DIABETES MANAGEMENT KNOWLEDGE 1 Diabetes Management Knowledge and Behavior Change Amongst At-risk Women Marisol Gandee Edson College of Nursing and Health Innovation, Arizona State University Author Note Marisol Gandee is a registered nurse in the neurological intensive care unit at Barrow Neurological Institute within St. Joseph’s Hospital and Medical Center in Phoenix, AZ. She has no conflict of interest to disclose. Correspondence should be addressed to Marisol Gandee, Edson College of Nursing and Health Innovation, Arizona State University, Downtown Campus, 550 N. 3rd Street, Phoenix, AZ 85004. Email: mhinoj1@asu.edu DIABETES MANAGEMENT KNOWLEDGE Abstract 2 Background: People with diabetes are at greater risk for comorbid cardiovascular disease, end stage organ damage, disability, and early death. There is substantial evidence that individualizing self-care education, such as eating a healthy diet, greatly improves diabetes management. Objective: The purpose of this paper is to review the outcomes of a diabetes education program offered to underserved women in the Southwestern United States. Methods: Four weekly nutrition classes were individualized and taught at a nonprofit organization in the southwest United States. Behavior change was measured using the Summary of Diabetes Self-Care Activities (SDSCA) tool. Classes were advertised via the center’s monthly class calendar and fliers. A total of nine participants (N=9) came to every class and took the SDSCA survey before and after class instruction. Results: Descriptive statistics and two 2-tailed t-tests with the critical value set at p<0.05 were used for data analysis. The participants were Hispanic women, most between the ages of 40-49, and had an income between $0-14,000. The mean difference between the variables of both general diet and specific diet pre and post-tests were significantly different from zero. The assumptions of normality and homogeneity were met. The results of both two-tailed paired sample t-tests were significant suggesting the means of general and specific diet pre-tests were significantly lower than the means of the general and specific diet post-tests. Discussion: The assumptions of normality and homogeneity were met and the results were significant. The pre-intervention scores for both categories were statistically significantly lower than the post-intervention scores for both categories. Thus, the desired outcome of helping clients within the organization modify, adapt, or change self-care behaviors related to diet was met. Keywords: diabetes mellitus type 2, women, ethnic minority, diet, low income, low education, educational intervention DIABETES MANAGEMENT KNOWLEDGE Diabetes Management Knowledge Amongst At-risk Women 3 Diabetes type 2 continues to impact millions of people throughout the United States (U.S.). Racial, ethnic, minority, rural communities, and low-income populations are especially vulnerable to diabetes due to the lack of resources and low health literacy experienced by these communities. Additionally, women are at higher risk for diabetes due to higher waist circumference, impaired glucose tolerance, low testosterone, job strain, less leisure time, low education and socioeconomic status, previous gestational diabetes, and polycystic ovarian syndrome (Kautzky-Willer et al., 2016). Background and Significance Problem Statement The incidence and prevalence of diabetes continues to grow in the United States and worldwide. People with diabetes are at greater risk for comorbid cardiovascular disease, end stage organ damage, disability, and early death. In the U.S., the prevalence of diagnosed type 2 diabetes was 8.6% or 21.0 million adults in 2016 (Bullard et al., 2018). There was a total of 7.8 million hospital discharges amongst diabetic adults in the United States in 2016 (Diabetes Research Institute, 2020). These discharges included 1.7 million related to cardiovascular diseases, 130,000 related to lower-extremity amputation, and 209,000 related to hyperglycemic crisis. In addition to hospitalizations, emergency room visits related to diabetes amongst adults in 2016 totaled 16 million (Diabetes Research Institute, 2020). Not only can diabetes lead to poor quality of life, disability, and early death, it can lead to high healthcare costs as well. About 10% of total healthcare budgets are spent on treating diabetes and its associated complications worldwide (Xin et al., 2020). Hospital costs alone have DIABETES MANAGEMENT KNOWLEDGE been identified as the main contributor to total costs of the economic/societal burden of diabetes 4 (Janssen et al., 2020; Andersson et al., 2020). Purpose and Rationale Diabetes rates in Arizona are slightly higher than the national rates and higher than about half of all U.S. states (America’s Health Rankings, 2021). Socioeconomic factors such as gender, race, level of education, and income level greatly influence these rates in Arizona. An effective diabetes education program focusing on nutrition positively impacts obesity and diabetes management (Sanchez et al., 2021). Since lower obesity rates and better diabetes management positively impacts health, the hope is that hospital visits, mortality, disability, and healthcare costs will decrease accordingly. The purpose of this review was to identify methods to address diabetes prevention and management education with an emphasis in nutrition to atrisk women within a nonprofit organization in an urban setting. Epidemiological data According to the Behavior Risk Factor Surveillance System (BRFSS), a U.S. survey that collects data on disease rates and health-related risk behavior, Arizona has a type 2 diabetes prevalence rate of 9.1% (Jaycox, S. & Paglialunga, 2018). In Maricopa County, the type 2 diabetes prevalence rate is even higher at 10.8%. The cost of diabetes type 2 in Arizona is estimated to be about $6.4 billion (American Diabetes Association, 2016). In the U. S., the cost of diabetes type 2 in 2017 was estimated to be $327 billion (Yang et al., 2018). Globally, diabetes type 2 prevalence among adults rose from 4.7% in 1980 to 8.5% in 2014 causing an estimated 1.6 million deaths worldwide (World Health Organization, 2021). Internal Evidence DIABETES MANAGEMENT KNOWLEDGE Population 5 The current literature discusses gender differences, social disparities, and behavioral change related to diabetes type 2. Low-income women have a higher lifetime risk of diabetes compared to men and/or higher income women (Silva-Tinoco et al., 2020; Van Herpt et al., 2020). In addition, Thornton et al. (2020) describes how minorities are socially disadvantaged and have a higher risk for diabetes. Morales et al (2020), appreciates that both diagnosed and undiagnosed diabetics with cardiovascular complications are approximately twice as high in the U. S. Hispanic population compared to the non-Hispanic white population due to skepticism of the healthcare system, food insecurity, and language barriers. The nonprofit organization where this project was conducted that serves low-income women has a Hispanic population of 61% of the total population; which is greater than the reported Hispanic population in Phoenix at 42.6% (United States Census Bureau, 2019). Interventions There is a gap of knowledge about diabetes prevention and management that can be addressed by providing self-care education through tailored interventions suitable for patients of different education levels and cultural backgrounds (Abouammoh & Alshamrani, 2020; Mufunda et al., 2018). In addition, access to resources and motivation to change self-behavior is imperative when teaching about self-care to prevent or manage diabetes (Muhwava et al., 2019; Yee et al., 2020). The project site offers resources and group classes, such as parenting and life skills classes that increase knowledge and motivation efforts. There is a great deal of literature supporting the use of lifestyle modifications via diet to aid in preventing and managing diabetes. Current Practice DIABETES MANAGEMENT KNOWLEDGE In the Glucose Lowering through Weight management (GLoW) trial, tailored diabetes 6 education and a behavioral weight management program (DEW) offered more effective results than diabetes education alone in treating diabetes (Ahern et al., 2020). In a prospective cohort study by Hendryx et al. (2020), many variables contributing to diabetes among women were explored including psychosocial variables such as optimism, depression, and social support. Providing resources to control these variables was deemed helpful when managing diabetes. The nonprofit organization chosen to address diabetes prevention and management education offers classes addressing the discussed variables, however, there were no specific diabetes related classes. Outcome The final desired outcome of this project was to help clients within the nonprofit organization where the project was implemented modify, adapt, or change self-care behaviors related to diabetes prevention and management via diet. In this manner, diabetes diagnosis and its associated complications should hopefully decrease among this group leading to less hospital visits, deaths, resource utilization, and healthcare costs (Ahern et al., 2020; Andersson et al., 2020; Janssen et al., 2020). Generalized diabetes care has shown to be ineffective when treating diabetic patients holistically. As evidenced by the reviewed literature, individualizing interventions for patients of different education levels, cultural backgrounds, socioeconomic status, and gender will help improve overall health and reduce the incidence of diabetes diagnosis and complications. In a nonprofit organization serving women and teen girls in the metro Phoenix area who are facing difficult life situations, diabetes education was a missing piece to the classes and programs offered at this organization. Staff at the center verbalized the need for diabetes DIABETES MANAGEMENT KNOWLEDGE education because their clients asked for information on this subject. The organization serves 7 over 1,000 clients per month who are predominantly low-income (86% under $14,000 per year income) women. The largest group of clients who utilize the resources at this organization are Hispanic (61%) and in their 30’s (32%). There is no data or electronic medical records on diabetes percentages of the clients within this organization, as it is not a health clinic. PICOT Interest in this problem led to a review of current evidence to determine the best interventions for diabetes prevention and management. Self-care, access to resources, and change in behavior are common themes found in the literature related to successful diabetes prevention and management. This inquiry has led to the clinically relevant PICOT question: In at-risk women, what is the effect of diabetes prevention and management education, compared to current practice, on behavior change within 4 weeks? Evidence Synthesis Search Strategy A thorough review of current evidence was done to answer the PICOT question using three databases. PubMed, Cochrane, and CINAHL were chosen because they cover the topics of interest and provide peer reviewed literature. These databases were extensively searched and the most relevant articles were chosen for this review. Combinations of key terms were used to search these databases. The key terms used included: underserved women, underprivileged women, neglected women, poor women, at risk women, diet teaching, nutritional teaching, healthy cooking teaching, healthy diet, nutritious diet, diabetes, adult-onset diabetes, diabetes mellitus type 2, non-insulin dependent diabetes mellitus (NIDDM). Boolean connector OR was used for each group of key words within a DIABETES MANAGEMENT KNOWLEDGE component of the PICO question while the Boolean connector AND was used to connect those 8 components. A limitation to the search included the dates of publication, 2018 to 2021. In the final evaluation of the evidence, all included studies had dates of publication between 20182020. When search results yielded close to 200 articles in each database, titles of those articles were reviewed. An initial search of PubMed using the key terms and Boolean connectors underserved women OR underprivileged women OR neglected women AND diet teaching OR nutritional teaching OR healthy cooking teaching AND diabetes mellitus type 2 OR adult-onset diabetes OR NIDDM yielded six results. The search was repeated using underserved women OR underprivileged women AND diet teaching OR nutritional teaching AND diabetes mellitus type 2 OR adult-onset diabetes and yielded five results. The terms and Boolean connectors underserved women AND nutritional teaching AND diabetes mellitus type 2 only yielded two results. Underserved women AND nutritional teaching AND diabetes yielded four results. The terms and Boolean connectors at risk women OR poor women AND diet OR nutrition AND diabetes yielded 9,053 results. Therefore, filters were applied for the date of publication (2015-2021) for this particular search yielding 4,571 results. Then, the date of publication was further changed from 2015-2021 to 2020-2021 yielding 1,010 results. The terms and Boolean connectors At risk women AND diet AND diabetes yielded 4,796 results. Then, the date of publication of 2021 was included in this particular search and only yielded 27 results. Poor women AND diet AND diabetes were then searched yielding 480 results. Date of publication of 2021 was included in this specific search and only yielded four results. Date of publication was further adjusted to this search (2015-2021) yielding 217 results. The titles of 217 articles were reviewed. DIABETES MANAGEMENT KNOWLEDGE 9 The initial search of CINAHL using the terms and Boolean connectors poor women AND diet AND diabetes yielded 24 results. At risk women AND diet AND diabetes yielded 571 results. At risk women OR poor women AND diet OR nutrition AND diabetes yielded 757 results. Publication dates of 2015 to 2021 were then added to these terms yielding 317 results. The titles of 317 articles were reviewed. The initial search of Cochrane using the terms and Boolean connectors poor women AND diet AND diabetes with publication dates 2020-2021 yielded two results. The search was broadened and publication date was changed from 2015-2021 yielding 128 results. The terms and Boolean connectors poor women AND knowledge AND diabetes were also searched yielding 38,840 results. The search was restricted using publication dates 2020-2021 yielding 131 results. The titles of 131 articles were reviewed. After reviewing all 3 databases using the key words mentioned above, Six-hundred and sixty-five titles were reviewed for content in totality. Abstracts were chosen with the inclusion criteria of people with diabetes or risk of diabetes, high BMI, lifestyle modification, minorities, low education, low socioeconomic status, women, adults, families, a component of diabetes knowledge, education, or nutrition. Based on this criteria, sixty abstracts were selected for further review. From those reviewed, 31 full text studies were reviewed in their entirety. A rapid critical appraisal checklist was used in order to finalize the ten studies providing the best evidence to address the PICO question. The studies included three randomized control trials, two systematic reviews, two cohort studies, and two cross sectional studies. Critical Appraisal The search strategy yielded quantitative studies addressing several important aspects to consider, such as culture, behaviors, beliefs, socioeconomic status, and education level, when DIABETES MANAGEMENT KNOWLEDGE addressing knowledge deficits and introducing change (see Appendix A, Table A1). Designs 10 included randomized control trials, systematic reviews, cohort studies, and cross sectional studies. All studies consisted of multiple authors throughout the world and were published between 2018-2020. There were multiple independent variables in these studies. However, self-care behavior and knowledge were the most widely used independent variables (see Appendix A, Table A2). The most widely used dependent variables in these studies included DM and HgA1c/glycemic control. Six studies used a large study sample while four studies used a smaller sample (<100) (see Appendix A, Table A1). Sampling included mostly adults, with one study including only women and another study including family units with children older than seven years old. The most widely used data analysis tools used in the studies included chi-square tests, t-tests, and logistic regression. Overall, findings in these studies showed that knowledge deficits and social disparities negatively affect diabetes control while self-care activities such as eating a healthy diet positively affect diabetes control. Large sample size, high-level evidence and long length of follow up contributed to the strengths of the studies. One setting, small sample size, short follow up, variability, selfreporting and lack of a control group contributed to the limitations of the studies. Heterogeneity in sample demographics, variables of interest, measurements, and outcomes somewhat obscured data evaluation. Some bias was found including some studies with no control group or no blinding of groups. Impact of Evidence This evidence suggested that interventions specifically addressing knowledge deficits and social disparities must be used to effectively produce diabetes education for lifestyle changes. DIABETES MANAGEMENT KNOWLEDGE Knowledge about self-care can be increased by tailoring interventions that are suitable for 11 patients of different education levels and cultural backgrounds while making resources accessible to them. Other variables such as optimism, depression, and social support should be addressed as well. With this information, a personalized diabetes education program was developed to improve knowledge and promote change within this population. Theoretical Framework and Implementation Framework Theory Application The Health Belief Model (HBM) stems from psychological and behavioral theory that was developed in the 1950’s by social scientists to better understand why people fail to assume disease prevention strategies for prevention of disease or worsening of a disease process (LaMorte, 2019). Belief in the threat of disease and belief in the effectiveness of a health behavior greatly predicts if a person will adopt that behavior. The desire to avoid disease, get better if already sick, and the belief that certain health behaviors will prevent or cure disease are the foundation of the HBM. There are six constructs to the HBM: perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cue to action, and self-efficacy (LaMorte, 2019). Perceived susceptibility entails a person’s subjective perception of the risk of a disease or illness, which includes personal feelings of vulnerability. Perceived severity involves a person’s feelings on the seriousness of the disease or illness, which a person considers the medical and social consequences. Perceived benefits become a person’s perception of the effectiveness of several behaviors or actions that reduce or eliminate the threat of disease or illness. At this point, a person will consider and evaluate both the perceived susceptibility to disease and benefit of an intervention before actually acting on the intervention. Perceived DIABETES MANAGEMENT KNOWLEDGE barriers affect a person’s feelings on the obstacles and constraints to performing a health 12 behavior or action. Obstacles that a person might consider include expense, side effects, unpleasantness, time-consuming, and/or inconvenience. The stimulus needed to make the decision to undertake a health behavior or action constitutes the cue to action construct. Multiple internal and/or external cues greatly affect the decision to action. Lastly, self-efficacy entails the person’s confidence and the ability to carry out the behavior or action successfully (See Appendix B, Figure B1). The HBM was applicable for the desired outcomes from the research evidence. It applied to several factors that were necessary to make a behavior change. The clients learned to commit to change by acknowledging the possibility for them to fall ill to diabetes and diabetic complications. They also realized how severe the complications from diabetes really are. Then, they understood that self-care actions, such as eating a healthy diet, positively affects their health and lowers the risk of diabetes and complications. In addition, barriers that caused them to fail were identified. The time for action was evident when the confidence to carry out the action became evident. Implementation Framework The Rosswurm and Larrabee Model uses a six step systematic process for changes to evidence-based practice (Duffy, 2004). This model was suitable for this evidence-based project as it used the six steps in alignment with goals of the project. The first step assesses the need for change in practice via internal data by comparing current practice to external data. There was no practice on diabetes prevention and management available at a nonprofit organization serving women and teen girls in the metro Phoenix area. Therefore, there was a need for implementation of a diabetes education program at this facility. The second step links the problem (lack of DIABETES MANAGEMENT KNOWLEDGE diabetes education) with an intervention (diabetes education) to improve outcomes. The third 13 step synthesizes the best evidence by a literature review and critical appraisal of research on the topic (diabetes). Next, the fourth step is to design a practice change based on feedback from stakeholders utilizing the available resources. The stakeholders provided their feedback and made it clear that they wanted to focus on nutrition for diabetes prevention and management. Step five consists of implementing and evaluating the change in practice. Classes were implemented and evaluated at this nonprofit organization. Data were collected and analyzed to determine efficacy of the project. Lastly, step six integrates and maintains the change in practice if the results support the new practice into standards of care. This project can become a legacy project as there are several topics to cover within diabetes . (See Appendix B, Figure B2). Methods Ethical Considerations Project managers for this project did not have access to any client’s personal, identifiable data. The center’s staff collects their own data so that they may track class attendance and demographics. This data is stored in the CEO’s office computer and paper records located in her office, in which she locks when she is not in her office. The CEO of the center never shares her computer password with anyone. The data is stored there indefinitely since clients may come and go at different intervals of their lives. There were not any audio or visual recordings of any kind during the project implementation. There were not any signed consents to store since the filling out of the survey by the clients served as consent for this project. Only the project managers had access to the completed surveys with no identifiable data on them and they were locked in a cabinet at the implementer’s DIABETES MANAGEMENT KNOWLEDGE 14 home until completion of the project. The surveys will then be shredded after project completion and dissemination. No contact information was needed for follow up. Clients have already been assigned a unique ID by the center’s staff upon initial registration for the center’s records. The unique ID was written at the top of the survey by center staff in order to link the pre and post surveys together. All demographic data was de-identified prior to releasing to the project manager. There were no foreseeable risks, discomforts, or inconveniences related to participation in the project other than time. The time it took to fill out the survey was approximately 10-15 minutes each time. Population and Setting The organization where the project was implemented is a faith-based, nonprofit organization serving women and teen girls in the metro Phoenix area who are facing difficult life situations. The women who come to this organization endure addiction, domestic abuse, sexual abuse, unplanned pregnancy, unemployment, loss of support system, human trafficking, the foster care system, and/or homelessness. Grief and recovery support groups, along with mentoring, are offered here. In addition, the organization provides multiple classes such as parenting, life skills, job skills, faith-based education, anger management, and prenatal classes. Crisis counseling is available at this center as well. Point incentive programs are used for material assistance. Women can attend the support groups, classes, and counseling in person or via Zoom to earn points to buy material goods and assistance. The center provides childcare for those that attend in person. Key stakeholders for this practice change included women and their families who utilize services at the center where the intervention took place, providers, and healthcare organizations. DIABETES MANAGEMENT KNOWLEDGE 15 The center is instrumental to the project because this is where the intervention took place since many women are gathered here for learning purposes already. The intervention outcome aligned with the center’s mission and values of encouraging, engaging, and supplying women and teen girls with education and resources. The criteria that were needed to participate in this project included: Women who were receiving services at the center, were 18 years old or older, were able to speak, read, and write either English or Spanish. Participants benefited by learning how to manage positive behavioral changes allowing them to eat healthier and prevent diabetes and its complications. Participants also benefited from learning how to cook healthy, low carb, low fat meals, keeping track of their calories, and learning how to portion control. Project Description The pre-intervention phase of the project consisted of IRB approval (which was obtained on 8/26/21), the establishment of a four-week class schedule (55 minutes each) at the center, and advertisement of the classes via the center’s monthly class calendar and a flier that was posted at the center in the front office where clients check in for classes. The calendar of classes is normally both printed and available online on the center’s website. The flier conveyed information such as the offering of extra points (redeemable in the boutique on campus) and the chance to win a prize for participation in these classes. The intervention phase consisted of four class interactions over a four-week period. Week one consisted of an introduction of the classes and program overview from the Centers of Disease Control and Prevention (CDC), project details in both English and Spanish, completion of the Summary of Diabetes Self-Care Activities (SDSCA) measure, handouts, and education session. Weekly session titles included: Track your food, Eat well to prevent type 2 diabetes, DIABETES MANAGEMENT KNOWLEDGE 16 Burn more calories than you take in, and Stay Motivated/Get Support. Week four also included closure, raffle drawing, and completion of the SDSCA once again. The post-intervention phase consisted of data analysis using Intellectus software. Descriptive statistics was used to describe the sample and outcome variable. Statistical analysis was performed using two 2-tailed tests with the critical value set at p<0.05. Data Analysis The outcomes that were measured consisted of the mediation of self-care behaviors facilitated by diabetes knowledge. The SDSCA questionnaire that was utilized for this project was developed by Dr. Deborah J. Toobert, Senior Scientist Emerita at Oregon Research Institute. The SDSCA tool is a brief, reliable, and valid self-report measure of diabetes self-management (Toobert, Hampson, & Glasgow, 2000). The original version of the SDSCA (in both English and Spanish), with permission, was employed for this project. The SDSCA consists of 11 questions related to diet, exercise, blood-glucose testing, foot care, and smoking status. Reliability of the SDSCA tool was determined to be high when the average inter-item correlations within scales was measured in several studies (mean=0.47) with the exception of the specific diet subscale. Test-retest correlations were moderate (mean=0.40). Correlations with other measures of diet and exercise sustained the validity of the SDSCA subscales (mean=0.23) (Toobert, Hampson, & Glasgow, 2000). Nine participants completed both the pre-survey before the intervention and the postsurvey after the intervention. These nine participants came to every class. The maximum number of participants in one class (the last class) was 15, however, six of these participants were not present during the first class and therefore did not complete the pre-survey. Scores of DIABETES MANAGEMENT KNOWLEDGE the SDSCA survey were then compared pre-intervention and post-intervention for the nine 17 participants who completed all four classes. Per the SDSCA scoring directions, for items 1-10, the number of days per week (0-7) was used. Higher number scores represented healthier behaviors. The means of each section (items 1-10) general diet, specific diet, exercise, blood glucose testing, and foot care were analyzed. Item number four was reversed scored. The last section (item 11), smoking status, was scored as 0 for smokers and 1 for non-smokers. Items 1-4 (general and specific diet) were included in the statistical analysis since answers to all of the other items were not applicable to the participants. The demographics that were collected by the center included income range, age range, marital status, and ethnicity/racial background. As previously mentioned, the data was analyzed using descriptive statistics and two 2-tailed t-tests using Intellectus software. The critical value was set at p<0.05. Budget The materials for operation of the classes included ink, paper, and pens. The estimation of copies needed for classes was based on 20 clients per center staff. Therefore, it was estimated that 1,024 copies of all participant and facilitator materials would be needed in totality. Also, it was estimated that 2 black and 3 color ink cartridges would be utilized. Sixty pens were bought as well. The project manager paid for most of the costs related to the project with assistance from Mountain Park Health Center, St Joseph’s Hospital and Medical Center, and the project site. Other costs such as gas mileage and prize were paid for by the project manager (See Appendix C, Table C1). The class instructor was the DNP student project manager and she did not charge for her time. Sustainability DIABETES MANAGEMENT KNOWLEDGE The CEO, program support coordinator, and Arizona State University (ASU) will help 18 facilitate the sustainability plan for this project. This project can easily continue on to become a legacy project at ASU since there are several topics for education purposes surrounding diabetes. Also, the program support coordinator would be instrumental in helping with training of both current and new volunteers about the program. The curricula provided by the CDC is easy to follow for both instructors and clients. Each client will continue to earn center points for future classes. The low cost of the program contributes to sustainability. Results Descriptive Statistics Introduction Frequencies and percentages were calculated for Marital Status, Income Range, Age Range, and Ethnicity/Racial Background. Frequencies and Percentages The most frequently observed category of Marital Status was married (n = 6, 66.67%). The most frequently observed category of Income Range was 0-14,000 (n = 7, 77.78%). The most frequently observed category of Age Range was 40-49 (n = 4, 44.44%). The most frequently observed category of Ethnicity/Racial Background was Hispanic (n = 9, 100.00%). Frequencies and percentages are presented in Table 3. Table 3 Frequency Table for Nominal Variables Variable Marital Status single married Missing n % 3 6 0 33.33 66.67 0.00 19 DIABETES MANAGEMENT KNOWLEDGE Income Range 0-14,000 30-44,000 15-29,000 Missing Age Range 50-59 40-49 60-69 Missing Ethnicity/Racial Background Hispanic Missing Note. Due to rounding errors, percentages may not equal 100%. 7 1 1 0 77.78 11.11 11.11 0.00 3 4 2 0 33.33 44.44 22.22 0.00 9 0 100.00 0.00 Two-Tailed Paired Samples t-Test Introduction A two-tailed paired samples t-test was conducted to examine whether the mean difference of General Diet Pre and General Diet Post was significantly different from zero. Assumptions Normality. A Shapiro-Wilk test was conducted to determine whether the differences in General Diet Pre and General Diet Post could have been produced by a normal distribution (Razali & Wah, 2011). The results of the Shapiro-Wilk test were not significant based on an alpha value of .05, W = 0.87, p = .116. This result suggests the possibility that the differences in General Diet Pre and General Diet Post were produced by a normal distribution cannot be ruled out, indicating the normality assumption is met. Homogeneity of Variance. Levene's test was conducted to assess whether the variances of General Diet Pre and General Diet Post were significantly different. The result of Levene's test was not significant based on an alpha value of .05, F(1, 16) = 0.71, p = .413. This result suggests DIABETES MANAGEMENT KNOWLEDGE it is possible that General Diet Pre and General Diet Post were produced by distributions with 20 equal variances, indicating the assumption of homogeneity of variance was met. Results The result of the two-tailed paired samples t-test was significant based on an alpha value of .05, t(8) = -3.12, p = .014. This finding suggests the difference in the mean of General Diet Pre and the mean of General Diet Post was significantly different from zero. The mean of General Diet Pre was significantly lower than the mean of General Diet Post. The results are presented in Table 1. A bar plot of the means is presented in Figure 1. Table 1 Two-Tailed Paired Samples t-Test for the Difference Between General Diet Pre and General Diet Post General Diet Pre General Diet Post M SD M SD t p 2.22 1.77 3.50 1.41 -3.12 .014 Note. N = 9. Degrees of Freedom for the t-statistic = 8. d represents Cohen's d. Figure 1 The means of General Diet Pre and General Diet Post with 95.00% CI Error Bars d 1.04 DIABETES MANAGEMENT KNOWLEDGE 21 Two-Tailed Paired Samples t-Test Introduction A two-tailed paired samples t-test was conducted to examine whether the mean difference of Specific Diet Pre and Specific Diet Post was significantly different from zero. Assumptions Normality. A Shapiro-Wilk test was conducted to determine whether the differences in Specific Diet Pre and Specific Diet Post could have been produced by a normal distribution (Razali & Wah, 2011). The results of the Shapiro-Wilk test were not significant based on an alpha value of .05, W = 0.89, p = .195. This result suggests the possibility that the differences in Specific Diet Pre and Specific Diet Post were produced by a normal distribution cannot be ruled out, indicating the normality assumption is met. 22 DIABETES MANAGEMENT KNOWLEDGE Homogeneity of Variance. Levene's test was conducted to assess whether the variances of Specific Diet Pre and Specific Diet Post were significantly different. The result of Levene's test was not significant based on an alpha value of .05, F(1, 16) = 0.24, p = .634. This result suggests it is possible that Specific Diet Pre and Specific Diet Post were produced by distributions with equal variances, indicating the assumption of homogeneity of variance was met. Results The result of the two-tailed paired samples t-test was significant based on an alpha value of .05, t(8) = -3.78, p = .005. This finding suggests the difference in the mean of Specific Diet Pre and the mean of Specific Diet Post was significantly different from zero. The mean of Specific Diet Pre was significantly lower than the mean of Specific Diet Post. The results are presented in Table 2. A bar plot of the means is presented in Figure 2. Table 2 Two-Tailed Paired Samples t-Test for the Difference Between Specific Diet Pre and Specific Diet Post Specific Diet Pre Specific Diet Post M SD M SD t p 3.17 1.15 3.94 0.88 -3.78 .005 Note. N = 9. Degrees of Freedom for the t-statistic = 8. d represents Cohen's d. Figure 2 The means of Specific Diet Pre and Specific Diet Post with 95.00% CI Error Bars d 1.26 DIABETES MANAGEMENT KNOWLEDGE 23 Discussion The demographic information of marital status, income range, age range, and ethnicity/racial background was collected prior to the intervention per the organization’s staff members. The majority of the participants were married, earned less than $14,000 per year, and were aged 40-49. All of the participants were Hispanic and spoke mainly Spanish. A two-tailed paired samples t-test was conducted on the general diet and specific diet items of the SDSCA survey as they directly relate to the project purpose: Addressing diabetes management and prevention education gaps with weekly classes with emphasis on nutrition. The mean results of each section pre-intervention and post-intervention were compared. The assumptions of normality and homogeneity were met and the results were significant. The pre-intervention scores for both categories were statistically significantly lower than the post-intervention scores for both categories. Thus, the desired outcome of helping clients within the organization modify, adapt, or change self-care behaviors related to diet was met. DIABETES MANAGEMENT KNOWLEDGE 24 The main limitation of this project was the sample size (N=9). The maximum capacity of each classroom is 20 clients. In addition, the same participants had to be willing to come to at least the first and last class and fill out the SDSCA survey twice in order to be included in statistical analysis. The nine participants did attend all of the classes. Another limitation included convenience sampling because participants were chosen from the same place of gathering. Furthermore, the time frame of four weeks to roll out the project was too short to sufficiently promote and measure behavioral change. As previously mentioned, Sanchez et al. (2021) articulates how an effective diabetes education program focusing on nutrition positively impacts obesity and diabetes management and prevention. Abouammoh and Alshamrani (2020) and Mufunda et al. (2018) reveal how the gap of knowledge about diabetes management and prevention can be addressed by providing self-care education through tailored interventions suitable for patients of different education levels and cultural backgrounds. Ahern et al. (2020) found that tailored diabetes education and a behavioral weight management program offered more effective results than diabetes education alone in treating diabetes. It is evident that individualizing interventions for people of different education levels, cultural backgrounds, socioeconomic status, and gender help improve overall health, thus improving diabetes management or preventing the onset of diabetes. There is already a plethora of research about different methods to help individuals manage their diabetes or prevent the onset of diabetes. However, more research needs to be done on which methods, specifically, are the most successful in helping individuals manage or prevent diabetes with behavioral change. This project can be carried out longer and with more participants in order to see if the intervention makes a long-lasting impact on this population’s DIABETES MANAGEMENT KNOWLEDGE health. These findings are not generalizable but the project can be carried out within other 25 organizations with different populations to assess its effectiveness. Conclusion The incidence and prevalence of diabetes continues to grow worldwide leading to poor quality of life, disability, early death, and high healthcare costs. It is apparent that Arizona diabetes rates are higher than those in the U. S. and social determinants of health greatly impact how individuals perceive and manage their health. The desired outcome of helping clients within an organization modify, adapt, or change self-care behaviors related to nutrition to help manage or prevent diabetes was achieved with this project. However, there are some limitations to this project and more research needs to be done in order to ascertain specific methods that are most successful in changing health behaviors. DIABETES MANAGEMENT KNOWLEDGE References 26 Abouammoh, N., & Alshamrani, M. (2020). Knowledge about diabetes and glycemic control among diabetic patients in Saudi Arabia. Journal of Diabetes Research, 2020, 1239735– 1239735. https://doi.org/10.1155/2020/1239735 Ahern, A., Woolston, J., Wells, E., Sharp, S., Islam, N., Lawlor, E., Duschinsky, R., Hill, A., Doble, B., Wilson, E., Morris, S., Hughes, C., Brennan, A., Bostock, J., Boothby, C., & Griffin, S. (2020). Clinical and cost-effectiveness of a diabetes education and behavioural weight management programme versus a diabetes education programme in adults with a recent diagnosis of type 2 diabetes: study protocol for the Glucose Lowering through Weight management (GLoW) randomised controlled trial. 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Clinical and costeffectiveness of a diabetes education and behavioural weight management programme versus a diabetes education programme in adults with a recent diagnosis of type 2 diabetes: study protocol for the Glucose Lowering Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Health Belief Model inferred Design: pragmati c, randomiz ed, single blind, parallel group, 2arm superiorit y trial. Sample/ Setting n=576 Demographics: BMI 25kg/m2 and higher, 18 years and older, dx within 36 months, capable of giving consent, English speaking Setting: Variable s Measureme nt/ Instrument ation IV1: DEW HgA1c IV2: DE DV: HgA1c Data Analysis linear regression, chained equations, logistic regression, F-test, ANCOVA Results/ Findings On going, benefits will be measured using HgA1c at 12 months, weight, and well-being. Qualitative data will be collected at Level of Evidence/ Application To Practice/ Generalizati on LOE: II Strengths: 12 months long, large sample, cost effective, patient tailored. Limitations: Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMIbody mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GP- general practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MES- medication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/p- outpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 32 DIABETES MANAGEMENT KNOWLEDGE Citation through Weight management (GLoW) randomised controlled trial. BMJ Open, 10(4), Article e035020. https://doi.org/10.1136/b mjopen-2019-035020 Country: United Kingdom Funding: NIHR, WW, NHS Bias: Not recognized Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Purpose: To evaluate the effect of tailored DEW versus DE on HbA1c at 12 months in adults with recent T2D dx. Sample/ Setting primary care practices Exclusion: using insulin, previous or planned bariatric sx, dx of eating d/o, already received DE, GP considers unsuitable, participation in another program within the last 3 months. Variable s Measureme nt/ Instrument ation Data Analysis Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on that time as well. Includes follow up at 6 and 12 months only. Feasibility: It is a simple intervention to recommend in practice. Attrition: NR Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 33 DIABETES MANAGEMENT KNOWLEDGE Citation Abouammoh, N., & Alshamrani, M. (2020). Knowledge about diabetes and glycemic control among diabetic patients in Saudi Arabia. Journal of Diabetes Research, 2020, 1239735–1239735. https://doi.or/10.1155/20 20/123975 Country: Saudi Arabia Funding: Vice Deanship of Scientific Research Chairs Bias: Not recognized Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Health Belief Model inferred Design: Cross sectional study design Purpose: To assess the level of knowledg e related to diabetes and glycemic control. Sample/ Setting n=435 Demographics: diagnosed with diabetes, over the age of 18, and under the care of the hospital Setting: Security Forces Hospital o/p clinics Exclusion: pregnant, physical and mental impairment Attrition: NR Variable s Measureme nt/ Instrument ation Data Analysis Results/ Findings IV1-IV7: Gender, age, qualificat ion, marital status, time since dx, occupatio n, and present medicatio n regime. 14 item MDKT questionnair e, HgA1 IBM SPSS version 25, descriptive analysis, frequencies, percentages, and KruskalWallos test. 53.3% had poor glycemic control, a diabetic diet is understood only by 40%, 44% were able to explain HgA1c, those in urban areas and/or low education level have poor knowledge DV: Knowled ge of diabetes Level of Evidence/ Application To Practice/ Generalizati on LOE: V Strengths: Large sample. Limitations: One setting, short time frame. Feasibility: Would be easy to apply in practice. Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 34 DIABETES MANAGEMENT KNOWLEDGE Citation Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Sample/ Setting Variable s Measureme nt/ Instrument ation Data Analysis and HgA1c Bekele et al. (2020). Barriers and strategies to Lifestyle and dietary pattern interventions for prevention and management of type-2 diabetes in Africa, systematic review. Journal of Diabetes Research, 1-14. https://doi.org/10.1155/2 020/7948712 Country: Ethiopia Social Design: Cognitive systemati Theory c review inferred Purpose: to review published articles that investigat e lifestyle and dietary pattern interventi n=50 Inclusion: 20112019, English, African population, LOE I-III Exclusion: redundancy Attrition: NR IV1-IV3: lifestyle barriers, interventi ons for diabetes treatment and managem ent, selfcare behavior DV: diabetes Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on of glycemic control. John Hopkins Method of Research Evidence Appraisal Tool, multivariate logistics regression analysis, cohort study design, convenience sampling Major themes include: dietary patterns, physical activity, lifestyle changes, adherence Increased prevalence in diabetes due to lack of knowledge /education, cost, poverty, population changes LOE: I Strengths: High level articles, consistent results, most had large sample sizes, adequate control groups, definitive conclusions, Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 35 DIABETES MANAGEMENT KNOWLEDGE Citation Funding: None Bias: publication bias Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose ons for diabetes preventio n and managem ent in Africa. Sample/ Setting Variable s Measureme nt/ Instrument ation Data Analysis Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on and consistent recommendat ions Limitations: a few articles had small sample sizes, little evidence, inconsistent results, difficulty of conclusion Feasibility: Useful data to utilize in Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 36 DIABETES MANAGEMENT KNOWLEDGE Citation Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Sample/ Setting Variable s Measureme nt/ Instrument ation Data Analysis Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on practice settings Chen et al. (2020). Effect of a 90 g/day lowcarbohydrate diet on glycaemic control, small, dense low-density lipoprotein and carotid intima-media thickness in type 2 diabetic patients: An 18month randomised controlled trial. PloS One, 15(10). https://doi.org/ Health Belief Model Design: Single center, parallel designed open label Randomi zed Control Trial Purpose: To explore n=92 IV1: LCD A1c, MES, lipids, Demographics: creatinine, adults aged 20-80 IV2: microalbum yrs with DM 2 for TDD in, over a year with A1c IMT, Tanita of 7.5%. DV: A1c, Body MES, Compositio Setting: lipids, n Analyzer, o/p clinics creatinine questionnair , es Exclusion: pregnant, microalb lactating, impaired umin, renal, liver, heart, gout, WLP, eating Taves covariateadaptive randomizatio n, paired t-test, independent t-test, GEE, AR covariance matrix, SAS statistical software Significant decrease in A1c, MES, BP, weight (p=<0.05) with LCD compared to TDD No significant change in lipid profiles, LOE: II Strengths: 18 months long, high completion rate (>90%), easy to follow LCD guide Limitations: larger sample size may be needed, Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 37 DIABETES MANAGEMENT KNOWLEDGE Citation Theoreti cal/ Concept ual Framew ork 10.1371/journal.pone.024 0158 Country: Taiwan Funding: None reported Design/ Method/ Purpose Sample/ Setting the effect of LCD in type 2 DM over 18 months d/o, unable to complete questionnaire. Design: systemati c review and metaanalysis n=28 Variable s Measureme nt/ Instrument ation Data Analysis IMT, weight, BP, ALT Bias: Not recognized Garcia-Molina et al. (2020). Improving type 2 diabetes mellitus glycaemic control through lifestyle modification Social Cognitive Theory inferred Demographics: adults 50-67 years old, not hospitalized or with diabetes IV1: individua lized life style modificat ion A1c, weight, and BMI two reviewers, piloted extraction form, a 3rd researcher, Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on creatinine, microalbu min, ALT, IMT (p=>0.05) with LCD compared to TDD longer follow up duration may be needed Both types of intervention s significantl y improve LOE: I Feasibility: Easy to recommend in practice (i.e.: dietician student hours) Strengths: large sample sizes, two reviewers Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 38 DIABETES MANAGEMENT KNOWLEDGE Citation implementing diet intervention: a systematic review and metaanalysis. European Journal of Nutrition, 59(4), 1313– 1328. https://doi.org/10.1007/s0 0394-019-02147-6 Country: Spain Funding: CIBER Epidemiologia y Salud Publica Bias: No included studies were blinded Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Purpose: To analyze the scientific evidence concernin g the nutritiona l interventi on in the glycemic control of type-2 diabetes mellitus Sample/ Setting complications, recruited from primary health care centers Inclusion: randomized controlled studies, including lifestyle modification (diet) with & without physical activity, full texts Exclusion: type 1 diabetes mellitus Variable s IV2: groupbased life style modificat ion IV3: both types DV: A1c, weight, BMI Measureme nt/ Instrument ation Data Analysis Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on Cochrane risk of bias tool for RCT’s, randomized effects model, Cochran’s Q statistic, I2 statistic, Stata v. 14 software glycemic control, especially with a weight loss of >5% and is extended over a longer period of time were utilized while a third was included when there was a discrepancy between the first 2 Limitations: variability, inevitable differences in the interventional approaches, and could not consider compliance to Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 39 DIABETES MANAGEMENT KNOWLEDGE Citation Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Sample/ Setting Variable s Measureme nt/ Instrument ation Data Analysis Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on pharmacologi cal treatment Feasibility: Easy to apply in practice Hendryx et al. (2020). Lifestyle and psychosocial patterns and diabetes incidence among women with and without obesity: A prospective latent class analysis. Prevention Science, 21(6), 850–860. https://doi.org/10.1007/s1 1121020-01130-6 Social Cognitive Theory inferred Design: Prospecti ve cohort study n=64,710 Purpose: to identify and characteri ze underlyin Setting: 40 clinical centers throughout the US Demographics: women aged 50-79 Exclusion: baseline diabetes, CVD, cancer IV1-IV7: height, smoking, weight, physical BMI activity, diet, sleep, optimism , depressio n, social support latent class analysis, chisquare tests, t-tests, BIC, Cox proportional hazards regression models, SAS software version 9.4 women with diabetes tended to be younger, a member of a racial or ethnic minority group, less educated, obese, poor LOE: IV Strengths: large & diverse sample representing several regions across the country, long follow up, Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 40 DIABETES MANAGEMENT KNOWLEDGE Citation Country: USA Funding: National Heart, Lung, & Blood Institute, National Institutes of Health, US Department of Health & Human Services Bias: Not recognized Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Sample/ Setting g subgroup Attrition: NR s with a heterogen eous populatio n by both health behaviors and & psychoso cial factors, then determin e the relationsh ips between Variable s DV: diabetes Measureme nt/ Instrument ation Data Analysis Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on diet quality, engage in minimal physical activity, higher depressive symptoms, less optimism, & lower social support availability of multiple risk variables & covariants Limitations: self reporting nature of the study, sample was restricted to postmenopau sal women Feasibility: Each variable can be addressed and applied in Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 41 DIABETES MANAGEMENT KNOWLEDGE Citation Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose subgroup members hip & incidence of type 2 diabetes Morales et al. (2020). Social Design: Understanding the impact Cognitive observati of five major Theory onal determinants of health inferred cohort (genetics, biology, trial that behavior, psychology, is cross society/environment) on sectional type 2 diabetes in US & Hispanic/Latino families: longitudi Mil Familias-a cohort nal study. BMC Endocrine Disorders, 20(1), 1–4. Purpose: to Sample/ Setting Variable s Measureme nt/ Instrument ation Data Analysis Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on practice (i.e.: dietician, psychology student hours) n= 1,000 IV1-IV5: blood Demographics: pressure, Latino individuals or waist families as units circumfer ence, Setting: Santa insulin Barbara County & sensitivit surrounding y, food communities or security, satellite sites activity levels height, weight, waist circumferen ce, BMI, blood pressure, foot screening, DNA, urine, stool, HbA1c, blood work, Chi-squared tests, t-tests, Z tests, lognormal transformatio n community health workers are highly effective in promoting health, particularly in the Latino community; data collected LOE: IV Strengths: large sample size, is following a successful pilot study Limitations: lack of an active control group Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 42 DIABETES MANAGEMENT KNOWLEDGE Citation https://doi.org/10.1186/s1 2902-019-0483-z Country: USA Funding: Eli Lily & Company & SDRI Bias: Not recognized Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose determin e the influence of the 5 major determin ants of human health on the burden of type 2 diabetes for Latino families Sample/ Setting Variable s Inclusion: 7 years or DV: older, Hispanic, co- diabetes resides with family member who is diabetic or self, informed consent Exclusion: life expectancy <6 months, language barriers, participation in other studies, known abuse of drugs or alcohol Attrition: NR Measureme nt/ Instrument ation questionnair es, activity monitoring Data Analysis Results/ Findings will be used to help determine future effective evidence based prevention and treatment intervention strategies that are equitable and culturally relevant Level of Evidence/ Application To Practice/ Generalizati on Feasibility: Once completed, information can be utilized in clinics where there is a large Hispanic population (i.e.: dietician student hours) Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 43 DIABETES MANAGEMENT KNOWLEDGE Citation Silva-Tinoco et al. (2020). Influence of social determinants, diabetes knowledge, health behaviors, and glycemic control in type 2 diabetes: an analysis from real-world evidence. BMC Endocrine Disorders, 20(1), 130– 130. https://doi.org/10.1186/s1 2902-020-00604-6 Country: Mexico Funding: Clinica Especializada en el Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Social Design: Cognitive multicent Theory er cross inferred sectional Sample/ Setting n=513 Demographics: 66.3% female, mean age 53.7, most Purpose: reported primary school or less, low to explore or very low self care socioeconomic behaviors status, mean diagnosis time of in relation 12.2 years, 48.4% to reported hypertension diabetes knowledg Setting: 28 primary e and glycemic outpatient centers in urban Mexico City control Variable s IV1: diabetes knowledg e Measureme nt/ Instrument ation HbA1c, fundoscopy, albumin/cre atinine ratio, GFR, IV2: self vibratory perception care behaviors tools, SKILLD DV: scale, glycemic SDSCA control Data Analysis Results/ Findings univariable & multivariable linear models, multivariable logistic regression models, Baron & Kenny’s steps, multiple mediator model, linear regression analysis, product of coefficients socioecono mic status & education greatly influences diabetes knowledge; self care behaviors mediate the effect of diabetes knowledge on glycemic control Level of Evidence/ Application To Practice/ Generalizati on LOE: IV Strengths: used validated tools, large population size Limitations: not able to conclude causality, small sample size, conducted in Mexico city, other factors may Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 44 DIABETES MANAGEMENT KNOWLEDGE Citation Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Sample/ Setting Variable s Measureme nt/ Instrument ation Inclusion: beneficiaries of Seguro Popular Manejo de la Diabetes, World Diabetes Foundation, National Institutes of Health, & Novo Nordisk method, multivariable adjusted logistic regression models, R software, Sobel test Attrition: NR Bias: not controlled Xin et al. (2020). Type 2 diabetes remission: 2 year within-trial and lifetime-horizon cost- Health Belief Model referred Design: within trial cost analysis n= 298 Demographics: in trial data Data Analysis IV1: Counter weight blood glucose, blood pressure decision analytic models, intention to Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on contribute to glycemic control, self reporting reliability Feasibility: this information can be utilized in primary care clinics whose clients fit this criteria LOE: VII the intervention generated a Strengths: 1337 large sample Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 45 DIABETES MANAGEMENT KNOWLEDGE Citation effectiveness of the Diabetes Remission Clinical Trial (DiRECT)/Counterweigh t-Plus weight management programme. Diabetologia, 63(10), 2112–2122. https://doi.org/10.1007/s0 0125-020-05224-2 Country: Mexico Funding: Clinica Especializada en el Manejo de la Diabetes, World Diabetes Foundation, National Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Purpose: to estimate the within trial & lifetime costeffective ness of the weight managem ent program which achieved 46% Sample/ Setting Setting: primary care Inclusion: dx of diabetes, BMI 2745, HbA1c > 6.5 or > 6 if on meds Attrition: NR Variable s plus program DV: cost Measureme nt/ Instrument ation Data Analysis Results/ Findings treat principle, boot strap iterations, Monte Carlo simulations, regression coefficient, Stata/MP version 14.2 coefficients method, multivariable adjusted logistic regression models, R software, Sobel test British pounds cost saving per participant Level of Evidence/ Application To Practice/ Generalizati on size, 2 year length Limitations: timing is too short for diabetes effects, relapse, weight gain Feasibility: this information can be utilized in primary care clinics whose clients fit this Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 46 DIABETES MANAGEMENT KNOWLEDGE Citation Theoreti cal/ Concept ual Framew ork Institutes of Health, & Novo Nordisk Bias: no control Mufunda et al. (2018). Limited knowledge of diabetes in patients attending an outpatient Health Belief Model Design/ Method/ Purpose Sample/ Setting remission s of type 2 diabetes at year 1 and 36% at year 2 in the Diabetes Remissio n Clinical Trial (DiRECT ) Design: n=96 Cross sectional Demographics: descriptiv Zimbabwean adults e study Variable s Measureme nt/ Instrument ation Data Analysis Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on criteria settings in a similar costeffective manner IV1: Diabetes knowledg Knowledge e Test descriptive statistics, bivariate correlations, chi-square Knowledge was poor in all categories LOE: V Strengths: expert consensus Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 47 DIABETES MANAGEMENT KNOWLEDGE Citation diabetes clinic at a referral hospital in Zimbabwe: A crosssectional study. Pan African Medical Journal, 144(29). https://doi: 10.11604/pamj. 2018.29.144.12301 Country: Zimbabwe Funding: grants from the Research Committee at the School of Health Sciences & Social Work, University of Vaxjo, & Swedish International Development Aid Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Purpose: assess patients diabetes awarenes s & level of diabetes knowledg e in Zimbabw ean adults with diabetes Sample/ Setting Setting: outpatient diabetes clinic Inclusion: dx > 1yr, mentally sound, able to consent, speak English or Shona Attrition: NR Variable s DV: diabetes Measureme nt/ Instrument ation Data Analysis test, t-test, one-way ANOVA, MannWhitney Utest, multiple logistic regression, multiple linear regression, SPSS Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on Limitations: only in central location Feasibility: Identify knowledge gaps to be addressed and adapt interventions suitable for patients of different cultural backgrounds Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 48 DIABETES MANAGEMENT KNOWLEDGE Citation Theoreti cal/ Concept ual Framew ork Design/ Method/ Purpose Sample/ Setting Variable s Measureme nt/ Instrument ation Data Analysis Results/ Findings Level of Evidence/ Application To Practice/ Generalizati on Bias: Not recognized Key: ALT- Alanine aminotransferase; AR- autoregressive; A1c- glycated hemoglobin; BIC- Bayesian information criterion; SDRI- Sansum Diabetes Research Institute; BMI- body mass index; CBC- complete blood count; CMP-complete metabolic panel; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; d/o- disorder; dx- diagnosis; DV-dependent variable; GFR- glomerular filtration rate; GPgeneral practitioner; GEE- generalized estimating equations; IMT- intima media thickness; IV- independent variable; LCD- low carbohydrate diet; MESmedication effect scores; n- number of participants; NHS- National Health Service; NIHR- National Institute for Health Research; NR- not reported; o/poutpatient; SDSCA- summary of diabetes self care activities; SKLLD-spoken knowledge in low literacy patients with diabetes; sx- surgery; T2D- type 2 diabetes mellitus; TDD- Traditional diabetic diet; WLP- weight loss program; WW- weight watchers. 49 DIABETES MANAGEMENT KNOWLEDGE Table A2 Synthesis Table Author Year Design Number of subjects Independent Variables DEW/DE Self-care behavior LCD/TDD Diet Knowledge CWP Lifestyle modification Other Dependent Variables Knowledge of DM HgA1c/glycemic control DM Cost of diabetes Weight/BMI Other Abouammo h 2020 CSDS 435 Ahern Bekel e 2020 2020 RCT SR 576 50 Chen GarciaMolina 2020 2020 RCT SR/MA 92 28 Hendry x 2020 PCS 64,710 Morales Mufunda SilvaTinoco 2020 2018 2020 CT CSDS CS 1,000 96 513 Xin 2020 TCA 298 X X X X X X X X X X X X X X X X X X X X X X X X X X X Key: BMI- body mass index; CS- cross sectional; CSDS- cross sectional study design; CT- cohort trial; CWP- counter weight plus program; DE- diabetes education; DEW- diabetes education and behavioral weight management program; DM- diabetes mellitus; HgA1c- hemoglobin A1c; LCD- low carbohydrate diet; MA- meta-analysis; PCS- prospective cohort study; RCT- randomized control trial; SR- systematic review; TCA- trial cost analysis; TDD- traditional diabetic diet. DIABETES MANAGEMENT KNOWLEDGE Appendix B Models and Frameworks Figure B1 The Health Belief Model Strecher & Rosenstock (1997) 50 DIABETES MANAGEMENT KNOWLEDGE Figure B2 Rosswurm and Larrabee Model Rosswurm & Larrabee (1999) 51 52 DIABETES MANAGEMENT KNOWLEDGE Appendix C Budget Table C1 Project Budget Phase Preparation Activities Cost Download and print class materials for clients and primary investigator (PI). Informed consent and survey print outs will be printed at SJHMC. Client materials=960 pages PI materials=64 pages Paper case of 1,500 pages=$20 2 black ink cartridges @ $40 each=$80 3 color ink cartridges @ $44 each=$132 $232 60 pens @ $6 $6 Pens for notes and to fill out surveys. Delivery subtotal Create power point presentation. PI already has Microsoft Office. $0 Pick up recipe print outs from Mountain Park Health Center. $0 Gas milage for travel to center x4 times for class. 30 miles/gallon @ 24 miles round trip $10 rounded up Total 53 DIABETES MANAGEMENT KNOWLEDGE x4=96 miles @ $3.10/gallon Evaluation Extra center points and prize for class attendance will be provided by center. $25 Results will be analyzed using Intellectus software which PI already has access to. $0 Data will be shredded at home of PI using shredder that PI already owns. $0 $25 $273 Revenue/cost savings The center is a nonclinical, non-profit organization that does not receive any payments from its clients and staff is primarily made up of volunteers. There will be no revenue or cost savings to the center itself, however, the overall savings to the community may be substantial. The cost of diabetes in Arizona is estimated to be about $6.4 billion (American Diabetes Association, 2016).