Aim 3. Both the Division (1.a above) and the Prevention Science and Methodology Group (PSMG) provide organizational support for this goal. The PSMG network, established 10 years ago and comprising more than 170 researchers and methodologists, conducts interdisciplinary methods presentations through weekly grand-rounds conference calls and facilitatesmethodological development and application in leading edge research nationally. Xx. Xxxxx heads this group, and Xx. Xxxxxxxxx has joined PSMG's steering committee so that it can address the Miami CTSI agenda for developing translational biostatistics research. This Component has also created a small grant program to stimulate cross-school collaborations in methodological development.
Aim 3. Examine Transition Assessment Literature & Identify Transition Factors
Aim 3. Our trainee, Dr. Xxxxx Kenya was selected as one of the four initial CTSI pilot trainees. Her project focuses on use home based Rapid HIV testing as a means to increase HIV screening in underserved African-American communities, one of the priority areas highlighted by the CTSI Community Advisory Board. Medical Student Xxxxxx Xxxxxx, building on a project showing high rates of dirty needles in Miami due to lack of needle exchange programs (another CAB identified community priority), has spearheaded a medical student led State-Wide campaign to write and introduce House and Senate bills in FL allowing for needle exchange programs in the state. This initiative has garnered 500 hours of service from the Florida Medical Association, the full support of our University’s lobbyists, support from over 10 State-wide organizations, Bills introduced in the State House and Senate and committee hearings.
Aim 3. To develop degree-granting and formal early career mentored programs that will expand and diversify the research workforce, with a particular focus on addressing health care disparities and culturally appropriate research methods.
Aim 3. To develop degree-granting and formal early career mentored programs that will expand and diversify the research workforce, with a particular focus on addressing health care disparities and culturally appropriate research methods.
i. Established the coursework required and enrolled the first class of students for the Masters in Clinical and Translational Science
ii. Enrolled Early Career Investigators into the K12 program.
iii. Involved career, scientific and clinical mentors into these programs
Aim 3. We plan to produce a paper on Scientific Equity that maps out design requirements for randomized trials of interventions and strategies for synthesizing findings from the literature related to health disparities. We, along with our collaborators, plan to submit an NIH application to develop the biostatistical and psychometric methodology for extending computerized adaptive testing to minority populations. This method would identify items that display differential item functioning as well as different underlying psychometric structures. We plan to submit this as an extension of measuring depressive, anxious, and bipolar symptoms in a Spanish speaking population as a model that can be generalized to other medical conditions and populations.
Aim 3 a. The RTS-Smartstore DNA storage robotic system, within the Hussman Institute Biorepository is now fully operational and implemented into the Nautilus LIMs system.
b. Adoption and development of the NCI-designated ca-Tissue for de-identified biospecimen management, cataloguing, tracking, and distribution with associated clinical data.
c. Initiated integration of sample acquisition and tracking between the Genomics Institute and the Cancer Center Tissue Bank Core Facility.
d. Initiated discussions with the CTSI Bioinformatics component for the interfacing of the BioResource specimen data with EPIC and the overarching Research Data Environment (URIDE).
Aim 3 i. We will continue working to identify meaningful discoveries (not only medical product candidates, but technologies developed in all of our scientific disciplines across our three UM campuses (e.g. engineering, medicine, physics, marine biology, etc.) and help research teams to develop them, and to advance those discoveries through all the stages required toward commercialization.
Aim 3. To develop an agent-based model evaluating the effectiveness of network-based and individual-targeting behavioral interventions. Evidence on the effectiveness of interventions targeting modifiable health behaviors for CVD prevention are mixed and, to date, no existing study comprehensively evaluated the potential effectiveness of different types of behavioral interventions. Different from existing studies, this dissertation aims to use a systems science approach to comprehensively evaluate the effectiveness of two major types of behavioral interventions – network-based intervention (e.g. popular opinion leader intervention) and individual-targeting intervention (e.g. incentivizing healthy behaviors), incorporating theories of individual behavioral choices and intervention diffusion on a social network. Through a combination of observational studies and computational experiments, this dissertation will address the following questions: 1). What are the network-level and individual-level contributing factors to individual’s health behaviors throughout life-course; 2) Given the knowledge of community network structure, target population characteristics and established community behavioral norms, what type of intervention and target population selection strategy would be most effective in maximizing the prevalence of health-benefiting behaviors in the long run; 3) Given specific target population’s characteristics, what type of data would be needed in the future behavioral intervention design and effectiveness evaluation? This dissertation will be the first to summarize major behavioral intervention strategies into computational model designs with pre-specified target population selection and model set-up to alter individual incentives. Also, different from prior research(76– 78) that centered around the influence of direct network connections (peer influence) on individual’s health behavior, this dissertation will evaluate the population-level impact of different intervention scenarios, conditioning upon both network-based diffusion processes and operationalized individual incentive as individual behavioral choice utility functions. Most importantly, this dissertation provides an opportunity to compare and contrast the empirical and systems science modeling approach for identifying causal mechanisms linking individual and network level factors to population level outcomes of complex behavioral interventions. Findings from this dissertation will motivate future...
