# Digital adherence technologies to facilitate completion of short-course tuberculosis preventive therapy among people living with HIV

> **NIH NIH K23** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2023 · $201,150

## Abstract

Project Summary/Abstract
Tuberculosis (TB) is the leading cause of death among people living with HIV (PLHIV), responsible for over
one-third of all HIV deaths worldwide. Tuberculosis preventive therapy (TPT), which can reduce TB incidence
by 30-50%, is recommended for all PLHIV by the World Health Organization (WHO). Although a new 12-dose,
once-weekly regimen of isoniazid and rifapentine (3HP) via directly observed therapy (DOT) is now available
and recommended, treatment completion remains a concern. Additionally, DOT is not a feasible strategy for
increasing TB preventive therapy uptake in high burden, low-income settings. To realize the promising
potential of 3HP to reduce TB mortality among PLHIV, there is an urgent need for studies that evaluate
approaches to support treatment completion with self-administered therapy.
The overall objective of this proposal is to determine whether low-cost digital adherence technologies (DATs)
can be used to monitor and support completion of 3HP among PLHIV. Our central hypothesis is that a theory-
informed adaptation of DATs to fit users' needs will result in high levels of DAT adoption and implementation
fidelity. This hypothesis is based on preliminary data from my work in using human-centered design (HCD)
methods to adapt a DAT platform to address the adherence challenges faced by patients with active TB. In my
mentor's stepped wedge randomized trial, this adapted DAT platform had high levels of acceptability for
patients and providers, and improved completion of treatment for active TB. The proposed studies will build
upon this prior work to support the use of DATs for scaling-up TB preventive therapy to a key high-risk
population. To test this hypothesis in Aim 1 I will identify barriers and facilitators to the use of DATs for
facilitating 3HP completion among PLHIV. In Aim 2 I will then adapt two low-cost DATs to fit users' needs using
the human centered design methodology. Last, in Aim 3, I will conduct pilot trials to assess the preliminary
effectiveness and implementation of each adapted DAT among PLHIV initiating 3HP. The results will provide
the preliminary data needed for an NIH R01 application proposing a randomized trial to evaluate the
effectiveness, implementation, and cost-effectiveness of one or both contextually adapted DATs for supporting
completion of short-course TB preventive therapy among PLHIV.
The proposed research aims map directly onto my training objectives including designing implementation
interventions using mixed methods research (Aims 1 & 2), tailoring implementation interventions using human-
centered design (Aim 2), and evaluating implementation interventions (Aim 3). Rigorous implementation
science-focused training coupled with an interdisciplinary mentorship team committed to my success will
catalyze me towards my career goal to become an independent physician-scientist focused on improving
uptake of evidence-based interventions to reduce TB burden among PLHIV.

## Key facts

- **NIH application ID:** 10681475
- **Project number:** 5K23HL156784-03
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Christopher Allen Berger
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $201,150
- **Award type:** 5
- **Project period:** 2021-09-08 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10681475

## Citation

> US National Institutes of Health, RePORTER application 10681475, Digital adherence technologies to facilitate completion of short-course tuberculosis preventive therapy among people living with HIV (5K23HL156784-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10681475. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*