Running head: IMPACT OF A BRIEF PREDIABETES EDUCATION

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Impact of a Brief Prediabetes Education on Physical Activity, Eating Habit and Self-Efficacy in
a Rural Primary Care Setting
Yunmi Lee Evans
Arizona State University

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Chapter 1 Introduction
Background & Significance
Diabetes is a metabolic disorder characterized by high blood glucose levels resulting
from an imbalance of insulin production, insulin action, or both and if left untreated may result in
serious life-altering complications such as heart disease, stroke, blindness, kidney failure,
amputations, and nerve damage (Centers for Disease Control and Prevention [CDC], 2014).
Diabetes-related treatment efforts have consumed tremendous healthcare resources and to date,
concerted efforts to ameliorate this epidemic health issue have been of minimal success.
Prediabetes and Awareness
Prediabetes is defined as a state of impaired fasting glucose (IFG), impaired glucose
tolerance (IGT) or both. More specifically, the IFG is a fasting glucose level between 100 and
125mg/dL and the IGT is an oral glucose tolerance test glucose level between 140 and 199mg/dL
in prediabetic state (ADA, 2015; Hendelsman et al., 2011). Without any interventions, 15-30
percent of people with prediabetes will develop type 2 diabetes mellitus (T2DM) within five
years (CDC, 2014).
Although awareness of prediabetes has slightly improved from 2005 to 2010, the
nationwide unawareness of the disease remains as high as 90% (Li, Geiss, Burrows, Rolka, &
Albright, 2013). Low awareness of prediabetes is prevalent especially among the young and
poorly educated, but higher awareness exists among the overweight with a greater than a high
school education, and among those with a family history of diabetes, health insurance and a
usual source of medical care. Identifying people with prediabetes and increasing awareness of
their risk factors on developing T2DM are a critical first step (Li, Geiss, Burrows, Rolka, &
Albright, 2013).

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Lifestyle Intervention and Outcomes
General knowledge about diabetes and its risk factors, management and prevention are
significant variables to adopt health-promoting behaviors (Chen & Lin, 2010). Even though it is
a daunting task during short office visits, healthcare providers must attempt to educate and
convince patients to change their lifestyle (Geiss et al., 2010). The literature has explored
several lifestyle interventions in the treatment of prediabetes. These include healthy eating,
moderate physical activity (PA), and weight loss (Thomas et al., 2010).
The Diabetes Prevention Program (DPP) Research Group (2002) conducted a large
randomized control trial (RCT) to evaluate the effectiveness of lifestyle intervention (LI)
programs including a low-calorie, low-fat diet and 150 minute per week moderate PA to prevent
or delay diabetes among adults with prediabetes. Compared to the control and metformin groups,
the LI group achieved greater weight loss and greater increase in PA. The diabetes incidence rate
was 58% lower (95% CI, 48-66%) than the control, and the estimated cumulative incidence of
diabetes at three years was the lowest (14.4%) in the lifestyle intervention group. Both
metformin and LI effectively delayed or prevented diabetes, and in particular, LI was more
effective, with one case of prevention per seven persons treated for three years, substantially
reducing the individual and public health burden of diabetes.
The Diabetes Prevention Study (DPS) in Finland (Eriksson et al., 1999) assessed the
efficacy of an intensive diet and exercise program in preventing or delaying T2DM, and
evaluated the effects of the study intervention on cardiovascular risk factors in persons with IGT.
The intervention group lost more weight than the control group, and their plasma glucose
concentrations were significantly lower as well. Additionally, serum triglycerides, systolic blood

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pressure and diastolic blood pressure measurements were lower compared to the control group.
The lifestyle intervention not only improved blood glucose level, but also affected heart health.
The landmark studies such as DPP and DPS have been translated into different practice
settings, communities, and underserved minorities. The translational studies successfully
produced significant weight loss, which reduces diabetes and cardiovascular risks (Almeida,
Shetterly, Smith-Ray, & Estabrooks, 2010; Jakicic et al., 2013; Jiang et al., 2013; Katula et al.,
2011; Katula et al., 2013; Look AHEAD Research Group, 2007; Ma et al., 2013; Matvienko &
Hoehns, 2009; Parikh et al., 2010); however, long-term cost-effectiveness of lifestyle
intervention programs remains questionable due to weight regain after the first year of lifestyle
modification (Kahn & Davidson, 2014).
While medications for diabetes can only affect glucose levels, the LI with education and
support may contribute more to improved overall health by directly impacting the diabetes risk
factors such as weight, eating habit (EH), physical activity (PA) and blood pressure, thus
preventing or delaying progression to T2DM (Diabetes Prevention Program Research Group,
2002; Eriksson et al., 1999). However, more evidence is necessary to evaluate the long-term
effect of the LI programs.
Environmental Factors
Urbanization contributes to easy access in foods that are high in fat, sugar and calorie
worldwide; however, the U.S. shows the opposite that is higher diabetes prevalence rate in rural
communities. Also, people living in low-income or minority neighborhoods are more likely to
suffer from diabetes or related complications. Limited access to nutritious food due to financial
insecurity is related to diabetes risk and higher diabetes prevalence rate. People with sedentary
lifestyles have an increased risk for diabetes. When the surrounding environment is safe and

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promotes outdoor recreations, people are more likely to increase PA and less likely to be
sedentary therefore reducing the risk of developing T2DM (Hill et al., 2013).
Internal Evidence
In a local healthcare clinic in Graham County, AZ, a lack of diabetes prevention program
is identified. The barriers are a lack of time to educate patients during short office visits, the
limited availability of local health resources, residents’ unawareness of their diabetes risk, and
other co-morbidities. The clinic serves a high volume of patients who are overweight and/or
obese that is a risk factor for diabetes.
Problem Statement
Diabetes is an epidemic health issue that affects quality of life and exhausts valuable
healthcare resources worldwide. It also disproportionately affects more ethnic minorities and
rural communities. There is a great need to shift the healthcare community’s focus from
diagnosis and treatment of the diabetes epidemic to outright prevention of the disease. The world
wide and national efforts to reverse the current trend of diabetes have not been very successful.
PICOT Question
In adults with prediabetes residing in a rural community (P), how would a lifestyle
intervention program (I) compared to no lifestyle intervention (C) affect blood glucose level (O)
in 3 months (T)?
Search Strategy
An exhaustive search included a database search and hand ancestry methods to obtain the
most current and high level of evidence and to evaluate and synthesize the studies. The electronic
databases consisted of Academic Search Premiers, Cumulative Index to Nursing and Allied
Health Literature (CINAHL), Cochrane Library, PubMed, and PsycINFO. The population was

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limited to adults only with prediabetes, and the intervention had to include any form of lifestyle
changes such as healthy eating and/or PA. The outcomes were change in fasting glucose, oral
glucose tolerance or HbA1c, or diabetes incidence. Studies with pregnant women, no
randomization, or the number of subjects less than 50 were excluded. Preferred studies were
original research or meta-analysis/systemic review. The database search was limited to English
language, human subjects and published date from 2010 to 2015.
Academic Search Premiers
The search terms included were “prediabetes”, “lifestyle intervention”, “blood glucose”,
“incidence” with a Boolean term AND, and synonyms like “prediabetic”, “lifestyle
modification”, “lifestyle change”, “behavioral modification”, “fasting glucose”, “hemoglobin
A1c”, “oral glucose tolerance”, and “diabetes” with a Boolean term OR, which yielding 57
articles.
CINAHL
For CINAHL database, the search was as follows Search (S) 1 “prediabetes OR
prediabetic state OR impaired fasting glucose OR impaired glucose tolerance” n=3,388; S2
“lifestyle intervention OR lifestyle modification OR healthy eating OR diet OR exercise OR
physical activity” n=189,809; S3 “diabetes incidence rate OR diabetes prevention” n=8,492; S4
“rural community OR rural health OR rural setting OR rural” n=39,636. Those four searches
were combined with a Boolean term AND in multiple different ways and produced a total of 246
studies. Thirty articles were retained for further review.
Cochrane Library
The Cochrane Library search was performed using the following keywords: prediabetic
state, lifestyle intervention, lifestyle change, diabetes prevention study, and rural population. The

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search produced two Cochrane Reviews, 12 other reviews, and four trials. After careful
evaluation, only two reviews were selected for the relevance to the research question.
PsycINFO
For PsycINFO database, the search terms included “prediabetes”, “lifestyle
intervention”, “behavioral modification” and a Boolean term AND, which resulting 20 scholarly
journals and four dissertations and theses.
PubMed
Searching PubMed database with Medical Subject Headings (MeSH) terms led to the
followings “prediabetic state” n=3,858; “life style” n=65,714; “primary prevention” n=113,798;
“rural community” n=40,572. The MeSH terms then combined with a Boolean term AND which
yielded 53 studies.
Final Yields
After an exhaustive literature search on prediabetes and lifestyle intervention, the final 10
studies were included: two systematic reviews (SR), five RCTs, two quasi-experiments, and one
cohort study. The studies were published within five years (See Table 1).
Evidence Synthesis
Eight studies utilized lifestyle modification with healthy eating or PA, or both as the
intervention. Lifestyle intervention was delivered in individual-based or group-based. One study
implemented both methods (See Table 2). People conducting the intervention were diverse
consisting of nurses, community health workers, or trained researchers.
Measured outcomes were weight, BMI, FBG, OGTT, cholesterol, or diabetes incidence
rate. Eight studies evaluated weight and reported statistically significant weight loss with either

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individual or group-based lifestyle interventions. Five studies evaluated diabetes incidence
outcomes. Of those, three showed significant changes in the incidence rate (See Table 2).
Overweight or obesity and sedentary lifestyle are one of the risk factors for developing
diabetes. The lifestyle intervention with healthy eating and PA helps to reduce diabetes risks.
The variable factors including variable intensities, delivery methods, practice settings and
follow-up periods of the intervention also affect the degree of the weight loss and fasting blood
glucose. Although the lifestyle intervention to reduce diabetes incidence rate is inconclusive, it
has been shown to be effective with the risk reduction behaviors in prediabetic population.
Implementation of healthy eating and exercise among prediabetic population will improve their
overall health.
Purpose Statement
The purpose of the project is to identify patients with the high risk for prediabetes and
implement lifestyle change intervention in a rural primary care setting. The project will benefit
patients with high risk for prediabetes by increasing awareness and knowledge of prediabetes
and by improving their physical activity (PA), eating habit (EH) and self-efficacy (SE).

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Chapter 2 Applied Clinical Project: Methods & Results
This chapter provides details on the evidence-based practice (EBP) model, conceptual
model, project methods, results, discussion and conclusion. The project methods illustrate
ethics, setting, organizational culture, participants, procedure, outcomes measures, data
collection, data analysis, and proposed budget.
Evidence Based Practice Model
The Model for Evidence-Based Practice (EBP) Change will systematically guide this
evidence-based practice change. The model includes the following six steps: Step 1 Assess the
need for change in practice; Step 2 Locate the best evidence; Step 3 Critically analyze the
evidence; Step 4 Design practice change; Step 5 Implement and evaluate change in practice; and
Step 6 Integrate and maintain change in practice.
In Step 1, internal data were collected to assess the need for change in practice. The key
stakeholders included physicians, certified diabetic educators, medical assistants and prediabetic
patients. The need to educate patients with high risk for prediabetes to prevent prediabetes and
T2DM was identified. In step 2, the best evidence was located by conducting an exhaustive
literature search in electronic databases. The types of evidence included practice guidelines,
systematic reviews, meta-analysis and RCTs. In step 3, the evidence was critically analyzed and
synthesized, and supported increasing prediabetes awareness and educating healthy lifestyle
change among patients with high risk for prediabetes to prevent T2DM in prediabetic population.
In step 4, a pilot program to identify patients with prediabetes or high risk for it was designed to
increase prediabetes awareness and improve PA and EH. The step 4 includes identifying needed
resources, desired outcomes, outcome measuring tools, and evaluation plan. In step 5, the pilot
program will be implemented in the clinic and data will be collected and analyzed. Evaluate the

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pilot program to decide if adaptation is warranted. Feedback of the participants and stakeholders
is an important step to make adjustments. In step 6, the results of the project will be presented to
the stakeholders and the practice change will occur if the pilot program supports positive effects
on diabetes prevention.
Conceptual Model
The Health Belief Model (HBM) was selected as the most effective conceptual model to
promote healthy lifestyle changes for this EBP project. The HBM conceptual model
incorporates six sequential components: perceived susceptibility, perceived severity, perceived
benefits, perceived barriers, cue to action, and SE (National Cancer Institute, 2005). The focus
of HBM, motivation, is widely applicable to many health situations, and the final element of the
model, SE, can play a critical role in promoting and achieving health behavior and lifestyle
changes among pre-diabetic populations.
While the evidence emphasizes the importance of lifestyle changes in preventing or
delaying diabetes among prediabetic adults, the HBM model strongly suggests that people with
prediabetes might not change their lifestyle to lose weight and increase PA because they do not
know their perceived susceptibility (e.g., slightly higher FBG levels than those considered
normal). Logically, perception must arise before motivation and SE. People with prediabetes
must perceive and understand that slightly high FBG can lead to diabetes and macrovascular and
microvascular diseases (perceived severity).
If knowledge, understanding and perceived benefits of healthy lifestyle changes can be
articulated, and, if barriers to success can be identified in advance, such awareness may aid both
individuals and groups in a reduction of risk for developing diabetes. Weekly meetings for
education, healthy eating and PA log books, social media support, and follow-up phone calls

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may cue continued action helping people to implement and comply. People with low confidence
might benefit by setting short-term goals and participating in groups for peer-support (selfefficacy) (See Figure 1).
Project Methods
Ethics and Recruitment
The Arizona State University (ASU) institutional review board (IRB) reviewed and
determined that this EBP project is adequate to protect the human subjects’ right (Appendix A).
Recruitment flyers were placed in the exam rooms of the champion clinicians. Any information
that is obtained in connection with this project and that can be identified with the participants
will remain confidential and will be disclosed only with their permission or as required by law.
The participants’ name will not be entered on the questionnaires or survey tools, which will be
coded by a number, not name, on the top of the forms. A master list of subject’s names and
study IDs will be created. The master list will be destroyed after data is matched. No
unauthorized persons will have access to this data. All demographic forms, questionnaires, and
surveys will be stored separately from the consent forms within the same locked drawer for one
year with this author and faculty advisor having access. The participants’ name and designated
phone number will be stored separately in a locked safe and used for the sole purpose of
reminder calls. The data will be disposed of by shredding immediately after the last phone call is
placed. All other forms associated with this project will be disposed of by shredding after 6
months.
After receiving IRB approval from ASU, the patients were recruited to participate in the
project from October 26th, 2015 to October 30th, 2015 by convenience sampling of available
patients in the primary care office for routine visits. The recruitment flyers were placed in the

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exam rooms of the Champion. The purpose and goal of the project were explained to eligible
candidates. Also, the participation was voluntary and the subjects can withdraw from the project
anytime if they desire.
Setting
The project was conducted at a rural outpatient family healthcare clinic, Gila Valley
Clinic, located in Safford, Arizona (AZ). The clinic was established in the community in 1994.
The staff consists of nine providers (five medical doctors, three nurse practitioners, and one
physician assistant), ten medical assistants, and ten administrative staff. The practice takes about
sixty percent of AHCCCS and Medicare patient groups. Also, they provide sliding scale
payment option for people with financial difficulties. Approximately eight five percent of
patient population is mostly Whites and Hispanics.
Organizational Culture
The Gila Valley Clinic (GVC) staff overall work together well to provide the best
healthcare to the community and actively involve in the community improvement activities.
Their mission is to provide quality full spectrum medical care to their patients. One of the
providers is identified as a Champion for the project because she expressed interests in diabetes
health in the Eastern Arizona and volunteered to help with this DNP project. Also, the MA’s of
the Champion verbalized the negative impacts of diabetes in the town and wanted to spread the
words to patients about the project. Open communication was encouraged to minimize possible
barriers.
Participants
Twenty-four participants were recruited from the clinic. Eligibility criteria were as
follows: adults who are 18 years of age or older; English speaking; cognitively intact; and risk

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for prediabetes. These risk factors include 45 years of age or older, being overweight or obese, a
family history of diabetes, ethnic background other than Caucasian, gestational diabetes, having
given birth to a baby weighing nine pounds or more, or being physically active less than three
times a week (CDC, 2014; CDC 2015). Exclusion criteria applied to those who have diagnosed
with Type 1 diabetes or Type 2 diabetes, pregnant women, or unable to consent. All participants
were explained with the goal of the DNP project and the benefits of participation. All questions
were answered and written informed consent was obtained from all participants.
Procedure (Intervention)
Once the patients agreed to participate in the project and sign the informed consent, their
demographic information was gathered including; age, gender, ethnicity, marital status,
education status, current health condition, prediabetes awareness, height in inches, and weight in
pounds. Their height and weight were extracted from their medical records. The CDC
Prediabetes Screening Test by National diabetes Prevention Program was used to obtain their
risk scores (CDC, 2015). The scores were divided into two groups, low risk or high risk for
prediabetes. If their score was 3 to 8 points, they were placed in the low risk for prediabetes
group. If their score was 9 or more points, they were placed in the high risk for prediabetes
group. Regardless of their risk scores, all participants received the same survey questions and
intervention. Each participants completed pre-intervention survey questions on PA, EH and SE
level. Then, they received written and verbal prediabetes information including the definition,
complications, risk factors, and simple lifestyle interventions with healthy eating and PA.
Weekly, they received a brief phone call for four weeks for follow-up. The final fourth week,
each participant completed post-intervention survey questions via phone calls. The pre and post
intervention survey questions were identical to measure any changes on PA, EH and SE levels.

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Outcome Measures
Demographic data were collected at baseline. The PA was measured by a 2-item
questionnaire, Brief Physical Activity Assessment. Each participant was asked the weekly
frequency of each vigorous PA (score 0-4) and moderate PA (score 0-4). A score is given to
each category. A score 0 to 3 meant insufficiently active and a score of 4 or more meant
sufficiently active. The k coefficients showed significant inter-rater agreement at k=0.53, p <
.001 (Marshall, Smith, Bauman, Kaur, & Bull, 2005). Eating habit was measured by an 8-item
food frequency questionnaire, Starting The Conversation. Each item was scored from 0 to 2,
higher score indicating the least healthful habit. All eight-item scores were added to yield a
summary score (0-16), lower score reflecting healthier eating and higher score meaning
unhealthy EH. All items and the summary scores were well intercorrelated, r = 0.39-0.59, p <
.05 (Paxton, Strycker, Toobert, Ammerman, & Glasgow, 2011). There was no preexisting
prediabetes specific SE measurement tool. A six item, 5-point Likert scale (0-4) questionnaire
(Prediabetes Lifestyle Change Self-Efficacy) was used to measure the confidence level of
participants, which was modified from Self-Efficacy for Diabetes (Lorig, Ritter, Villa, & Armas,
2009) to reflect the information on prediabetes and lifestyle change given during the intervention
session (See Appendix B-G).
Data Collection and Analysis Plan
Demographic data were collected on the day of visit to the clinic. The PA, EH and SE
data were collected via the phone call during the fourth week follow up. Participant data were
statistically analyzed using SPSS Statistics 23.0. The frequency and descriptive analysis were
done on the demographic data. A paired samples t-test was appropriate to measure any

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differences of PA, EH and SE between pre and post intervention. Statistical significance was set
at p < .05.
Proposed Budget
The main cost of the implementation of the project was the printed educational material
and time spent by the person providing education who can be a nurse practitioner (NP) or
medical assistant (MA) and the follow up phone call time. The estimated costs for NP and MA
range $11.96 ~ $13.54 and $3.86 ~ $4.36, respectively (See Appendix H). There was no
monetary compensation for the participants. People with diabetes are twice more likely to spend
in medical expenses than those without diabetes. Also, they tend to lose more workdays and die
prematurely compared to those without it (CDC, 2014). Therefore, it is much more beneficial to
prevent diabetes with the brief intervention.
Project Results
Participant Characteristics
A total of 24 participants completed the pre-intervention assessment. Of those, 16
finished the post-intervention assessment. The mean age of participants was 56.6  13.0 years,
had a height of 65.0  3.3 inches, and had a weight of 201.4  38.2 pounds. The mean score of
the CDC Prediabetes Screening Test was 12.3  4.7 points, which interpreted a score of 9 or
more points indicates high risk for having prediabetes. The majority of the participants were
female (81.3%), and more than half identified as Caucasian (62.5%). Most participants reported
married (81.3%), and over half (56.3%) described their health condition as good. The three
quarters (75%) noted they have heard of the term prediabetes (See Table 3).
Outcome Variables

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A paired samples t-test was performed to compare the changes in PA, EH and SE from
pre-intervention to post-intervention within the participants. The paired t-test revealed that mean
PA differed before the intervention (M = 2.88, SD = 2.53) and after the intervention (M = 5.31,
SD = 2.77) at the significance level of .05 (t = -3.31, df = 15, n = 16, p = .005, 95% CI for mean
difference -4.01 to -.87, r = .37). On average PA was increased after the short lifestyle
modification education. The paired t-test showed that mean EH decreased before the
intervention (M = 6.94, SD = 2.52) and after the intervention (M = 5.00, SD = 2.48) at the
significance level of .05 (t = 3.08, df = 15, n = 16, p = .008, 95% CI for mean difference .60 to
3.28, r = .49). On average EH was improved after the short lifestyle modification education.
The paired t-test indicated that mean SE increased before the intervention (M = 16.69, SD =
4.19) and after the intervention (M = 19.88, SD = 3.28) at the significance level of .05 (t = -3.49,
df = 15, n = 16, p = .003, 95% CI for mean difference -5.14 to -1.24, r = .54). On average SE
was improved after the short lifestyle modification education (See Table 4).
Discussion
The lifestyle modification is a proven method to prevent or delay the diabetes
development (Diabetes Prevention Program Research Group, 2002). However, translating it into
a primary care setting can be challenging due to time constraints. The Diabetes Prevention
Program (DPP) lifestyle intervention is composed of a 16-week intensive lifestyle-modification
intervention. The shortest translational study was 3 month long (Whittemore, 2011). This DNP
project was only 4 weeks long and the actual intervention took only 3-5 minutes during the
interview session. Many clinicians are challenged with short visit times with their patients;
therefore, keeping the intervention short is an important factor to consider.

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The participants were recruited at a primary care clinic. The Champion clinician
encouraged the participants to get involved in the project, so it was likely that they wanted to
please their clinician by participating even though they were not interested in it. The
incompletion rate at the fourth week was as high as 33%.
The phone call follow-up was challenging because some of the participants were not
answering the calls. Multiple calls per participant were necessary to complete the follow up
surveys each week. According to the U.S. Department of Health and Human Services [HHS]
(2014), many studies have shown that health text messaging can help improve health knowledge,
behaviors and outcomes. With increasing use of smartphones, health text messaging can make
the follow up process easier and less time consuming for future study.
Compared to the DPP study, this project had a less intensive intervention (Diabetes
Prevention Program Research Group, 2002). The intervention was provided one time during one
office visit and no other visits were required. Nevertheless, it showed improvements in PA, EH
and SE level with the short intervention.
The Finnish Diabetes Prevention Study (DPS) illustrated that the lifestyle intervention
group demonstrated changes in dietary and exercise habits by eating less fat and more vegetables
and increasing exercise (Eriksson et al., 1999). In this DNP project, the participants had
statistically significant improvements in their PA and EH. Therefore, discussing prediabetes risk
and lifestyle modification during the office visit is an important first step towards to preventing
T2DM.
This current project showed an improved SE level between pre and post intervention.
This finding is consistent with the results of the study by Chen and Lin (2010). Their analysis
revealed a significant positive correlation between SE and health-promoting lifestyle.

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Limitations
There were multiple limitations for this DNP project. The sample size was small, and the
attrition rate was high at 33%. The phone call follow-ups were burdensome because of the
participants’ low rate of answers, so it required multiple attempts on calls each week. In
addition, a 4-week of follow up on lifestyle change was very short to make strong conclusions.
Also, it was conducted at one practice site that limits generalizability. Furthermore, the subjects
who participated in the project could be already motivated to change their lifestyle for better
health before enrolled in.
Conclusions
The results reject the null hypotheses that there would be no differences in PA, EH or SE
level from pre-intervention to 4 weeks post-intervention. Providing lengthy classes for lifestyle
changes can be challenging in a primary care setting due to time constraints, space and staffing.
The findings of this DNP project illustrate that the lifestyle change education can be brief and
effective to increase PA, eat healthier and improve SE level. Larger sample study over a longer
period time is necessary to exam the long-term effect of lifestyle change.
There is a great need to shift the healthcare community’s focus from diagnosis and
treatment of the diabetes epidemic to outright prevention of the disease. Early identification of
people who are at risk for prediabetes is the first step in preventing T2DM. Also, providing them
with a simple guideline on lifestyle change can help change the trend of diabetes before it begins.
The practice site values the time of both their staff and patients. Thus, it is likely to adopt the
practice change if the lifestyle change education is brief and succinct for the both parties. Future
research is needed on innovative methods to implement lifestyle changes in a primary care
setting.

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Chapter 3 Organizational/Health Policy Impact & Sustainability
With the increasing number of T2DM, early identification of prediabetes is an important
step followed by lifestyle change intervention (American College of Endocrinology & American
Association of Clinical Endocrinologists, 2008). The project findings suggest that the lifestyle
change education is achievable in a primary care setting. This chapter will address impact of the
project on practice, financial implications, impact of current policy, the role as innovative leader,
sustainability plan, implications for further study, and identified gaps.
Impact on Practice
It requires interprofessional collaboration to have a successful DNP project (Conrad,
2014). This author only could recruit the Champion clinician for the project. The main reason
of non-participation of other providers was the time restraint and resistance to change of their
routine. For other clinicians, meeting the high volume of patients was their priority. With the
clear evidence of early identification of prediabetes and lifestyle change education and the
positive impact on lifestyle, the Champion continues with the brief lifestyle change education.
This author remains hopeful to change the practice in the setting gradually with the assistance of
the Champion clinician. A few medical assistants (MAs) expressed the importance of early
lifestyle education with their high-risk patients and stated that they were interested in doing the
education if the time is allowed. Instead of pushing for change with the resistance, the gradual
change approach would benefit the site and staff.
Cost and Benefit Analysis
The project budget was $50 to cover supplies and educational materials. A total of
$26.60 was spent, and no monetary compensation was provided for the participants or provider.
The space was limited in the setting; hence, the phone call follow-up was chosen. Also, the

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participants did not have to pay another co-pay with the calls and no loss of workdays. If a
physician, NPs and MAs provided the education and follow-ups, it would cost $23.10 - $26.18,
$11.96 - $13.54, and $3.86 - $4.36, respectively (See Appendix H). It is cost beneficial when
MAs provide the education and follow up with the patients.
Impact of Policy
In 2010, the Congress passed the Patient Protection and Affordable Car Act (ACA). The
goal is to expand health insurance accessibility and make it more affordable resulting in more
people to be covered. It is good news for people with chronic conditions such as diabetes
because it is against the law to deny their coverage due to their pre-existing conditions (Longest,
2016). Additionally, the preventive health services that are evidence-based must be provided.
Currently, T2DM screening for asymptomatic adults with high blood pressure is covered
(Mason, 2011). This leaves out the estimated 86 million prediabetic Americans with other risk
factors such as obesity or a family history (CDC, 2014). However, on March 23rd, the HHS
(2016) announced that they are considering the expansion of the Diabetes Prevention Program
(DPP) to the Medicare beneficiaries with prediabetes because the positive health impacts with
financial benefits are too significant to ignore. With the recent consideration, there is a need to
increase the number of qualified educators or community workers who can teach the healthy
lifestyle education to the beneficiaries.
Innovative Leader
According to Chism (2010), a DNP graduate exhibits excellent leadership and
collaboration that increase patient satisfaction and decrease conflict. One of the most important
leadership attributes is effective communication skill. At the initial of the project planning, the
Champion clinician verbalized a concern for limited time and space at the clinic for group

IMPACT OF A BRIEF PREDIABETES EDUCATION

21

intervention sessions. This DNP student used the democratic style of leadership to resolve the
conflict. The democratic leader considers all viewpoints and utilizes good communication skills
to collaborate, resolve conflict and influence others (Chism, 2010). The project was modified to
the individual session with follow-up calls by the MAs to address the Champion clinician’s
concern. Then, the MAs raised a concern for implementing the project due to their limited
patient care time. The student provided other options for implementation methods and all agreed
the student to implement the intervention. Once they observed the actual process being quick
and easy during the implementation period, a few MAs verbalized their interest on the education
part. It was a learning process. If the student held a meeting with both the clinician and staff at
the same time, their both concerns could have been addressed at once. This DNP project
provided valuable lessons for the future EBP process to be successful.
Sustainability
Many factors play a role for sustainability of a project. One essential element is readiness
for change (Alt-White & Pranulis, 2011). Even though the Champion clinician and a few MAs
were part of this DNP project, the organization as a whole was not ready to change their practice
due to their limited patient care time. The operation cost of the project was minimal (Appendix
H); yet, insufficient employee and managerial time constrained the system-wide use of the
project (Alt-White & Pranulis, 2011). Although the project did not convince the organization as
a whole to change the practice, the Champion clinician continues to educate the patients.
Additionally, the recent announcement of DPP expansion to Medicare beneficiaries with
prediabetes may influence the organization’s practice change in the future (HHS, 2016).
Implications for Further Application and Research

IMPACT OF A BRIEF PREDIABETES EDUCATION

22

HealthyPeople 2020 identified diabetes health as a part of their nationwide initiative to
focus efforts on improving national health. The objective related to prediabetes is to increase
prevention behaviors for prediabetic people with high risk for diabetes (HHS, 2014).
Assessing the prediabetes risk scores with a standardized questionnaire such as the CDC
Prediabetes Screening Test, other than blood work, can help identify people who are at risk for
prediabetes in clinics before developing it. This DNP project showed that one time brief lifestyle
change education could positively impact PA, EH and SE in people with high risk for
prediabetes in a primary care clinic. Further study is needed to develop other innovative ways
such as using patient portal, mobile applications and electronic messages to implement lifestyle
change education without affecting patient care time in primary care settings.
Gaps
During the project, a gap was identified that people who are at high risk for developing
prediabetes heard the term prediabetes, but they were not formally educated on their risk factors
or healthy lifestyle education. Primary prevention is an essential key to prevent prediabetes that
can lead to T2DM. The focus should be on the risk reduction behaviors like weight loss,
increased PA and healthy eating and less on the laboratory values. The successful DPP research
with prediabetic people is abundant (Almeida, Shetterly, Smith-Ray, & Estabrooks, 2010; DPP
Research Group, 2002; Eriksson et al., 1999; Jiang et al., 2013; Katula et al., 2013); however, the
insurance only covers the program for the people with T2DM. Researchers and healthcare
providers need to work together to lessen the gap from research results to practice and policy.
Conclusion
This EBP project demonstrated how to translate evidence into a real practice setting by
utilizing EBP Change model and conceptual framework. The internal data were assessed for the

IMPACT OF A BRIEF PREDIABETES EDUCATION

23

need for practice change. Then, the exhaustive search for the best evidence was completed
followed by evidence synthesis. Next, the project was developed with the approval of IRB. The
findings illustrated that the lifestyle change education can be brief and effective to increase PA,
eat healthier and improve SE level. Larger sample study over a longer period time is necessary
to exam the long-term effect of lifestyle change. The project abstract got accepted for the 4th
Annual Interprofessional Rural Health Professions Conference and the 2016 National Nurse
Practitioner Symposium for the result dissemination.

IMPACT OF A BRIEF PREDIABETES EDUCATION

24

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31

Running head: IMPACT OF A BRIEF PREDIABETES EDUCATION
Table 1 Evaluation Table
Citation

Conceptual
Framework

Design/Method

Sample/Setting

Major Variables
& Definitions

Measurement

Data Analysis

Findings

Almeida, F. A.,
Shetterly, S.,
Smith-Ray, R.
L., Estabrooks,
P. A. (2010).
Reach and
effectiveness of
a weight loss
intervention in
patients with
prediabetes in
Colorado.
Preventing
Chronic Disease,
7(5), 1-5.
Retrieved from
www.cdc.gov/pc
d/issues/2010/se
p/9_0204.htm

Patientcentered
approach

Design: Matched
cohort longitudinal
study

N=1520,
(760 matched
pairs)

Weight, BMI

Purpose: To
investigate the
effectiveness of a
theory-based, brief,
small-group wt loss
intervention for
diabetes prevention
and to determine the
potential reach of the
intervention

Demographics:
mean age 63,
53% F,
LI: 188.3 lbs,
BMI 29.8

IV=a single 90
minute small
group session
that targeted
personal action
planning for
healthful eating,
PA, and wt
management

Mixed models
analyses to
adjust for
matching
variables and
covariates and to
account for
individual
random effects
over time.
Nonparametric
X2 test of
independence to
test for group
differences
between groups.

Wt in LI
decreased sig
more than that
for CG (mean wt
loss -3 lbs
[95%CI -3.6 to 2.4] for control, 1.4 lbs [95%CI 2.0 to -0.8],
(p<.001).
LI were 1.5 X
(95% CI, 1.22.0) more likely
to lose at least
5% of their wt
than CL.

Setting: Kaiser
Permanente
Colorado, an
integrated health
care organization

DV=wt change
in medical
records

Country:
Denver, U.S.
FA:
Department of
Preventive
Medicine at
KPCO
C/B: none

Balagopal, P.
(2012). A
communitybased
participatory

TTM

Design: Cohort study
Method: CBPR
method by using
trained CHW,

N= 1638
male 766, female
872,
high SES 873,
low SES 764

IV: ten face to
face encounters
for lifestyle
intervention
(advice on

Dietary recall

SPSS 19

ADA 7-item DM
risk test

Multivariate
regression

% change in
BMI= -0.46
(p<.001)
% change in

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice
Level 4
Strength:
Theory based
study
Weakness: not
randomized, wt
measurement not
done by trained
research staff,
generalizability
is unclear.
CO:
A single-session,
theory based wt
loss program can
be modestly
effective, but
many not have
sufficient reach
to be effective as
a population
approach.
CS: Supports
short and one
time LI
education for sig
wt loss to reduce
DM risk factors
Level 3
Strength: large
sample size,
door-to-door

32

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

diabetes
prevention and
management
intervention in
rural India using
community
health workers.
The Diabetes
Educator, 38(6),
822-834. DOI:
10.1177/014572
1712459890.
FA: American
Association of
Physicians of
Indian Origin in
collaboration
with Texas
A&M University
and Maharaja
Sayajirao
University of
Baroda

Conceptual
Framework

Design/Method

interventions given to
all participants
Purpose: to test the
effectiveness of a 6month communitybased diabetes
prevention and
management program
in rural Gujarat, India
No monetary
compensation
IRB approval by
Texas A&M
University

Sample/Setting

D: mean age
41.9+/-15.9,
high SES had a
below-poverty
level of 24% and
illiteracy of
9.7%, and low
SES had 51%
and 50.5%
respectively
Setting: rural
community in
Gujarat, India
IC: all adults,
age 18 and older,
from a rural
community, 25
km from
Vadodara,
Gujarat

Measurement

healthy diet and
regular physical
activity)

11-item AHA
risk calculator

DV: BMI, waist,
PA, fruit/veg
intake,
knowledge of
DM and CVD
risk factors,
SBP, DBP, and
FBG

PA modified
version from
IDPP study
Fasting capillary
blood glucose
Averaged 3 BP
measurements
Ht/Wt/WC/HC

Data Analysis

Findings

WC= -1.25
(p=.001)
Change in SBP=
-7.37 mmHg
(p<.001)
Change in DBP=
-3.24 mmHg
(p<.001)
Change in FBG=
-1.28 mg/dL
(p<.001)
Change in DM
knowledge
score= 0.78
(p<.001)
Change in CVD
knowledge
score= 1.64
(p<.001)
Change in fruit
intake =.04
(p<.001)
Change in veg
intake = 0.19
(p<.001)
% change in

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice
visits, culturally
sensitive LI,
high community
support
WE: no
randomization or
control group,
door-to-door
visits, vulnerable
population
CO:
Communitybased DM
prevention
program reduced
FBG and
increased DM
knowledge in
both high and
low SES in rural
community.

CS: CBPR is
useful method
and CHW plays
Country: India
a critical role in
implementation.
A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;
C/B: none

EC: migrant
workers

Major Variables
& Definitions

33

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

Conceptual
Framework

Design/Method

Sample/Setting

Major Variables
& Definitions

Measurement

Data Analysis

Findings

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice

PA= 11.6
(p<.001)
Cardona-Morrell
et al. (2010).
Reduction of
diabetes risk in
routine clinical
practice: Are
physical activity
and nutrition
interventions
feasible and are
the outcomes
from reference
trials replicable?
A systematic
review and metaanalysis
FA: not stated
C/B: none

NA

Design: SR/MA
Method: Multiple
databases were
systematically
reviewed and a MA
was done of RCTs that
evaluated LI in adults
at risk for DM
Purpose: to determine
whether lifestyle
interventions delivered
to high-risk adult
patients in routine
clinical care settings
are feasible and
effective in achieving
reductions in risk
factors for DM.

N=363 papers
potentially
eligible
N=41 papers
examed for full
eligibility
N=12 included
in final review &
bias assessment
N=4 for MA
7 RCTs, 3
before-after
designs without
a CG and 2
before-after
designs with a
CG
Limits: English,
published 1990Aug 2009
IC: translational
research studies,

IV: LI (nutrition
and/or PA) with
or without med
DV1: weight
loss or WC
DV2: metabolic
outcomes
indicative of DM
risk reduction
DV3: selfreported or
objectively
measured
behavioral
outcomes
Secondary
outcome:
prevention of
DM (incidence
% or delay in
onset)
MA main

Denominator for
effect sizes= #of
subjects in
whom the
outcome had
been assessed

Critically
reviewed.

Study results
were categorized
as +//inconclusive

Forest plots

Study quality
score
Changes in
means, and tests
of heterogeneity
between trials
were calculated
with random
effects models
SD of mean
differences in

MA with NCSS
software version
7.1.1.9

Mean wt
reduction was
1.82kg greater in
tx than CG (95%
CI: -2.7 to .99kg), pooled
mean waist
measurement
reduction in tx
exceeded CG by
4.6 cm (95% CI:
-5.8 to -3.4 cm),
FPG reduction
was 0.19 greater
in tx (95% CI: .44 to +.06),
OGTT 0.04
(95% CI: -.49 to
+.42)

Level 1
Strength:
SR/MA
reviewing LI for
feasibility and
replication
Weakness: Only
12 studies
included. Many
studies’ f/u
period was short
and only modest
sample sizes
CO:
Modification of
the original
research to real
life practice
made LI
feasible,
affordable or
replicable in

A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;

34

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

Conceptual
Framework

Design/Method

Sample/Setting

Major Variables
& Definitions

Measurement

routine clinical
practice setting,
intervention as
single or
combined
(nutrition or PA)
programs with or
without med

outcomes:
changes in wt,
FPG, WC, 2hour
OGTT

outcome
measures were
calculated from
# of subjects and
standard errors
or from 95% CI

Data Analysis

Findings

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice
clinical settings
Transferability is
still questionable
d/t diminished
outcome effect
over time.

CS: No specific
recommendation
EC: program
on the most
delivering DM
effective features
education
of the LI.
material only,
The direction of
med-only studies
the effects on wt,
FPG, WC,
OGTT is
encouraging.
The feasibility of
the translational
studies is still
worth promoting
LI in clinical
settings.
Need more
studies with
large samples
and longer study
period.
Jiang, L.,
TTM
Design: QuasiN=2553,
IV=HD and
Annual OGTT,
On average, tx
Crude DM
Level 3
A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;

35

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

Manson, S. M.,
Beals, J.,
Henderson, W.
G., Huang, H.,
Acton, K. J., &
Roubideaus,
Y. (2013).
Translating the
diabetes
prevention
program into
American Indian
and Alaska
Native
communities:
Results from the
special diabetes
program for
Indians diabetes
prevention
demonstration
project. Diabetes
Care, 36(7),
2027-2034. doi:
10.2337/dc121250

Conceptual
Framework

Design/Method

Sample/Setting

Major Variables
& Definitions

Measurement

Data Analysis

experiment

1891(74%)
postcurriculum
completion,
1503(59%) 1st
annual
assessment,
1079(42%) 2nd
annual
assessment,
834(33%) 3rd
annual
assessment

increased PA
with cultural
adaptation
(talking circles,
indigenous
foods, drumming
into intervention
sessions)
DV1=DM
incidence
DV2=wt loss,
BP, lipid profile,
PA

semiannual
FBG, body wt,
ht, BMI, BP,
HDL cholesterol,
LDL cholesterol,
triglyceride,
average min of
PA per wk.
Used
standardized lab
protocol for any
measurements in
the study, so it is
reliable and valid
tests.

group lost 9.6lbs
after completion
(4.4% wt loss),
22.5% of
participants who
completed the
postcurriculum
assessment
achieved the 7%
wt loss goal by
the end of the
classes, 17.5%
met this goal 3
yrs after the
intervention
began. 181 min
PA/wk after LI.
FBG decreased
by 4mg/dL.

Findings

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice

incidence 4%/yr.
Cumulative DM
Strength: Large
Method: all
incidence among sample, reports
participants were
participants who
DM incidence
assigned to
attended all 16
intervention
classes was
WE: only AI/AN
significantly
as participants,
P: to evaluate a
lower than those
high rates of f/u
translational
who attended
loss, not as
implementation of
less than 15
rigorously
DPP in a diverse set of
(p<.0001).
controlled, no
AI/AN communities.
Crude incidence
placebo group to
of DM was
compare
Demographics:
~3.5% each yr.
¾ female,
22.5%
CO: The study
46.6yrs, BMI
participants
supports the
35.8 at baseline
achieved 7% wt
feasibility of
loss by the end
translating the LI
of classes, 17.5% across a wide
Setting: 6 IHS
met this goal 3
range of Native
hospitals/clinics,
yrs after the LI
communities. It
30 tribal or IHSbegan. PA goal
will need other
contracted HCP
increased to
retention
administered by
56%. FBG
strategies.
tribes.
decreased by
~4mg/dL. SBP,
CS: Supports
DBP, LDL,
DPP
Country: U.S.A.
triglyceride
translational
decreased
study are
A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;

36

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

Conceptual
Framework

Design/Method

Sample/Setting

Major Variables
& Definitions

Measurement

Data Analysis

FA: IHS
C/B: none
Kang, J. Y.
(2010). Effect of
a continuous
diabetes lifestyle
intervention
program on male
workers in
Korea. Diabetes
Research and
Clinical Practice,
90, 26-33. DOI:
10.1016/j.diabres
.2010.06.006
Country: South
Korea
FA: the Korea
Hydro &
Nuclear Power
project

TTM

Design: RCT
Method: Subjects were
randomly assigned to
either the CG, 1 yr, or
2 yr intervention group
Purpose: to compare
the effects of 2 year LI
to no intervention or 1
year of intervention on
DM risk factors in
male workers with
IFG or DM

N= 123
industrial male
workers (CG 75,
1 yr 23, 2 yr 25)
D: No
differences
among groups in
terms of age and
proportion of
IFG and DM.
Annual income
was higher in 1
yr group.
EC: subjects
taking meds for
glucose, lipid,
HTN,
manifesting CV
disease and
chronic ETOH
and/or drug
abuse

IV: LI consisting
2 parts (#1 part5X of 20-30 min
of face to face
counseling, #2
part-email
nutrition
education Q3
wks, a total of
10X)
DV1:
anthropometric
measurements
DV2: FPG,
HbA1c, total
cholesterol HDL,
LDL, HOMA-IR
DV3: dietary
intake

Ht, Wt, WC, BP,
FPG, HbA1c,
total cholesterol
HDL, LDL,
HOMA-IR
Computerized
food frequency
questionnaire

SPSS program
(SPSS 15.0 KO
for Windows)
Chi-squarehomogeneity of
the proportion of
IFG and DM,
and annual
income
Paired t-testdifferences
between baseline
and after
intervention
values
ANOVA with
Tukey’s post hoc
to compare
groups.

Findings

significantly.
HDL
significantly
increased
1 yr: SBP, FPG,
HOMA-IR and
HDL sig
decreased
(p<.05)
2 yr: Wt, BMI,
WC, SBP, DBP,
FPG, HbA1c
decreased
(p<.05)
Total energy
intake in 1 yr
group after
intervention
(p<.05)
Total energy,
carb, protein and
sodium level
decreased in 2 yr
group (p<.05).

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice
effective to delay
DM.

Level 2
Strength: RCT,
using email
nutrition
education for f/u
WE: small
sample size,
exercise level
was not
considered;
some baseline
data was higher
in 2 yr group
than the others.
Used ADA
guideline for
IFG resulting
difficulty
comparing other
studies with
WHO
guidelines.

Changes in WC,
SBP, total
cholesterol in 2
yr group were
A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;
C/B: none

37

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

Conceptual
Framework

Design/Method

Sample/Setting

Major Variables
& Definitions

Measurement

Data Analysis

Findings

greater than in
CG or 1 yr group
(p<.05)

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice
CO: Male
Korean
industrial
workers with
IFG or DM,
continuous LI
over 2 yrs
improved DM
risk factors
CS: Email for f/u
can be useful
and resource
saving.
Level 2

Katula, J. A.,
TTM
Design: RCT
N=301 (G=150,
IV=LI
Wt, BMI, waist,
T-test, Fisher
LI:
Vitolins, M. Z.,
I=151)
glucose, insulin,
exact for
body wt 87.44
Rosenberger, E.
Method: Subjects
DV= FBG,
HOMA-IR, %
baseline
+/- 1.28
Strength:
L., Blackwell, C.
randomly assigned to
Criteria: BMI
insulin and
wt loss
comparisons
(p<.001), waist
LI delivered by
S., Morgan, T.
LI group or usual care
25-40 with FG
anthropometry
All biochemical
99.22+/-0.90
CHW in
M., Lawlor, M.
group.
95-125mg/dL
measurements
General linear
(p<.001)
communityS., & Goff, D. C.
No differences
were performed
models for
based setting,
(2011). One-year
Purpose:
between the
in lab by
repeatedFBG 101.11+/minimizing
results of a
To translate the
groups at
technicians
measures
0.84 (p<.001).
resources and
communitymethods of the DPP
baseline
masked to the
ANCOVA to
maximizing
based translation
into the community
(42.5% M, mean
intervention
compare the
LI decreased in
community
of the diabetes
via key modifications
age 57.9 yrs,
assignment. FPG main effect of
insulin and
involvement
prevention
to enhance feasibility
26%
coefficients of
the intervention
HOMA-IR
program:
and dissemination
race/ethnicity
variation were
on the 6, 12
2.48+/-0.13
WE: the study
Healthy living
other than W,
6.45%. Insulin:
month values
(p<.001)
conducted in
A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;

38

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

partnerships to
prevent diabetes
(HELP PD)
project. Diabetes
Care, 34, 14511457. doi:
10.2337/dc102115/-/DC1
Country: U.S.A.
Funding:
NIDDKD
C/B: none

Conceptual
Framework

Design/Method

Sample/Setting

80% beyond HS)
Setting:
community
setting
Attrition: 6

Major Variables
& Definitions

Measurement

Data Analysis

the overall
within-assay
variability was
3.9%.

measured during
the 1 yr f/u.

Findings

Wt: -5.73+/-0.42
BMI: -1.90+/0.14
Waist: -5.05+/0.38
Glucose: 3.76+/-0.76
Insulin -3.75+/0.58
HOMA-IR: 1.08+/-0.17
%wt loss: 6.11+/-0.44

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice
only one
community.
Training
program must be
developed to
prepare CHW.
Reimbursement
policy is needed.
CO:
Empowering
community
members
through
partnerships with
existing DEPs
may effectively
translate DM
prevention
efforts and
ultimately alter
the course of
obesity and DM
epidemics.

CS: low-cost,
community
based LI using
CHW is
A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;

39

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

Conceptual
Framework

Design/Method

Sample/Setting

Major Variables
& Definitions

Measurement

Data Analysis

Findings

Ma, J., Yank, V.,
Xiao, L., Lavori,
P. W., Wilson, S.
R., Rosas, L. G.,
& Stafford, R. S.
(2013).
Translating the
diabetes
prevention
program lifestyle
intervention for
weight loss into
primary care: A
randomized trial.
JAMA Internal
Medicine,
173(2), 113-121.
doi:10.1001/201
3.jamainternmed
.987

TTM

D: RCT

N=241 (CG 81,
IG1=79,
IG2=81)

IV=LI (face to
face or home
based DVD to
self-directed
intervention)

BMI, wt change,
waist
circumference,
DBP, TG, HDL,
FBG

DV1=BMI
DV2=anthropom
etric and BP
measurements

All biochemical
measurements
were performed
in central lab by
technicians.

Intention-to-treat
using tests of
group by time
interactions in
repeatedmeasures mixedeffects linear for
continuous
outcomes or
logistic models
for categorical
outcomes.

Mean BMI
change from
baseline was -2.2
in the coach-led
(p<.001 vs. C,
p=.03 vs. selfdirected), -1.6 in
self-directed
(p=.02 vs. usual
care).
37% lost 7%
DPP-based st
loss goal
(p=.003) in
coach-led,
35.9% (p=.004)
in self-directed.

P: To evaluate the
effectiveness of 2
adapted DPP lifestyle
interventions among
over wt or obese adults
with prediabetes,
metabolic syndrome,
or both.

Demographics:
Mean age 52.9
yrs, BMI 32.0,
47% F, 78% W,
17% A/PI, 4.1%
H, majority had
high educational
attainment,
family annual
income

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice
encouraging for
wt loss in DM
prevention
Level 2
Strength: used
different
delivery methods
for LI (face to
face or selfdirected)
WE: primarily
high
socioeconomic
status
participants, so
difficult to
generalize the
findings.
Difficult to
evaluate the long
term effects and
comparative
costeffectiveness of
the 2
interventions.

Setting: a single
primary care
clinic within the
Silicon Valley
(Los Altos, CA)
that is part of a
Country: U.S.A.
large
multispecialty
Funding:
group practice in
multiple grants
the San
Francisco Bay
A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;

40

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

Bias: NCOI

Conceptual
Framework

Design/Method

Sample/Setting

Area.

Major Variables
& Definitions

Measurement

Data Analysis

Findings

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice
CO: Proven
effective in a PC
setting, the 2
DPP-based LI
are readily
scalable and
exportable with
potential for
substantial
clinical and PH
impact.
Level 2

Parikh, P.,
SelfDesign: RCT
N=99(age: 48,
IV=peer-led LI
Wt, Waist
Bivariate
Wt -7.2 (7.3),
Simon, E. P.,
efficacy
F=85%)
circumference,
comparisons
waist -1.3 (2.6),
Fei, K., Looker,
theory
Method: Randomly
CG=49(age: 50,
DV=wt loss
BP, LDL
with t tests, X2
FPG 10 (13),
Strength:
H., Goytia, C., &
assigned to LI or
F=84%
cholesterol,
tests, analysis of
OGTT 3 (34),
community
Horowitz, C. R.
delayed intervention in IG=50, F=86%)
FBG, OGTT,
variance for
HgA1c -0.3
based and peer(2010). Results
1 yr.
HbA1c, PA,
demographic
(0.2).
led intervention.
of a
Demographics:
food intake
characteristics
LI group lost
pilot diabetes
Purpose: to develop
Mean age of 48
Paired t-test for
significantly
Weakness: small
prevention
and pilot a simple,
yrs (range25wt and behaviors more wt than
sample size to
intervention in
peer-led intervention
84yrs),
between baseline CG; lost average generalize the
East Harlem,
to promote wt loss,
predominantly
and 12 months
7.2 lbs (p=.01).
findings.
New York City:
which can prevent DM female (85%),
Waist
Possible
Project HEED.
and eliminate
Hispanic (89%),
Focus group
circumference
contamination of
American
racial/ethnic
Spanish
interviews to
decreased
intervention to
Journal of Public
disparities in incident
speaking (77%),
study
significantly. LI
the control
Health 100,
DM among over wt
unemployed
experiences
reported eating
group.
S232-S239. doi:
adults with
(70%), uninsured
more green salad Vulnerable
10.2105/AJPH.2
prediabetes.
(49%), low
(p=.05), drinking group
A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;

41

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

009.170910
Country: U.S.A.
Funding:
National Center
on Minority
Health and
Health Disparity
Bias: NCOI

Conceptual
Framework

Design/Method

Sample/Setting

income (62%
were below the
poverty level),
undereducated
(58% had not
graduated from
high school).
Setting:
community sites
in East Harlem
in NYC

Major Variables
& Definitions

Measurement

Data Analysis

Findings

fewer sugary
beverages
(p<.01).
The incidence
rate of DM was
the same in both
groups.

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice
CO:
A communitydriven approach
to DM
prevention in
high-risk
community of
color may be
quite feasible
and effective.
This type of
program may
help to narrow
racial and ethnic
disparities

Attrition: 83
participants
returned at 3 mo,
79 at 6 mo, 72 at
12 mo. 4 became
CS: Support LI
ineligible d/t
program using
pregnancy. 23
CHW in
lost to f/u at 12
vulnerable
mo. Reasons:
population/com
relocation,
munity.
family
responsibilities,
and doctors
telling them that
their BG didn’t
need attention.
A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;

42

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

Conceptual
Framework

Design/Method

Sample/Setting

Major Variables
& Definitions

Measurement

Data Analysis

Findings

Sakane et al.
(2011).
Prevention of
type 2 diabetes
in a primary
healthcare
setting: Threeyear results of
lifestyle
intervention in
Japanese
subjects with
impaired glucose
tolerance. BMC
Public Health,
11, 40, doi:
10.1186/14712458-11-40

TTM

D: RCT

N=304
Ni=152, nc=152

IV=LI by nurse
in PC

Demographics:
mean BMI 24.5,
mean age 51,
50% F. No
differences
between two
groups.

DV=DM
incidence

Ht, wt, waist,
BP, OGTT, total
cholesterol,
HDL,
triglyceride,
creatinine, uric
acid, AST, ALT,
GGT, HbA1c,
FBG, insulin,
dietary intake,
PA

Two tailed
unpaired t test or
X2 test, two
tailed paired t
test, survival
curves, two
sided log rank
test

Wt 63.5+/-12.9
(p=.023)
FPG 5.8+/-0.6
(p=.698)
OGTT 8.0+/-2.1
(p=.083)
The estimated
cumulative
incidence of DM
was 8.2% in LI,
14.8% in CG.
RR 53% with LI
(p=.097). The LI
effect was not
apparent in the
lowest BMI
quartile.
BMI>22.5
revealed a sig
decrease in the
cumulative
incidence with
LI (p=.027).

Country: Japan
Funding:
Ministry of
Health, Welfare,
and Labor of
Japan

P: to test whether LI
by a PC setting using
existing resources, can
reduce the incidence
of T2DM in Japanese
with IGT

Setting: PC
Attrition: 91
during 3 yrs

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice
LOE: II
Weakness: only
Japanese middle
aged subjects,
Possible
contamination of
CG with LI
information
Strength: RCT
Conclusion:
Even if the
statistical sig
was weak, LI
using existing
HC resources is
beneficial in DM
prevention.

Bias: none
Thomas et al.
NA
SR
8 studies, with
NA
All 8 studies
Not reported
RR of 33% for
LOE=I,
A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;

43

IMPACT OF A BRIEF PREDIABETES EDUCATION
Citation

(2010). A
systematic
review of
lifestyle
modification and
glucose
intolerance in the
prevention of
type 2 diabetes.
Current Diabetes
Reviews, 6(6),
378-387.

Conceptual
Framework

Design/Method

P: to identify and
evaluate studies that
have investigated
impact of LI on the
prevention of the
development of DM
incidence in those with
glucose intolerance

Sample/Setting

populations
including any
non-pregnant
adult 18 and
older with 100 or
more
participants,
focusing on
activity or
dietary aspects,
RCT. Excluded
reviews, no
assessment of
incidence of
DM, sub-study
publications

Major Variables
& Definitions

Measurement

were RCT,
measured
incidence of
DM, LI as
intervention
strategy

Data Analysis

Findings

the benefits of
dietary
modifications,
51% reduction
with exercise
interventions,
51% reduction
with
combination of
LI, pooled
reduction of the
interventions of
49%.

Level/Quality of
Evidence,
Decision for
Practice/Applicat
ion to Practice
Weakness: only
8 studies,
Strength: highest
level of evidence
Conclusion:
LI has shown to
reduce the
incidence of DM
and risk of
developing one.
However, more
study is needed
to translate the
findings into the
PC settings with
less laborintensive
interventions.

A: Asian, AI: American Indian, ALT: alanine aminotransferase, AN: Alaska Native, AST: aspartate aminotransferase, BMI: body mass index, BP=blood pressure, CBPR:
community-based participatory research, CG=control group, CHW: community health workers, CI: confidence interval, CO- conclusions; CS- clinical significance; CV:
cardiovascular, DEP: DM education program, DM: diabetes, DPP: Diabetes Prevention Program, DV- dependent variable; DV2- dependent variable 2; d/t=due to, EC- exclusion
criteria; F= female, FA-Funding Agency; FBG=fasting blood glucose, FPG: fasting plasma glucose, f/u=follow-up, GGT: gamma-glutamyltransferase, HbA1c: glycosylated
hemoglobin, HC-hip circumference; Ht-height; HCP: health care programs, HD=healthy diet, HDL: high density lipoprotein, HOMA-IS: homeostasis model assessment of insulin
resistance, HS: high school, IDPP- Indian Diabetes Prevention Program; IHS: Indian Health Services, IV-independent variable; KPCO: Kaiser Permanente Colorado, LDL: low
density lipoprotein, LG: lifestyle group, LI: lifestyle intervention, M: male, MA: meta-analysis, MAQ: modifiable activity questionnaire, MG: metformin group, N: total number of
participants, n: number of sub-category participants, nc=number of participants in control group, ni=number of participants in intervention group, NA: not applicable, NCOI: no
conflict of interest, NIDDKD: National Institute of Diabetes and Digestive and Kidney Diseases, NIH: National Institutes of Health, OGTT: oral glucose-tolerance test, P: purpose,
PA=physical activity, PC: primary care, PH: public health, PI: Pacific Islander, PG: placebo group, RCT: randomized clinical trial, RR: risk reduction, SES- socioeconomic status;
SR: systemic review, TG: triglycerides, TTM-Transtheoretical model; TX: treatment, U.S.A.: United States of American, W: white, WE- weaknesses wk: week, wt: weight, yrs:
years D-demographics; IC- inclusion criteria; V2- independent variable 2; IV3-independent variable 3; MA- meta-analysis; N- sample size; NIH-National Institute of Health; PAphysical activity;

44

Running head: IMPACT OF A BRIEF PREDIABETES EDUCATION

I

Design

CS

QE

MA,

Length

SR

2013

2010

2

2

2

2

1

RCT

RCT

RCT

RCT

SR

2013 2010 2011
3
QE

2
RCT

6mo

3yr

2yr

2yr

15mo 12mo

2011 2010

3yr

Samples

1520

1638

2553

123

301

241

99

304

LI

X

X

X

X

X

X

X

X

Group

X

X

X

X

X

Individual
Wt 
BMI

X
X

X

X

X
X

X

X
X

X

X

X

X

X

X

X

OGTT

X

X

X

X

X

DMI
Knowledge

No 
No 

X
Cholesterol

X

X
X

X

FBG

X

No 

No

No

No

No

X

X

No 

X

X

No 

X

X

X

*

X

MTC
PA
HE

X

X

X

Thomas

3

Sakane

4

Parikh

LOE

Ma

2010

Katula

2012

Kang

2010

Jiang

Year

Morrell

Studies

Almeida

Cardona-

Balagopal

Table 2 Synthesis Table

X

Running head: IMPACT OF A BRIEF PREDIABETES EDUCATION

Table 3
Participant Characteristics (N=16)
Age, years

56.6  13.0 (M  SD)

Gender
Male

3 (18.8%)

Female

13 (81.3%)

Ethnicity
Caucasian

10 (62.5%)

Hispanic

6 (37.5%)

African American

0

Native American

0

Asian

0

Marital status
Single

1 (6.3%)

Married

13 (81.3%)

Divorced/Separated

2 (12.5%)

Widowed

0

Education
HS or GED

8 (50%)

Some college

2 (12.5%)

Bachelor

5 (31.3%)

Master or higher

1 (6.3%)

45

IMPACT OF A BRIEF PREDIABETES EDUCATION
Current health condition
Fair

2 (12.5%)

Good

9 (56.3%)

Very good

4 (25%)

Excellent

1 (6.3%)

Heard prediabetes/borderline
diabetes
Yes

12 (75%)

No

4 (25%)

Height, inches

65.0  3.3 (M  SD)

Weight, pounds

201.4  38.2 (M  SD)

Prediabetes screening score

12.3  4.7 (M  SD)

46

47

IMPACT OF A BRIEF PREDIABETES EDUCATION
Table 4
Results of Paired t-test for PA,EH and SE (N=16)

Outcomes
PA
EH
SE

Preintervention
M (SD)
2.88 (2.53)
6.94 (2.52)
16.69 (4.19)

Postintervention
M (SD)
5.31 (2.77)
5.00 (2.48)
19.88 (3.28)

Note. * indicates statistical significance.

95% CI
LL
-4.01
.60
-5.14

UL
-.87
3.28
-1.24

t(15)
-3.31
3.08
-3.49

p
.005*
.008*
.003*

48

IMPACT OF A BRIEF PREDIABETES EDUCATION

Perceived
susceptibility
&
Perceived
severity

Perceived
barriers

Perceived
benefits

Perceived
threat

Self-efficacy

Cues to
action
Figure 1. Health Belief Model. Adopted from Glanz, K., Rimer, B.K. & Lewis, F.M. (2002).
Health Behavior and Health Education. Theory, Research and Practice. San Fransisco: Wiley &
Sons.

IMPACT OF A BRIEF PREDIABETES EDUCATION
Appendix A
IRB Approval Letter

EXEMPTION GRANTED
Monica Rauton
CONHI - DNP
928/639-7242
monica.rauton@asu.edu
Dear Monica Rauton:
On 9/10/2015 the ASU IRB reviewed the following protocol:
Type of Review: Initial Study
Title: The impact of prediabetes awareness and a brief
education for prediabetic patients on eating habit,
physical activity and self-efficacy in a primary care
setting
Investigator: Monica Rauton
IRB ID: STUDY00003005
Funding: None
Grant Title: None
Grant ID: None
Documents Reviewed: • InformedConsent_RV3.pdf, Category: Consent
Form;
• Lee_Y_IRB_HRP_503a_SocialBehavioral_RV5.docx,
Category: IRB Protocol;
• Lee_Y_CITItraining2.pdf, Category: Non-ASU
human subjects training (if taken within last 3
years to grandfather in);
• FollowUpPhoneCallsWk1-3.pdf, Category:
Measures (Survey questions/Interview questions
/interview guides/focus group questions);
• Pre and post survey for diet assessment,
Category: Measures (Survey questions/Interview
questions /interview guides/focus group
questions);
• Recruitment Flyer_RV.pdf, Category: Recruitment
Materials;
• Pre&PostSurvey_Brief Physical Activity

49

IMPACT OF A BRIEF PREDIABETES EDUCATION
Assessment.pdf, Category: Measures (Survey
questions/Interview questions /interview
guides/focus group questions);
• Pre and post survey for self-efficacy
questionnaire, Category: Measures (Survey
questions/Interview questions /interview
guides/focus group questions);
• brief preDM education, Category: Participant
materials (specific directions for them);
• PostInterventionSurveyWk4.pdf, Category:
Measures (Survey questions/Interview questions
/interview guides/focus group questions);
• PreSurvey_Demographic_RV.pdf, Category:
Measures (Survey questions/Interview questions
/interview guides/focus group questions);
The IRB determined that the protocol is considered exempt pursuant to Federal
Regulations 45CFR46 (2) Tests, surveys, interviews, or observation on 9/2/2015.
In conducting this protocol you are required to follow the requirements listed in the
INVESTIGATOR MANUAL (HRP-103).
Sincerely,

IRB Administrator
cc:

Yunmi Lee
Yunmi Lee

IBR# STUDY00003005

IMPACT OF A BRIEF PREDIABETES EDUCATION
Appendix B
Informed consent
Prediabetes Awareness and Healthy Lifestyle
I am a graduate student under the direction of Monica Rauton in the College of Nursing and
Health Innovation at Arizona State University. I am conducting a project to assess the
impact of prediabetes awareness and a simple education on healthy lifestyle.
I am inviting you to participate in an evidence-based practice project, which will involve
one 5-minute education session of your day, once a week follow-up phone calls for 4 weeks,
and pre and post surveys. During this education session, you will learn about prediabetes,
your risk factors, and lifestyle modifications.
Your participation in the project is voluntary. You can skip questions in the survey if you
wish. If you choose not to participate or to withdraw from the project at any time, there
will be no penalty. It will not affect the care you receive prior to, during, or after your
participation in the project. Participation in this project will not affect your treatment in
this clinic. You must be 18 years of age or older to participate in this project.
Responses to the questionnaires will be used to evaluate the impact of prediabetes
awareness and education on healthy lifestyle. There are no foreseeable risks or
discomforts to your participation in this project.
Your responses on the questionnaires and surveys will be anonymous and will be identified
only by a number that will not be connected to your name or other personal identifying
information. The results of this project may be used in reports, presentation, or
publications, but your name will be not be known or used.
If you have any questions concerning this project, please contact the following team
members: Yunmi Lee, RN, BSN, DNP student (602-476-9254 or yunmi.lee@asu.edu) or
Monica Rauton, DNP, ANP-BC (928-301-7793 or monica.rauton@nahealth.com).
If you have any questions about your rights as a subject/participant in this project, or if you
feel you have been placed at risk, you can contact the Chair of the Human Subjects
Institutional Review Board, through the ASU Office of Research Integrity and Assurance, at
(480) 965-6788. Please let me know if you wish to be part of the project.

IBR# STUDY00003005

IMPACT OF A BRIEF PREDIABETES EDUCATION

By signing below you are agreeing to be part of the project.
Name:
Signature:

IBR# STUDY00003005

Date:

/

/

IMPACT OF A BRIEF PREDIABETES EDUCATION
Appendix C
Demographic Information
1. Age:

years

2. Gender:
1. ☐ male
2. ☐ female
3. Ethnicity:
1. ☐ Caucasian
2. ☐ Hispanic
3. ☐ African American
4. ☐ Native Indian
5. ☐ Asian
6. ☐ Others: specify
4. Marital Status:
1. ☐ Single
2. ☐ Married
3. ☐ Divorced/Separated
4. ☐ Widowed
5. Education Status:
1. ☐ No high school diploma
or GED
2. ☐ Have a high school
diploma or GED
3. ☐ Have a college degree
4. ☐ Have a Bachelor degree
5. ☐ Have a Master degree or
higher
6. How would you describe your
current health condition?
1. ☐ Excellent
2. ☐ Very good
3. ☐ Good
4. ☐ Fair
5. ☐ Poor

IBR# STUDY00003005

7. Have you ever heard of
prediabetes or borderline
diabetes?
1. ☐ Yes
2. ☐ No
8. Height:

in

9. Weight:

lbs

ID#
Pre/Post-intervention
Appendix D
Lifestyle Change Intervention
PREDIABETES INFORMATION
What is PREDIABETES?
Prediabetes is a condition that can lead to type 2 diabetes. It means your blood glucose
(sugar) levels are higher than normal but are not high enough to be called diabetes.
Diabetes can cause other health problems such as heart disease, stroke, blindness,
kidney failure, amputations, and nerve damage. There are no clear symptoms of
prediabetes. You can have it and not know it.
Who is at RISK for PREDIABETES?
Your risk for prediabetes will go up if you:
 are age 45 or older
 have a parent, brother, or sister with diabetes
 are a woman who had diabetes during pregnancy
 are overweight
 are NOT physically active
We have a GOOD NEWS for you.
The good news is that you can prevent or delay type 2 diabetes with healthier lifestyle
changes such as:
 healthier eating
 physical activity
 weight loss
How do I make HEALTHY CHANGES?
You do not have to make a big change. Try small steps to eat healthy, be active, and
lose weight. Here are some tips for you.










Eat healthier
Cut back on regular soda and juice. Have water or calorie-free drinks.
Eat smaller serving sizes of your usual foods.
Choose baked, grilled, and steamed foods instead of pan-fried or deep-fried.
Eat more vegetables, whole grains, and fruit.
Cut back on starchy food such as white rice, flour tortilla, pasta, potato, or
bread.
Start each dinner with a salad of leafy greens with low-fat dressing.
Choose fruit instead of cake, pie or cookies.
Eat lean meats such as the round or loin cuts, chicken without the skin, or fish.
Cut back on high fat and processed meats like hot dogs, sausage, and bacon.
Be active

IBR# STUDY00003005

ID#
Pre/Post-intervention



Find physical activity you like to do such as gardening, walking the dog, or
dancing.
Walk briskly 30 minutes a day, 5 days a week. Or split the 30 minutes into
three 10-minute walks.

Lose weight
 Research suggests that if you are overweight, losing 7% of your weight may
prevent your risk for diabetes. In fact, losing even a few pounds will help you.

IBR# STUDY00003005

ID#
Pre/Post-intervention
Appendix E
Physical Activity Questionnaire
Brief Physical Activity Assessment
1. How many times a week, do you usually do 20 minutes of vigorous physical activity
that makes you sweat or puff and pant? (For example, jogging, heavy lifting, digging,
aerobics, or fast bicycling)
☐ >3 times/week

☐ 1-2 times/week

☐ none

2. How many times a week, do you usually do 30 minutes of moderate physical activity
or walking that increases your heart rate or makes you breath harder than normal?
(For example, mowing the lawn, carrying light loads, bicycling at a regular pace, or
playing doubles tennis)
☐ >5 times/week

IBR# STUDY00003005

☐ 3-4 times/week ☐ 1-2 times/week ☐ none

ID#
Pre/Post-intervention
Appendix F
Eating Habit Questionnaire
Starting The Conversation
Over the past 4 weeks:
1. How many times a week did you eat fast food meals or snacks?
☐ Less than 1 time

☐ 1-3 times

☐ 4 or more times

2. How many servings of fruit did you eat each day?
☐ 5 or more

☐ 3-4

☐ 2 or less

3. How many servings of vegetables did you eat each day?
☐ 5 or more

☐ 3-4

☐ 2 or less

4. How many regular sodas or glasses of sweet tea did you drink each day?
☐ Less than 1

☐ 1-2

☐ 3 or more

5. How many times a week did you eat beans (like pinto or black beans), chicken, or fish?
☐ 3 or more times

☐ 1-2 times

☐ less than 1 time

6. How many times a week did you eat regular snack chips or cracker (not low-fat)?
☐ 1 time or less

☐ 2-3 times

☐ 4 or more times

7. How many times a week did you eat desserts and other sweets (not the low-fat kind)?
☐ 1 time or less

☐ 2-3 times

☐ 4 or more times

8. How much margarine, butter, or meat fat do you use to season vegetables or put on
potatoes, bread, or corn?
☐ Very little

IBR# STUDY00003005

☐ some

☐ a lot

ID#
Pre/Postintervention
Appendix G
Prediabetes Lifestyle Change Self-Efficacy
Tell us how confident you are in doing certain activities. For each of the following
questions, please choose the number that corresponds to your confidence that you can do
the tasks regularly at the present time.
(0=not at all confident, 1=a little confident, 2=somewhat confident, 3=very confident,
4=totally confident).
1. How confident are you that you can
cut back on regular soda or juice?

0

1

2

3

4

2. How confident are you that you can
eat smaller serving size?

0

1

2

3

4

3. How confident are you that you can
eat more vegetables and fruits?

0

1

2

3

4

4. How confident are you that you can
walk 30 minutes a day, 5 days a week?

0

1

2

3

4

5. How confident are you that you can
lose weight?

0

1

2

3

4

6. How confident are you that you can
prevent or delay type 2 diabetes?

0

1

2

3

4

IMPACT OF A BRIEF PREDIABETES EDUCATION

59

Appendix H
Budget
Item
Printed education material
(colored)
Education time (3-5 min) by MD
Education time (3-5 min) by NP
Education time (3-5min) by MA
Follow up time (3 min) by
MD/week
Follow up time (3 min) by
NP/week
Follow up time (3 min) by
MA/week
Total cost/participant with MD
Total cost/participant with NP
Total cost/participant with MA

Cost
$0.11

Occurrence
1

$4.62-$7.70
$2.37-$3.95
$0.75-$1.25
$4.62

1
1
1
4

$2.37

4

$0.75

4

$23.10-$26.18
$11.96-$13.54
$3.86-$4.36