# Modeling mood course to detect markers for effective adaptive interventions

> **NIH NIH K01** · UNIVERSITY OF WISCONSIN-MADISON · 2020 · $122,170

## Abstract

Project Summary
Bipolar (BP) disorder is a chronic illness of profound shifts in mood ranging from mania to depression. BP is
successfully treated by combining medication with psychosocial therapy, but care can prove inadequate in
practice. With gaps in coverage and medication, along with imprecise guidelines on when, where, and how to
intervene, promising psychosocial therapies require adaptive strategies to better address the specific needs of
individuals in a timely manner (NIMH Strategy 2). To accomplish this, however, requires evidence-based
practices for adapting a psychosocial therapy. This Mentored Research Scientist Development Award aims to
address this knowledge gap, by (1) establishing a mobile health platform for translating a psychosocial therapy
in BP into an effective adaptive intervention and (2) facilitating the transition of a junior researcher, at the
interface of mathematics and psychiatry, into an independent researcher of effective adaptive interventions.
The research effort is founded on a mobile health platform that combines evidence-based markers of mood for
long-term monitoring with a micro-randomized trial, designed for optimizing mobile health adaptive
interventions. In Aim 1, we use modeling to characterize and test new markers of mood course that account for
volatility, a feature that masks effects of a therapy on mood. In Aim 2, we explore the potential for long-term
monitoring of BP with interpretable markers from actigraphy. In Aim 3, best practices from Aim 1 and 2 are
integrated with a micro-randomized trial into a mobile health platform. We then test the feasibility of using the
platform to translate a psychosocial therapy, clinical phone call, into an adaptive intervention. If successful, this
work will advance the Candidate's independent goal of adaptive scheduling of phone-calls with BP individuals.
To complement the research agenda, the award will expand the Candidate's background in Computational
Psychiatry into the area of Translational Psychiatry by providing training in five strategic areas: (1) clinical
assessments, (2) psychosocial therapy, (3) mobile health interventions, (4) adaptive clinical trials, and (5)
open-access scheduling. Dr. Melvin McInnis, Thomas B and Nancy Upjohn Woodworth Professor of Bipolar
Disorder and Depression and Professor of Psychiatry at the University of Michigan, will be the primary mentor
and will guide clinical aspects of the training (Training Objectives 1–3); Dr. Amy Kilbourne, Professor of
Psychiatry and Acting Director of VA/HSR&D's Quality Enhancement Research Initiative, will guide training in
the application of adaptive trial designs that involve psychosocial therapy (Training Objectives 2,4–5); and Dr.
Susan Murphy, Herbert E. Robbins Distinguished Professor of Statistics, will guide training into methodology
for adaptive trial design and mobile health interventions (Training Objectives 3–4).
The proposed K01 award promises to train a junior scholar to address te...

## Key facts

- **NIH application ID:** 9921485
- **Project number:** 5K01MH112876-05
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** Amy Louise Cochran
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $122,170
- **Award type:** 5
- **Project period:** 2017-12-04 → 2021-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9921485

## Citation

> US National Institutes of Health, RePORTER application 9921485, Modeling mood course to detect markers for effective adaptive interventions (5K01MH112876-05). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/9921485. Licensed CC0.

---

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