Dr. Vorderstrasse is Associate Professor of Nursing with Tenure and Director of the Florence S. Downs PhD Program in Nursing Research and Theory. She received a B.S.N. from Mount Saint Mary College, a M.S.N. from Yale University School of Nursing, and a D.N.Sc. from Yale University School of Nursing.
Dr. Vorderstrasse’s research in the development and implementation of behavioral interventions for diabetes and cardiovascular disease (CVD) aims to expand preventive and self-management support for adults at risk for, or living with chronic diseases. Her contributions in chronic disease prevention have identified that genetic risk testing for chronic conditions may improve risk reduction in particular groups. She is also among the first to demonstrate that virtual environments are a feasible and effective way to provide self-management education and support to improve outcomes in diabetes and CVD. Her research has been supported with competitive funding from the Air Force Medical Sciences, NINR, NLM and NHLBI. As an expert in these areas, she has presented her work at the American Diabetes Association Scientific Sessions, American Heart Association Scientific Sessions, the International Society of Nurses in Genetics, and the American College of Preventive Medicine. She was an invited panelist for the first ANCC Advance Genetics Nursing certification portfolio. Through these presentations, consultations and research studies, she has been a thought leader for research, education and policy in nursing and the implementation of novel technologies, such as genomics and virtual environments.
Prior to joining the faculty at NYU, Dr. Vorderstrasse was Associate Professor of Nursing and Faculty Lead for Precision Health research at the Duke University School of Nursing.
Certificate NIH/NINR Summer Genetics InstituteDNSc, Yale University School of NursingMSN, Yale University School of NursingBSN, Mount Saint Mary College
Fellow, American Academy of NursingInternational Society of Nursing in GeneticsAmerican Heart Association
Participation of Racial and Ethnic Minorities in Technology-Based Interventions to Self-Manage Type 2 Diabetes: A Scoping ReviewAbstractPurpose: Strategies to decrease societal and cultural barriers for ethnic minorities to participate in health research are well established. However, limited data are available regarding participation of ethnic minorities in mobile and Internet technology–based interventions to self-manage type 2 diabetes where health disparities are predominant. Thus, the purpose was to understand the participation of ethnic minorities in technology-based intervention programs to manage type 2 diabetes. Design/Method: A scoping review was used to review a total of 21 intervention studies containing participant information about ethnic minorities and one qualitative study discussing participation of ethnic minorities. Findings: There was limited enrollment and participation of ethnic minorities. Technological barriers in addition to existing societal and cultural barriers were identified. Strategies to decrease the barriers were recommended. Conclusions: Technological barriers were identified on top of the societal and cultural barriers in traditional interventions. Further research to reduce the barriers is warranted.
Place of Residence and Cognitive Function among the Adult Population in IndiaAbstractBackground: The place of residence has been linked to cognitive function among adults in developed countries. This study examined how urban and rural residence was associated with cognitive function among adults in India. Methods: The World Health Organization Study on Global AGEing and Adult Health data was used to examine cognition among 6,244 community-residing adults age 50+ in 6 states in India. Residential status was categorized as urban, rural, urban-to-urban, rural-to-urban, rural-to-rural, and urban-to-rural. Cognition was assessed by immediate and delayed recall tests, digit span test, and verbal fluency test. Multilevel models were used to account for state-level differences and adjusted for individual-level sociodemographic, psychosocial, and health-related factors. Results: Urban residents and urban-to-urban migrants had the highest levels of cognition, whereas rural residents and those who migrated to (or within) rural areas had the lowest cognition. The differences largely persisted after adjustment for multiple covariates; however, rural-to-urban migrants had no difference in cognition from urban residents once socioeconomic factors were taken into account. Conclusion: Cognition among adults in India differed significantly according to their current and past place of residence. Socioeconomic factors played an important role in the cognitive function of adults in urban areas.
Polygenic signal for symptom dimensions and cognitive performance in patients with chronic schizophreniaAbstractGenetic etiology of psychopathology symptoms and cognitive performance in schizophrenia is supported by candidate gene and polygenic risk score (PRS) association studies. Such associations are reported to be dependent on several factors - sample characteristics, illness phase, illness severity etc. We aimed to examine if schizophrenia PRS predicted psychopathology symptoms and cognitive performance in patients with chronic schizophrenia. We also examined if schizophrenia associated autosomal loci were associated with specific symptoms or cognitive domains. Case-only analysis using data from the Clinical Antipsychotics Trials of Intervention Effectiveness-Schizophrenia trials (n = 730). PRS was constructed using Psychiatric Genomics Consortium (PGC) leave one out genome wide association analysis as the discovery data set. For candidate region analysis, we selected 105-schizophrenia associated autosomal loci from the PGC study. We found a significant effect of PRS on positive symptoms at p-threshold (PT) of 0.5 (R2 = 0.007, p = 0.029, empirical p = 0.029) and negative symptoms at PT of 1e-07 (R2 = 0.005, p = 0.047, empirical p = 0.048). For models that additionally controlled for neurocognition, best fit PRS predicted positive (p-threshold 0.01, R2 = 0.007, p = 0.013, empirical p = 0.167) and negative symptoms (p-threshold 0.1, R2 = 0.012, p = 0.004, empirical p = 0.329). No associations were seen for overall neurocognitive and social cognitive performance tests. Post-hoc analyses revealed that PRS predicted working memory and vigilance performance but did not survive correction. No candidate regions that survived multiple testing corrections were associated with either symptoms or cognitive performance. Our findings point to potentially distinct pathogenic mechanisms for schizophrenia symptoms.
Residential Mobility and Cognitive Function Among Middle-Aged and Older Adults in ChinaAbstractObjectives: To assess the association between rural and urban residential mobility and cognitive function among middle-aged and older adults in China. Method: We used data from the World Health Organization Study on global AGEing and adult health that included adults age 50+ from China (N = 12,410). We used multivariate linear regressions to examine how residential mobility and age at migration were associated with cognitive function. Results: Urban and urban-to-urban residents had the highest level of cognitive function, whereas rural and rural-to-rural residents had the poorest cognitive function. Persons who migrated to/within rural areas before age 20 had poorer cognitive function than those who migrated during later adulthood. Socioeconomic factors played a major role in accounting for the disparities in cognition; however, the association remained significant after inclusion of all covariates. Discussion: Residential mobility and age at migration have significant implications for cognitive function among middle-aged and older adults in China.
Analyzing Unstructured Communication in a Computer-Mediated Environment for Adults With Type 2 Diabetes:: A Research Protocol PMID: 28438726
Creating a sustainable collaborative consumer health application for chronic disease self-managementAbstractAs the prevalence of chronic diseases increase, there is a need for consumer-centric health informatics applications that assist individuals with disease self-management skills. However, due to the cost of development of these applications, there is also a need to build a disease agnostic architecture so that they could be reused for any chronic disease. This paper describes the architecture of a collaborative virtual environment (VE) platform, LIVE
Diabetes self-management quality improvement initiative for medically underserved patientsAbstractThe burden of diabetes is greater for minorities and medically underserved populations in the United States. An evidence-based provider-delivered diabetes self-management education intervention was implemented in a federally qualified health center for medically underserved adult patients with type 2 diabetes. The findings provide support for the efficacy of the intervention on improvement in self-management behaviors and glycemic control among underserved patients with diabetes, while not substantially changing provider visit time or workload.
Diabetes Self-management Training in a Virtual EnvironmentAbstractDiabetes self-management training (DSMT) improves diabetes health outcomes. However, low numbers of patients receive DSMT. Using virtual environments (VEs) for DSMT is an innovative approach to removing barriers for patients. The purpose of this paper is to describe the experience of health professionals and diabetes educators establishing and teaching DSMT in a VE, Diabetes LIVE
Genetic Basis of Positive and Negative Symptom Domains in SchizophreniaAbstractSchizophrenia is a highly heritable disorder, the genetic etiology of which has been well established. Yet despite significant advances in genetics research, the pathophysiological mechanisms of this disorder largely remain unknown. This gap has been attributed to the complexity of the polygenic disorder, which has a heterogeneous clinical profile. Examining the genetic basis of schizophrenia subphenotypes, such as those based on particular symptoms, is thus a useful strategy for decoding the underlying mechanisms. This review of literature examines the recent advances (from 2011) in genetic exploration of positive and negative symptoms in schizophrenia. We searched electronic databases PubMed, Web of Science, and Cumulative Index to Nursing and Allied Health Literature using key words schizophrenia, symptoms, positive symptoms, negative symptoms, cognition, genetics, genes, genetic predisposition, and genotype in various combinations. We identified 115 articles, which are included in the review. Evidence from these studies, most of which are genetic association studies, identifies shared and unique gene associations for the symptom domains. Genes associated with neurotransmitter systems and neuronal development/maintenance primarily constitute the shared associations. Needed are studies that examine the genetic basis of specific symptoms within the broader domains in addition to functional mechanisms. Such investigations are critical to developing precision treatment and care for individuals afflicted with schizophrenia.
Genetic correlates of insight in schizophreniaAbstractInsight in schizophrenia is clinically important as it is associated with several adverse outcomes. Genetic contributions to insight are unknown. We examined genetic contributions to insight by investigating if polygenic risk scores (PRS) and candidate regions were associated with insight. Method: Schizophrenia case-only analysis of the Clinical Antipsychotics Trials of Intervention Effectiveness trial. Schizophrenia PRS was constructed using Psychiatric Genomics Consortium (PGC) leave-one out GWAS as discovery data set. For candidate regions, we selected 105 schizophrenia-associated autosomal loci and 11 schizophrenia-related oligodendrocyte genes. We used regressions to examine PRS associations and set-based testing for candidate analysis. Results: We examined data from 730 subjects. Best-fit PRS at p-threshold of 1e-07 was associated with total insight (R 2 =0.005, P =0.05, empirical P =0.054) and treatment insight (R2 =0.005, P =0.048, empirical P =0.048). For models that controlled for neurocognition, PRS significantly predicted treatment insight but at higher p-thresholds (0.1 to 0.5) but did not survive correction.Patients with highest polygenic burden had 5.9 times increased risk for poor insight compared to patients with lowest burden. PRS explained 3.2% (P = 0.002, empirical P = 0.011) of variance in poor insight. Set-based analyses identified two variants associated with poor insight- rs320703, an intergenic variant (within-set P = 6e. -04, FDR P = 0.046) and rs1479165 in SOX2-OT (within-set P = 9e. -04, FDR P = 0.046). Conclusion: To the best of our knowledge, this is the first study examining genetic basis of insight. We provide evidence for genetic contributions to impaired insight. Relevance of findings and necessity for replication are discussed.