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1Running head: INPATIENT DIABETES SELF-MANAGEMENT EDUCATION

A Nurse-Led Inpatient Diabetes Self-Management Education and Support Program to Improve

Patient Knowledge and Treatment Adherence

by

Antony Macido MSN, ACNP-BC, CNS

Evidence-Based Practice Project Report

Richard Pessagno DNP, CRNP, FAANP, Scholarly Chair Person

Submitted to the College of Nursing of Maryville University,

Maryville, Missouri

in partial fulfillment of the requirements

For the Degree of

DOCTOR OF NURSING PRACTICE

2018

2INPATIENT DIABETES SELF-MANAGEMENT EDUCATION

DEDICATION

My sincere dedications to almighty Lord and my loving parents, my wife, my son, and

my daughter.


ACKNOWLEDGEMENTS

I would like to acknowledge the continuous support from Richard Pessagno DNP, CRNP,

FAANP as my Scholarly Project Chair. I would also I like to thank all the instructors who guided

me through the journey to achieve the DNP degree and Dr. Michael Landry who helped me with

the statistics involved in the study.


TABLE OF CONTENTS

Chapter Page

DEDICATION………………………………………………………………………..2

ACKNOWLEDGMENTS…………………………………………………………….3

TABLE OF CONTENTS……………………………………………………………..4

LIST OF TABLES……………………………………………………………………6

ABSTRACT…………………………………………………………………………..7

CHAPTERS

CHAPTER I - Introduction……………………………………………………..9

CHAPTER II - Theoretical Framework and Literature Review……………….17

CHAPTER III - Implementation of Practice Change…………………………..34

CHAPTER IV - Findings……………………………………………………….45

CHAPTER V - Discussion……………………………………………………..51

REFERENCES………………………………………………………………………….55

AUTOBIOGRAPHICAL STATEMENT………………………………………………63

ACRONYM LIST………………………………………………………………………65

APPENDICES

APPENDIX A - Literature Review Matrix……………………………………..67

APPENDIX B - The Health Promotion Model…………………………………69

APPENDIX C - Project Flyer……………………………………………………70

APPENDIX D – Informed Consent……………….. ……………………………71

APPENDIX E – Revised Diabetes Knowledge Test…..………………………..73

APPENDIX F - Medication Adherence Questionnaire…………………………74


APPENDIX G - AADE7™ Diabetes Self-Care Brochure………………………75


LIST OF TABLES

Table Page

Table 4.1 Descriptive Statistics………………………………………...46

Table 4.2 Participant Demographics.…………………………………..46

Table 4.3 Paired Samples Statistics…………………………………….47

Table 4.4 Paired Sample Correlations………………………………….47

Table 4.5 Paired Samples Test…………………………………………48

Table A1 Literature Review Matrix……………………………………67


Abstract

Diabetes mellitus (DM) is a growing problem in the United States and worldwide.

Diabetes has emerged as a major malady in the healthcare arena that possesses a significant

burden on the healthcare costs. An evidence-based, practical, and economically feasible strategy

to tackle the growing burden of DM is imminent. Diabetes self-management education and

support (DSMES) is the backbone to improve the care in DM (Powers et al., 2017). An

evidence-based practice (EBP) project called a nurse-led inpatient DSMES program was

designed and implemented in a community hospital on the west coast to improve patient

knowledge of DM and medication adherence with DM. A descriptive, pretest-posttest study was

employed to evaluate the effects of a DSMES program in an inpatient setting. The results of the

study revealed a statistically significant improvement (p = .026) in the participant knowledge on

DM after the provision of DSMES. Although not statistically significant (p = 1.000), the

program did not reveal any change in the participant medication adherence as a result of the

DSMES. Provision of DSMES by nurses can improve the outcomes of patients with DM. Further

large-scale studies are needed to generate further evidence to support the provision of DSMES

by nurses.

Key Words: diabetes mellitus, diabetes self-management education and support, patient

knowledge, medication adherence.


Chapter I


Introduction

Diabetes mellitus is a growing problem in the United States and worldwide. According to

the Centers for Disease Control and Prevention (CDC) (2017), more than 12% of the adults in

the United States suffer from DM. Around 3% of the patients with DM are undiagnosed (CDC,

2017). In the United States, DM is the seventh leading cause of death (Kochanek, Murphy, Xu,

& Tejada-Vera, 2016). It is estimated that in 2050 one in three adults will have DM in the United

States (Boyle, Thompson, Gregg, Barker, & Williamson, 2010). Every year there are 1.5 million

newly diagnosed cases of DM in the United States (American Diabetes Association [ADA],

2017).

Diabetes has emerged as a major chronic illness that is putting significant strain on the

current healthcare system. Individuals with DM undiagnosed or diagnosed and those with pre-

diabetes are more prone to hospitalizations when compared to those without DM (Schneider et

al., 2016). In 2010, DM contributed towards 34.67 million hospital days in the United States and

622,000 hospitalizations had DM as the primary diagnosis upon discharge (McEwen & Herman,

2016). According to McCoy et al. (2017), acute diabetes-related complications (ADC) is the

second most common reason for hospitalizations in patients with DM. Evidence suggests that

prior ADC history strongly predicts hospital readmissions for ADC and non-ADC reasons

(McCoy et al., 2017).

Patient education has always been a major dimension of nursing care of patients. Patient

education by healthcare providers had shown increased medication adherence in patients with

DM (Larkin, Hoffman, Stevens, Douglas, & Bloomgarden, 2015). Inpatient diabetes education

(IDE) has shown to improve glycemic control in patients who were novel to insulin after one

year of discharge from hospitals (Wexler et al., 2012). Diabetes self-management education


(DSME) implies the method of facilitating the ability, knowledge, and skills imminent for self-

care in DM. On the other hand, diabetes self-management support (DSMS) involves the support

needed for initiating and maintaining coping behaviors and skills to self-manage on a continuous

basis (Powers et al., 2017). The ADA recommends provision of DSME and DSMS together

referred to as DSMES to all individuals with DM at the time of diagnosis and as needed after that

(ADA, 2017).

Purpose of the Project

The purpose of this scholarly project was to utilize an evidence-based nurse-led DSMES

program in a community hospital on the west coast to improve patient knowledge of DM and

thereby improve patient adherence to treatment strategies. According to Worral, Levin, and

Arsenault (2009), EBP projects have the capability of improving practice beyond a local area or

a given facility. The project was also intended to be a first step towards using the DSMES

program as the standard of care of patients with DM in the setting where the project was

conducted.

In a community hospital on the west coast, it has been noted that a large proportion of

patients get hospitalized due to DM and its complications. It was noticed that a considerable

proportion of the admissions for DM and its complications are related to poor adherence to

medications and dietary restrictions. A significant number of readmissions to the hospital also

happen because of DM and its complications. Readmissions for DM and its complications can

also be attributed to poor patient compliance with medications and dietary restrictions.

Knowledge deficiency about DM and its management is profound in the DM patients admitted to

this hospital. Therefore, knowledge deficiency could be a contributing factor towards poor

medication compliance in the patients with DM.


Inadequate diabetes knowledge and poor skills in self-management can be linked to the

emergency department (ED) visits and hospitalizations related to uncontrolled DM (Magee,

Khan, Desale, & Nassar, 2014). Evidence suggests a shorter length of stay and improved

outcomes post-discharge after IDE (Nettles, 2005). Many guidelines for EBP uses the acronym

PICOT for forming clinical questions. The PICOT implies the population of interest (P), the

intervention planned (I), the comparison (C), the outcome (O), and the time (T) (Polit & Beck,

2017). After a careful review of the literature available on diabetes education, a clinical question

was identified for the scholarly project for the doctor of nursing practice (DNP) program using

PICOT. In patients with DM (P) who are admitted to a local community hospital on the west

coast during a six-month period (T), what are the effects of a nurse-led DSMES project (I) in

improving (C) their knowledge on DM and their compliance with the treatment strategies (O)?

Background of the Problem

Diabetes is a common diagnosis in a general practitioner’s routine practice. Diabetes is

associated with an increased risk of hospital readmissions (Ostling et al., 2017) and increased

medical expenditure (ADA, 2017). According to ADA (2013), in 2012 the estimated cost of

diagnosed DM in the U.S. was $245 billion with $176 million accounting for direct medical

costs and 43% of the medical cost was accounted for inpatient care. Hospital readmissions had

emerged as a quality measure in healthcare and a focus of cost reduction (Rubin, 2015). The

Centers for Medicare and Medicaid Services (CMS) has started penalizing hospitals that have

more than the recommended 30-day readmission rates as per the Hospital Readmission

Reduction Program (Kocher & Adashi, 2011).

Literature available on effective inpatient interventions to decrease readmissions and

improve the medical expenditure associated with DM is scarce. Inpatient diabetes education is an


important strategy in preventing early readmissions in patients with DM (Rubin, Donnell-

Jackson, Jhingan, Golden, & Paranjape, 2014). The role of nurses including advanced practice

nurses (APN) in inpatient DSMES remains vague. Diabetes management by nurse practitioners

(NP) and physician assistants (PA) with training in inpatient diabetes management has shown an

improved use of the basal-bolus insulin recommended by the ADA and lower average blood

glucose levels at discharge (Mackey et al., 2014).

Significance of the Problem Related to Healthcare and Advanced Practice Nursing

Diabetes possesses a significant strain on the hospital system in the United States (Cook,

2017). Efficient inpatient management of DM is vital to today’s healthcare. Diabetes is

associated with an increased length of hospital stay (Lee et al., 2017). According to McEwen and

Herman (2016), in 2009, individuals with DM were 2.6 times more prone to get hospitalized than

their non-DM counterparts. Patients with DM as a primary or secondary diagnosis has higher

rates of hospital readmissions (Ostling et al., 2017). With the increasing number of patients with

DM, the number of hospitalizations of patients with known DM and newly diagnosed DM is

projected to increase (Wei, Grant, Nathan, & Wexler, 2012). The average medical expenses of

patients with DM is 2.3 times higher than those without DM (ADA, 2017).

Diabetes self-management education and support is the backbone to improve the care in

DM (Powers et al., 2017). Self-management implies a core component in the care of DM and

appropriate self-management can positively impact the health outcomes of patients with DM

(Albisser, Harris, Albisser, & Sperlich, 2001). Diabetes self-management implies taking control

of the treatment, symptoms, psychological, and physical consequences, and the lifestyle changes

associated with DM (Barlow, Wright, Sheasby, Turner, & Hainsworth, 2002; Wagner et al.,


2001). Evidence suggests that DMSES can reduce hospital readmissions and hospital admissions

in patients with DM (Duncan et al., 2011; Healy, Black, Harris, Lorenz, & Dungan, 2013).

There are four critical times when assessment and delivery of DSMES are very essential.

The four critical times include at diagnosis, during the transition of care, when there are new

complicating circumstances that influence self-management, and annually (Powers et al., 2017).

Among the four critical times, inpatient hospitalizations may result in two critical times that

require assessment and delivery of DSMES. Two critical times that can occur from inpatient

hospitalizations include the transition of care and presence of complicating factors that can affect

self-management. Therefore, inpatient hospitalizations provide an important opportunity for the

provision of DSMES. Advanced practice nurses and nurses who deliver care to patients with DM

in inpatient settings are privileged to have better opportunities to provide DSMES at critical

times during inpatient hospitalizations.

How the Practice Setting Will Support the Project

The practice setting at which the project was implemented is a 350-bed community

hospital on the west coast. The majority of the patients admitted to this facility have inadequate

health insurance and fewer outpatient follow-up visits. A considerable proportion of these

patients also frequently have poor adherence to DM management that often results in frequent

readmissions to the hospital because of DM and its complications. Therefore, provision of

DSMES would be an ideal option to improve the diabetes self-management skills in the

hospitalized patients who otherwise do not have appropriate outpatient resources to teach and

reinforce diabetes self-management. Evidence suggests that a single session of one-to-one

dietetic and diabetic education in individuals with poorly controlled DM can improve diabetic

control in these subjects up to one year (Banerjee, Macdougall, & Lakhdar, 2012).


The practice setting has two certified diabetes educators (CDE), and they are

overwhelmed by the volume of patients with DM getting admitted to this facility because of

ADC. The CDEs were very receptive to any interventions or projects that can improve the care

of diabetic patients in the facility. Moreover, the hospital management has always supported

EBP projects that are intended to improve the care of the patients. The hospital management was

very interested to learn about the project and offered all the support required to complete the

project.

Benefits of the Project to Practice

The project will improve the patient knowledge of DM and thereby the treatment

adherence of inpatients with DM at the community hospital described earlier in this paper.

Improved treatment adherence can potentially decrease the complications related to poor DM

self-management and thereby prevent frequent readmissions from diabetes-related complications

to the facility. Preventing readmissions from diabetes-related complications implies cost savings

from frequent readmissions to the facility. Implementation of the project requires a relatively low

cost as this does not use any sophisticated tools such as electronic devices or expensive teaching

aids. The project only involves bedside instructions with the help of handouts from the NP or

nurses, along with a pretest and posttest to assess the improvement in patient knowledge.

Implementation of this project is not very time consuming and can be incorporated into the daily

patient care routines of nurses and APNs.

This project has the potential to be utilized in other facilities including outpatient

facilities for the provision of DSMES. Implementation of this project is inexpensive, and the

nurses including APNs do not require any special training to employ this project. No special

settings such as classrooms or expensive platforms are necessary to implement this project.


Therefore, facilities with limited funding for education like the one where the project was

conducted can introduce DSMES to be used by nurses while taking care of patients with DM.


Chapter II


Literature Review

Theoretical Framework

Theoretical frameworks and conceptual models are often utilized to form the foundation

for EBP projects. Nola Pender’s Health Promotion Model (HPM), a popular conceptual model

was utilized as the framework for this EBP project. The HPM uses wellness orientation while

explaining health-promoting behaviors (Pender, Murdaugh, & Parsons, 2015). According to

Pender et al. (2015), health promotion implies activities geared towards generating resources that

enhance or maintain an individual’s wellbeing. The HPM involves many theoretical propositions

that were employed in the project.

The HPM addresses individual characteristics and experiences, behavior-specific affect

and cognitions, and also behavioral outcomes that influence the development of a health-

promoting behavior (Pender et al., 2015). Therefore, the HPM was an optimal choice for the

implementation of this project that was intended to develop health-promoting behaviors in

hospitalized DM patients. The identified outcomes of the project include improved knowledge of

DM and improved medication adherence, all of which are dimensions of behaviors that can

promote health. The important components of the HPM are explained below along with the

application of the respective concepts in the intended project. Please see Figure 1 in Appendix B

for a visual representation of the HPM.

Individual Characteristics and Experiences

The prior experiences and phenotype of individuals play a crucial role in their behavior

patterns. The first component of the HPM involves an individual’s experiences and

characteristics that contribute towards the individual’s behavior. The HPM model attempts to

understand the most important variable that can predict an intended change in behavior. For


evaluating the important variables applicable to a person, one has to evaluate prior behaviors and

personal factors (Pender et al., 2015).

Prior related behaviors. Different individuals have their own health-related behaviors.

Prior related behaviors imply the frequency of the similar health-related behaviors in the past

(Pender et al., 2015). According to Pender et al. (2015), prior related behaviors can have indirect

and direct effects on predicting future health-related behaviors. Direct effects of prior related

behaviors can reinforce habit formation because of repeated performance of the behaviors

(Pender et al., 2015). For example, patients with DM who are compliant with oral medications

alone are likely to be compliant with dose adjustments to their oral medications or the addition of

a second oral agent. A few participants in the project taking oral medications for DM with

uncontrolled DM verbalized better potential for compliance with the addition of a second oral

agent versus addition of insulin to control the blood sugars.

On the other hand, indirect effects of prior related behaviors include perceived barriers

and benefits of action, perceived self-efficacy, and activity-related affect (Pender et al., 2015).

Healthcare personnel including nurses can play a role in enhancing or mitigating the indirect

effects of prior related behaviors related to a health-promoting behavior. The examples of

indirect effects of prior related behavior in inpatients with DM are explained in the behavior-

specific cognitions and affect under the HPM.

Personal factors. The personal factors that affect health-promoting behaviors include

sociocultural, psychological, and biological characteristics of an individual (Pender et al., 2015).

The sociocultural factors can include race, occupation, socioeconomic status, and education. The

psychological factors include self-esteem, self-motivation, and perceived health status. The

biological factors can include gender, age, weight, height, and so on. The personal factors can


predict a given health-related behavior. For example, individuals’ perception of having a

sedentary job can make them motivated to work out intensely after their job. One of the

participants in the project who was a taxi driver was educated on the unfavorable effects of

sedentary life, and he seemed to be very motivated to join a local gym.

Behavior-Specific Cognitions and Affect

The second major proposal of HPM is named behavior-specific cognitions and affect that

involves perceived benefits and barriers to action, activity related affect, perceived self-efficacy

as well as interpersonal and situational influences. Together, all the concepts mentioned in

behavior-specific cognitions and affect contribute towards a commitment to an action plan with

an immediate consideration for competing demands and preferences (Pender et al., 2015). All the

concepts mentioned in behavior-specific cognitions and affect are discussed further.

Perceived benefits of action. Eager to know the potential results of an action is a basic

human instinct. Perception of an action to be potentially beneficial will create a commitment to

an action plan in an individual (Pender et al., 2015). The positive benefits of medication

adherence, dietary adherence, and self-management skills were provided to inpatients with DM

using the proposed project. The perceived benefits of the proposed actions would be

demonstrated as better overall blood sugar levels, fewer episodes of hyperglycemia or

hypoglycemia, fewer complications from DM, shorter length of hospital stay, and fewer

readmissions to the hospital. Because of time constraints the perceived benefits of the

participants were not measured and recorded.

Perceived barriers to action. Presence of barriers to complete an action can be

counterproductive. It is key to identify and address any perceived barriers that can prevent a

person from performing a health-promoting behavior. The perceived barriers to action may


include real, anticipated, or imaginary blocks that can hinder the completion of a health-

promoting behavior (Pender et al., 2015). Examples of perceived barriers can include inadequate

knowledge of DM, lack of health insurance, unavailability of follow-ups, fear of medication

side-effects, fear of relapse in treatment, and social stressors. Evaluation of perceived barriers by

interviewing the patients and finding potential solutions to the perceived barriers was also part of

the project.

Perceived self-efficacy. Perceived self-efficacy implies an individual’s capability of

organizing and performing a health-promoting behavior (Pender et al., 2015). The higher the

perceived self-efficacy, the more the chances of accomplishing the health-promoting behaviors.

The project employed measures to improve the self-efficacy of the participants in the form of

diabetes education to improve knowledge. Improvement in perceived self-efficacy can, in fact,

mitigate the influence of perceived barriers that can, in turn, motivate health-promoting

behaviors.

Activity-related affect. Activity-related affect implies emotions or subjective feelings

that occur during, before, and after a given health-related behavior. The subjective feelings can

be positive or negative. If the activity-related affect is positive, it can in turn increase perceived

self-efficacy that can further reinforce a health-promoting behavior. On the other hand, if the

activity-related affect is negative the activity will be terminated (Pender et al., 2015). For

instance, if the hospitalized DM patients enjoy the subjective feelings of improved blood sugars

by adhering to medications and dietary modifications, the chances are more for these individuals

to continue the health-promoting behavior (adherence to medications and recommended diet).

Interpersonal influences. Humans are social animals, and interpersonal influences often

impact their behavioral aspects. Interpersonal influences can include peers, family, models,


social norms, social support, and even the influence of providers (Pender et al., 2015).

Interpersonal influences result from individuals’ comprehension of the beliefs of others

concerning a particular behavior. For example, in the EBP project, it was important to

understand the patients’ interpersonal influences that can potentially improve the participants’

knowledge, treatment adherence, and self-management skills. The interpersonal influences were

assessed by effectively communicating with the patients and evaluating the demographic details

of the patients from the hospital medical records.

Situational influences. Situational influences include cognitions and perceptions of an

individual that can facilitate or dismiss a given behavior. Situational influences involve cognition

of available options, demand characteristics, and the aesthetic outlook of the environment where

the proposed health-promoting behavior will take place (Pender et al., 2015). For example, in

hospitalized patients with DM, the perception of available options may include the availability of

oral anti-diabetics with minimal side effects versus using injectable forms and availability of low

carbohydrate foods that are more appealing to the patient. The availability of an effective oral

anti-diabetic agent may motivate a patient with treatment adherence who is afraid of injectable

forms. Demand characteristics may involve the nature and magnitude of motivation from the

providers to perform a health-promoting behavior. The more the patients are motivated, the more

the likelihood of the patients engaging in health-promoting behaviors. Assessment of situational

influences was done by interviewing the patients, and the influences were optimized by the

provision of more appealing choices to improve health-promoting behaviors in these patients.

Commitment to a plan of action. This particular step in the HPM involves the intention

to perform and the creation of a planned strategy to carry out a health-promoting behavior

(Pender et al., 2015). This is one of the critical stages in the HPM where the individuals commit


to a plan and identify strategies to reinforce the health-promoting behaviors. Commitment to a

plan of action needs intense and deliberate efforts from the patients. While committing to a plan

of action the individuals have not reached the end point of the HPM. There are more hurdles to

overcome before reaching the endpoint.

Behavioral Outcome

Behavioral outcome is the third major proposal in the HPM. This involves immediate

competing demands and preferences along with the final step of health-promoting behavior.

Immediate competing demands and preferences. Immediate competing demands

involve other behaviors over which the patients have low control and can counteract the efforts

of involving in the health-promoting behavior (Pender et al., 2015). Examples of immediate

competing demands may include work schedule and social responsibilities that may affect

effective performance of health-promoting behaviors. On the other hand, immediate competing

preferences are other behaviors over which patients have reasonably high control (Pender et al.,

2015). An example of an immediate competing preference may include a patient’s option to take

an oral antidiabetic versus to skip it at a given time. Both immediate competing demands and

preferences can affect the successful implementation of health-promoting behaviors, and they

need to be tackled effectively. For the patients in this EBP project, the immediate competing

demands and preferences were assessed and tackled with educational interventions.

Health-promoting behavior. The HPM culminates in the health-promoting behavior,

which is the intended behavioral outcome. The intended goal of the behavioral outcome is

fulfilled once the individual becomes cognizant of the beneficial effects of a health-promoting

behavior and becomes compliant with the health-promoting behavior (Pender et al., 2015). The

intended outcomes of the project are improved patient knowledge and improved medication


adherence. These outcomes were measured with pretests and posttests that measured the

respective outcomes with the implementation of the project.

Concepts and Definitions in the Project

The project involves the utilization of many concepts and definitions. Therefore, a better

understanding of the concepts and definitions used is important to get a better idea of the project.

Knowledge

Knowledge implies a logical prerequisite for performing a health-related behavior

intentionally (Qurieshi, Ganesh, Leelamoni, & Kurian, 2016).

Medication Adherence

Medication adherence implies the degree to which the behavior of medication intake

correlates with the recommendations of the provider (Bukhart & Sabate, 2003).

Diabetes Self-Management Education

Diabetes self-management education (DSME) is an ongoing process of promoting and

advancing the skills, ability, and knowledge needed for self-care in patients with DM. The

objectives of DSME involve supporting self-care behaviors, decision making, problem-solving,

and collaborating with healthcare personnel to improve health status, quality of life, and clinical

outcomes (Haas et al., 2013).

Diabetes Self-Management Support

Diabetes self-management support (DSMS) involves activities that help the individuals

with diabetes or pre-diabetes in initiating and sustaining behaviors necessary to manage their

condition on a continuous basis beyond training in self-management. The DSMS involves

clinical, psychosocial, educational, and behavioral support (Haas et al., 2013). The diabetes self-


management support and diabetes self-management education are often referred together as

diabetes self-management education and support (DSMES).

Literature Review

Synthesis of evidence on inpatient diabetes self-management programs was relevant to

plan the proposed project effectively. The first step in the synthesis of evidence was to conduct a

literature search on inpatient diabetes self-management programs.

Literature Search Strategies

The objective of the literature search was to identify all the available original research

studies that involved topics including hospitalized patients with diabetes mellitus and inpatient

management including the use of DSMES. The search terms used included “nurse-led diabetes

self-management education,” “diabetes self-management support,” “inpatient diabetes care,”

“hospitalized diabetes patients,” “inpatient diabetes education,” “inpatient diabetes

management,” “inpatient diabetes program,” et cetera. A limit was made on the published dates

for no more than five years from the time this project was conducted. Most of the literature

search was done using the major electronic databases including Cumulative Index to Nursing and

Allied Health Literature (CINAHL), Medical Literature On-Line (MEDLINE), Cochrane

Library, and ProQuest. The search criteria were refined to full-text and peer-reviewed articles.

The Google Scholar and PubMed were also used to identify the research articles using the same

search terms that were used for the electronic databases. The Boolean operators such as “AND,”

and the truncation symbol asterisk were also used for searching the articles.

Diabetes Self-Management Education and Support

In the previous versions of National Standards on Diabetes Self-Management Education

and Support, the DSME and DSMS were mentioned separately. However, in the latest version,


the DSME and DSMS are integrated together to form the DSMES. The DSMES forms the basis

of the proposed project. The DSMES involves a continuous process of improving the skill,

knowledge, and ability needed for self-care of diabetes and prediabetes along with activities that

aid a person in initiating and sustaining the behaviors required to manage one’s condition on a

continuum outside of formal training in self-management (Beck et al., 2017). There is a large

body of literature available on the effectiveness of DSMES in the improvement of DM.

Use of DSMES has been associated with improvement in different clinical aspects of

diabetes management of individuals. Evidence suggests significant improvement in glycemic

control in DM with the use of DSMES (Chrvala, Sherr, & Lipman, 2016; Cooke et al., 2013).

Improved quality of life from DSMES has also been reported (Cooke et al., 2013). Use of

DSMES has also been associated with improved self-care behaviors (Tang, Funnell, & Oh, 2012)

and decreased distress related to DM (Fisher et al., 2013).

Use of DSMES has been associated with not only improvement in the clinical aspects of

DM but also with improved economic and healthcare aspects related to DM. Evidence suggests

that DSMES can reduce hospital readmissions and hospital admissions in patients with DM

(Duncan et al., 2011; Healy, Black, Harris, Lorenz, & Dungan, 2013). Use of DSMES has been

found to decrease healthcare costs secondary to a decreased risk for complications (Brown et al.,

2012). In fact, DSMES seems to be an ultimate tool for effective management of DM. However,

literature available on the use of DSMES by nursing personnel in improving diabetes care in

inpatient settings is scarce.

Diabetes Self-Management Education and Support in Hospitalized Patients

The literature available on the use of DSMES in hospitalized patients is reviewed and

evidence on inpatient DSMES is synthesized here. Three studies are reviewed here and these


three studies are dated not less than five years from the time this paper was written. Please see

Table A1 in Appendix A for further details and the literature review matrix.

Magee et al. study. The study by Magee et al. (2014) was a pilot study that was

prospective and non-randomized conducted in a teaching hospital in the United States. The study

assessed the effectiveness of an inpatient knowledge-based skills education on diabetes on

medication adherence, patient knowledge, and hospital admissions or visits to the ED in the

specified time period. The design was a one-group pretest-posttest design without any control

groups. The education program was developed and designed by a multidisciplinary team

following the key areas suggested by the Joint Commission and the ADA (Magee et al., 2014).

The researchers collected patient demographics and clinical history on baseline visits

including a history of prior hospitalizations or ED visits within the previous three months of the

current hospitalization. The patients were given the Diabetes Knowledge Survey along with the

Medication Adherence Questionnaire (MAQ). The initial evaluation was followed by the

diabetes education program that included the patients watching the Diabetes to Go DVD with

specific stress on the areas of knowledge deficit evident on the initial survey and other mandated

contents. The education program reinforced key concepts with repetitions. Upon discharge, the

patients were provided with copies of the DVD and a companion Diabetes to Go book. The

patients were contacted via phone at two weeks and three months to assess MAQ and inquire

about any further hospitalizations following discharge (Magee et al., 2014).

The important outcomes of the study were to assess the changes in patient knowledge and

changes in medication adherence. There was a significant improvement in diabetes knowledge

assessed with Diabetes Knowledge Survey after the education program as evidenced by an

improvement in the percentage of patients getting five out of eight questions correctly in the


pretest and posttest (61% Vs. 89%, p < .0001). The medication adherence measured by MAQ

also showed improvement from the pretest and posttest readings. When compared to the

baseline, the odds of the patients being highly adherent as per MAQ were significantly higher at

two-week (OR = 2.85, 95% CI [1.77, 4.58], p = <.0001) and three-month intervals (OR = 3.75,

95% CI [2.06, 6.81], p = <.0001) (Magee et al., 2014).

Although this is a pilot study, the sample of the study was relatively large. This study is a

well-designed controlled trial without randomization. Therefore, the study has a level three

evidence as per the Melynk levels of evidence (Melnyk, & Fineout-Overholt, 2015). The study

findings provide evidence to suggest that inpatient DSMES can improve patient knowledge of

DM and enhance medication adherence.

Korytkowski et al. study. The study by Korytkowski, Koerbel, Kotagal, Donihi, and

DiNardo (2014) was a randomized controlled trial (RCT) to evaluate the effectiveness of

DSMES in hospitalized patients. The study outcomes involved improved glycemic control and

improved patient satisfaction in care when compared to the control group. The study outcomes

also included measurement of patient knowledge and health status. The study involved 21

patients randomized into two groups, one group that received DSMES and the other group that

received routine care. A CDE evaluated the patients in the study group with the modified

Michigan Diabetes Knowledge Test (DKT). The CDE developed individualized and structured

educational plans after assessment of the respective DKTs. The topics of educations also

involved early identification of hypoglycemia and hyperglycemia, information of medications,

use of glucometer, sick day management, and meal planning. The patients in the control group

also took the DKT and received a routine hospital guide on diabetes. Educational needs of the

control group were also addressed but were not given any structured education (Korytkowski et


al., 2014). At the time of enrollment, all the participants finished the Medical Outcomes General

Health Survey (MOS SF-36) and the Diabetes Treatment Satisfaction Questionnaire (DTSQ). An

inpatient DTSQ referred to as DTSQ-IP was also completed by all the participants before

discharge. Capillary blood glucose (CBG) levels measured with a glucometer were recorded on

the admission day, the first day of study, and on the discharge day (Korytkowski et al., 2014).

Although not statistically significant, the education group had low DKT scores when

compared to the usual care group for patients not treated with insulin (p = 0.17) and for those

treated with insulin (p = 0.09). Both groups had similar scores with MOS SF-36 except for

perceived general health. The Education Group reported more perceived general health when

compared to the control group. Both groups had similar DTSQ scores except for the perception

of hyperglycemia, which was more in the control group both during (p = 0.04) and before

hospitalization (p = 0.03). In the DTSQ-IP, the Education Group reported better satisfaction with

inpatient treatment. The Education Group had a mean lower CBG at discharge (p = 0.02) when

compared to the control group while both groups had similar mean CBG on admission and the

beginning of the study. The Education Group had less documented episodes of severe

hypoglycemia and severe hyperglycemia when compared to the control group (Korytkowski et

al., 2014).

Although the study sample is small, this is a well-executed RCT. Therefore, the study has

a level two evidence as per the Melynk levels of evidence (Melnyk, & Fineout-Overholt, 2015).

The study findings provide evidence to suggest that inpatient DSMES can improve patient

outcomes in patients hospitalized with DM.

Debussche et al. study. The study was an RCT that was done on Reunion Island. The

objective of the study was to evaluate the effectiveness of an inpatient intensive education


program along with subsequent quarterly outpatient visits by dieticians and nurses on blood

sugar control, exercise, and dietary habits in type 2 DM patients. The Reunion Diabetes study

referred to as REDIA Prev-2 involved participants from The Regional Hospital of Reunion

Island. The participants were invited to the study after completing an inpatient education

program by a dietician, a nurse educator, and an exercise physiologist. The study topics involved

understanding DM, blood glucose control, dietary modifications, prevention of foot

complications, and physical activity. The participants then completed questionnaires and had

their baseline measurements taken. The participants were randomized to the study group and

control group before discharge from the hospital (Debussche et al., 2012).

The treatment group had quarterly outpatient visits at three, six, and nine months with a

nurse and a dietician. Both the treatment group and the control group were encouraged to

continue their routine follow-up visits. Both the groups were evaluated at 12 months. The

primary outcome measured at 12 months was the change in hemoglobin A1C (HbA1C).

Although the mean HbA1C decreased (p <.0001) in both groups at 12 months when compared to

the baseline, the differences between the control group and the treatment group were not

statistically significant (p = 0.22). The average triglyceride levels in the intervention group

increased while the triglyceride levels in the control group (the group that received only inpatient

education) decreased (p < 0.03). Over a one–year period, there was a considerable decrease in

the total energy intake, improvement in protein and fat percent values, and the saturated-to-

unsaturated fatty acid intake in both groups, even though there was no significant difference

between the treatment and the control groups. The findings of the study confirm no added

benefits of routine outpatient visits after provision of an inpatient diabetes education program.

However, the study demonstrates the effectiveness of self-management education in improving


diabetes outcomes as evidenced by an improvement in the outcomes in both the intervention and

the control group after receiving the inpatient diabetes education.

Being an RCT, the study has a level two evidence as per the Melynk levels of evidence

(Melnyk, & Fineout-Overholt, 2015). The sample size of the study was adequate as the

researchers mentioned an adequate statistical power of the study to make comparisons between

the study groups. Evidence generated by the study suggests the potential use of inpatient DSMES

in improving outcomes of diabetes including the improvement in average blood sugars.

Synthesis of Evidence and Strength of Evidence

Based on the literature review on inpatient DSMES, the following conclusions have been

made. Out of the three studies reviewed, only two of them were RCTs and had level two

evidence as per the Melynk levels of evidence. The third study was a pilot study with level three

evidence with a relatively large sample and well-designed controlled trial, although not

randomized. All the studies reviewed demonstrated improved diabetic outcomes from the use of

inpatient DSMES. However, it was hard to find any systematic reviews or meta-analyses on

inpatient DSMES that would have provided a level one evidence which is the highest level of

evidence as per the Melynk levels of evidence.

The literature reviewed on inpatient DSMES primarily involved studies conducted in the

United States except for one study on an island in the Indian Ocean (Debussche et al., 2012). The

samples involved in the studies had individuals hailing from different ethnicities, different

socioeconomic classes, and speaking different languages. For example, the Magee et al. (2014)

primarily involved African American women, and the Debussche et al. (2012) study employed a

diverse population on an island in the Indian Ocean. The diversity of the samples involved in the

study improves the generalizability of the findings from these studies. The sample sizes involved


in the studies reviewed are also adequate except for the Korytkowski et al. (2014) study that had

a sample size of 21. A reasonable sample size in all the studies reviewed also adds to the

generalizability of the findings from these studies to the adults with DM.

While considering the major outcomes of the study, only the outcomes of interest in the

proposed project are reviewed here. The outcomes of the proposed project are improved patient

knowledge of DM and improved medication adherence. Improved patient knowledge of DM as a

major outcome of the study was addressed by two studies. The Magee et al. (2014) study

reported significant improvement (61% Vs. 89%, p < .0001) in the patient knowledge of DM

after provision of inpatient DMSES over the period of the study. On the other hand, the

Korytkowski et al. (2014) study did not show any reasonable improvement in patient knowledge

of DM from inpatient DSMES, and in fact, the control group had better scores on DKT than the

experiment group although not statistically significant (p = 0.17). Therefore, both the pilot

studies reviewed provide conflicting evidence on the beneficial effects of inpatient DSMES in

improving patient knowledge of DM. Although the Korytkowski et al. (2014) study is an RCT

that has higher level of evidence than the Magee et al. (2014) study, the sample size involved in

Korytkowski et al. (2014) study was relatively small and the measurement of diabetes knowledge

was not statistically significant (p = 0.17). Meanwhile, the Magee et al. (2014) study had a

relatively larger sample although it provides a level three evidence because of being a quasi-

experimental study. Therefore, one can argue that the findings of the Magee et al. (2014) are

more reliable in commenting on the effects of inpatient DSMES on diabetes knowledge.

Patient medication adherence from inpatient DSMES was evaluated by Magee et al.

(2014) study. Employment of inpatient DSMES showed improved likelihood of patients being

adherent to their medications measured by MAQ in participants at 14-day (OR = 2.85, 95% CI


[1.77, 4.58], p = <.0001) and 90-day intervals (OR = 3.75, 95% CI [2.06, 6.81], p = <.0001)

(Magee et al., 2014). Being a quasi-experimental study the Magee et al. (2014) study provides

level three evidence on the effectiveness of inpatient DSMES in improving medication

adherence in patients with DM.

Finally, the Debussche et al. (2012) study did not directly measure any of the outcomes

of interest in the proposed project. The study findings suggest no significant benefits of routine

outpatient visits following an inpatient DSMES. However, the study showed improvement in the

overall outcomes of diabetes from the provision of inpatient DSMES as evidenced by

improvement in the outcomes of both the intervention group (the group that received outpatient

follow-up visits) and the control group (the group that received only inpatient DSMES).

Therefore, the study provides an idea of how inpatient DSMES can impact the knowledge of the

patients that can, in turn, reflect an improvement in the outcomes of DM.


Chapter III


Implementation of the Project

Methodology

The domain of the project was primarily quantitative. The participants involved patients

with DM who were admitted to a community hospital on the west coast. The inclusion criteria

for the project comprised adults greater than 18 years old but less than 66 years old with a

diagnosis of DM type 1 or type 2 who were hospitalized as inpatients for any acute conditions

(related to DM or not). The inclusion criteria also involved participants who can read, speak,

write, and understand English. Any participants who cannot actively participate in the project

including patients with cognitive impairments, sensory impairments, and critically ill patients

were not involved in the study. Individuals with newly diagnosed DM during the current

hospitalization and any pregnant or nursing women were excluded from the study.

The potential participants were identified from the daily list of inpatients with DM who

were admitted to the facility where the project was conducted. The majority of the participants

came from the patient population directly under the care of the principal investigator. Nurses in

the respective units who were involved in the care of patients with DM also helped to identify

participants who could potentially benefit from the project. A flyer on the project was given to

the potential participants by the principal investigator and unit nurses. A copy of the Project

Flyer can be seen in Appendix C.

The first session started with the participants signing the informed consent followed by

the introduction of the project. Please refer to Appendix D for a copy of the informed consent.

The project involved assessment of the participants’ knowledge of DM using the Revised

Diabetes Knowledge Test (DKT2) and medication adherence using the Morisky, Green, and

Levine Adherence Scale also referred to as the MAQ. The initial DKT2 and MAQ formed the


pretest. Permission was obtained to use the DKT2 and MAQ for the project. Please see Appendix

E for a copy of DKT2 and Appendix F for a copy of MAQ.

After obtaining the baseline data, the subjects participated in a one-to-one non-structured

education that included the delivery of DSMES with the use of a brochure on American

Association of Diabetic Educators (AADE) seven Self-Care Behaviors™ designed by the

principal investigator. Please see Appendix G for a copy of the brochure. The seven self-care

behaviors referred to as AADE7 Self-Care Behaviors™ are healthy eating, active lifestyle,

monitoring blood sugars, medication adherence, problem-solving, risk reduction, and healthy

coping (AADE, 2017). The project ended by obtaining posttest surveys using the DKT2 and

MAQ from the same participants after the delivery of the DSMES. The second session was done

as a separate session 24 hours after the first session.

Survey research was employed in data collection. A survey is devised to extract data on

the distribution, prevalence, and interrelations of phenomena in a given population. Surveys are

dependent on participants’ self-report on a number of questions designed by the investigator.

Survey research includes personal interviews, telephone interviews, questionnaires, etc. While

interviews are administered by the investigators, questionnaires are often self-administered (Polit

& Beck, 2017). Therefore, the two self-administered questionnaires (SAQ) in the form of DKT2

and MAQ were used in the data collection. Both the questionnaires used in the project have

fixed-alternatives also referred to as closed-ended questions.

Needs Assessment

A needs assessment implies the careful examination of a given situation in which things

are being done and determining how things need to be done for an overall improvement of the

situation (University of Minnesota, 2017). The needs assessment process for the project involved


informal conversations with the healthcare providers at the facility where the project was

conducted. The main concerns of the providers regarding the care of DM patients admitted to

this hospital were poor medication adherence, lack of knowledge of DM, and frequent

hospitalizations. Lack of awareness on DM among the family and friends of the DM patients also

aroused as a major concern. Often there were incidences when the DM patients had uncontrolled

blood sugars from the food and other concentrated sugars brought in by the friends and families

visiting these patients. The unavailability of a structured DSMES at the facility also evolved as a

major concern in the care of inpatients with DM. Informal conversations with the registered

nurses (RN) taking care of the DM patients also revealed the same concerns that the healthcare

providers had raised. Some of the RNs also reported certain patients refusing insulin injections at

times because of unclear reasons.

Project Design

A single group descriptive, pretest-posttest design was used to implement the project,

which involved the use of a nurse-led DSMES program to help improve patient knowledge of

DM and improve medication adherence. The design did not include any randomization as the

project involved only a single group. The sampling method employed was convenience

sampling. The primary outcomes of the project measured were patient knowledge of DM and

medication adherence both before and after the provision of the DSMES program.

Data Collection Tools

The data collection tools mainly involved the DKT2 and MAQ. The initial version of the

Diabetes Knowledge Test (DKT) was created by experts in diabetes care and diabetes education

and was published in 1998. The DKT can be used to assess client knowledge in patients with

type 1 and type 2 DM. The DKT involves a 23-item questionnaire, 14 of which assess general


knowledge of DM and the rest of the questions assess the patient knowledge of insulin.

Therefore, the DKT may involve only 14 questions if the patient being assessed is not using

insulin and can involve 23 questions if the patient with DM is also using insulin. The DKT was

updated to make the DKT2, and this also involves 23 questions. The DKT2 is a reliable and valid

tool for assessing the general knowledge on DM in patients with type 1 and type 2 DM. The

structure and core content of the DKT2 is similar to that of DKT, thereby robustness and

generalizability of DKT2 are almost identical to that of DKT (Fitzgerald et al., 2016).

The MAQ is a four-item questionnaire with a yes or no format. If the answer to a

question is yes, then it corresponds to zero points, and if the answer to a question is no, then it

corresponds to one point. The score for MAQ ranges from zero to four, zero being the highest

(most adherent) and four being the lowest (least adherent). The MAQ has good predictive

validity (Morisky, Green, & Levine, 1986). According to Culig and Leppee (2014), the MAQ is

closest to the gold-standard among self-reported scales of medication adherence although the

reliability is better with some other scales. A systematic review by Perez-Escamilla, Franco-

Trigo, Moullin, Martinez-Martinez, and Garcia-Corpas (2015), showed that the MAQ showed

similar indicators of validity and reliability as the other commonly used self-reported scales of

medication adherence.

Validity and Reliability of the Data Collection Tools

Validity

Validity reflects how well a tool can measure what it is supposed to measure (Polit &

Beck, 2017). While referring to validity, there are different types of validity that are discussed

below.


Content validity. Content validity implies the adequacy of an instrument in covering all

the concepts related to the phenomenon being evaluated (Mateo & Kirchoff, 1999). There are no

objective methods to measure content validity, and researchers often seek expert opinion for

evaluating content validity of new instruments. Expert opinions on each item on an instrument

are used to calculate the content validity index (Polit & Beck, 2017). Since the instruments used

in this project are not new, the calculation of content validity index was not used. On the other

hand, when referring to the content validity of an instrument one can refer to literature on expert

reviews on the instrument, specifically published reports on the testing and development of the

instrument (Tappen, 2016). Therefore, the content validity of the instruments used in the project

was confirmed using literature available on testing and development of the instruments. The

study by Fitzgerald et al. (2016) showed that the DKT2 is a valid tool for assessing the general

knowledge on DM in patients with type 1 and type 2 DM. The study by Morsiky, Green, and

Levine (1986) showed that MAQ is a valid tool in measuring self-reported medication

adherence.

Criterion-related validity. Criterion-related validity can be either concurrent validity or

predictive validity. Predictive validity reflects the ability of a tool to predict the future behavior

or performance of an individual, while concurrent validity refers to the ability of a tool to

measure a respondent’s status to a criterion at a given time (Mateo & Kirchhoff, 1999). The

study by Morsiky et al. (1986) showed that MAQ has good predictive validity. Concurrent

validity of an instrument can be evaluated by reviewing the instrument’s ability to measure a

given concept when compared to a golden standard (Mateo & Kirchhoff, 1999). A literature

search did not reveal any golden standard for measuring the knowledge of DM in patients.

However, a recent study by Dawson, Walker, and Egede (2017) revealed a modest correlation


among three common scales that are used to assess diabetes knowledge and one of the scales was

the DKT. The correlation among the scales used to measure the knowledge on DM indicates the

concurrent validity of DKT.

Construct validity. Construct validity refers to the ability of an instrument to adequately

measure an underlying concept (Mateo & Kirchhoff, 1999). In other words, construct validity

confirms if the scores on an instrument are reflective of the degree to which individuals possess

the measured trait (Glod, 2014). For example, when compared to the pretest scores if the scores

on DKT2 improve on a majority of subjects after the provision of DSMES, this is a proof of the

construct validity of the instrument. Similarly, if the MAQ scores of individuals improve after

the provision of DSMES, this will indicate the construct validity of the instrument.

Reliability

Reliability reflects the consistency and accuracy of the information obtained from a study

(Polit & Beck, 2017). Three aspects are considered while determining the reliability of

instruments, which are stability, equivalence, and homogeneity (Mateo & Kirchhoff, 1999).

Stability. The stability of an instrument implies its ability to measure the concept being

studied consistently, and it is evaluated using test-retest reliability. Test-retest reliability is

measured by administering a given instrument to the same individuals at two different occasions

and comparing the scores to derive a correlation. A period of two to four weeks is recommended

between the testing times. Reliability coefficients range between zero and 1.00. The higher the

value, the greater is the reliability of the tool (Mateo & Kirchhoff, 1999). Stability of the

instruments used in the project can be obtained by getting test-retest reliability by providing the

instruments to the study subjects if they happen to get re-hospitalized two to four weeks after the

provision of the initial tests. However, none of the study participants get re-hospitalized during


the timeline of the project. Therefore, the test-retest reliability of the instruments could not be

done during this project.

Equivalence. Equivalence of instruments used can be determined by having two or more

observers use the tool to evaluate the measured trait, which is referred to as interrater reliability.

The scores obtained by the two observers have to be similar to demonstrate adequate interrater

reliability (Mateo & Kirchhoff, 1999). Interrater reliability of the instruments used for the project

can be determined by having the author provide an instrument (DKT2) to a subject, followed by

a nurse or another healthcare personnel providing the same instrument to the same subject at a

later time. If the scores on both the instruments are similar, then it can be inferred that the tool

has good interrater reliability. The interrater reliability of the instruments was not evaluated

during this project because of time constraints.

Homogeneity. The homogeneity of an instrument is often determined by calculation of

Cronbach’s alpha coefficient. Cronbach’s alpha is used to determine that the individual items in

an instrument measure the same concept. A Cronbach’s alpha of 0.70 or more is usually

considered acceptable (Glod, 2014). The original study by Morisky et al. (1986) showed a

Cronbach alpha for MAQ of 0.61. On the other hand, Cronbach alpha for DKT2 in the original

study was 0.77 for the general test and 0.84 for the insulin use subscale (Fitzgerald et al., 2016).

Plan for Data Analysis

The plan was to do the data analysis using the Statistical Package for the Social Sciences

(SPSS). Descriptive statistics were planned to be done using SPSS while referring to the

participants’ age and mean DKT2 scores. The independent variable in the project is DSMES, and

this is a categorical variable with two levels (with the provision of DSMES and without the

provision of DSMES). The dependent variables are patient knowledge of DM and medication


adherence. Among the dependent variables, medication adherence measured with MAQ and

patient knowledge of DM measured with DKT2 are scalar variables. As such, the effects of

DSMES on MAQ and DKT2 were planned to be done using the related sample t-test. Related

sample t-test also referred to as the dependent samples t-test is used to compare a group to itself

at two separate times (Kim & Mallory, 2017).

Resources Needed

The resources needed for the project implementation included the materials necessary for

assessment of patient knowledge on DM and evaluation of medication adherence. The materials

for the project were primarily the copies of DKT2 and MAQ. Copies of brochures on AADE7

Self-Care Behaviors™ and flyers on the project were also needed. No additional staff or

assistance was needed for provision of the project to the participants. An adequate number of

copies of the patient education brochures were also needed. Data collected were filed into a

Microsoft Excel sheet and later transferred to SPSS software. A secure file organizer was used to

keep the data collected from the participants that had protected health information (PHI).

Project Budget

The data collection tools are DKT2 and MAQ. The budget needed for making copies of

DKT2 and MAQ was relatively cheap. A reasonable price of $0.10 per copy was spent to make

the needed number of copies for DKT2 and MAQ. Thirty copies of DKT2 and MAQ were made,

three dollars each with a total of six dollars. Thirty copies of informed consent cost another three

dollars. A reasonable price for making color copies for the brochure was $0.89 per copy. For 30

copies of the brochure, the budget was $26.70. Color copies of 30 flyers cost $26.70. Stationery

supplies needed for the project was around $70. Purchasing SPSS under student discount cost


$35.99. The total cost for the project was around $200. The estimated budget and the real budget

for the project were reasonable.

Project Timeline

The estimated project timeline was six months. This timeline included the time for

implementation of the project in a reasonable number of participants. The timeline also included

the time needed for data collection, data analysis, and arriving at conclusions. The project

timeline was mainly influenced by the time required for approval of the project from the

Maryville University Institutional Review Board (IRB) to commence the project. The estimated

project timeline and the time required to complete the project was more or less the same.

Protection of Human Subjects

The hospital where the study was conducted has no IRB. The IRB approval was sought

only from Maryville University IRB. The participants were provided with informed consents of

the project including the purpose, risks, benefits, protection of privacy, and voluntary

involvement or withdrawal. The participants were assured that their involvement is completely

voluntary and their participation in the project will not affect the care or treatments during the

hospitalization. The participants were informed that there will not be any penalty for withdrawal

from the project.

A secure file organizer was used to keep the data collected from the participants that have

PHI such as the participants’ age and diagnosis of DM. A secure file organizer is a document

holder with a lock that can be accessed only by the principal investigator and the head of the

hospital Quality Assurance (QA) department. The data were stored in a password protected

computer in the QA office that has access only to the principal investigator and the QA head.

The participants were identified using numeric codes corresponding to the participant names. All


the identifiable data will be disposed of securely by shredding all the papers and erasing all the

electronic data as soon as the completion of the project.


Chapter IV


Data Analysis

Data analysis was done using the SPSS. Descriptive statistics were done using SPSS

while referring to the participants’ age and mean scores of DKT2. The independent variable in

the project is diabetes education, and this is a categorical variable with two levels (before and

after the provision of DSMES). The dependent variables are patient knowledge of DM and

medication adherence. Among the dependent variables, medication adherence measured with

MAQ and patient knowledge of DM measured with DKT2 are scalar variables.

The effects of diabetes education utilizing DSMES on MAQ and DKT2 was done using

the related sample t-test. The study evaluated the effectiveness of diabetes education using

DSMES in the same group before and after the provision DMSES. A t-test is a parametric

method for determining the differences in the group means. When comparing the group means of

the same group before and after the provision of treatment, then the paired t-test or the related

sample t-test can be employed (Kim & Mallory, 2017).

Statistical Analysis

Descriptive Statistics

Statistical analysis was done by obtaining descriptive statistics. Descriptive statistics

imply the description of the data in a research study. Descriptive statistics analyze data that help

to condense the trends that are reflected in the data (Kim & Mallory, 2017). The sample size is

10, and the mean age of the participants is 46 years with a standard deviation of 9.37. More than

one 57-year-old individuals were involved in the analysis as evidenced by a mode of 57. Please

be also aware that there is more than one mode for some measurements and the smallest among

them are reported in the table in the respective columns. The mean score on the DKT2 before the

intervention was 73 and after the intervention, the score was 79.5. Please see the descriptive


statistics in Table 4.1. More than 50% of the participants in the project were Hispanics, followed

by Caucasians. The sample had only one Asian participant (see Table 4.2). The male to female

ratio of the sample was 1:1.

Table 4.1

Descriptive Statistics

Age DKT2 Pretest DKT2 PosttestN Valid 10 10 10

Missing 0 0 0Mean 46.50 73.04 79.56Median 48.00 73.91 80.43Mode 57 65.21a 73.91a

Std. Deviation 9.37 17.73 16.66

Table 4.2

Participant Demographics

Ethnicity Frequency Percent Valid Percent Cumulative Percent

Caucasian 3 30.0 30.0 30.0Hispanic 6 60.0 60.0 90.0

Asian 1 10.0 10.0 10.0Total 10 100.0 100.0

Inferential Statistics

The participant knowledge on DM measured with mean DKT2 before the provision of

DSMES referred to as DKT2 pretest is compared to the mean participant score on DKT2 after

the provision of DSMES described as the DKT2 posttest. The mean DKT2 pretest is 73.04 with a

standard error of 5.61, and the mean DKT2 posttest is 79.56 with a standard error of 5.27 (see

Table 4.3 for details). There is a difference of 6.52 units in the measurements before and after the


provision of DSMES. On the other hand, the participants’ compliance with medications

measured with mean MAQ is the same (62.50) before (MAQ pretest) and after (MAQ posttest)

the provision of DSMES indicating no effect of DSMES on medication adherence in the given

sample. However, the statistical significance of the differences needs to be evaluated.

Table 4.3

Paired Samples Statistics

Mean N Std. Deviation Std. Error MeanPair 1 DKT2 Pretest 73.04 10 17.73 5.61

DKT2 Posttest 79.56 10 16.66 5.27Pair 2 MAQ Pretest 62.50 10 39.53 12.50

MAQ Posttest 62.50 10 41.25 13.04

The measurements (DKT2 pretest and DKT2 posttest) are significantly correlated in this

scenario as evidenced by a correlation coefficient of .901 with an associated p-value of .000

(please see Table 4.4). Similarly, the measurements (MAQ pretest and MAQ posttest) are

significantly correlated in this scenario as evidenced by a correlation coefficient of .958 with an

associated p-value of .000 (please see Table 4.4).

Table 4.4

Paired Sample Correlations

N Correlation Sig.Pair 1 DKT2 Pretest & DKT2 Posttest 10 .901 .000Pair 2 MAQ Pretest & MAQ Posttest 10 .958 .000

The calculated t-statistic for DKT2 is -2.67 with a degree of freedom of 9 (please see

Table 4.5). The p-value here is .026. The p-value is less than .05, the preset alpha. Hence the null

hypothesis can be rejected. It can be inferred that on average, the mean DKT2 (M = 79.56, SE =


5.27) is significantly higher after the provision of DSMES when compared to the mean DKT2

before the provision of DSMES (M = 73.04, SE = 5.60), t (9) = -2.67, p = .026. The low degree

of freedom here is because of the small sample size in this EBP project.

The calculated t-statistic for MAQ is .00 with a degree of freedom of 9 (please see Table

4.5). The p-value here is 1.00. The p-value is greater than .05, the preset alpha. Hence the null

hypothesis cannot be rejected. It can be inferred that on average, the mean MAQ (M = 62.50, SE

= 13.04) is not significantly higher after the provision of DSMES when compared to the mean

MAQ before the provision of DSMES (M = 62.50, SE = 12.50), t (9) = .00, p = 1.00.

Table 4.5

Paired Samples Test

Paired Differences T Df Sig. (2-tailed)Mean Std.

DeviationStd. Error

Mean95% Confidence

Interval of the Difference

Lower Upper

Pair 1 DKT2 Pretest - DKT2 Posttest

-6.52 7.74 2.45 -12.06 -.99 -2.67 9 .026

Pair 2 MAQ Pretest - MAQ Posttest

.000 11.78 3.73 -8.431 8.431 .000 9 1.000

Results

The results of the project were very supportive of the use of DSMES in the management

of patients with DM. Statistical analysis of the data confirmed the effectiveness of the DSMES in

improving patient knowledge of DM in the inpatient setting where the project was conducted. On

the other hand, the analysis showed that the DSMES did not have any effects on the medication

adherence of the participants in the project. Nevertheless, the analysis that predicted no effects of

DSMES on patient medication adherence was not statistically significant.


Significance of the Results

Statistically speaking, the DSMES can improve the patient knowledge of DM. But what

is the clinical significance of this finding? Clinical significance implies the practical importance

of the research findings to produce genuine effects in clinical practice. The study clearly defines

the distinction between statistical significance and clinical significance. Clinical significance was

reported in terms of information on a group level. Being a single group pretest-posttest design,

for group-level clinical significance, often referred to as practical significance, confidence

interval (CI) can be used in this project (Polit & Beck, 2017). A CI of 95% was utilized in the

statistical analyses for the scholarly project that ensured the clinical significance of the results of

this project.

The project possesses the characteristics to be replicated. Data retrieved with quantitative

methods are believed to produce more accurate and objective findings because of the use of

collection methods that are standardized, and therefore, quantitative studies possess the

properties to be replicated (National Science Foundation, n. d.). The scholarly project with the

use of standardized measures such as DKT2 and MAQ can be replicated by other researchers.


Chapter V


Discussion

The EBP project was designed as an answer to the PICOT question: In patients with DM

(P) who are admitted to a local community hospital on the west coast during a six-month period

(T), what are the effects of a nurse-led DSMES project (I) in improving (C) their knowledge on

DM and their compliance with the treatment strategies (O)? The EBP project had confirmed the

effectiveness of DSMES delivered by nurses to improve the patient knowledge of DM. On the

other hand, the medication adherence measured by the MAQ did not change as a result of the

intervention in the scholarly project. The project (educational intervention with the posttest done

in 24 hours) was done in a 24-hour period and 24 hours may not be enough for the participants to

have a change in their medication adherence behavior.

Provision of DSMES has been found to be cost-effective by decreasing hospital

admissions and readmissions (Healy et al., 2013). The DSMES is a relatively cheap tool that can

be used in healthcare organizations where DM patients seek medical attention. Training nurses in

the provision of DSMES are relatively easier. Delivery of DSMES is not complicated as this

requires no use of any sophisticated teaching tools or gadgets and DSMES provision requires

relatively less time. Provision of DSMES can be easily incorporated into the routine care

provision of nurses to DM patients. Therefore, incorporation of DSMES provision by nurses into

the care of DM patients should become the standard of care.

Patient education is a vital role for all nurses (Fowler, 2012). Provision of DSMES by

nurses has the potential to improve outcomes of patients with DM. Delivery of DSMES has been

found to improve HbA1c by about 1% (Steinsbekk, Rygg, Lisulo, Rise, & Fretheim, 2012).

Regrettably, a majority of individuals with DM or pre-diabetes do not receive appropriate

DSMES services (Thalheimer, 2018). A better comprehension of evidence-based practices such


as DSMES by nurses involved in the care of hospitalized patients with DM can improve the care

outcomes (Yacoub et al., 2015).

Limitations

One of the limitations of this scholarly project is the length of time that was available to

complete the project. The approval for the project from Maryville University IRB was obtained

relatively late and this limited the time available for completing the project on time. The

relatively less time available for the DNP project resulted in recruiting a lower number of

participants within the timeframe. A small sample size was a challenge to the credibility of the

results of the project. Since this is an EBP project, no power analysis was used to obtain the

minimum number of participants needed to ensure generalization of the results of the project.

Unlike research, an EBP does not involve producing new knowledge. A minimum of 10 patients

can help generalize the results of the project because the population of interest was more or less

homogenous. Homogeneity implies the extent to which the individuals in a population match one

another while referring to the elements being evaluated in a study. Therefore, smaller samples

are sufficient if the individuals in a population are more homogenous (Terry, 2015).

Use of convenience sampling was another limitation of the project. “Although all

convenience samples have less clear generalizability than probability samples, we argue that

homogeneous convenience samples have clearer generalizability relative to conventional

convenience samples” (Jager, Putnick, & Bornstein, 2017, p. 13). As mentioned before, the

sample population was homogeneous. Although not the best type of sampling, convenience

sampling is the most frequently used sampling method in nursing research (Convenience

sampling, 2010). Convenience sampling allows quick exploration of a hypothesis (Battaglia,

2008). Another limitation of this project is that the participants included only those who can


read, write, speak, and understand English. Therefore, one can question the applicability of the

project in non-English speaking patients.

Applications to Practice

Implementation of inpatient DSMES as the standard of care in the facility where the

project was conducted is the first step. The project will improve the knowledge and thereby the

treatment adherence of inpatients with DM at the community hospital described earlier in this

paper. Improved treatment adherence can potentially decrease the complications related to poor

DM self-management and thereby prevent frequent readmissions from diabetes-related

complications to the facility. The project will be discussed in the next hospital interdisciplinary

practice committee meeting to be considered as the standard of care for patients with DM

admitted to the hospital. This project has the potential to be utilized in other facilities including

outpatient facilities for the provision of DSMES.

Implications for Future Research

Further large-scale studies in different clinical settings to evaluate the effects of DSMES

are required to strengthen the evidence of the effects of DSMES on the different aspects of

DSMES. Clinical studies using DSMES in different languages are also needed to find the effects

of DSMES on different ethnicities. Studies to evaluate the effectiveness of DSMES provision by

nurses versus other healthcare providers can compare the effectiveness of DSMES provision by

different personnel who are directly involved in the care of the patients with DM.

Conclusion

To conclude, DM is a growing epidemic in the United States and worldwide. Diabetes is

associated with increased hospitalizations, increased length of stay, and increased readmissions

(Lee et al., 2017; McCoy et al., 2017). Inadequate knowledge and poor self-management skills


have been linked to hospitalizations from uncontrolled DM (Magee et al., 2014). Diabetes self-

management education and support is the backbone to improve the care in DM (Powers et al.,

2017) and DSMES can reduce hospital readmissions and hospital admissions in patients with

DM (Duncan et al., 2011; Healy et al., 2013). The role of nurses including APNs in the provision

of DSMES remains vague. There is an imminent need for an evidence-based DSMES program to

be used as the standard of care in patients with DM. Implementation of a nurse-led DSMES

project has the potential to improve patient knowledge and diabetes self-management skills,

which can, in turn, improve treatment adherence and potentially prevent frequent hospitalizations

in patients with DM. Provision of DSMES by nurses should be considered to be utilized as the

standard of care of patients with DM not only in inpatient settings but also in other clinical

settings where the provision of DSMES is amenable.


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https://dx.doi.org/10.1016/S0738-3991(02)00032-0


ANTONY MACIDO

Antony Macido graduated with Associates degree in nursing from a community

nursing school in India in 2003. He volunteered in the rescue of victims of tsunami in

India in December 2005. He worked as a critical care nurse in India until he immigrated

to the United States in 2006. He graduated with Bachelor of Science in Nursing from

University of Phoenix in 2009. Meanwhile, Antony continued to work as a critical care

nurse until 2013. Antony graduated with a Master of Science in Nursing from University

of California Los Angeles in 2012 while achieving his certifications as a nurse

practitioner (NP) and a clinical nurse specialist (CNS). Antony has practiced as an NP in

pulmonary and critical care medicine for two years until he joined the current job as a

hospitalist nurse practitioner. In the past four years as a hospitalist NP he came across a

large number of patients with poor diabetes control and diabetic foot ulcers (DFU). This

made him passionate about making contributions to DM. Antony had already published a

review article on DFU. Pursuing his DNP with Maryville University had given him an

opportunity to show his passion with DM with this EBP project. After graduating with

DNP, he plans to continue working as a hospitalist NP while trying to enter teaching in

one of the local nursing schools.


Acronym List

AADE: American Association of Diabetes Educators

ADA: American Diabetes Association

ADC: acute diabetes related complications

APN: advanced practice nurse

CBG: capillary blood glucose

CDC: Centers for Disease Control and Prevention

CDE: certified diabetes educator

CI: confidence interval

CMS: Centers for Medicare and Medicaid Services

DKT2: Revised Diabetes Knowledge Test

DM: diabetes mellitus

DNP: doctor of nursing practice

DSME: diabetes self-management education

DSMES: diabetes self-management education and support

DSMS: diabetes self-management support

DTSQ: Diabetes Treatment Satisfaction Questionnaire

EBP: evidence-based practice

ED: Emergency Department

HbA1c: hemoglobin A1c

HPM: Health Promotion Model

IDE: inpatient diabetes education

IRB: Institutional Review Board


MAQ: Medication Adherence Questionnaire

MOS SF-36: Medical Outcomes General Health Survey

NP: nurse practitioner

PA: physician assistant

PHI: protected health information

PICOT: Patient population, intervention of interest, comparison intervention or status, outcome,

and timeframe

QA: Quality Assurance

RCT: randomized controlled trial

RN: registered nurse

SAQ: self-administered questionnaire

SPSS: Statistical Package for the Social Sciences


Appendix A

Literature Review Matrix

Table A1

Literature Review Matrix

Author, Year, & Level of Evidence

Purpose Sample Design Data Analysis Findings Strengths & Weaknesses

Magee et al., 2014.

Level of evidence = Level 3.

The study assessed the effectiveness of an inpatient knowledge-based skills education on diabetes on medication adherence, patient knowledge, and hospital admissions or visits to the emergency room in a specified time period (Magee et al., 2014).

The study sample constituted a total of 125 patients primarily African Americans and females. The study was conducted in a 900-bed teaching hospital in the United States (Magee et al., 2014). The sampling was not randomized.

This was a pilot study that was prospective and non-randomized that used a pretest-posttest design.

The researchers used the McNemar test for analyzing the changes in the proportion of data from pretest to posttest. Proportionate changes at three points were measured using odds ratios with a confidence interval of 95% derived from repeated measures logistic regression (Magee et al., 2014).

The study reported a significant improvement (61% Vs. 89%, p < .0001) in the patient knowledge on DM after provision of inpatient diabetes education. The study showed improved likelihood of patients being adherent to their medications measured by MMAS-4 in participants at 14-day (OR = 2.85, 95% CI [1.77, 4.58], p = <.0001) and 90-day intervals (OR = 3.75, 95% CI [2.06, 6.81], p = <.0001). The study also showed improvement in readmission rates and ED visits after three months following the provision of inpatient diabetes education (14% to 5.3%, p

The authors indicate the strength of their recommendations by being confident that the they “strongly suggest” improvement in medication adherences as a result of the intervention. The diabetes knowledge survey utilized to measure the diabetes knowledge in patients was locally developed, and its validity has not formally tested. The sampling was not randomized (Magee et al., 2014).


= .0588) (Magee et al., 2014).

Korytkowski et al. (2014).


The objective of the study was to evaluate the effectiveness of inpatient diabetes education on glycemic control, patient satisfaction, patient knowledge, and health status (Korytkowski et al., 2014).

The study involved a sample of 21 subjects hospitalized at a university hospital in the United States.The sampling was randomized.

The study was a randomized controlled trial.

The researchers employed student t-tests to compare group differences in DTSQ, SF36, DKT scores, and differences in CBG. Categorical data were compared using Fishers Exact test (Korytkowski et al., 2014).

The control group had better scores on DKT than the experiment group although not statistically significant (p = 0.17). The treatment group had a mean lower CBG at discharge (p = 0.02) when compared to the control group. Both groups had similar MOS SF-36 and DTSQ scores (Korytkowski et al., 2014).

The strength of the study is that it is an RCT. The sample size is relatively small, which is a major limitation of the study.

Debussche et al., 2012.


The primary outcome of the study was to evaluate the effectiveness of routine outpatient visits following an inpatient diabetes teaching program. The primary outcome measured was change in Hb A1C 12 months after hospitalization (Debussche et al., 2012).

The sample involved 398 adults with type 2 DM hospitalized at The Regional Hospital of Reunion Island. The sampling was randomized (Debussche et al., 2012).

The study was a single center RCT.

Fisher’s exact tests or the chi-square test were done as appropriate for categorical variables and the Wilcoxon rank-sum test, or student’s t-test was done for continuous variables as appropriate. Confounders were adjusted utilizing theanalysis of covariance (ANCOVA) (Debussche et al., 2012).

Although the mean HbA1C decreased (p <.0001) in both groups at 12 months when compared to the baseline, the differences between control group and the treatment group were not statistically significant (p = 0.22).

Being an RCT makes this study superior to non-randomized trials. The study sample also included multiple ethnicities that improve the generalization of the findings. Being a single center study makes it less superior. The study also had many dropouts that might have influenced the results of the study.


Appendix B

Figure 1. The Health Promotion Model that illustrates the important concepts of the model.

Adapted from The University of Michigan Library, By N. J. Pender, 1996, Retrieved

from https://deepblue.lib.umich.edu/handle/2027.42/85351. Copyright 2017 by the University of

Michigan.

https://deepblue.lib.umich.edu/handle/2027.42/85351


Appendix C

Project Flyer

Diabetes Self-Management Education

Research Project on Diabetes EducationInterested in improving your diabetes management?Your participation is voluntary.Takes less than an hour to complete.Involves some surveys to assess your knowledge on diabetes followed by teaching and repeating the surveys.

Please Contact Antony Macido, NP @ 7993


Appendix D

Informed Consent

Agreement to Participate in “A Nurse-Led Inpatient Diabetes Self-Management Education and Support Program to Improve Patient Knowledge and Treatment Adherence” Study

Antony Macido, Principal InvestigatorYou are being asked to participate in a project conducted through Maryville University by Antony Macido ACNP-BC, MSN, CNS, a Doctor of Nursing Practice student and a hospitalist Nurse Practitioner. I am working under the direction of my faculty advisor Dr. Richard Pessagno DNP, CRNP, FAANP, Associate Professor of Nursing. The University requires everyone who agrees to participate in this project to provide a signed consent to do so. The overall purpose of this research is to evaluate the effectiveness of a diabetes self-management program on improving the patient knowledge and improving the self-management skills of diabetic patients. Your participation will involve doing a survey to check your knowledge on diabetes and doing a second survey to check your compliance with taking diabetic medications. This will be followed by a brief one-to-one education by the principal investigator and repeating the two surveys that were previously done. The amount of time of your participation will be approximately 45 minutes. On the first day, two surveys will be given to you and 15 minutes will be allowed to complete the two surveys. The survey on diabetes knowledge has 23 multiple choice questions and the survey on diabetes medication adherence has four yes/no questions. Once you finish these surveys, the surveys will be collected by the principal investigator. Soon after the surveys are done, the principal investigator will have a 15-minute education on diabetes self-management and will provide you a brochure for your future reference. The brochure integrates the strategies recommended by the American Diabetes Association (ADA) for self-management of diabetes. On the following day, you will be asked to redo the two surveys that you had done on the previous day and 15 minutes will be provided to finish the two surveys. The researcher will also use your age, ethnicity, and gender to make conclusions on the study. Therefore, the researcher will ask your age, sex, and ethnicity during the consent process. This research study may include some risks or discomfort which would involve possible disappointment with a survey result and a potential for embarrassment upon realizing that your knowledge and insight about diabetes is worse than you might have thought. The researcher will help you to mitigate any such discomfort or potential disappointment that may arise from the research by explaining to you any questions, concerns, or doubts that may arise from the research. The researcher will allow you to interrupt any sessions or surveys if you feel overwhelmed. There is also a potential for perception of coercion among the participants to participate in the project because of being admitted in the hospital for an acute condition. To avoid any feeling of being coerced, you need to understand that the participation in this project is voluntary and does not have any influence on the standard of care or length of stay for your acute illness.A possible breach of confidentiality is another potential risk. The researcher will follow stringent measures to protect your confidentiality and information, and will not share any of your personal information. The researcher will safely destroy all your personal information at the end of the research. A code will be used as an identifier for your information, and only the researcher and the head of the hospital Quality Assurance (QA) department will have access to the link between your code and your name. The sheet connecting participant names to their codes will be stored along with the signed consent forms, but separately from all the other data in a separate secure document holder that can be accessed only by the principal investigator and the head of hospital QA. All the data will be stored electronically protected with a password in a computer that will be stored in a locked place that can be accessed only by the principal investigator and the head of hospital QA department. Data collecting instruments with numeric codes and all the data from the project will be destroyed by shredding as soon as the project ends. Initials ________ Date _________


All the electronic data will be deleted form the password protected computer permanently upon completion of the project. The possible benefits for you from this research are improving your knowledge on diabetes and improving your overall health. You will also receive a brochure on diabetes self-management as part of the study that you can retain with you. We do not promise any incentives for participation in this research. Your decision to participate in this research is completely voluntary and there is no penalty for withdrawing at any time. An alternative to participating in this research is not to participate in this project, and your decision is completely voluntary, and a decision of not to participate will not affect the standard care you receive for your condition/illness.The results of this study will be printed in a doctoral project and may be shared as a poster presentation or published in academic journals. The results of this study will also be shared in a presentation to the Maryville University community as a requirement for earning a doctoral degree for the principal investigator. Neither the name of the organization nor the names of the participants will be revealed while publishing the results of the study. If you have any questions regarding this study, or if any problems arise, you may call the researcher, Antony Macido at 408-368-8191or the researcher’s faculty advisor, Dr. Richard Pessagno, at 609-760-5283. You may also ask questions, state concerns regarding your rights as a research subject, or express any feelings of pressure to participate by contacting: Dr. Robert Bertolino, Chair of the Institutional Review Board at Maryville University, (314) 529-9659.Maryville University recognizes its federally mandated responsibility to ensure that research be conducted in an ethical and scholarly manner, respecting the rights and welfare of all the human participants. Any research misconduct including but not limited to fabrication, falsification, or plagiarism in proposing, performing and reviewing research, or in reporting research results, should be reported to Dr. Tammy Gocial, the Research Integrity Officer at Maryville University at (314) 529-6893.Maryville University investigators, and their colleagues who are conducting research, recognize the importance of your contribution to the research studies which are designed to improve the knowledge and care of hospitalized diabetic patients’ therapeutic care. Maryville University investigators and their staffs will make every effort to minimize, control, and treat any complication that may arise as a result of this research. If you believe you are injured solely as a result of the research question being asked in this study, please contact the principal investigator or the Chair of the Institutional Review Board. Maryville reserves the right to make decisions concerning payment for medical treatments for injuries solely and directly related to your participation in the research. By signing this form, you acknowledge that you are at least 18 years of age, that you have read and understood this form, and that you have had an opportunity to ask questions about the research project. You are voluntarily agreeing to participate in a study based on the information presented to you. You may choose to withdraw at any time without prejudice or penalty. You will receive a copy of this form, which will include the name and phone number of the researcher and the IRB at Maryville University, should you have any questions.

___________________________________________________ ______________Subject / participant’s signature Date_______________________________________ __________________ ______________Researcher’s signature Date Phone Number

The date approval stamp on this consent form indicates that the project has been reviewed and approved by the Maryville University Institutional Review Board.

Institutional Review BoardProtocol #17-80Initiation Date: April 2, 2018Termination Date: April 1, 2019Approved by: Tammy M. Gocial, Ph.D.


Appendix E

Revised Diabetes Knowledge Test

1. The diabetes diet is:

a. the way most American people eatb.* a healthy diet for most peoplec. too high in carbohydrate for most

peopled. too high in protein for most people

2. Which of the following is highest in carbohydrate?

a, Baked chickenb. Swiss cheesec.* Baked potatod. Peanut butter

3. Which of the following is highest in fat?a.* Low fat (2%) milkb. Orange juicec. Cornd. Honey

4. Which of the following is a “free food”?a. Any unsweetened foodb. Any food that has “fat free” on the labelc. Any food that has “sugar free” on the

labeld.* Any food that has less than 20 calories

per serving

5. A1C is a measure of your average blood glucose level for the past:

a. dayb. weekc.* 6-12 weeksd. 6 months

6. Which is the best method for home glucose testing?

a. Urine testingb.* Blood testingc. Both are equally good

7. What effect does unsweetened fruit juice have on blood glucose?

a. Lowers itb.* Raises itc. Has no effect

8. Which should not be used to treat a low blood glucose?

a. 3 hard candiesb. 1/2 cup orange juicec.* 1 cup diet soft drinkd. 1 cup skim milk

9. For a person in good control, what effect does exercise have on blood glucose?

a.* Lowers itb. Raises itc. Has no effect

10. What effect will an infection most likely have on blood glucose?

a. Lowers itb.* Raises itc. Has no effect

11. The best way to take care of your feet is to:a.* look at and wash them each dayb. massage them with alcohol each dayc. soak them for one hour each dayd. buy shoes a size larger than usual

12. Eating foods lower in fat decreases your risk for:

a. nerve diseaseb. kidney diseasec.* heart diseased. eye disease

13. Numbness and tingling may be symptoms of:a. kidney diseaseb.* nerve diseasec. eye diseased. liver disease

14. Which of the following is usually not associated with diabetes:

a. vision problemsb. kidney problemsc. nerve problemsd.* lung problems

15. Signs of ketoacidosis (DKA) include:a. shakinessb. sweatingc.* vomitingd. low blood glucose

16. If you are sick with the flu, you should:a. Take less insulinb. Drink less liquidsc. Eat more proteinsd.* Test blood glucose more often

17. If you have taken rapid-acting insulin, you are most likely to have a low blood glucose reaction in:

a.* Less than 2 hoursb. 3-5 hoursc. 6-12 hoursd. More than 13 hours

18. You realize just before lunch that you forgot to take your insulin at breakfast. What should you do now?

a. Skip lunch to lower your blood glucoseb. Take the insulin that you usually take at

breakfastc. Take twice as much insulin as you

usually take at breakfastd.* Check your blood glucose level to

decide how much insulin to take

19. If you are beginning to have a low blood glucose reaction, you should:

a. exerciseb. lie down and restc.* drink some juiced. take rapid-acting insulin

20. A low blood glucose reaction may be caused by:

a.* too much insulinb. too little insulinc. too much foodd. too little exercise

21. If you take your morning insulin but skip breakfast, your blood glucose level will usually:

a. increaseb.* decreasec. remains the same

22. High blood glucose may be caused by:a.* not enough insulinb. skipping mealsc. delaying your snackd. skipping your exercise

23. A low blood glucose reaction may be caused by:

a.* heavy exerciseb. infectionc. overeatingd. not taking your insulin

*Answer to the question.

The project described was supported by Grant Number P30DK092926 (MCDTR) from the National Institute of Diabetes and


Digestive and Kidney Diseases.Appendix F

Medication Adherence Questionnaire

Yes No

Do you ever forget to take your medicine?

Are you careless at times about taking your medicine?

When you feel better do you sometimes stop taking your medicine?

Sometimes you feel worse, when you take the medicine, do you stop taking it?


Appendix G

AADE7™ Diabetes Self-Care Brochure

Healthy Coping

AADE7 Self-Care Behaviors™ Healthy Eating Being Active Monitoring Taking Medication Problem Solving Reducing Risks Healthy Coping

Diabetes Self-Care


Reducing Risks

Getting Started...............................................................................................2

What to Include.............................................................................................2

Focus on What You Do Best.........................................................................2

Don’t Forget the Mission...............................................................................3

Make It Your Own.........................................................................................4


Customize in Almost No Time......................................................................4

Make It Picture Perfect..................................................................................4

Our Products and Services.............................................................................5

Problem Solving

Check if you ate more carbohydrates than usual? You may need extra insulin.

Check if you have an infection? Infections cause increase in sugars, and you may need additional medications/insulin.

Always seek expert help from your provider or diabetes educator if in doubt.

Always carry an extra snack for a low blood glucose reaction (feels shaky and sweaty) that can be caused by too much insulin, skipping a meal, or over-activity.


Regular and as needed visits to your providers including specialists are important to prevent complications from diabetes.

Look at your feet and wash them every day. Diabetes can cause kidney, nerve, and eye problems. Tingling and numbness may indicate nerve involvement. Excessive thirst, frequent urination, abdominal pain, and excessive

nausea and vomiting reflects a high blood glucose reaction. In such case, please seek medical attention immediately.

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Taking Medications


If you are using insulin, rotate the sites. Do not inject cold insulin. Know the purpose and side effects of your medications. Remain up-to-date with your pneumonia and flu vaccines. Avoid taking metformin within 48 hours of any imaging studies that

use IV contrast (please tell your provider before getting images that you are on metformin.

To try out other looks for this brochure, on the Design tab of the ribbon, check out the Themes, Colors, and Fonts galleries.Have your own company fonts or colors? No problem! Those galleries give you the option to add your own.Make It Picture PerfectTo replace any photo with your own, just right-click it and then click Change Picture.If your photo is not a flawless fit for the space, you can crop it to fit in almost no time. Just select the picture and then, on the Picture Tools Format tab, click Crop.

Healthy Eating


Diabetes diet is a healthy diet for most people. Avoid concentrated sugars like desserts, soda, etc. Eat free foods (any food with less than 20 calories per serving). Count carbohydrates and substitute complex carbohydrates for your

carbohydrate intake.

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Being Active

“Your company is the greatest. I can’t imagine anyone living without you.” —Very smart customer

Focus on What You Do BestIf you’re using this booklet for a company brochure, these middle pages are a good place for a summary of competitive benefits or some of those glowing testimonials, like the one above.

You might also want to mention a few of your most impressive clients here:

Big, important company

Really well-known company

Very impressive company

Additionally, you could include a bulleted list of products, services, or major benefits of working


with your company. Or just summarize your finer points in a few concise paragraphs.

Monitoring

A1C measures average glucose over the past 6-12 weeks.

Checking 2 hours after eating reflects the true sugar levels from eating.

Low blood glucose reaction can occur 2 hours after taking a rapid-acting insulin without food.

Blood testing is the best method of home glucose testing.

Do not use alcohol but use soap and water to clean your fingers before sugar checks.


Start slowly and gradually increase your activity to 30 minutes at a time at least 5 times per week.

Overdoing can cause a low blood glucose reaction. Keep track of your activity that will help you feel good about yourself. Check your sugars before and after exercising. Exercise without

overdoing (you can talk but not sing while exercising) can lower your sugars safely.

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