# Optimizing a Sensor-Enabled mHealth Intervention for Adolescents with Suboptimal Asthma Control

> **NIH NIH R34** · UNIVERSITY OF KANSAS LAWRENCE · 2024 · $243,287

## Abstract

PROJECT SUMMARY
Asthma affects 9% of adolescents in the United States and is a leading cause of youth morbidity. National
asthma guidelines emphasize the importance of asthma self-management behaviors to control asthma and
promote quality of life. Adolescents have suboptimal adherence to asthma self-management behaviors driven
by an underdeveloped and highly variable capacity to self-regulate cognitions, emotions, and behaviors; and a
normative decrease in parental support while multiple demands are increasing. Each adolescent experiences
different threats to their ability to self-regulate at different moments in time, necessitating personalized and
adaptive self-regulatory support to increase daily self-management behaviors and achieve sustained asthma
control. Smartphones are an optimal mechanism for improving adolescent adherence, however, existing
asthma self-management apps do not combine what is known about evidence-based behavior change
strategies and adaptive intervention technologies that tailor the experience based on user data. Our team
recently developed Responsive Asthma Care for Teens (ReACT; R56 HL141394), a technological ecosystem
including a smartphone app, mobile sensors to assess medication dosing, a Smarthub to achieve real-time
data listening, and cloud-based intervention delivery algorithms. ReACT provides personalized and adaptive
self-regulatory support to improve asthma self-management via goal-setting, feedback, and barrier
identification with problem-solving skills. Results of our pilot work demonstrated that ReACT was acceptable
and produced post-intervention changes in our hypothesized mechanisms of self-regulation and problem-
solving skills. The proposed study will optimize ReACT based on lessons learned from our pilot work and
updated national asthma guidelines. We will conduct an unbalanced (2:1) randomized pilot trial to examine
feasibility of our multisite trial protocol, determine if ReACT produces a clinically significant effect on proximal
mechanisms hypothesized to drive asthma control, and explore the impact of ReACT on asthma control and
asthma-related quality of life. Adolescents ages 13-17 with suboptimal asthma control (n=120) will be
randomized to ReACT or a mHealth control condition stratified by regimen for 6-months. Adolescents in the
control condition will receive an app that includes static asthma education information and a form for recording
symptoms and adherence. The control condition is designed to mirror standard of care, optimize recruitment,
and sustain interest while concurrently having a minimal impact on asthma management. Assessments will
occur at baseline, 3-month, and post-intervention (6-month) time points. Mechanisms of intervention effect will
be collected via both self-report (e.g., self-regulation) and objective (e.g., medication adherence) assessments.
We will assess planned future clinical trial outcomes (e.g., asthma control and asthma-related quality of life) to
provide effe...

## Key facts

- **NIH application ID:** 10917228
- **Project number:** 5R34HL167214-02
- **Recipient organization:** UNIVERSITY OF KANSAS LAWRENCE
- **Principal Investigator:** Christopher C Cushing
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $243,287
- **Award type:** 5
- **Project period:** 2023-09-15 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10917228

## Citation

> US National Institutes of Health, RePORTER application 10917228, Optimizing a Sensor-Enabled mHealth Intervention for Adolescents with Suboptimal Asthma Control (5R34HL167214-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10917228. Licensed CC0.

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