The overall goal of this project is to analyze existing behavioral interventions designed to reduce HIV incidence in order to examine the mechanisms (i.e., mediators) that predict efficacy, and the subgroups for whom (i.e., moderators) interventions are efficacious. We propose to use advanced approaches to analyzing mediators and moderators. Specifically, we will utilize methods that allow indirect (mediated) effects to be directly tested and quantified, even in interventions that do not find a significant total X Y effect (i.e., efficacy). We propose to analyze data from four large-scale randomized controlled trials (RCTs) testing the efficacy of behavioral interventions on an HIV incidence outcome; two trials were showed a significant effect on HIV, two had null results on HIV. We will use the novel approach called ?conditional process modeling? which simultaneously models mediators and moderators and tests both how and for whom an intervention works, helping to identify different processes leading to efficacy for different subgroups (AIM 1). We will compare the significant and the null trials in their significant mediators and moderators and model characteristics to examine possible situations of masked efficacy in the null trials (AIM 2). We will utilize cutting-edge advancements in causal mediation analysis. Specifically, we will conduct sensitivity analysis to estimate the extent to which a mediator is primarily responsible for producing effects on HIV, strengthening causal inference about mediators leading to reduced HIV transmission in the interventions (AIM 3). To our knowledge these novel statistical approaches have never been used to analyze mediators and moderators in HIV intervention RCTs. We will also explore the use of biomedical strategies as moderators of mediated pathways to explore whether participants who reported use of a biomedical tool show a different causal process in intervention efficacy (AIM 4). Understanding mediators and moderators of existing behavioral HIV prevention interventions will help to inform how to pare down or ramp up interventions to their most effective elements and which subgroups and contexts must be targeted to produce briefer, cheaper, and more impactful interventions. These interventions could be used in combination with biomedical prevention strategies.!By also analyzing biomedical tools (i.e., nPEP use and male circumcision status) as potential moderators of mediated effects, we gain valuable insight into whether and which behavioral mechanisms must be targeted in interventions when these specific biomedical strategies are used. To meet our aims we will analyze data from studies using the ?gold-standard? method for evaluating HIV prevention interventions. Specifically, we will use data from four different two-arm RCTs that were powered to test HIV incidence as the primary outcome. These RCTs tested the efficacy of behavioral HIV prevention interventions among men who have sex with men in the U.S., men and women in South Africa and Uganda, and people who inject drugs in Ukraine. Thus, the current proposal will analyze four unique intervention datasets from some of the most HIV-affected populations globally.

Public Health Relevance

In order to curb the global HIV epidemic, there is an urgent need to determine how, why, and for whom behavioral HIV prevention interventions work. Findings from the proposed research will provide an understanding of the mechanisms and conditions under which behavioral interventions are effective at reducing HIV incidence. The proposed research will help to inform how to pare down interventions to their most effective elements and which subgroups and contexts must be targeted to produce briefer, cheaper, and more impactful interventions for use in combination (behavioral and biomedical) HIV prevention programs.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
5R01DA042666-02
Application #
9751263
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Jenkins, Richard A
Project Start
2018-08-01
Project End
2023-05-31
Budget Start
2019-06-01
Budget End
2020-05-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093