project targets diabetes patients; hence, the findings might provide insight into improving medication adherence among other home-based care populations (i.e., those with hypertension or heart disease). This will add to the current literature and address the gap found regarding non-medication factors among home health diabetic patients. Comment by Author: Must be cited instead of saying various researchers

The theoretical framework that will be used in this quality improvement project is Orem’s self-care deficit theory. The primary expectations of the theory are that a person should be self-reliant and responsible for their care (RenpenningcN et al., 2003). The theory also notes that nursing is an action described as an interaction between two or more individuals (RenpenningcN et al., 2003). The third assumption is that an individual who successfully meets the self-care conditions understands that it is a primary component in health prevention and illness (RenpenningcN et al., 2003). Hence, their knowledge promotes positive self-care behaviors. The theory is comprised of three related sections: theory of self-care, self-care deficit, and the nursing system (RenpenningcN et al., 2003). It fits the project because it includes healthcare providers assisting patients in their self-care and management to improve their function at a home level (RenpenningcN et al., 2003). The patients cannot effectively manage medication adherence for diabetes, which affects their quality of life and health. Comment by Author: When was Orem’s Theory Found? Please indicate when she did the Theory and Implemented? It is not 2003, please find when’ Cite the source and connect it to your project and how has the theory advance your project

The change model that will be used is the Diffusion of Innovation Model developed by Rogers (2003). There are five stages:

a. Knowledge or awareness- the individual is exposed to the change and lacks information.

b. Persuasion or interest-the individual becomes interested in the new idea and seeks more information.

c. Decision or evaluation- the individual mentally applies the idea to their present and future situation, hence deciding whether to try it.

d. Implementation or trial-the individual uses the idea fully.

e. Confirmation or adoption- the individual continues to use the idea in their everyday life and health practices.

Utilizing these methods will help the project advance by helping the healthcare providers to implement a standardized method in evaluating the patient’s medication-taking behaviors.

Significance of the Project Comment by Author: You don’t need to write the whole Clinical Question here

The significance of the project is that there continues to be a steady rise in chronic diseases has resulted in more patient care options (Polonsky & Henry, 2016). To meet various population groups’ unique needs, home-based care has gained popularity (Holly, 2020). Type II diabetes patients who qualify for home-based care options must demonstrate their willingness to work with the home healthcare agency at the selected project site. When patients who receive home-based care fail to adhere to the care requirements set forth, adverse outcomes can ensue (Polonsky & Henry, 2016).

The possible results based on the clinical question and problem statement should increase patient compliance related to medication adherence. The project also helps to empower healthcare providers to adequately address medication questions and patient concerns and ensure the patients keep track of their medication regimen, resulting in a reduction in adverse events. Holecki et al. (2018), when the MAP resources were utilized, medication adherence increased significantly.

The findings noted by Holecki et al. (2018) reinforce the beneficial nature of implementing the MAP resources, as this can improve the quality of patient care received. For this quality improvement project, it fits within helping to correct the gap noted in the literature (regarding medication adherence) for this population. Furthermore, it contributes to the clinical site by helping the patients maintain their medication regimen. Hence, decreasing potential infections, hospitalizations, and incurring financial costs to (patients and the facility).

Rationale for Methodology

The methodology chosen for this quality improvement project is quantitative.

Creswell and Creswell (2017) noted a quantitative methodology is best suited for projects that require data in numerical form. In this project, the numerical data will be presented using charts and graphs. These charts and graphs will allow readers to compare medication adherence rates pre-project implementation and post-project implementation.

While qualitative research studies are beneficial, they examine experiences, perspectives, and beliefs about a specific issue (Creswell & Creswell, 2017). The data collection used in this type of methodology is interviews (semi-structured, one-on-one, and focus groups). For this project, the primary investigator is not seeking to understand the participants’ feelings, behaviors, or lived experiences related to medication adherence.

The clinical question for this project is: To what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The independent variable is the MAP resources and educational intervention and the dependent variable is the medication adherence rates. The clinical question will be answered using collected retrospective data prior to the project’s implementation (four weeks) from the electronic medical record and four week’s post-implementation. This strategy will use statistical data that concentrates on the numbers collected and analyzed using an independent t-test.

Nature of the Project Design

A quasi-experimental design will be used for this project. Quasi-experimental designs are used to compare data before and after the implementation of an initiative/intervention. Price et al. (2017), “In a pretest-posttest design, the dependent variable is measured once before the treatment is implemented and once after it is implemented” (Chapter 7, para. 6). Often, these designs are used when research occurs in a controlled environment. While this project will not happen in a controlled environment, the primary investigator selected a quasi-experimental design since it is more cost-effective than an experimental project design (Schweizer et al., 2016). Furthermore, since data pre-project implementation and post-project implementation need to be collected and analyzed to explore the intervention’s impact, a quasi-experimental design is most appropriate.

A correlational design was considered but not appropriate for the project because the primary investigator is not seeking to understand the relationships occurring among the variables (Creswell & Creswell, 2017). This design is typically descriptive relying on a hypothesis (Leedy & Ormord, 2014). The primary investigator will not seek the relationships between the independent variable (MAP resources and education intervention) and the dependent variable (medication adherence rates).

The targeted population are home health patients ages 35 to 64 years old. The selected site serves approximately 100 patients annually, and 30 patients are diagnosed with Type II diabetes. The inclusion criteria are males and females diagnosed with Type II diabetes, oral medication or insulin, and home health patients. The exclusion criteria are individuals with language or cognitive deficits and diagnosed with Type I diabetes.

The data collection process will begin once approved by Grand Canyon University IRB. Recruitment will occur from informational flyers given to the patients during their home health visits with the providers. The nurses will answer any questions regarding the project’s risks, benefits, and purpose and be instructed that the participation is voluntary. The primary investigator will use a convenience sample because of the access to the participants. Comment by Author: Spell out the IRB

Data will be collected retrospectively four weeks prior to project implementation from the electronic medical records (Cradle Solutions) (medication adherence rates). In the last portion of the first week, the primary investigator will educate the healthcare providers regarding using the MAP resources. The staff will begin implementing the tool, and the post medication adherence rates will be assessed four weeks post-implementation. The primary investigator will document the data in a Microsoft Excel 2016 codebook developed by the primary investigator. Once completed, it will be exported into the SPSS-27 and analyzed using an independent t-test. A five-item demographic questionnaire will be used for descriptive statistics of the population. The survey will include (age, gender, years with Type II diabetes, oral or insulin, and education). Comment by Author: Cite. Refer to the Software Comment by Author: Don’t say the last portion. You must be specific

Pre-intervention and post-intervention data will be obtained via the project site’s EHR. The questions that will be analyzed are: (1) “Have you experienced any increase in thirst?” (2) “How often do you urinate?” (3) “Do you often feel fatigued even when doing little tasks?” and (4) “Do you experience blurred vision?” In addition to the aforementioned questions, home healthcare providers will ask the patient “Are you taking your medications?” Any information attained from the question and due to probing, observation of patient’s medications, and patient-related medication adherence will be documented in the project site’s EHR. The data will be analyzed using an independent t-test to determine the statistical significance.

Definition of Terms Comment by Author: You must follow the Template. Please look at the Template

Adherence Assessment Pad. The Adherence Assessment Pad is part of the MAP resources that explores answers via the patient perspectives. Using the Adherence Assessment Pad, nursing staff members will be able to explore the concerns of patients and adjust, pending further project team review, to the patient’s medication regimen (Starr & Sacks, 2010).

Diabetes For this project, Type II diabetes is the topic of exploration. It is described as an impairment of the body regulating and using glucose as a fuel source. Type II diabetes is a chronic condition where an excess amount of sugar is circulating in the blood stream (Mayo Clinic, 2019). Comment by Author: This must state Diabetes Type II

Home-based healthcare. The term home-based healthcare or home healthcare references the medical care that is provided to patients in the comfort of the patient’s home (Polonsky & Henry, 2016). Home-based healthcare services differ depending on a patient’s needs, diagnosis, and other factors.

Medication adherence. The term medication adherence references the extent to which a patient, caregiver, or home nurse follows the recommended guidelines on managing a medical condition (Ahmed et al., 2018).

My Medications List. Is a list that provides a breakdown of the patient’s medications, in an easy-to-follow chart format, thereby improving patient medication adherence (Starr & Sacks, 2010).

Questions to Ask Poster. Is a part of the MAP toolkit, which will be utilized during this project. When using the Questions to Ask Poster, home healthcare providers answer six questions to patients about medication adherence and medication knowledge. The questions that providers will answer include: (1) “Why do I need to take this medicine?,” (2) “Is there a less expensive medicine that would work was well?,” (3) “What are the side-effects and how can I deal with them?,” (4) “Can I stop taking any of my other medicines?,” (5) “Is it okay to take my medicine with over-the-counter drugs, herbs, or vitamins?,” and (6) “How can I remember to take my medicine?” Providers must answer all of the questions and should assume that individuals have no medication knowledge, thereby confirming that patients know and understand these critical answers (Starr & Sacks, 2010).

Assumptions, Limitations, Delimitations Comment by Author: This should be about 4-6 Paragraphs

As with all practice improvement projects, there are assumptions, limitations, and delimitations that must be addressed. For this project, the first assumption is that medical non-adherence among diabetes patients is caused by lacking medication-specific knowledge, inaccessibility to resources (i.e., physical, or financial), and inadequate information about the benefits of medications. The second assumption is that after the healthcare providers engage in dialogue with patients and thoroughly addressing their concerns, medication-related barriers will be minimized. The third assumption is that medication adherence will improve when patients are provided with a detailed schedule, which is patient-driven and provider-supported, using the MAP resource entitled “My Medications List.”

The limitations of the project are self-reporting of medication adherence by the patients. The second limitation is the healthcare organization being impacted by the COVID-19 pandemic. The new COVID-19 guidelines have affected the current healthcare delivery model. The third limitation is the location of the project and its setting. The fourth limitation is the time to conduct the project (four weeks). A longer timeframe would help the primary investigator analyze the site’s challenges, trends, and sustainability.

One project delimitation noted is the inclusion criteria of the participants. Patients with diabetes, ages 35 to 64, are included in the project. Since this project’s focus is to explore medication adherence among diabetes patients, which is a concern at the project site, it has narrowed the field to learn about other patients and their compliance issues. The second delimitation is the project being conducted in one urban area, located in the southeastern region of the United States, thereby impacting the generalizability of any findings.

Summary and Organization of the Remainder of the Project

The aging population continues to grow at an increasing rate in the United States, hence snowballing the number of individuals taking medications to manage their Type II diabetes. Kyarnstrom et al. (2017) emphasized that for Type II diabetics it is essential that proper and effective medication adherence be maintained. For home healthcare patients 45% of this population fail to maintain glycemic control < 7% (Polonsky & Henry, 2016). This is attributed to poor medication adherence (Polonsky & Henry, 2016). Healthcare providers are a critical component in making a difference by helping patients learn and maintain medication adherence.

The quality improvement project will use a quantitative methodology. The rationale for using this method is to collect numerical data that can be statistically analyzed. A quasi-experimental design will answer the clinical question to determine if the outcome impacted the medication adherence rates. The project will be guided by Orem’s self-care deficit theory and Diffusion of innovation model developed by Rogers (2003).

Chapter 1 provided detailed support for utilizing the MAP resources to improve medication adherence among diabetic patients of the project site. A quantitative, quasi-experimental design will be utilized to explore the impact of the MAP intervention on improving medication adherence among type II diabetes patients of the selected project site. The project site has a history of lacking medication adherence among diabetic patients, which is due to many factors (e.g., lacking medication knowledge, inadequate understanding of medication regimen requirements, etc.). Through utilizing the MAP resources, which foster communication among home healthcare providers and patients and equipping patients to use the My Medications List, medication adherence will likely improve. Comment by Author: This is not according to the Template. Please read the Template. This summary is not accurate. The last sentences are not necessary Comment by Author: According to the Chair, the chapters 1, 2 and 3 mentioned here are not necessary because I don’t understand why they are needed here.

Chapter 2 provides a detailed summary of the literature collected related to the project’s clinical question. Information about the theoretical framework and change model is detailed. The chapter comprises five sections, which highlight information about literature obtained from 2016 to 2021. The information presented provides readers in-depth knowledge and the importance of each chosen section.

Chapter 3 presents research methodology details, which the PI will employ. The information presented in the chapter includes the selected research design, the target population, and the sample size. Furthermore, data collection tools (specifically the MAP’s resources) and data analysis procedures are discussed. The reliability and validity of the project instruments are detailed. Finally, ethical considerations for collecting data are addressed.

Chapter 4 will present research findings, which will be analyzed using statistical methods. Results regarding the descriptive and inferential data analyses will be offered. Furthermore, a brief discussion of project-related findings will be provided. Information in Chapter 4 will be presented using graphics and tables. Chapter 5 will present conclusions and recommendations drawn from the project’s results. The impact of the findings, in terms of practical and theoretical knowledge, will be offered.

Chapter 2: Literature Review Comment by Author: The chair is saying that chapter 2 must be 22 pages Comment by Author: Chair will not review. Wants us to review the Template and understand what they asking for, then make corrections before resubmitting

Diabetes mellitus (DM) is a global epidemic in this era, and many diabetic patients comprise Type II diabetes mellitus (Rana et al., 2019). Medication adherence is a critical component and key determinant in obtaining therapeutic success and reducing diabetic complications (Rana et al., 2019). For Type II diabetic home health patients, this is vital in self-care and management of the disease. Unfortunately, approximately 30% to 50% of patients adhere to their medication regimen (Hennessey & Peters, 2019).

Diabetes is a lifestyle disease, which can be prevented or avoided by making lifestyle changes. Disease management can also occur through adhering to one’s prescribed medication regimen(s). Medication adherence is important since it can help to reduce the likelihood of diabetes-related challenges and complications.

In the United States (U.S.), the problem is associated with increased morbidity and mortality rates, with approximately 125,000 deaths and 10% of hospitalizations annually (Hennessey & Peters, 2019). Furthermore, medication nonadherence costs the U.S. healthcare systems roughly $100 billion to $317 billion yearly (Kini & Ho, 2018). The purpose of this quantitative quasi-experimental project is to determine to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks.

The primary investigator conducted a literature review utilizing peer-reviewed articles from 2016 to current. The inclusion criteria were articles written in English, topics specific to the project such as barriers to medication adherence, MAP resources, medication adherence, and Type II diabetes. The exclusion criteria were articles not written in English, more than six years, Type I diabetes, or involved children. Databases reviewed were PubMed, Google Scholar, CINAHL, Cochrane Library, EBSCOhost, and Grand Canyon University online library. The review revealed over 632,000 plus results; however, the primary investigator selected 30 articles for this chapter for this project.

One of the most problematic issues associated with home care for diabetes patients is adherence to medications. According to Bonney (2016), patients take their medication as prescribed only 50% of the time. Furthermore, patients are often reluctant to share medication compliance details, thereby resulting in health-related complications. This project hopes to enhance medication adherence, at the project site, which offers home-based care to diabetes patients. This project will also analyze the role of educating patients on medication adherence in improving their medication adherence.

Chapter 2 reintroduces the project’s subject matter, background, theoretical framework, and change model. Other segments include a review of literature on previous and current empirical research related to medication adherence in Type II diabetic home health patients. The chapter’s themes are related to patient-related factors (non-pharmacological and pharmacological lifestyle changes, patient beliefs). Socio-economic factors (medication costs, health literacy, lack of social support), health system factors (trust in the healthcare provider, complicated medication regimen), and interventions (patient education, motivational interviewing, and MAP resources).

Type II diabetes mellitus is at an epidemic proportion globally (Centers for Diseases and Prevention Control, 2020). The incidence of the disease will continue to rise from 382 million individuals to 417 million by 2035 (Polonsky & Henry, 2016; Rana et al., 2019). Healthcare experts are becoming increasingly concerned because of the costs, morbidity, and mortality rates linked with the disease (Polonsky & Henry, 2016). One of the elements contributing to the problem is poor medication adherence (Rana et al., 2019). This is particularly true in-home health Type II diabetic patients. Medication adherence in adults with chronic conditions is roughly between 30% to 50% (Kini & Ho, 2018; Neiman et al., 2017). Furthermore, the healthcare system associated with medication nonadherence is costing the U.S. healthcare system $100 billion to $317 billion annually (Rana et al., 2019).

As adults in this country age, many are afflicted with chronic diseases such as diabetes (Type II). It is one of the main reasons for admission to home health agencies (Sertbas et al., 2020; Wong et al., 2020). Home health agencies have been in existence for over 30 years (Choi et al., 2019). These organizations will continue to grow and impact medical advances and technology (Wong et al., 2020). Hence, there is a need for healthcare providers to become familiar with strategies and barriers linked with medication adherence for this population. Many home health patients have difficulty adhering to their medication regimens. They often express difficulty adhering to the regimens, which reinforces the critical role of home healthcare providers (Wong et al., 2020). This is partly due to them not having knowledge and education related to the disease and proper self-management (Wong et al., 2020).

Theoretical Foundations

Orem’s self-care deficit theory was selected to guide this quality improvement project. The theory was chosen because of its expectations that an individual must be self-reliant and responsible for their care (Orem, 1985). Dorothea Orem’s theory states self-care is an activity that a person engages in to maintain, restore, or enhance their health (Orem, 1985). The theory further states that nurses should not consider patients as inactive or sheer recipients of healthcare; instead, they should be considered reliable, responsible individuals who can make informed decisions and be active in their health care (Orem, 1985).

This theory describes nursing as an action between two or more individuals (RenpenningcN et al., 2003). Furthermore, it assumes that a successful patient with self-care understands it is a primary element in health prevention and illness (RenpenningcN et al., 2003). The theory fits the project because the healthcare providers are in supportive educational roles, which assists the patient when they are ready to learn or cannot complete a task without guidance (Orem, 1985). Also, the theory relates to healthcare providers assisting patients in their self-care and management to improve their function at a home level (RenpenningcN et al., 2003). The theory has been used in multiple studies regarding patients with chronic diseases (Borji et al., 2017; Afrasiabifar et al., 2016; Khademian et al., 2020).

The change model that will be used is the Diffusion of Innovation Model developed by Rogers (2003). There are five stages:

f. Knowledge or awareness- the individual is exposed to the change and lacks information.

g. Persuasion or interest-the individual becomes interested in the new idea and seeks more information.

h. Decision or evaluation- the individual mentally applies the idea to their present and future situation, hence deciding whether to try it.

i. Implementation or trial-the individual uses the idea fully.

j. Confirmation or adoption- the individual continues to use the idea in their everyday life and health practices.

Utilizing these methods will help the project advance by helping the healthcare providers to implement a standardized method in evaluating the patient’s medication-taking behaviors.

Review of the Literature

Diabetes is prevalent in the United States and globally (Rana et al., 2019). Medication adherence remains a challenge for Type II diabetic home health patients, which can impact their quality of life. Medication adherence among this population deserves a higher level of attention from healthcare providers. Healthcare professionals who understand medication adherence related to patient-related, socioeconomic, condition-related, health system factors, and interventions.

Medication adherence is a major healthcare challenge that impacts a patient’s quality of life. Researchers are constantly exploring ways to minimize medication non-adherence and continue to develop evidence-based strategies to improve medication adherence among patients. Medication non-adherence is a critical issue that deserves a higher level of attention. Understanding medication adherence-related barriers, addressing those barriers, and inspiring patients to change their actions/beliefs is an important step in improving health among patients.

At the selected project site, healthcare workers, who work directly with diabetic patients, believe it is critical to ensure medication adherence. Patients present with unique health-related challenges, thereby reinforcing the importance of minimizing health-related threats. Lacking medication adherence can mean the difference between life and death (Rathish et al., 2019). Adherence to antiretroviral therapy is considered a predictor of effective clinical outcomes among diabetic patients, which is one of the reasons why medication adherence is essential.

Patient-related Factors

The World Health Organization (2017) stated patient related factors encompass an individual’s resources, knowledge levels, belief system, perspectives, and expectations. These factors can vary dependent on the non-pharmacologic and pharmacologic lifestyle changes that the person maintains (Nduaguba et al., 2017). Type II diabetes management involves not just medication adherence but observance to monitoring diet and exercise, follow-up, and self-care (Nduaguba et al., 2017).

Medication adherence.

Medication adherence is a term that refers to one taking medication as prescribed by their healthcare practitioner (Ahmed et al., 2018). Healthcare providers must ensure that the prescriptions provided to patients are suitable to the individual’s conditions.

While medication adherence is important, there is a plethora of literature available that expresses the prevalence of medication non-adherence among patients. Various factors continue to impact medication adherence, which includes, but are not limited to, fear, costs, misunderstanding, too many medications, lack of symptoms, mistrust, worry, and depression (American Medical Association [AMA], 2020). To prevent medication non-adherence, providers can seek to understand the needs of patients and provide them with resources that can aid in overcoming non-adherence.

Ahmed et al. (2018) emphasized that the quality of healthcare can be influenced by the body’s ability to respond to the treatment. A study conducted by Rana et al. (2019) was related to exploring medication adherence to prescribed treatments as a crucial factor for hospitalized Type II diabetic patients in a Bangladesh hospital. The quantitative, descriptive cross-sectional study involved 112 Type II diabetic patients recruited from medical and endocrinology wards. Much of the sample size age was 57.46, 60.7% were male and married. The patient’s medication adherence was measured using the 7-item MCQ scale modified by Ahmad et al. (2013). Data were analyzed using SPSS-21. Descriptive statistics were used to measure the participants’ demographics. An independent sample t-test and one-way ANOVA with post hoc comparisons were used to evaluate the relationships between the variables (p =.05).

The results from the Rana et al. (2019) study showed 72.3% of the participants forgot to take their medications, 96.4% chose not to take the medication or miss a dose when feeling better. Most of the patients, 81.3%, did not take their medications with them when traveling. The mean scores of the MCQ were 26.46 (SD =1.58). The study’s results concluded that the level of medication adherence among Type II diabetic patients was suboptimal (Rana et al., 2019). The authors recommended that more attention needed to be given to varied age groups related to medication adherence.

Lee et al. (2017) conducted a quantitative study to determine the medication adherence among Type II diabetic patients in an Asian community. This cross-sectional study involved 382 Asian participants from a primary outpatient care clinic in Singapore. The patient’s medication adherence was measured using a five-item Medication adherence report scale (MARS-5). A low medication adherence score was <25. The sample size was predominately female, with a mean age of 62 years. Using univariate analysis, the results showed 57% of the participants had a low medication adherence score, which was attributed to them being married or widowed, taking fewer than four medications daily, and poor glucose control. The study concluded that younger patients were susceptible to low medication adherence scores (Lee et al., 2017).

Both studies involved participants of Oriental descent and had an adequate sample size. Although the studies were conducted in different settings (primary care and hospital), the results demonstrated a need for healthcare providers to focus on different age groups and their reasons for not adhering to their medication regimen. The studies were cross-sectional, which indicated the authors were unable to evaluate the participant’s habits and trends. This could have changed if they could assist the patients with barriers they faced during the studies.

To handle the issue of medication adherence among the diabetic patients who have had an issue with adherence to medication needs to come up with a variety of strategies that have been attained from scholarly reviews as well as journals for purposes of well researched data on the concept. Appropriate types of medications are usually considered to be the identified cornerstone regarding the prevention as well as disease treatment yet according to numerous research carried out, there is solely about half of the individual patients who adhere to the instructions of their prescribed medication (Bosworth, 2015). This usually causes a common as well as costly public health-associated challenge especially for the healthcare system in the US.

Since the aspect and issue of inappropriate as well as inefficient medication adherence are considered to be a complex change with a variety of contributing causes, there is no universal solution (Rodriguez-Saldana, 2019). The following theme breaks down into three subcategories that form the basis of the sub-themes associated with this theme. The sub-themes are used to offer a comprehensive analysis of all the vital types of interventions that are effective in enhancing medication adherence among diabetic patients but are also considered to be potentially scalable, that is they are easy to implement in any given scenario and population (Bosworth, 2015). Key traits that make these interventions effective are discussed throughout the DPI. The information offered under each sub-theme is vital to explain, as it can result in enhanced medication adherence through the implementation of documented and cost-effective solutions.

Non-pharmacological indicators.

There are many medications used for the effective management of diabetes (Raveendran et al., 2018). Effective non-pharmacological therapy should be explored with all Type II diabetics. The measures could include nutrition and exercise. Nutrition interventions are critical in a person with diabetes maintaining an optimal glucose level (80-120mg). The dietary pattern that must be encouraged is consuming fruits, vegetables, low-fat dairy foods, whole grains, and minimal red meat (Asif, 2014).

Pharmacological factors.

Type II diabetic patients typically take multiple medications for their condition and other comorbidities (Kirkman et al., 2015). Following one’s medication regimen and treatment improves patient outcomes, reduces healthcare costs, hospitalizations, and mortality (Kirkman et al., 2015). A retrospective study conducted by Kirkman et al. (2015) determined patient, medication, and prescriber factors that influenced diabetic patients and medication adherence. A sample size of 200,000 participants (from 50 states, including the Virgin Islands) was extracted from a pharmacy database (Medco Health Solutions). The participants’ eligibility was based on the medication, benefits, and prescription history. Each patient was followed for one year from the medication date to post-implementation of the study.

Medication adherence was described as a medication possession ratio > 0.8 (Kirkman et al., 2015). Logistic regression analyses were conducted to evaluate factors independently linked with adherence. The results demonstrated that 69% of the participants were adherent. Other findings illuminated that adherence was associated with one’s age (older), male, higher education and income, and the use of the mail order versus retail pharmacies. Individuals with a new diagnosis of diabetes were less likely to be compliant with their medication regimen.

The authors concluded that demographic, clinical, and system-level factors influenced the participants’ medication adherence regimen (Kirkman et al., 2015). The authors emphasized that younger individuals, newly diagnosed and had minimal medications to take, were at a higher risk for non-adherence. Individuals who used mail-order pharmacies resulted in higher medication adherence due to lower out-of-pocket costs (Kirkman et al., 2015).

Patient’s belief system.

One’s culture influences a patient’s beliefs regarding medications, which ultimately affects their medication adherence (Lemay et al., 2018). This remains a challenge for healthcare providers in helping patients to understand the significance of medication adherence (Shahin et al., 2019). A study conducted by Shanin et al. (2019) used a systematic review to determine the importance of an individual’s cultural belief influenced medication adherence. A total of 2,646 articles were selected from various databases such as PubMed, CINAHL, EMBASE, and PsychINFO. Twenty-five of them met the inclusion criteria. The studies focus on diabetes or hypertension.

The study results from Shanin et al. (2019) revealed personal and cultural factors linked with medication adherence. Ten articles (40%) demonstrated an individual’s perception of the illness, five (20%) were affiliated with health literacy, four (16%) cultural beliefs, three (12%) self-efficacy, and five (20%) knowledge illness (Shanin et al., 2019). Shanin et al. (2019) study concluded that one’s cultural influences affect their perception of the importance of medication adherence. Healthcare providers must understand their patients’ pre-existing perspectives of diabetes before offering new information. This is an opportunity for healthcare professionals and patients to have a dialogue to diffuse misconceptions related to the patient’s perceptions. The authors suggested that future research should identify the religious beliefs associated with disease knowledge and medication adherence.

Strengthening the Relationships with Patients

Patients usually consider their healthcare providers (HCPs) as the most dependable source of data regarding their health condition and treatment. Patients are highly likely to effectively follow the treatment plan when they are involved in having a good relationship with their HCP due to the confidence and trust that has been built over time. Relationship building in healthcare is a vital aspect in the day to day lives of healthcare practitioners due to the nature of their job, which necessitates that they maintain long-term relationships with their patients for enhanced medication and treatment outcomes (Heston, 2018).

Trust is critical to developing, specifically since patients can experience improve health-related outcomes when they value relationships with their HCPs. Patients who have trust in their HCP often believe that their provider has a high level of competence and truly cares about their health-related outcomes (Heston, 2018). Mistrust develops when the patients attain unrealistic, inconsiderate, or insensitive advice from their HCPs, as well as feel emotional distance from them.

Socioeconomic Factors

Socioeconomic-related factors that affect medication adherence include one’s location of residence, medical costs of treatment, and finances (Yeam et al., 2018). Other factors that could influence medication adherence are low health literacy, education level, lack of social support, living conditions, and medication costs (Hennessey & Peters, 2019). Health care providers must conduct a thorough assessment before providing a patient the prescription and consider any of the factors as mentioned above.

Medication costs.

Kang et al. (2018) conducted a quantitative, longitudinal study to examine factors that affected cost-related medication nonadherence. Cost-related medication nonadherence (CRMN) is defined as taking medication then indicated or prescribed due to costs (Kang et al., 2018). Unknown sample size noted, but the Behavioral Risk Factor Surveillance System data for 2013–2014 was used to identify individuals with diabetes and their CRMN. Weighted multivariable logistic regressions were used, and analyses were conducted using the Survey suite of programs in Stata SE version 14. The survey weights were used to obtain population-level estimates and subpopulation methods to estimate standard errors for the subgroup’s analyses (Kang et al., 2018).

The results demonstrated that CRMN among American adults was 16.5% (Kang et al., 2018). Individuals with an annual income of < $50k and without health insurance had the highest rates of CRMN. Insulin users had a 1.24 times higher risk of CRN than those not using insulin. Factors influencing CRMN were diabetes care and lifestyle factors, depression, arthritis, and asthma (Kang et al., 2018). Health insurance was the most significant factor for the participants < 65 years of age and depression for respondents > 65 years (Kang et al., 2018).

The authors (Kang et al., 2018) concluded that one’s annual income and health insurance status were the most significant factors for younger adults, while depression was for older adults > 65 years. When the younger and older groups were combined, it showed the largest impact of CRMN affecting individuals < 55years of age and having higher rates of non-medication adherence (Kang et al., 2018). Recommendations were for healthcare organizations to develop policies, resources, and support systems that address the factors to help improve CRMN.

Health literacy.

Health literacy is described as one’s ability to obtain, communicate, process, and comprehend basic health information and navigate health services to make an informed decision (Sawkin et al., 2015). Medication adherence is broadly identified as a patient’s ability to follow a prescribed medical treatment (Sawkin et al., 2015). Researchers Glanz et al. (2015) have explored the impact of low health literacy rates on patient compliance with medications and health-related advice. The authors stated that approximately 35% of American adults possess basic or below basic health literacy levels (Glanz et al., 2015). Chima et al. (2020) conducted a systematic review to evaluate the impact of health literacy and medication adherence. Literature searches were performed using Ovid Medline, CINAHL, EMBASE, Scopus, and PsycInfo. The inclusion criteria for the articles were conducted in the United States, 18 years or older with a diagnosis of Type I or II diabetes, medication adherence was an outcome variable, quantifiable measure reported, and was a full text journal article. Articles were graded using Joanna Briggs Institute Critical Appraisal Checklists, which is appropriate for the respective study designs identified. Thirteen articles were retained in the review, most of which used a cross-sectional design.

The results demonstrated four of the 11 studies found a positive association between health literacy and medication adherence (Chima et al., 2020). Two of the four studies had methodological shortcomings. The authors concluded there was some evidence that health literacy is linked with medication adherence among diabetic adults in the United States. Recommendation for future research to design and execute longitudinal studies to determine a deeper relationship between the variables (health literacy and medication adherence (Chima et al., 2020).

Given inadequate literacy rates, among members of the general population, world practitioners continue to create unique strategies that can be used to reduce lacking health adherence among patients with diabetes. Improved literacy is a theme that should be of the utmost priority, specifically since it creates the foundation for long-term sustained profitability. Furthermore, as patients can understand the importance of medication compliance, adherence to medication regimens improves (Glanz et al., 2015).

Using universally implemented and published resources that can improve medication adherence is important. Tools and resources can be utilized by HCPs to identify patients who are not taking their prescribed medications. Prescriptions need to be taken seriously for exceptional results and for the continued well-being of patients who have critical illnesses like diabetes.

The use of simple language by HCPs, as well as by medication manufacturers, can encourage providers to meet patients where they are and utilize teach-back techniques to ensure a patient’s understanding of his/her prescribed medication regimen. Teach-back methods have been utilized to enhance medication adherence among many types of non-adhering patients. Most of the time people opt to not take their medication as they cannot read all the instructions written on the medicine and are afraid that they will die, especially in the cases that they mistake those drugs for poison or some drug that may look like a famous poison causing death. This is a key issue that has left most of the people victims of non-adherence (National Academies of Sciences, Engineering, and Medicine, 2018).

Huang et al. (2020) conducted a cross-sectional study aimed to identify patient factors linked with diabetes medication adherence and health literacy levels. One hundred and seventy-five participants were involved in the study and recruited from two family medical clinics. All the participants were over the age of 20, diagnosed with Type II diabetes, taken one oral diabetic medication, and understood English. The authors evaluated the participants’ health literacy levels using the Newest Vital Sign, a six-item questionnaire, and an eight-item Morisky Medication Adherence Scale.

The results showed a self-reported status of (β = 0.17, p = 0.015) and medication self-efficacy (β = 0.53, p, 0.001), which were positively associated with diabetes and medication adherence (Huang et al., 2020). Health literacy was neither associated with diabetes medication adherence (β = −0.04, p = 0.586). The authors concluded that health literacy measured using the Newest Vital Sign did not correlate with medication adherence or glucose control among Type II diabetics. They recommended that healthcare clinics develop interventions to improve their patients’ self-efficacy of medication to improve the medication adherence rates (Huang et al., 2020).

Reading instructions and making a patient understand what is written on a medicine bottle or package should never be taken for granted as it is key for determining how patients will effectively or ineffectively adhere to the given drugs for treatment and disease control purposes. For the medical practitioner to be aware and sure that what they have explained to the patients has been delivered safely and appropriately, there is the need for a verification test. The patients as well as their identified support individuals need to be asked to explain in their own words stating what they have understood from everything the practitioner has told them regarding their health, along with drug management and intake. This teaching back method is vital in offering additional data on the key topic of interest; thus, it should be used often.

Concerns associated with the issues of side effects can be challenges to medication regimen adherence, especially when the given advantages associated with taking the medication are not properly comprehended. To minimize the potential concerns that are associated with the side effects of drugs, since this can be identified as one of the reasons why patients may opt to not adhere to medications in fear that they will experience the side effects and be greatly inconvenienced, there is the need for HCPs to offer the relevant data regarding the common types of side effects when they are in the prescription process.

There have been issues of people and patients dying or experiencing very negative and disturbing side effects when it comes to them taking the medication prescribed by their doctors. These cases have always been used as examples to explain the reason why people have been reluctant to take medications for prolonged periods. When an individual has a critical illness, it is not uncommon that he/she needs to take the prescribed medication for a long period, as this can result in improved medication efficiency. Lacking understanding of medication-related details has caused patients to withdraw from their prescribed medication regimen, which is due to lacking knowledge and prolonged side effect issues that are associated with their medication (Institute of Medicine [IOM], 2016). For example, when offering metformin, to enable adherence to the drug there is a need to inform patients that are suffering from diarrhea during their time of prescription to anticipate that the loose bowel issues will be over in about a week if the drug is continued. It is also vital to offer brief explanations about medication side effects and benefits due to time limitations. If a patient cannot have additional time with his/her provider, then other members of the health care team should aid in answering their questions and provide additional education. Education can be in the form of printed handouts, websites, or a teaching module that should be readily available for use with the identified patient.

Tools/Support Strategies for Improving Self-Efficacy and Medication Adherence

Using tools and instruments that are considered effective and appropriate is vital in supporting adherence in different ways and in achieving self-efficacy among the various patients. Positive family and social support are considered to be vital aspects associated with adherence to the issue of diabetes management (Rodríguez-Saldana, 2019). The engagement of family members can enhance self-care activities for patients suffering from diabetes, including eating effective and healthy foods, keeping fit, monitoring blood glucose, and adhering to medication.

A web-based portal is an innovative resource that can be used to assist patients. This web-based portal can improve medication reconciliation processes among patients and providers. The web-based portal can help patients with various regimens navigate challenges. Furthermore, this medication information, available through the portal can help individuals understand medication requirements, as the portal often helps to clarify and verify inaccuracies. The web portal aims to enhance medication adherence and prevent the improved use of the medication (Forman & Shahidullah, 2018).

When patients can verify information in their electronic medical records to ensure proper medication adherence, this can enhance patient well-being. The EMR provides an accurate list of a patient’s medications and provides detailed medication information (e.g., type of drug, what the drug is used to treat, frequency of drug use, etc.). Also, the use of screening tests is vital in understanding how well patients are taking their drugs. If there is no consistency in medication-taking then motivation aspects should be utilized to enhance adherence (Eskola, Waisanen, Viik, & Hyttinen, 2018).

Diabetes Care Concepts

When dealing with patients who are reluctant to take their medications, various care concepts must be understood. Through improving one’s literacy, knowledge about the medication, and offering patient-specific details, enhanced outcomes can occur. Improved medication adherence can result in enhanced patient outcomes, thereby reinforcing positive long-term health-related outcomes. The following themes noted below, provided comprehensive knowledge, as well as in-depth illustrations, about the distinct components associated with clinical control for patients who have been diagnosed with diabetes. The review offers effective clinical practice guidelines, which must be considered, to enhance population health. It is important to note that to ensure identified optimal outcomes (discussed below), individualized patient care is critical.

Patient-Centeredness. Patient-centeredness entails ensuring that all the identified interventions described in the first theme are focused on the individual patient who is being helped to effectively adhere to the given medication during home care settings. Patients who have been diagnosed with various critical illnesses and have been asked to go home for home-based care have been associated with poor adherence to the medications they are given when they are discharged from the hospital (Steinberg & Miller, 2015).

Practice recommendations, whether they are focused on evidence or expert opinion, are intended to offer the desired guidance on an overall approach to care (da Costa, van Mil, & Alvarez-Risco, 2018). The science, as well as the art associated with medicine, usually come together when the identified clinician is experiencing or has experienced some sort of situation whereby, they have to make treatment recommendations for any patient who would be considered to not have effectively met the eligibility criteria for the studies on which the given guidelines were based.

Diabetes Across the Life Span. An increment in the identified proportion associated with patients that suffer from diabetes is usually considered to be mostly adults (Balogh, Miller, & Ball, 2015). For the less salutary reasons, the identified incidences associated with type II diabetes are considered to be highly increasing in the creating in the children as well as the young adults. Patients that possess type II diabetes as well as those that have type I diabetes are considered to have good lives even in their older age, which is regarded as a stage of life whereby there is minimal evidence from the identified clinical traits to be used in the guidance of therapy (Bonney, 2016). All these toes of demographic alterations are usually involved in highlighting another key challenge to high-quality diabetic patient care. In this case, the identified need is usually considered to be the enhancement of the coordination between clinical teams as well as patients in the effective transitioning via the dysfunction phases enticed in life span (Corcora & Roberts, 2015).

Advocacy for Individuals with Diabetes. Advocacy is a vital aspect in healthcare since it addresses the needs of the patient who need the utmost help and care, thereby allowing them to go back to their previous health state (D’Onofrio, Sancarlo, & Greco, 2018). Advocacy is an aspect that can be referred to as active support, as well as engagement, that aims to effectively develop a cause as well as a policy (Mollaoglu, 2018). Furthermore, advocacy is usually needed to enhance the lives of individuals suffering from diabetes. The various issues that diabetic patients experience, such as obesity, physical inactivity, and societal challenges reinforce the need for advocacy (Firstenberg & Stanislaw, 2017).

In summary, health literacy was chosen because the level of health literacy is high among Americans. This contributes significantly to the challenges healthcare providers face in caring for Type II diabetic patients. The subject emphasizes the need for healthcare professionals to assess their patient’s health literacy abilities and educate them according to their level. An educated patient will better understand what actions to take and improve their quality of life.

Summary

The prevalence of Type II diabetes is affecting one in ten Americans (Ahmed et al., 2018). The disease is expected to continue rising higher by 2030 (Lin et al., 2018). Medication adherence for Type II diabetic home health patients is critical in decreasing the poor patient outcomes associated with the disease. Medication adherence with Type II diabetic patients remains a challenge for many healthcare professionals. Education for the healthcare providers and the patients can make a difference in this population’s lives.

Chapter 2 discussed reintroduced the topic and presented the theoretical framework and change model to guide the project. Other sections include the literature review related to patient-related, socio-economic, and health system factors.

A summary of the chapter was provided with an introductory sentence that previews Chapter 3.

Chapter 3 will reinstate the select topic. Other segments will present project methodology, design, population, and sample selection. A discussion of the MAP resource and the electronic medical record. The validity and reliability of the instrument was demonstrated, data collection and data analysis procedures, potential bias. The last few sections discuss the ethical considerations, limitations, and a summary that leads into Chapter 4.

 

Chapter 3: Methodology

Medication adherence is a critical component in minimizing adverse patient-related outcomes among individuals with chronic illnesses (Type II diabetic patients). Ahmed et al. (2018) stated medication adherence for this quality improvement project refers to the extent to which a home healthcare patient can correctly take their medications in the absence of their health care providers. Medication adherence requires an individual to adhere and comply with all the medical instructions provided (Bellou et al., 2018).

Type II diabetes affects one in ten Americans (Ahmed et al., 2018). Furthermore, due to the increase in older-aged adults and the rising prevalence of the disease, it is expected to elevate higher by 2030 (Lin et al., 2018). The home health services continue to grow, hence illuminating the need for education regarding medication adherence. Roughly 45% of the patients cannot maintain their glucose levels (Polonsky & Henry, 2016). Poor medication adherence is associated with higher financial obligations for the patient, hospital, and insurance companies. Polonsky and Henry (2016) emphasized the adverse outcomes cause frequent hospitalizations and lower quality of life for patients and their families.

Chapter 3 will reinstate the selected topic. Other sectors include the statement of the problem, clinical question, project methodology (quantitative), and project design (quasi-experimental). The chapter describes the population and sample selection, the instrumentation (MAP resources), validity, reliability, and data collection procedures. The last few segments include the data analysis procedures, potential bias, ethical considerations, limitations, and a summary.

Statement of the Problem

It is not known if or to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The targeted population is Type II diabetic patients in an urban healthcare facility in urban Texas. In collaboration with the stakeholders, it was noted that medication adherence among the patients was lacking. The information will be obtained from the electronic medical records (Cradle Solutions), which showed that ten percent of the diabetic patients were not adhering to their medication regimen.

Factors that influence poor medication adherence are numerous and include poor knowledge or awareness of the disease, medication costs, and lack of understanding of the medication treatment, which reinforced the project’s purpose (Heath, 2019; Sharma et al., 2020). Healthcare providers play an essential role in assisting patients with medication adherence. The primary investigator will introduce a standardized strategy for the facility’s healthcare providers to assess the patients’ medication adherence using MAP resources (Starr & Sacks, 2010).

Using a standardized method will help to solve the facility’s problem with medication adherence rates. It will also help improve the healthcare providers’ knowledge levels and awareness regarding the barriers associated with medication adherence. Complying with the new guidelines developed by the Centers for Disease Control and Prevention (2020) could help patients control their glucose levels, minimize healthcare costs, hospitalizations, and potential infections.

Clinical Question

The clinical question that will direct the primary investigator’s answer is: To what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The independent variable is the MAP resources and educational intervention. The dependent variable is the medication adherence rates.

The data collection process will not begin before approval is received by Grand Canyon University IRB. The primary investigator will develop informational flyers for the nurses to give their patients during their home health visits. The staff will answer any questions related to the project regarding risks, benefits, and purpose while instructing that participation is voluntary. A convenience sample will be used because of the easy access to the participants for the primary investigator.

The primary investigator will collect data retrospectively (four weeks) prior to implementation of the project. The data will be collected from the electronic medical records using Cradle Solutions for the impact of the MAP resources and medication adherence rates. In the first week, the primary investigator will educate the staff to use the MAP resources. Once the staff begins to implement the tool, post-medication rates will be assessed post-four weeks. The data will be inserted into a Microsoft Excel 2016 codebook developed by the primary investigator. It will then be exported into SPSS-27 and analyzed by using an independent t-test. The five-item demographic survey will collect the descriptive statistics of the home healthcare patients. The questionnaire comprises (age, gender, years with Type II diabetes, oral or insulin, and education).

Project Methodology

A quantitative methodology will be used for this quality improvement project. According to Creswell and Creswell (2017), a quantitative methodology is appropriate for projects that use data in its numerical form. For this project, the data will be presented using figures, graphs, charts, and tables. This will allow the readers to compare the medication adherence rates pre-implementation and post-implementation of the project.

A qualitative methodology was considered but not used, although they are beneficial. It explores the patient’s experiences, perspectives, and lived experiences regarding a phenomenon (Creswell & Creswell, 2017). Data collected using this methodology is semi-structured interviews, one-on-one interviews, and focus groups (Creswell & Creswell, 2017). The primary investigator aims not to understand the home health participants’ emotions, behaviors, or experiences related to medication adherence.

A quantitative methodology supports the project because it will permit the primary investigator to remain objective in providing the project’s findings (Leedy & Ormord, 2014). Furthermore, the methodology allows the primary investigator to summarize the data that could support generalizations for a larger or similar population. The methodology is less costly with easy replication for future quality improvement projects to obtain the same results.

Project Design

Quasi-experimental designs are utilized to compare data before and post-implementation of an intervention (Price et al., 2017). The design is frequently used in a controlled environment. For this project, the design was chosen because it is cost-effective versus an experimental project design (Schweizer et al., 2016). A quasi-experimental design allows the primary investigator to analyze the impact of MAP resources on medication adherence rates.

An experimental design was not considered because the primary investigator is not seeking to conduct the project under a controlled environment (Leedy & Ormrod, 2014). This design observes the independent variable (MAP resources) and the dependent variable (medication nonadherence rates). It is a simple test that is performed in various physical and natural settings (Leedy & Ormrod, 2014).

A correlational design was considered but not appropriate for the project because the primary investigator is not seeking to understand the relationships occurring among the variables (Creswell & Creswell, 2017). This design is typically descriptive relying on a hypothesis (Leedy & Ormord, 2014). The primary investigator will not seek the relationships between the independent variable (MAP resources and education intervention) and the dependent variable (medication adherence rates).

The targeted population are home health patients ages 35 to 64 years old. The selected site serves approximately 100 patients annually, and 30 patients are diagnosed with Type II diabetes. The inclusion criteria are males and females diagnosed with Type II diabetes, oral medication or insulin, and home health patients. The exclusion criteria are individuals with language or cognitive deficits and diagnosed with Type I diabetes. Five registered nurses will help to implement the project. They are individuals who work full-time and have been employed over a year.

The data collection process will begin once approved by Grand Canyon University IRB. Recruitment will occur from informational flyers given to the patients during their home health visits with the providers. The nurses will answer any questions regarding the project’s risks, benefits, and purpose and be instructed that the participation is voluntary. The primary investigator will use a convenience sample because of the access to the participants.

Data will be collected retrospectively four weeks prior to project implementation from the electronic medical records (Cradle Solutions) (medication adherence rates). In the last portion of the first week, the primary investigator will educate the healthcare providers regarding using the MAP resources. The staff will begin implementing the tool, and the post medication adherence rates will be assessed four weeks post-implementation. The primary investigator will document the data in a Microsoft Excel 2016 codebook developed by the primary investigator. Once completed, it will be exported into the SPSS-27 and analyzed using an independent t-test. A five-item demographic questionnaire will be used for descriptive statistics of the population. The survey will include (age, gender, years with Type II diabetes, oral or insulin, and education).

Pre-intervention and post-intervention data will be obtained using the MAP resources. The questions that will be analyzed are: (1) “Have you experienced any increase in thirst?” (2) “How often do you urinate?” (3) “Do you often feel fatigued even when doing little tasks?” and (4) “Do you experience blurred vision?” In addition to the questions, home healthcare providers will ask the patient “Are you taking your medications?” Any information attained from the question and due to probing, observation of patient’s medications, and patient-related medication adherence will be documented in the project site’s EHR. The data will be analyzed using an independent t-test to determine the statistical significance.

The electronic medical record that will be used to collect data is Cradle Solutions a software for home health companies. It serves the specialized needs of home health care providers that give a web-based point-of-contact information entry and management (Cradle Solution, 2021). It is compliant with HIPPA security features for billing, reporting, administrating, and managing patient information (Cradle Solution, 2021). Liss et al. (2020) emphasized that electronic health records can be used for quality measures as a snapshot or calendar year. The primary investigator will obtain the measurement of the medication adherence rates and align it with new protocols and guidelines developed by the facility.

Population and Sample Selection

The specific population that will be addressed are home health patients ages 35 to 64 years old. The selected site serves approximately 100 patients annually, and 30 patients are diagnosed with Type II diabetes. A G* power analysis was conducted using version 3.1.9.2, the alpha measure of 0.05, effect size of 0.5, power of 80% to calculate the lowest sample size needed, which was (n=34). The inclusion criteria are males and females diagnosed with Type II diabetes, oral medication or insulin, and home health patients. The exclusion criteria are individuals with language or cognitive deficits and diagnosed with Type I diabetes. Five staff nurses will help to implement the quality improvement project. They are individuals who are registered nurses, work full-time, and have been employed with the facility over one year, and have access to Cradle Solution EHR system.

The geographical location of the project is in a metropolitan area of Houston, Texas. The County statistics show that approximately 17.6% of the population have Type II diabetes (Houston, 2021). During 2016-2018, 20.2% of the population was hospitalized due to diabetic complications (Houston, 2021). There are over 700 000 Medicare participants in a three-county radius, which is higher than the national average (Understanding Houston, 2021). Data further showed that preventable hospital stays occur in older adults 65 and above (Understanding Houston, 2021). This suggested a trend to overuse the hospitals as a primary source of care (Understanding Houston, 2021).

The informed consent process will consist of the nurses explaining the project’s purpose, risks, and benefits. The participants will be informed that participation is voluntary and can withdraw without repercussions to their professional or personal lives. No compensation will be provided to the participants in the project. The participants’ identities and privacy will be protected throughout the project by the primary investigator not using their names or other identifiable information. The participants will be assigned a random number for security purposes. The primary investigator will abide by the University’s IRB guidelines and the Belmont Report (justice, respect for persons, and beneficence) (U.S. Department of Health & Human Services, 2018).

Hard copies of the data will be stored on a flash drive and kept in the primary investigator’s home office (in a locked file cabinet). The data files will be kept on the primary investigator’s laptop, which is digitally protected. The data will be stored for three years according to Grand Canyon University procedures (June 2023). Once the project is completed and the requirements met, the primary investigator will destroy the information using Iron Mountain shredding services and software ERASER on the laptop.

Instrumentation or Sources of Data

The instruments to be used in the project are the MAP Toolkit and Training Guide resources, which includes (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list. The questions to ask poster encourages patients to ask the provider about their medication. For this project, the nurses will review the medications with the Type II diabetic patients. Six questions will be asked (1) Why do I need to take this medicine, (2) Is there a less expensive medicine that would work as well, (3) What are the side-effects and how can I deal with them, (4) Can I stop taking any of my medicines, (5) Is it okay to take my medicine with over the counter drugs, herbs, or vitamins, and (6) How can I remember to take my medicine?

The second section, the Adherence assessment pad, explores answers the barriers to the patient’s maintaining medication adherence. The questions include (1) makes me feel sick, (2) I cannot remember, (3) too many pills, (4) costs, (5) nothing, and (6) other.

The third component is my medication list. It provides detailed information in chart form, which is discussed between the patient and the healthcare provider. It comprises of (1) name and doses of my medicine, (2) this medication is for my diabetes, (3) when do I take and how much (options include: morning, noon, evening, or bedtime), and (4) I will remember to take my medicine (a blank that will be filled in).

The source of data for this project is the electronic medical record. The facility uses Cradle Solutions, software for home health companies. It serves the specialized needs of home health care providers that give a web-based point-of-contact information entry and management (Cradle Solution, 2021). It is compliant with HIPPA security features for billing, reporting, administrating, and managing patient information (Cradle Solution, 2021). Liss et al. (2020) emphasized that electronic health records can be used for quality measures as a snapshot or calendar year. The primary investigator will measure the medication adherence rates and align them with new protocols and guidelines developed by the facility.

Validity

Validity conveys how accurately a method is measured (Creswell & Creswell, 2018). If the method measures what it should and the findings correspond closely, it is considered valid. There are four types of validity are constructs, content, face, and criterion (Creswell & Creswell, 2018). For this project, construct and face validity is applicable to the instrument. A group of professionals developed the tool, which consisted of physicians, pharmacists, nurses, and medical assistants (Starr & Sacks, 2010). It was based on their years of work experience in their perspective fields. The toolkit’s improvements were adjusted and in alignment with the CDC and other healthcare governing bodies.

Reliability

Reliability refers to the consistency of instrument measuring something (Creswell & Creswell, 2018). If the same results occur regularly by using the same procedures under the same conditions, the measurement is reliable (Creswell & Creswell, 2018). For this project, the MAP toolkit reliability was confirmed by inter-rater reliability (Starr & Sacks, 2010). The observers noted the same results associated with using the instrument, which aligned with the literature findings regarding collecting data for medication adherence rates.

A study conducted by Harrell (2017), occurred over 90 days, where weekly medication adherence rates were assessed. Seventy-eight percent of the patients prior to the study’s implementation did not adhere to their prescribed medication regimen. Post three-months of the project, 56% of the patients improved regarding medication adherence rates. For this project, test-rest reliability will be noted, because the nurses will be using the MAP toolkit over time (two different times) (Creswell & Creswell, 2018).

Data Collection Procedures

The data collection process will begin once approved by Grand Canyon University IRB. Recruitment will occur from informational flyers given to the patients during their home health visits with the providers. The nurses will answer any questions regarding the project’s risks, benefits, and purpose and be instructed that the participation is voluntary. The primary investigator will use a convenience sample because of the access to the participants.

Other recruitment strategies include the primary investigator reaching out to the nurses at the project site to assist in the educational intervention. The training sessions will be offered twice so that the nurses working on the weekends can participate. The primary investigator will offer two 45-minute Zoom training sessions. During these sessions, the primary investigator will provide information regarding using the MAP toolkit and resources. A 10-minute PowerPoint presentation will be included during the 45-minute training session, along with a MAP toolkit binder for each participant.

The primary investigator will work with the information technology department, who will ensure that the three MAP resources are inserted into the Cradle Solution documentation software. During week one, the nurses will provide the patients with informed consent, answer questions related to the project, a five-item demographic survey, and a pre-MAP survey. The second to fourth week, the nurses will examine the patient’s medication list and adherence (ten minutes). Each week the nurses will record the medication adherence information in the patient’s electronic medical record.

Week four, all input by the nursing staff will be completed. If the patient expresses, they have not adhered to the medication regimen; it will be recorded in the system. Post scores will be collected by the primary investigator regarding the medication adherence rates. The results will be entered into the Microsoft Excel 2016 codebook developed by the primary investigator. The data will be exported into SPSS-27 be analyzed using an independent t-test.

Data Analysis Procedures

The primary investigator will collect retrospective data four weeks prior implementation regarding medication adherence rates. Descriptive statistics will use to determine the demographics of the participants, which will be illustrated using graphs, tables, and figures. The pre-and post-intervention scores will be entered into the SPSS-27 for analysis. The data will be evaluated for missing data, which will be assigned -99. Pre- and post-surveys missing data will be discarded from the project.

The clinical question that is guiding the project is:

To what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The independent variable is the MAP resources and education intervention. The dependent variable is the medication adherence rates. The primary investigator will answer the clinical question by evaluating the mean scores of the pre-and-post implementation scores from the MAP resources using an independent t-test (parametric test). This statistical test compares two groups to determine the statistical significance (p <0.5). The Microsoft Excel spreadsheet (2016) and exported into SPSS-27 for the final analysis.

Potential Bias and Mitigation

Bias is described as any tendency that prevents impartial consideration of a clinical question (Pannucci & Wilkins, 2010). It can occur at any stage of the research, study design, data collection or analysis, and publication (Pannucci & Wilkins, 2010). One potential bias is related to the selection process. The primary investigator will avoid bias by selecting individuals and using strict inclusion and exclusion criteria previously developed for the project. The participants will originate from the specified population.

The second bias is related to recall bias, a systematic error that occurs when the participants do not remember prior events or experiences accurately (Creswell & Creswell, 2018). The project could be affected because the participants are self-reporting to the nurses using the MAP resources. To avoid this type of bias, the nurses will be trained to carefully train each participant using the same method, which will prevent influencing their responses (Creswell & Creswell, 2018).

Ethical Considerations

The primary investigator will abide by the University’s IRB and Belmont report guidelines while conducting the project. The three principles to be followed are respect for participants, justice, and beneficence (Belmont, 1979). The primary investigator and the nurses will show the participants respect by listening, validating their feelings, and answering the questions regarding the education or project. The primary investigator will occasionally monitor the nurse’s interaction with the participants throughout the project. The participants will be instructed that there are no repercussions to their personal or professional lives upon withdrawing from the project. Nor do they need to provide details on the reason they withdraw. The primary investigator and the nurses will always protect the participants’ privacy and confidentiality by not discussing the project, the participants, or its findings with anyone not involved in the project or without the participant’s permission.

Beneficence will be shown to the participants by informing the participants that the primary investigator or the nurses will stop the questioning immediately if they feel emotionally harmed. A psychological resource will be provided to participants who feel affected by the questions or project. All participants will be informed of the risks, benefits, and minimal harm that can occur to them, such as loss of data, social or emotional conflict with family and friends, and anxiety or depression.

The Belmont Report (1979) states justice is the “distribution of the burden.” During this project, it is possible that the participants could perceive unwanted stigma from the colleagues, family members, or friends. Each participant will be treated uniformly following their wishes, so it will not affect the project’s findings. There could be a potential conflict of interest with the project since the primary investigator works at the facility. To minimize the conflict, the primary investigator will not interact with the participants.

Limitations

The limitations of the project are self-reporting of medication adherence by the patients. To minimize this limitation, the primary investigator has validated the self-reporting instrument (MAP resources) before utilizing it for data collection (Althubaiti, 2016). Furthermore, the patient’s self-reporting will be compared to their fasting blood glucose levels, medical records, or reports from family and friends (Althubaiti, 2016).

The second limitation is the healthcare organization being impacted by the COVID-19 pandemic. The new COVID-19 guidelines have affected the current healthcare delivery model. The pandemic has caused the primary investigator to redirect resources and halt in-person training sessions for the nurses. The recruitment process has been limited to Zoom meetings and telephone calls. The third limitation is the location of the project and its setting. The project findings cannot be generalized to other home healthcare agencies of similar populations. The fourth limitation is the time to conduct the project (four weeks). A longer timeframe would help the primary investigator analyze the site’s challenges, trends, and sustainability.

Summary

Medication adherence among Type II diabetic home health patients remains a critical factor in their quality of life. The purpose of this quantitative quasi-experimental project is to determine to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. A quasi-experimental design allowed the primary investigator to evaluate the impact of the MAP resources and educational intervention on the dependent variable (medication adherence rates). The medication adherence rates will be collected before and after project implementation (four weeks). Data will be collected by the primary investigator and stored on the digitally protected laptop and hard copies will be locked in a secured file cabinet at the residence. Chapter 4 will reinstate the topic, along with descriptive data of the participants. Other sections will consist of the data analysis procedure, project findings, and summary.

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 past tense and reflects how the project was 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:

Is there sufficient data to answer each of the clinical question(s) asked in the project? (see Appendix C) One procedure for determining a sample size ahead of the project is a power analysis.

Is there sufficient data to support the conclusions you will make in Chapter 5? (see Appendix D) If using SPSS version 26 to perform analyses, the data is entered and coded using numbers or numerical codes.

Is the project written in the third person? Never use the first person.

Is the data clearly explained using a table, graph, chart, or text? (see Appendix E)

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. See Appendix E for examples of APA formatted tables and figures.

CriterionLearner 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, education level or employee classification, (if appropriate), 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. 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 3. 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 7th Edition.

Table 3

A Sample Data Table Showing Correct Formatting

 Column A

M (SD)

Column B

M (SD)

Column C

M (SD)

Row 110.1 (1.11)20.2 (2.22)30.3 (3.33)
Row 220.2 (2.22)30.3 (3.33)20.2 (2.22)
Row 330.3 (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. Reprinted with permission.

CriterionLearner 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). 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 the 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.

CriterionLearner Score (0, 1, 2, or 3)Chairperson Score (0, 1, 2, or 3)Comments or Feedback
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

   
Describes in detail the data analysis procedures.   
Explains and justifies any differences in why the data analysis section does not match what was approved in Chapter 3 (if appropriate).   
Provides validity and reliability of the data in statistical terms for quantitative methodology.   
Identifies sources of error and potential impact on the data.   
For a quantitative project, justifies how the analysis aligns with the clinical question(s) and is appropriate for the DPI project design.   
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).

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(s). List the clinical question(s) as you are discussing them in order to ensure that the readers see that the question has been addressed. Answer the clinical question(s) in the order that they are listed for quantitative studies. The key components included in this section are:

The data and the analysis of that data should be presented in a narrative, non-evaluative, 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.

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. Refer to the APA Style Manual for additional lists and examples. 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. 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 4 presents example results of an independent t test comparing Emotional Intelligence (EI) mean scores by gender.

Table 4

t-Test for Equality of Emotional Intelligence Mean Scores by Gender

 t test for equality of means
 tDfp
EI1.90834.065

After completing the first draft of Chapter 4, ask these general questions:

1. Are the findings clearly presented, so any reader could understand them?

Are all the tables, graphics or visual displays well-organized and easy to read?

Are the important data described in the text?

Is factual data information separate from analysis and evaluation?

Are the data organized by clinical questions?

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: + 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.

Refer to your APA manual for specific details on representation of statistical information. 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

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 introducepresent, 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 and figure for you to review. (see Table 5 and Figure 4)

 

Table 5

The Servant Leader

TraitDescriptors
Values PeopleBy 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 4

Scattor Plot Example – Strong Negative Correlation

scatter-plot-example-negative-correlation.jpg

Note, 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.

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RESULTS

This section, which is the primary section of this chapter, presents an analysis of the data in a nonevaluative, unbiased, organized manner that relates to the clinical question(s). List the clinical question(s) as you are discussing them in order to ensure that the readers see that the question has been addressed. Answer the clinical question(s) in the order that they are listed.

   
The analysis of the data is presented in a narrative, nonevaluative, unbiased, organized manner by clinical question(s).   
Includes 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 analyzed.   
Quantitative: Findings are presented by 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.   
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).

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(s). Finally, it provides a lead or transition into Chapter 5, where the implications of the data and data analysis relative to the clinical question(s) will be discussed. The summary of the data must be logically and clearly presented, with the factual information separated from interpretation. For quantitative studies, summarize the statistical data and results of statistical tests in relation to the clinical question(s). Finally, provide a concluding section and transition to Chapter 5.

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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(s). Finally, it provides a lead or transition into Chapter 5, where the implications of the data and data analysis relative to the clinical question(s) will be discussed.

   
Summary of data is logically and clearly presented.   
The factual information is separated from analysis.   
Quantitative: Summarizes the statistical data and results of statistical tests in relation to the clinical question(s).   
Provides a concluding section and transition to Chapter 5.   
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.

 

Chapter 5: Summary, Conclusions, and Recommendations

This section introduces Chapter 5 as a comprehensive summary of the entire project. It reminds the reader of the importance of the topic and briefly explains how the project intended to contribute to the body of knowledge on the topic. It informs the reader that conclusions, implications, and recommendations will be presented.

Chapter 5 is perhaps the most important chapter in the practice improvement project manuscript because it presents the investigator’s contribution to the body of knowledge. For many who read evidence-based literature, this may be the only chapter they will read. Chapter 5 typically begins with a brief summary of the essential points made in Chapters 1 and 3 of the original DPI project and includes why this topic is important and how this project was designed to contribute to the understanding of the topic. The remainder of the chapter contains a summary of the overall project, a summary of the findings and conclusions, recommendations for future practice, and a final section on implications derived from the project.

No new data or citations should be introduced in Chapter 5; however, references should be made to findings or citations presented in earlier chapters. The investigator can articulate new frameworks and new insights. The concluding words of Chapter 5 should emphasize both the most important points of the project and what the reader should take from them. This should be presented in the simplest possible form, making sure to preserve the conditional nature of the insights. Refer to the Grand Canyon University practice improvement project rubric for guidance on the content of this chapter.

 

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INTRODUCTION

Provides an overview of why the project is important and how the project was designed to contribute to our understanding of the topic.

   
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).

 

Summary of the Project

This section provides a comprehensive summary of the overall project that describes the content of the project to the reader in the simplest possible terms. It should recap the essential points of Chapters 1-3, but it should remain a broad, comprehensive view of the project. It reminds the reader of the clinical question(s) and the main issues being evaluated, and provides a transition, explains what will be covered in the chapter and reminds the reader of how the project was conducted.

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SUMMARY OF THE PROJECT

Reminds the reader of the clinical question(s) and the main issues being evaluated.

   
Provides a transition, explains what will be covered in the chapter and reminds the reader of how the project was conducted.   
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).

Summary of Findings and Conclusion

This section of Chapter 5 is organized by clinical question(s), and it conveys the specific findings of the project. The section presents conclusions made based on the data analysis and findings of the project and relates the findings back to the literature, significance of the project in Chapter 1, advancing scientific knowledge in Chapter 1. Significant themes/ findings are compared and contrasted, evaluated and discussed in light of the existing body of knowledge. The significance of every finding is analyzed and related to the significance section and advancing scientific knowledge section of Chapter 1. Additionally, the significance of the findings is analyzed and related back to Chapter 2 and ties the project together. The findings are bounded by the DPI project parameters described in Chapters 1 and 3, are supported by the data and theory, and directly relate to the clinical question(s). No unrelated or speculative information is presented in this section. This section of Chapter 5 should be organized by clinical question(s), theme, or any manner that allows summarizing the specific findings supported by the data and the literature. Conclusions represent the contribution to knowledge and fill in the gap in the knowledge. They should also relate directly to the significance of the project. The conclusions are major generalizations, and an answer to the practice problem developed in Chapters 1 and 2. This is where the project binds together. In this section, personal opinion is permitted, as long as it is backed with the data, grounded in the project methods and supported in the literature.

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Summary of Findings and Conclusions

This section is organized by clinical question(s), and it conveys the specific findings of the project. It presents all conclusions made based on the data analysis and findings of the project. It relates the findings back to the literature, significant chapters in Chapter 1, and advancing scientific knowledge in Chapter 1.

   
Organized by the same section titles as Chapter 4, clinical question(s) or by themes.   
Significant themes/ findings are compared and contrasted, evaluated and discussed in light of the existing body of knowledge.   
Significance of every finding is analyzed and related to the significance section and advancing scientific knowledge section of Chapter 1.   
The conclusion summarizes the findings, refers back to Chapter 1, and ties the project together.   
The findings are bounded by the DPI project parameters described in Chapters 1 and 3.   
The findings are supported by the data and theory, and directly relate to the clinical question(s).   
No unrelated or speculative information is presented in this section.   
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).

Implications

This section should describe what could happen because of this project. It also tells the reader what the DPI project results imply theoretically, practically, and for the future. Additionally, it provides a retrospective examination of the theoretical framework presented in Chapter 2 in light of the practice improvement project’s findings. A critical evaluation of the strengths and weaknesses of the project, and the degree to which the conclusions are credible given the methodology, project design, and data, should also be presented. The section delineates applications of new insights derived from the practice improvement project to solve real and significant problems. Implications can be grouped into those related to theory or generalization, those related to practice, and those related to future projects. Separate sections with corresponding headings provide proper organization.

Theoretical Implications

Theoretical implications involve interpretation of the practice improvement project findings in terms of the clinical question(s) that guided the project. It is appropriate to evaluate the strengths and weaknesses of the project critically and include the degree to which the conclusions are credible given the method and data. It should also include a critical, retrospective examination of the framework presented in the Chapter 2 Literature Review section in light of the practice improvement project’s new findings.

Practical Implications

Practical implications should delineate applications of new insights derived from the practice improvement project to solve real and significant problems.

Future Implications

Two kinds of implications for future projects are possible: one based on what the project did find or do, and the other based on what the project did not find or do. Generally, future DPI projects could look at different kinds of subjects in different kinds of settings, interventions with new kinds of protocols or dependent measures, or new theoretical issues that emerge from the project. Recommendations should be included on which of these possibilities are likely to be most fruitful and why.

CriterionLearner Score (0, 1, 2, or 3)Chairperson Score (0, 1, 2, or 3)Comments or Feedback
Implications

This section should describe what could happen because of this DPI project results. It also tells the reader what the outcome and results implies theoretically, practically, and for the future.

   
Provides a retrospective examination of the theoretical framework presented in Chapter 2 in light of the practice improvement project’s findings.   
Critically evaluates the strengths and weaknesses of the project, and the degree to which the conclusions are credible given the methodology, project design, and data.   
Delineates applications of new insights derived from the practice improvement project to solve real and significant problems.   
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).

Recommendations

Summarize the recommendations that result from the project. Each recommendation should trace directly to a conclusion.

Recommendations for Future Projects

This section should contain a minimum of four to six recommendations for future DPI projects, as well as a full explanation for why each recommendation is being made. Additionally, this section discusses the areas of project that need further examination or addresses gaps or new patient, or system needs the project found. The section ends with a discussion of “next steps” in forwarding this line of DPI project evaluations. Recommendations relate back to the project significance and advancing scientific knowledge sections in Chapter 1.

CriterionLearner Score (0, 1, 2, or 3)Chairperson Score (0, 1, 2, or 3)Comments or Feedback
Recommendations for Future PROJECTS

This section should contain a minimum of four to six recommendations for future DPI projects, as well as a full explanation for why each recommendation is being made. The recommended project methodology/design should also be provided.

   
Contains a minimum of four to six recommendations for future projects.   
Identifies and discusses the areas that need further examination, or addresses gaps or new patient or system needs the project found.   
Suggests “next steps” in forwarding this line of evidence and clinical implications.   
Recommendations relate back to the project significance and advancing scientific knowledge sections in Chapter 1.   
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 AQR 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).

Recommendations for Practice

This section should contain two to five recommendations for future practice based on the results and findings of the project, as well as a full explanation for why each recommendation is being made. It provides a discussion of who will benefit from reading and implementing the results of the project and presents ideas based on the results that practitioners can implement in the work or educational setting. Unrelated or speculative information that is unsupported by data is clearly identified as such. Recommendations should relate back to the project significance section in Chapter 1.

CriterionLearner Score (0, 1, 2, or 3)Chairperson Score (0, 1, 2, or 3)Comments or Feedback
Recommendations for Future Practice

This section should contain two to five recommendations for future practice based on the results and findings of the project, as well as a full explanation for why each recommendation is being made.

   
Contains two to five recommendations for future practice.   
Discusses who will benefit from reading and implementing the results of the project.   
Discusses ideas based on the results that practitioners can implement in the work or educational setting.   
Unrelated or speculative information unsupported by data is clearly identified as such.   
Recommendations relate back to the project significance section in Chapter 1.   
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).

 

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Szanton, S. L., Leff, B., Wolff, J. L., Roberts, L., & Gitlin, L. N. (2016). Home-based care program reduces disability and promotes aging in place. Health Affairs35(9), 1558-1563. https://doi.org/10.1377/hlthaff.2016.0140

Understanding Houston. (2021). Access to healthcare in Houston. https://www.understandinghouston.org/topic/health/access-to-healthcare/#uninsured_rate_children

U.S. Department of Health & Human Services. (2018). Read the Belmont report.

https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/read-the-belmont-report/index.html

Wong, Z. S., Siy, B., Da Silva Lopes, K., & Georgiou, A. (2019). Improving patients’ medication adherence and outcomes in Nonhospital settings through eHealth: Systematic review of randomized controlled trials (Preprint). https://doi.org/10.2196/preprints.17015

World Health Organization. (2017). Adherence to long-term therapies: Evidence for

action.  http://apps.who.int/iris/bitstream/10665/42682/1/9241545992.pdf

Yeam, C., Chia, S., Tan, H., Kwan, Y., Fong, W., & Seng, J.  (2018). Systematic

review of factors affecting medication adherence among patients with osteoporosis. Osteoporosis International29(12), 2623-2637. https://doi.org/10.1007/s00198-018-4759-3

 

 

 

 

 

 

 

 

 

Appendix A

The Parts of a Practice Improvement Project

GCU requires the Publication Manual of the American Psychological Association (7th ed.) as the style guide for writing and formatting Direct Practice Improvement (DPI) Projects. A DPI Project has three parts: preliminary pages, main text, and supplementary pages. Some preliminary or supplementary pages may be optional or not appropriate to a specific project. The learner should consult with his or her practice improvement project chairperson and committee regarding inclusion or exclusion of optional pages.

Preliminary Pages

The following preliminary pages precede the main text of the practice improvement project.

Title Page

Copyright Page (optional)

Approval Page

Abstract

Dedication Page (optional)

Acknowledgements (optional)

Table of Contents

List of Tables (if you have tables, a list is required)

List of Figures (if you have figures, a list is required)

Main Text

The main text is divided into five major chapters. Each chapter can be further subdivided into sections and subsections.

Chapter 1: Introduction to the Project

Chapter 2: Literature Review

Chapter 3: Methodology

Chapter 4: Data Analysis and Results (not included in the proposal)

Chapter 5: Summary, Conclusions, and Recommendations (not included in the proposal)

Supplementary Pages

Supplementary pages, which follow the body text, include reference materials and other required or optional addenda.

References

Appendices

Appendix A for the manuscript is the Grand Canyon University IRB Outcome Letter.

Appendix B is the Instruments/tool used.

Appendix C is permission to use the instrument/tool.

Appendix D is another tool if applicable (Appendix E is permission for second instrument/tool) otherwise you are done.

Keep in mind that most formatting challenges are encountered in the preliminary and supplementary pages. Allocate extra time and attention for these sections to avoid delays in the electronic submission process. In addition, as elementary as it may seem, run a spell check and grammar check of your entire document before submission.

 

2

 

Appendix B

What is my DPI project design?

 

THIS IS NOT PART OF THE PAPER JUST A REFERENCE FOR THE LEARNER

 

 

 

 

26

 

 

Appendix C

Power Analysis Using G Power

Note: Public source G-Power Software available https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower.html

Appendix D

Example SPSS Dataset & Variable View

 

26

The SPSS database is set up with all variables coded to compare between or within the comparison groups. A comparison may be made within the same individual and it coded 1 for before and 2 after the intervention. Or if measuring between individuals, the data would be coded the same 1 for before and 2 after as noted in the Group Column. Software supplied by Grand Canyon University.

Appendix E

How to Make APA Format Tables and Figures Using Microsoft Word

Tables vs. Figures

0. See APA Publication Manual, Chapter 7 for additional details (APA, 2019).

0. Tables consist of words and numbers where spatial relationships usually do not indicate any numerical information.

0. Tables should be used to present information that would be too wordy, repetitive, or difficult to read as text.

0. Figures typically communicate numerical information using spatial relations. For example, as you move up the Y axis of bar graph the scores usually go up.

 

1. Examples of APA Tables

A. Descriptive table

Table 1

Characteristics of Variables

VariableVariable TypeLevel of Measurement
Group, Intervention or ToolIndependentNominal

 

Rates or eventsDependentNominal

 

Socio Economic Status or Categories in an orderDependentOrdinal

 

Time, TemperatureDependentInterval

 

Age, height, Scores of testsDependentRatio

Note. Add notes here = (Provide any reference, 2019).

Table 1

Number of Handoff Per Groups

Group# of Handoffs (%)
Pre-Intervention Group (Baseline)150 (50%)
SBAR Group150 (50%)
  

Note. SBAR handoff was defined as …. (IHI, 2020)

Table 1

Number of Hours Per Week Spent in Various Activities

GroupBaseline

(n = 30)

Post Intervention (n = 30)Total Sample

(n = 60)

 M (SD)M (SD)M (SD)
Schoolwork18.23 (7.79)16.23 (3.99)17.63 (1.2)
Physical activities19.54 (3.63)14.23 (2.84)*18.67 (1.0)
Socializing16.23 (3.99)17.63 (1.2)18.23 (7.79)
Watching television14.23 (2.84)18.67 (1.0)19.54 (3.63)
Extracurricular activities19.54 (3.63)18.23 (7.79)19.22 (5.45)

Note. Schoolwork was defined as time spent doing class work outside of regular class time.

*statistically significant at p <.05

 

B. Chi-Square example (Group IV x Group DV)

Table 1

Crosstabulation of Gender and Chronic Pain

Chronic

Pain

Gender  
 FemaleMaleχ2Φ
 

Yes

2

(-2.7)

 

8

(2.7)

7.20**,60
 

No

8

(2.7)

 

2

(-2.7)

  

Note. Adjusted standardized residuals appear in parentheses below group frequencies.

**= p < .01.

 

 

C. t-Test Example (Dichotomous Group IV x Score DV) –Notice two separate t-test results have been reported.

Table 1

Chronic Paint Score and Exercise time for Males and Females

 Gender  
 FemaleMaleTdf
 

Pain Score

 

3.33

(1.70)

 

3.75

(1.79)

-2.20*175
 

Exercise Time

 

4.28

(.7509)

 

3.87

(.9280)

4.2**176

Note. Standard Deviations appear in parentheses below means.

* = < .05, *** = < .001.

 

D. One Way ANOVA with 3 Groups Example (Group IV x Score DV)

Remember with an ANOVA, you have to report paired comparisons associated with post hoc or planned comparisons) for significant analyses. The results of paired comparisons are indicated by the subscripts on the means within rows. Also, notice in this table that we report the results of four separate analyses. This is the real power of tables: we can convey a large amount of information very concisely.

Table 1

Analysis of Variance for Sleep Times and Experimental Groups

 Experimental Group  
 Aerobic ExerciseWeight LiftingNo ExerciseFη2
Total Sleep Time8.23a

(.55)

7.93b

(.90)

7.73ab

(.55)

 

3.98***

 

.18
Total Wake Time3.58a

(.70)

3.62a

(.55)

3.54a

(.90)

.03.00
Total Light Sleep3.19c

(.73)

2.80a

(.72)

3.02b

(.49)

2.95*.06
Total Deep Sleep3.21b

(.19)

3.10a

(.28)

3.30a

(.19)

.20.01

Standard deviations appear in parentheses bellow means. Means with differing subscripts within rows are significantly different at the p < .05 based on Fisher’s LSD post hoc paired comparisons.

* = < .05, *** = < .001.

 

E. Factorial ANOVA Example 2 x 3 between subject’s design.

Notice that two tables are used here. The first table reports the overall results for the 2×3 factorial ANOVA, which includes the Main Effects for the two IV’s and the Interaction Effect for the two IV’s. The second table reports the means and simple effects tests for the significant interaction effect.

Table 1

Experimental Group x Sex Factorial Analysis of Variance for Sleep Scores

SourceDfFη2p
 

Experimental Group

 

2

 

7.93

 

.17

 

.001

 

Sex

 

 

1

 

 

31.41

 

 

.34

 

 

.001

 

Group x Sex (interaction)

 

2

 

7.85

 

.17

 

.002

 

Error (within groups)30   

 

 

Table 1

Analysis of Sleep Scores for Experimental Groups by Gender

 Aerobic ExerciseWeightliftingNo ExerciseSimple Effects:

F df (2, 30)

 

Males

10.37a

(2.50)

10.30a

(2.34)

10.33a

(1.63)

.04
 

Females

4.83a

(1.60)

10.50b

(2.59)

4.50a

(1.52)

15.74**
 

Simple Effects:

F df (1, 30)

 

23.56**

 

 

.00

 

23.56** 

Note. Standard deviations appear in parentheses bellow means. Means with differing subscripts within rows are significantly different at the p < .05 based on Fisher’s LSD post hoc paired comparisons.

** = < .01

 

Notice that the simple effect comparing the 3 experiment groups only for females, requires follow up tests in order to determine which groups are significantly different. In this case, Fisher’s LSD test was used, and the results are represented with the different subscripts for each mean. In this case, female participants in the Aerobic exercise group did not differ from the no exercise group so they are given the same subscript (a). However, women in the control group and women in the Weightlifting group significantly differed from the Aerobic watching group and so the Weightlifting group was labeled with a different subscript (b). The male subjects did not differ from one another, so they all share the same subscript (a).

 

 

F. Correlations (Scores IV x Scores IV)

Table 1

Pearson’s Product Moment Correlations for Chronic Pain Score, Exercise Attitude Scores and Physical Activity

 Demographic Influences on Exercise
  
 WeightAge
Chronic Pain Score

 

Pain Level

 

.39***

 

 

-.07

 

Pain Intensity

 

.15

 

.22*

 

Physical Exercise

 

Type of Exercise

 

 

-.26**

 

 

-.19†

 

Time of Exercise

 

-.13

 

 

-.21*

 

Intent to Exercise.02-.10

Note. N = 96 for all analyses.

† = .10, *= .05, **= .01, ***= .001.

1. Examples of APA Figures

Generally, the same features apply to figures as have been previously provided for tables: They should be easy to read and interpret, consistent throughout the document when presenting the same type of figure, kept on one page if possible, and supplement the accompanying text or table.

Figure 1

Graph of Scores Before and After

 

Note: Reprinted from S. GCU. Or Adapted from or www.website.com. Reprinted with permission.

If the figure is not your own work, note the source or reference where you found the figure. Write, “Reprinted from” or “Adapted from,” followed by the title of the book, article, or website where you found the figure. Include the page number where you found the figure as well if you are citing a figure from a book. If you are citing a figure from a website, you may write, “Reprinted from The Huffington Post.” Or include the author’s first and second initial as well as their surname. Use the author’s first and second initial, if available, rather than the author’s full first name. Note their last name as well.

References:

American Psychological Association [APA]. (2019). Publication manual of the American Psychological Association. (7th ed.). Washington, DC; Author

Microsoft Word ®. (2019). Retrieved from https://products.office.com/

Appendix F

Writing up your statistical results

Identify the analysis technique.

In the results section (Chapter 4), your goal is to report the results of the data analyses used to answer your project question. To do this, you need to identify your data analysis technique, report your test statistic, and provide some interpretation of the results. Each analysis you run should be related to your clinical question or PICOT. If you analyze data that is exploratory or outside your clinical question, you need to indicate this in the results.

 

Format test statistics.

Test statistics and p values should be rounded to two decimal places (If you are providing precise p-values for future use in meta-analyses, 3 decimal places are acceptable). All statistical symbols (sample statistics) that are not Greek letters should be italicized (M, SD, t, p, etc.).

 

Indicate the direction of the significant difference.

When reporting a significant difference between two conditions, indicate the direction of this difference, i.e. which condition was more/less/higher/lower than the other condition(s). Assume that your audience has a professional knowledge of statistics. Do not explain how or why you used a certain test unless it is unusual (i.e., such as a non-parametric test).

 

How to report p values.

Report the exact p value (this is the preferred option if you want to make your data convenient for individuals conducting a meta-analysis on the topic).

Example: t(33) = 2.10, = .03.

 

If your exact p value is less than .001, it is conventional to state merely < .001. If you report exact p values, state early in the results section the alpha level used as a significance criterion for your tests. For example: “We used an alpha level of .05 for all statistical tests.”

 

If your results are in the predicted direction but are not significant, you can say your results were marginally significant. Example: Results indicated a marginally significant preference for pie (= 3.45, SD = 1.11) over cake (= 3.00, SD = .80), t(5) = 1.25, = .08.

 

If your p-value is over .10, you can say your results revealed a non-significant trend in the predicted direction. Example: Results indicated a non-significant trending in the predicted direction indicating a preference for pie (= 4.25, SD = 2.21) over cake (= 3.25, SD = 2.60), t(5) = 1.75, = .26.

 

Descriptive Statistics

Mean and Standard Deviation are most clearly presented in parentheses:

 

The sample as a whole was relatively young (= 19.22, SD = 3.45).

The average age of students was 19.22 years (SD = 3.45).

 

Percentages are also most clearly displayed in parentheses with no decimal places:

Nearly half (49%) of the sample was married.

 

Frequencies or rates are reported including the range, mode, or median.

 

t-tests

There are several different designs that utilize a t-test for the statistical inference testing. The differences between one-sample t-tests, related measures t-tests, and independent samples t tests are clear to the knowledgeable reader so eliminate any elaboration of which type of t-test has been used. Additionally, the descriptive statistics provided will identify which variation was employed. It is important to note that we assume that all p values represent two-tailed tests unless otherwise noted and that independent samples t-tests use the pooled variance approach (based on an equal variances assumption) unless otherwise noted:

 

There was a significant effect for gender, t(54) = 5.43, < .001, with men receiving

higher scores than women.

Results indicate a significant preference for pie (= 3.45, SD = 1.11) over cake (= 3.00, SD = .80), t(15) = 4.00, = .001.

The 36 study participants had a mean age of 27.4 (SD = 12.6) were significantly older

than the university norm of 21.2 years, t(35) = 2.95, = .01.

Students taking statistics courses in psychology at the University of Washington reported studying more hours for tests (= 121, SD = 14.2) than did UW college students in general, t(33) = 2.10, = .034.

The 25 participants had an average difference from pre-test to post-test anxiety scores of -4.8 (SD = 5.5), indicating the anxiety treatment resulted in a significant decrease in

anxiety levels, t(24) = -4.36, = .005 (one-tailed).

The 36 participants in the treatment group (= 14.8, SD = 2.0) and the 25 participants in the control group (= 16.6, SD = 2.5), demonstrated a significance difference in

performance (t[59] = -3.12, = .01); as expected, the visual priming treatment inhibited

performance on the phoneme recognition task.

UW students taking statistics courses in Psychology had higher IQ scores (= 121, SD = 14.2) than did those taking statistics courses in Statistics (= 117, SD = 10.3), t(44) =

1.23, = .09.

Over a two-day period, participants drank significantly fewer drinks in the experimental group (M= 0.667, SD = 1.15) than did those in the wait-list control group (M= 8.00, SD= 2.00), t(4) = -5.51, p=.005.

 

ANOVA and post hoc tests.

ANOVAs are reported like the t test, but there are two degrees-of-freedom numbers to report. First report the between-groups degrees of freedom, then report the within-groups degrees of freedom (separated by a comma). After that report the F statistic (rounded off to two decimal places) and the significance level.

 

One-way ANOVA:

The 12 participants in the high dosage group had an average reaction time of 12.3.

seconds (SD = 4.1); the 9 participants in the moderate dosage group had an average

reaction time of 7.4 seconds (SD = 2.3), and the 8 participants in the control group had a

mean of 6.6 (SD = 3.1). The effect of dosage, therefore, was significant, F(2,26) = 8.76,

p=.012.

A one-way analysis of variance showed that the effect of noise was significant, F(3,27) = 5.94, = .007. Post hoc analyses using the Scheffé post hoc criterion for significance indicated that the average number of errors was significantly lower in the white noise condition (= 12.4, SD = 2.26) than in the other two noise conditions (traffic and industrial) combined (= 13.62, SD = 5.56), F(3, 27) = 7.77, = .042.

Tests of the four a priori hypotheses were conducted using Bonferroni adjusted alpha

levels of .0125 per test (.05/4). Results indicated that the average number of errors was

significantly lower in the silence condition (= 8.11, SD = 4.32) than were those in both

the white noise condition (= 12.4, SD = 2.26), F(1, 27) = 8.90, =.011 and in the

industrial noise condition (= 15.28, SD = 3.30), (1, 27) = 10.22, = .007. The

pairwise comparison of the traffic noise condition with the silence condition was nonsignificant.

The average number of errors in all noise conditions combined (= 15.2, SD

= 6.32) was significantly higher than those in the silence condition (= 8.11, SD = 3.30),

F(1, 27) = 8.66, = .009.

 

Multiple Factor (Independent Variable) ANOVA

There was a significant main effect for treatment, F(1, 145) = 5.43, < .01, and a

significant interaction, F(2, 145) = 3.13, < .05.

The cell sizes, means, and standard deviations for the 3×4 factorial design are presented

in Table 1. The main effect of Dosage was marginally significant (F[2,17] = 3.23, =

.067), as was the main effect of diagnosis category, F(3,17) = 2.87, = .097. The

interaction of dosage and diagnosis, however, has significant, F(6,17) = 14.2, = .0005.

Attitude change scores were subjected to a two-way analysis of variance having two

levels of message discrepancy (small, large) and two levels of source expertise (high,

low). All effects were statistically significant at the .05 significance level. The main

effect of message discrepancy yielded an F ratio of F(1, 24) = 44.4, < .001, indicating

that the mean change score was significantly greater for large-discrepancy messages (=

4.78, SD = 1.99) than for small-discrepancy messages (= 2.17, SD = 1.25). The main

effect of source expertise yielded an F ratio of F(1, 24) = 25.4, < .01, indicating that the

mean change score was significantly higher in the high-expertise message source (=

5.49, SD = 2.25) than in the low-expertise message source (= 0.88, SD = 1.21). The

interaction effect was non-significant, F(1, 24) = 1.22, > .05.

A two-way analysis of variance yielded a main effect for the diner’s gender, F(1,108) =

3.93, < .05, such that the average tip was significantly higher for men (= 15.3%, SD

= 4.44) than for women (= 12.6%, SD = 6.18). The main effect of touch was nonsignificant, F(1, 108) = 2.24, > .05. However, the interaction effect was significant,

F(1, 108) = 5.55, < .05, indicating that the gender effect was greater in the touch

condition than in the non-touch condition.

 

Chi Square

Chi-Square statistics are reported with degrees of freedom and sample size in parentheses, the Pearson chi-square value (rounded to two decimal places), and the significance level:

The percentage of participants that were married did not differ by gender, X2(1, N = 90) = 0.89, > .05.

The sample included 30 respondents who had never married, 54 who were married, 26

who reported being separated or divorced, and 16 who were widowed. These frequencies

were significantly different, X2 (3, N = 126) = 10.1, = .017.

As can be seen by the frequencies cross tabulated in Table xx, there is a significant

relationship between marital status and depression, X2 (3, N = 126) = 24.7, < .001.

The relation between these variables was significant, X2 (2, N = 170) = 14.14, < .01.

Catholic teens were less likely to show an interest in attending college than were

Protestant teens.

Preference for the three sodas was not equally distributed in the population, X2 (2, N =

55) = 4.53, < .05.

 

Correlations

Correlations are reported with the degrees of freedom (which is N-2) in parentheses and the significance level:

The two variables were strongly correlated, r(55) = .49, < .01.

 

Regression analyses

Regression results are often best presented in a table. A

PA doesn’t say much about how to report regression results in the text, but if you would like to report the regression in the text of your Results section, you should at least present the standardized slope (beta) along with the t-test and the corresponding significance level. (Degrees of freedom for the t-test is N-k-1 where k equals the number of predictor variables.) It is also customary to report the percentage of variance explained along with the corresponding F test.

Social support significantly predicted depression scores, = -.34, t(225) = 6.53, < .01. Social support also explained a significant proportion of variance in depression scores, R2 = .12, F(1, 225) = 42.64, < .01.

 

Tables

Add a table or figure.

Adding a table of figure can be helpful to the reader. See the current APA Publication manual for examples. In reporting the results of statistical tests, report the descriptive statistics, such as means and standard deviations, as well as the test statistic, degrees of freedom, obtained value of the test, and the probability of the result occurring by chance (p value).

 

•APA style tables do not contain any vertical lines

•There are no periods used after the table number or title.

•When using columns with decimal numbers, make the decimal points line up.

•Use MS Word tables to create tables

American Psychological Association [APA]. (2019). Publication manual of the American Psychological Association (7th ed.). Washington, DC: Author.

 

Before 38 36 43 35 37 37 39 36.027027027027025 35.054054054054056 39 42.05263157894737 36 37 36 37 36 36.027027027027025 36 36 37 37 After 25 24 23 22 27 30 27 33 29 37 30 22 23 29 33 34 30 29 31 35 32