Clinical trial NCT03358238: Modeling Mood Course to Detect Markers of Effective Adaptive Interventions
Official title: Modeling Mood Course to Detect Markers of Effective Adaptive Interventions
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Bipolar Disorder
Lead sponsor: University of Wisconsin, Madison
Sponsor class: OTHER
Collaborators: name: University of Michigan
name: National Institute of Mental Health (NIMH)
First posted: 2017-11-30
Enrollment: 50
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: HEALTH_SERVICES_RESEARCH

Brief summary: The goal of this study is to learn how to engage individuals with bipolar disorder in long-term monitoring of daily patterns of mood, stress, sleep, circadian rhythm, and medical adherence. Knowledge gained will be used to develop a mobile health platform for the translation of a psychosocial intervention for bipolar disorder into an effective adaptive intervention.

Detailed description: Bipolar disorder is a chronic illness of profound shifts in mood ranging from mania to depression. Bipolar disorder 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. To accomplish this, however, requires evidence-based practices for adapting a psychosocial therapy. The long-term goal of this study is to address this knowledge gap, by establishing a mobile health platform for translating a psychosocial therapy in bipolar disorder into an effective adaptive intervention.

An important first step and the specific goal of this study is to answer the question of how to engage individuals with bipolar disorder in long-term monitoring of their daily patterns of mood, stress, sleep, circadian rhythm, and medical adherence. To answer this question, individuals with bipolar disorder will interact with a smart-phone application and activity tracker over six weeks. Individuals will record their symptoms twice-daily with the smart-phone application while activity, sleep, and heart rate are recorded with their activity tracker. In addition, individuals will be interviewed on a weekly basis. The study focuses on testing three engagement strategies: using activity trackers rather than self-reports; reviewing recorded symptoms with another person on a weekly basis; and synthesizing a person's data into charts and graphs.

Eligibility criteria: Inclusion Criteria:

* Individuals diagnosed with bipolar disorder
* Individuals with a smart-phone

Exclusion Criteria:

* None

Primary outcomes:
measure: Proportion of Participants Who Report They Are More Likely to Use a Smart-phone App Over an Activity Tracker to Monitor Their Symptoms
timeFrame: Study end (6 weeks)
measure: Average Proportion of Study Days With At Least 50% Completion of Daily Self-Reports Questions
timeFrame: Study end (6 weeks)
measure: Average Proportion of Study Days With At Least 12 Hours of Activity Tracking
timeFrame: Study end (6 weeks)
measure: Proportion of Participants Who Have Higher Adherence Rates for Self-reporting Symptoms Than Adherence Rates for Activity Tracking
timeFrame: Study end (6 weeks)
Secondary outcomes:
measure: Average Change From Baseline in Severity of Manic Symptoms, as Measured With the Young Mania Rating Scale
timeFrame: Baseline, study end (6 weeks)
measure: Average Change From Baseline in Severity of Depressive Symptoms, as Measured With the 17-item Structured Interview Guide for the Hamilton Rating Scale for Depression
timeFrame: Baseline, study end (6 weeks)
Other outcomes:
Locations:
city: Ann Arbor
country: United States
facility: University of Michigan
state: Michigan
city: Madison
country: United States
facility: University of Wisconsin
state: Wisconsin
Study officials:
affiliation: University of Wisconsin, Madison
name: Amy L Cochran, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Van Til K, McInnis MG, Cochran A. A comparative study of engagement in mobile and wearable health monitoring for bipolar disorder. Bipolar Disord. 2020 Mar;22(2):182-190. doi: 10.1111/bdi.12849. Epub 2019 Oct 25.
citation: Cochran A, Belman-Wells L, McInnis M. Engagement Strategies for Self-Monitoring Symptoms of Bipolar Disorder With Mobile and Wearable Technology: Protocol for a Randomized Controlled Trial. JMIR Res Protoc. 2018 May 10;7(5):e130. doi: 10.2196/resprot.9899.