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- All Subjects: Diabetes
- Creators: Shaibi, Gabriel
- Creators: Dean, W.P. Carey School of Business
- Status: Published
Major themes emerging from the data included illness perception, support, and the process of medication adherence. Acceptance of the diabetes diagnosis was imperative for medication adherence. Stigmatization of diabetes was salient in the recruitment process and as it related to mechanisms for adherence. Furthermore, many informants were not aware of a family history of diabetes before their own diagnosis. Four gendered emerging typologies were identified, which further illuminated major themes. Moreover, an eight-step process of medication adherence model is discussed. The researcher was able to identify culturally compatible strategies that may be extended to those struggling with medication adherence. The implications section suggests a set of strategies that healthcare providers can present to people with diabetes in order to increase medication adherence.
2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.
2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers, but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.
This project aimed to identify barriers to participation and develop strategies to increase the accessibility of a diabetes prevention program in the Latino community. Surveys were administered to past participants of a randomized control trial at a community event where study results were shared. The top concerns expressed by respondents were related to the use of personal information. Primary barriers to participation included work/school commitments and transportation issues. Strategies to increase accessibility included providing flexible class times, having bilingual research staff, and using multiple forms of community outreach such as flyers, health events, phone calls, texts, and social media. Expanding community partners was also identified as a primary strategy for increasing program reach. Researchers should focus on addressing confidentiality concerns, providing financial compensation for attendance, flexible scheduling, and utilizing diverse outreach methods to enhance access to diabetes prevention programs in the Latino community
