# Design and analysis considerations for a sequentially randomized HIV prevention trial

## TL;DR

This paper discusses the design and analysis of the TechStep HIV prevention trial, which uses a sequential randomization approach and causal inference methods to evaluate mobile health interventions for transgender adolescents.

## Contribution

It introduces a causal framework and targeted estimators for analyzing complex sequentially randomized trial data in HIV prevention research.

## Key findings

- Causal estimands are formalized for the trial.
- Targeted minimum loss-based estimators are developed.
- Simulations demonstrate estimator performance.

## Abstract

TechStep is a randomized trial of a mobile health interventions targeted towards transgender adolescents. The interventions include a short message system, a mobile-optimized web application, and electronic counseling. The primary outcomes are self-reported sexual risk behaviors and uptake of HIV preventing medication. In order that we may evaluate the efficacy of several different combinations of interventions, the trial has a sequentially randomized design. We use a causal framework to formalize the estimands of the primary and key secondary analyses of the TechStep trial data. Targeted minimum loss-based estimators of these quantities are described and studied in simulation.