Modeling Mood Course to Detect Markers of Effective Adaptive Interventions

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.

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.

Individuals will not review self-report and activity tracker data with an interviewer on a weekly basis over the phone.

Individuals will review self-report and activity tracker data with an interviewer on a weekly basis over the phone.

Each week in the study, an interviewer will review manic and depressive symptoms self-reported by a participant and patterns of activity, sleep, and heart rate collected by the participant's activity tracker.

Proportion of Participants Who Report They Are More Likely to Use a Smart-phone App Over an Activity Tracker to Monitor Their Symptoms

Likelihood of using app over activity tracker is measured using a survey designed specifically for this study to evaluate participant engagement in monitoring symptoms. The relevant question asks 'Which are you more likely to use to monitor your symptoms' and has two mutually-exclusive options for an answer: 'An activity tracker' or 'A smart-phone app'. Engagement survey is conducted over the phone by an interviewer.

For each individual, adherence rate for self-reporting symptoms is measured/defined as the proportion of study days with at least 50% completion of of daily self-reports questions (i.e. 6 questions completed out of a total of 12). This measure is the average adherence rate for individuals in each of the two intervention arms: individuals who review their data with an interviewer ('Weekly review' arm) vs those who do not review their data with an interviewer ('No weekly review' arm).

For each individual, adherence rate for activity tracking is measured as the proportion of study days with at least 12 hours of activity tracking. This measure is the average adherence rates among individuals in either arm: individuals who review their data weekly with an interviewer ('Weekly review' arm) compared to individuals who do not review their data weekly with an interviewer ('No weekly review' arm)

Proportion of Participants Who Have Higher Adherence Rates for Self-reporting Symptoms Than Adherence Rates for Activity Tracking

For each individual, adherence rate for activity tracking is measured as the proportion of study days with at least 12 hours of activity tracking, whereas adherence rate for self-reporting symptoms is measured as the proportion of study days with at least 50% of daily self-reports survey questions completed.

Average Change From Baseline in Severity of Manic Symptoms, as Measured With the Young Mania Rating Scale

The Young Mania Rating Scale consists of clinician-rated 11 items to evaluate symptoms of mania, such as elevated mood, energy, and irritability. Item scores are added together to get a total score, ranging from 0 to 60. A higher score indicates more severe manic symptoms.

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

The 17-Item Structured Interview Guide for the Hamilton Rating Scale for Depression consists of 17 clinician-rated items to evaluate symptoms of depression, such as guilt, fatigue, and depressed mood. Item scores are summed to get a total score, ranging from 0 to 52. Higher scores indicate more severe symptoms.

Inclusion Criteria: Individuals diagnosed with bipolar disorder Individuals with a smart-phone Exclusion Criteria: None

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.

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.