# App-Enhanced CBT for Adolescents at High Risk for Severe Mood Disorders

> **NIH NIH K23** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2023 · $194,832

## Abstract

PROJECT SUMMARY
This K23 career development award will position the candidate to become an independent clinical researcher
with expertise in the application of mobile health (mHealth) technologies to improve psychosocial clinical trials
for youth at high risk for severe mood disorders (SMD; i.e., bipolar I/II disorder and recurrent or unremitting
major depression). BACKGROUND. Psychosocial treatments (most notably cognitive-behavioral therapy
(CBT)) for adolescents at high risk for SMD show some efficacy in reducing symptoms and rates of mood
episode relapse; however, the size of the effects range from small to moderate. A contributing factor to the
variable effect sizes is the low rates of adherence to CBT’s prescribed treatment tasks (e.g., cognitive
reappraisal). CBT’s mechanisms of therapeutic change hinge upon practice and implementation of the
treatment tasks between sessions. However, adolescents commonly report low motivation, forgetfulness, and
a lack of resources as barriers to completing the CBT treatment tasks. This challenges clinical researchers to
devise better methods of engaging patients in these treatment tasks. SPECIFIC AIMS. This proposal aims to
better engage participants in treatment and bridge treatment sessions by (1) adapting and testing the
acceptability of an existing mobile application (app) that will reinforce session content, facilitate practice of
treatment skills, and allow participants to log and monitor thoughts and symptoms; and (2) conducting a
randomized-controlled trial (RCT) to test the efficacy of an app-enhanced CBT for adolescents (ages 13-17) at
high risk for SMD in improving participant adherence. TRAINING. The candidate will achieve short-term goals
through a resource-rich institutional environment and a cohesive training plan in (1) the planning, delivery, and
evaluation of mHealth technologies, (2) the conduct of clinical trials, and (3) statistical methodologies to
examine high dimensional mHealth data through the use of functional data analysis. MENTORSHIP. The
candidate will be supported by an expert interdisciplinary team: David Miklowitz, PhD (primary mentor), Bonnie
Zima, MD, MPH (co-mentor), Catherine Sugar, PhD (co-mentor), Armen Arevian MD, PhD (collaborator), Eric
Granholm, PhD (consultant), and Jill Ehrenreich-May, PhD (consultant). IMPACT. In line with NIMH funding
priorities, the proposed research will answer critical questions about (1) the acceptability and initial efficacy of a
mobile app in improving participant adherence and acceptability for adolescents at high risk for SMD and (2)
begin to uncover the initial mechanisms by which a mobile app can influence participant adherence. While
initial studies will focus on adolescents at high risk for SMD, it is anticipated that the candidate’s training and
research will have broad applications to a range of age populations and psychiatric conditions. Through this
K23 award, the candidate will gain the training and preliminary data necessar...

## Key facts

- **NIH application ID:** 10597003
- **Project number:** 5K23MH124015-03
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Marc Joshua Weintraub
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $194,832
- **Award type:** 5
- **Project period:** 2021-04-01 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10597003

## Citation

> US National Institutes of Health, RePORTER application 10597003, App-Enhanced CBT for Adolescents at High Risk for Severe Mood Disorders (5K23MH124015-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10597003. Licensed CC0.

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