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Modeling Mood Course to Detect Markers of Effective Adaptive Interventions

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ClinicalTrials.gov Identifier: NCT03358238
Recruitment Status : Enrolling by invitation
First Posted : November 30, 2017
Last Update Posted : December 6, 2017
Sponsor:
Collaborators:
University of Michigan
National Institute of Mental Health (NIMH)
Information provided by (Responsible Party):
University of Wisconsin, Madison

November 26, 2017
November 30, 2017
December 6, 2017
November 27, 2017
February 1, 2019   (Final data collection date for primary outcome measure)
  • Proportion of participants who report they are more likely to use a smart-phone app over an activity tracker to monitor their symptoms [ Time Frame: Study end (6 weeks) ]
    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.
  • Difference in adherence rates for self-reporting symptoms between 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) [ Time Frame: Study end (6 weeks) ]
    For each individual, 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.
  • Difference in adherence rates for activity tracking between 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) [ Time Frame: Study end (6 weeks) ]
    For each individual, adherence rate for activity tracking is measured as the proportion of study days with at least 12 hours of activity tracking.
  • Proportion of participants who have higher adherence rates for self-reporting symptoms than adherence rates for activity tracking [ Time Frame: Study end (6 weeks) ]
    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.
Same as current
Complete list of historical versions of study NCT03358238 on ClinicalTrials.gov Archive Site
  • Change from baseline in severity of manic symptoms, as measured with the Young Mania Rating Scale [ Time Frame: Baseline, study end (6 weeks) ]
    The Young Mania Rating Scale consists of 11 items to evaluate symptoms of mania, such as elevated mood, energy, and irritability. Item scores are added together to get a total score.
  • Change from baseline in severity of depressive symptoms, as measured with the 17-item Structured Interview Guide for the Hamilton Rating Scale for Depression [ Time Frame: Baseline, study end (6 weeks) ]
    The 17-item Structured Interview Guide for the Hamilton Rating Scale for Depression consists of 17 items to evaluate symptoms of depression, such as guilt, fatigue, depressed mood. Item scores are summed to get a total score.
Same as current
Not Provided
Not Provided
 
Modeling Mood Course to Detect Markers of Effective Adaptive Interventions
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.

Interventional
Not Applicable
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)
Primary Purpose: Health Services Research
Bipolar Disorder
  • Behavioral: Weekly review
    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.
  • Other: No weekly review
    An interviewer will not review self-report symptoms and patterns collected from an activity tracker.
    Other Name: Placebo
  • Placebo Comparator: No weekly review
    Individuals will not review self-report and activity tracker data with an interviewer on a weekly basis over the phone.
    Intervention: Other: No weekly review
  • Experimental: Weekly review
    Individuals will review self-report and activity tracker data with an interviewer on a weekly basis over the phone.
    Intervention: Behavioral: Weekly review
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.

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Enrolling by invitation
50
Same as current
February 1, 2019
February 1, 2019   (Final data collection date for primary outcome measure)

Inclusion Criteria:

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

Exclusion Criteria:

Sexes Eligible for Study: All
18 Years and older   (Adult, Senior)
No
Contact information is only displayed when the study is recruiting subjects
United States
 
 
NCT03358238
K01MH112876( U.S. NIH Grant/Contract )
K01MH112876 ( U.S. NIH Grant/Contract )
HUM00126732 ( Other Identifier: University of Michigan )
2017-1322 ( Other Identifier: University of Wisconsin )
No
Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Plan to Share IPD: Undecided
University of Wisconsin, Madison
University of Wisconsin, Madison
  • University of Michigan
  • National Institute of Mental Health (NIMH)
Principal Investigator: Amy L Cochran, PhD University of Wisconsin, Madison
University of Wisconsin, Madison
December 2017

ICMJE     Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP