This Mentored Research Scientist Career Development Award will provide Dr. David Barker with focused training to enable him to leverage modern statistical modeling methods in identifying promising areas of intervention, and to collaborate with multidisciplinary teams to implement effective HIV-prevention programs for adolescents and young adults. One challenge to the effective dissemination of existing prevention programs is the limited understanding of who responds or does not respond to a given program. Providing such information to policy makers and program directors will help match existing prevention programs to the needs of target populations. Identifying which prevention program works best for which subgroups of youth requires sophisticated statistical modeling and large samples to identify and describe the subgroups. Combining across studies is a cost-effective way to increase the sample size of individual trials. However, combining data introduces complexity due to differences in how studies are designed and in how key outcomes are collected, analyzed and interpreted. The proposed research combines data from five NIH-funded trials of HIV-prevention programs for youth with mental health concerns to compare the efficacy of the programs and identify which youth respond or do not respond to current programs. The proposed research assists Dr. Barker in achieving his career and training goals to: (1) learn modern modeling approaches to address complex data structures that arise when combining multiple datasets, (2) learn methods for drawing causal inferences when integrating data across multiple clinical trials, (3) learn methods to compare the efficacy of prevention programs not tested in a "head-to-head" trial, (4) extend his training in HIV-risk prevention to key vulnerable populations identified in the National HIV/AIDS Strategy for the United States, namely substance using populations and sexual minority populations, (5) develop a program of research that utilizes existing data to identify promising areas for improving prevention efforts, and (6) develop collaborations with prominent scientist involved in HIV-prevention to develop high-quality research manuscripts and grants.
The specific aims of the proposed research are to (1) build a database that links data from 5 NIH-funded prospective HIV-prevention trials, (2) Apply consistent analyses across the 5 trials by jointly modeling the multiple dimensions of adolescent sexual risk behavior, (3) compare the efficacy of current prevention programs for youth with mental health concerns, and (4) Identify and describe subgroups of adolescents with mental health concerns who responded or did not respond to each prevention approach.
These aims will be achieved by using the skills learned through this K23 mechanism to address the analytic complexities of combining data across multiple prevention trials. Training will include a combination of didactic coursework, workshops, and mentoring by a team of experts in modern analytic approaches and HIV-prevention. The mentoring will include tailored reading assignments, regular face-to-face meetings, mentored research, and collaborative projects and manuscripts. The training received through this K23 application will place Dr. Barker in a position to collaborate with prominent HIV-prevention scientists in funded research focused on leveraging modern analytic modeling techniques to improve HIV-prevention efforts.
Effective dissemination of current HIV-prevention programs requires understanding who responds or does not respond to a given program. This K23 application will combine information from five trials of HIV-prevention programs designed for youth with mental health concerns. Modern analytic modeling techniques will be used to identify and describe youth who respond or do not respond to current programs. Results will help policy- makers better match prevention programs to the needs of specific subpopulations of vulnerable youth.