Exchanges in a Virtual Environment for Diabetes Self-Management Education and Support: Social Network Analysis.

BACKGROUND: Diabetes remains a major health problem in the United States, affecting an estimated 10.5% of the population. Diabetes self-management interventions improve diabetes knowledge, self-management behaviors, and clinical outcomes. Widespread internet connectivity facilitates the use of eHealth interventions, which positively impacts knowledge, social support, and clinical and behavioral outcomes. In particular, diabetes interventions based on virtual environments have the potential to improve diabetes self-efficacy and support, while being highly feasible and usable. However, little is known about the patterns of social interactions and support taking place within type 2 diabetes-specific virtual communities. OBJECTIVE: The objective of this study was to examine social support exchanges from a type 2 diabetes self-management education and support intervention that was delivered via a virtual environment. METHODS: Data comprised virtual environment-mediated synchronous interactions among participants and between participants and providers from an intervention for type 2 diabetes self-management education and support. Network data derived from such social interactions were used to create networks to analyze patterns of social support exchange with the lens of social network analysis. Additionally, network correlations were used to explore associations between social support networks. RESULTS: The findings revealed structural differences between support networks, as well as key network characteristics of supportive interactions facilitated by the intervention. Emotional and appraisal support networks are the larger, most centralized, and most active networks, suggesting that virtual communities can be good sources for these types of support. In addition, appraisal and instrumental support networks are more connected, suggesting that members of virtual communities are more likely to engage in larger group interactions where these types of support can be exchanged. Lastly, network correlations suggest that participants who exchange emotional support are likely to exchange appraisal or instrumental support, and participants who exchange appraisal support are likely to exchange instrumental support. CONCLUSIONS: Social interaction patterns from disease-specific virtual environments can be studied using a social network analysis approach to better understand the exchange of social support. Network data can provide valuable insights into the design of novel and effective eHealth interventions given the unique opportunity virtual environments have facilitating realistic environments that are effective and sustainable, where social interactions can be leveraged to achieve diverse health goals

Associations between DNA methylation age acceleration, depressive symptoms, and cardiometabolic traits in African American mothers from the InterGEN study

Background : African American women (AAW) have a high risk of both cardiometabolic (CM) illness and depressive symptoms. Depressive symptoms co-occur in individuals with CM illness at higher rates than the general population, and accelerated aging may explain this. In this secondary analysis, we examined associations between age acceleration; depressive symptoms; and CM traits (hypertension, diabetes mellitus [DM], and obesity) in a cohort of AAW. Methods : Genomic and clinical data from the InterGEN cohort (n = 227) were used. Age acceleration was based on the Horvath method of DNA methylation (DNAm) age estimation. Accordingly, DNAm age acceleration (DNAm AA) was defined as the residuals from a linear regression of DNAm age on chronological age. Spearman’s correlations, linear and logistic regression examined associations between DNAm AA, depressive symptoms, and CM traits. Results : DNAm AA did not associate with total depressive symptom scores. DNAm AA correlated with specific symptoms including selfdisgust/ self-hate (−0.13, 95% CI −0.26, −0.01); difficulty with making decisions (−0.15, 95% CI −0.28, −0.02); and worry over physical health (0.15, 95% CI 0.02, 0.28), but were not statistically significant after multiple comparison correction. DNAm AA associated with obesity (0.08, 95% CI 1.02, 1.16), hypertension (0.08, 95% CI 1.01, 1.17), and DM (0.20, 95% CI 1.09, 1.40), after adjustment for potential confounders. Conclusions : Associations between age acceleration and depressive symptoms may be highly nuanced and dependent on study design contexts. Factors other than age acceleration may explain the connection between depressive symptoms and CM traits. AAW with CM traits may be at increased risk of accelerated aging.The InterGEN study was funded by the National Institute of Nursing Research of the National Institutes of Health (R01NR013520).https://journals.sagepub.com/home/gaeam2023Psycholog

Developing and testing a web-based platform for antiretroviral therapy (ART) adherence support among adolescents and young adults (AYA) living with HIV

Objective: Describe the development and testing of a web-based platform for antiretroviral treatment (ART) adherence support among HIV+ adolescents and young adults (AYA) in a randomized controlled trial (RCT). Methods: A seven-member multi-disciplinary team operationalized the flat, password protected, web-based platform. Manualized protocols guided the objectives and content for each of the eight web-based sessions. Team members evaluated usability and content validity. Client satisfaction and perceived ease of use was evaluated with the first ten HIV+ AYA participants. Results: The web-based platform was developed, evaluated, refined, implemented and pilot tested between September 2020 to April 2022. Usability was rated as high; the evaluation of content validity showed an excellent fit between session content and objectives. HIV+ AYA participants (mean age = 24.2 years) were satisfied with the quality, type, and amount of support/education received, and found the platform easy to use, operate, and navigate. Average time spent per session was 6.5 min. Conclusion: Findings support the usability, validity, acceptability, and feasibility of this web-based platform for ART adherence support among HIV+ AYA. Innovation: Our research and findings are responsive to research gaps and the need for transparency in the methodological development and testing of web-based control arms for ART adherence support among HIV+ AYA

Perspectives on Genetic and Genomic Technologies in an Academic Medical Center: The Duke Experience

In this age of personalized medicine, genetic and genomic testing is expected to become instrumental in health care delivery, but little is known about its actual implementation in clinical practice. Methods. We surveyed Duke faculty and healthcare providers to examine the extent of genetic and genomic testing adoption. We assessed providers’ use of genetic and genomic testing options and indications in clinical practice, providers’ awareness of pharmacogenetic applications, and providers’ opinions on returning research-generated genetic test results to participants. Most clinician respondents currently use family history routinely in their clinical practice, but only 18 percent of clinicians use pharmacogenetics. Only two respondents correctly identified the number of drug package inserts with pharmacogenetic indications. We also found strong support for the return of genetic research results to participants. Our results demonstrate that while Duke healthcare providers are enthusiastic about genomic technologies, use of genomic tools outside of research has been limited. Respondents favor return of research-based genetic results to participants, but clinicians lack knowledge about pharmacogenetic applications. We identified challenges faced by this institution when implementing genetic and genomic testing into patient care that should inform a policy and education agenda to improve provider support and clinician-researcher partnerships

Perspectives on Genetic and Genomic Technologies in an Academic Medical Center: The Duke Experience

UnlabelledIn this age of personalized medicine, genetic and genomic testing is expected to become instrumental in health care delivery, but little is known about its actual implementation in clinical practice.MethodsWe surveyed Duke faculty and healthcare providers to examine the extent of genetic and genomic testing adoption. We assessed providers' use of genetic and genomic testing options and indications in clinical practice, providers' awareness of pharmacogenetic applications, and providers' opinions on returning research-generated genetic test results to participants. Most clinician respondents currently use family history routinely in their clinical practice, but only 18 percent of clinicians use pharmacogenetics. Only two respondents correctly identified the number of drug package inserts with pharmacogenetic indications. We also found strong support for the return of genetic research results to participants. Our results demonstrate that while Duke healthcare providers are enthusiastic about genomic technologies, use of genomic tools outside of research has been limited. Respondents favor return of research-based genetic results to participants, but clinicians lack knowledge about pharmacogenetic applications. We identified challenges faced by this institution when implementing genetic and genomic testing into patient care that should inform a policy and education agenda to improve provider support and clinician-researcher partnerships

Perspectives on Genetic and Genomic Technologies in an Academic Medical Center: The Duke Experience

In this age of personalized medicine, genetic and genomic testing is expected to become instrumental in health care delivery, but little is known about its actual implementation in clinical practice. Methods. We surveyed Duke faculty and healthcare providers to examine the extent of genetic and genomic testing adoption. We assessed providers’ use of genetic and genomic testing options and indications in clinical practice, providers’ awareness of pharmacogenetic applications, and providers’ opinions on returning research-generated genetic test results to participants. Most clinician respondents currently use family history routinely in their clinical practice, but only 18 percent of clinicians use pharmacogenetics. Only two respondents correctly identified the number of drug package inserts with pharmacogenetic indications. We also found strong support for the return of genetic research results to participants. Our results demonstrate that while Duke healthcare providers are enthusiastic about genomic technologies, use of genomic tools outside of research has been limited. Respondents favor return of research-based genetic results to participants, but clinicians lack knowledge about pharmacogenetic applications. We identified challenges faced by this institution when implementing genetic and genomic testing into patient care that should inform a policy and education agenda to improve provider support and clinician-researcher partnerships