ArticleJMIR research protocols2018
Engagement Strategies for Self-Monitoring Symptoms of Bipolar Disorder With Mobile and Wearable Technology: Protocol for a Randomized Controlled Trial.
Article in JMIR research protocols, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03358238 (Modeling Mood Course to Detect Markers of Effective Adaptive Interventions), which is not on this map. Cited by 10 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Modeling Mood Course to Detect Markers of Effective Adaptive Interventions
Who cites it
10 citing papers in PubMed.
- A self-management intervention for bipolar disorder using a WeChat mini program (Mood Calm): study protocol for intervention design, development, and a preliminary trial.Frontiers in psychology · 2026Article
- Digital tools for assessing bipolar disorder: A scoping review of the current landscape.Neuroscience applied · 2026Article
- KIOS: A smartphone app for self-monitoring for patients with bipolar disorder.Bipolar disorders · 2024Article
- The Minimum Feature Set for Designing Mobile Apps to Support Bipolar Disorder-Affected Patients: Proposal of Essential Functions and Requirements.Journal of healthcare informatics research · 2023Article
- Mobile Acceptance and Commitment Therapy in Bipolar Disorder: Microrandomized Trial.JMIR mental health · 2023Article
- A digital self-report survey of mood for bipolar disorder.Bipolar disorders · 2021Article
- Optimizing an Acceptance and Commitment Therapy Microintervention Via a Mobile App With Two Cohorts: Protocol for Micro-Randomized Trials.JMIR research protocols · 2020Article
- Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder.JMIR mental health · 2020Article
- A comparative study of engagement in mobile and wearable health monitoring for bipolar disorder.Bipolar disorders · 2020Article
- Emotion Recognition in the Real-World: Passively Collecting and Estimating Emotions from Natural Speech Data of Individuals with Bipolar Disorder.IEEE transactions on affective computingArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundMonitoring signs and symptoms in bipolar disorder (BP) is typically based on regular assessments from patient-clinician interactions. Mobile and wearable technology promises to make monitoring symptoms in BP easier, but little is known about how best to engage individuals with BP in monitoring symptoms.
objectiveThe objective of this study was to provide the rationale and protocol for a randomized controlled trial that investigates engagement strategies for monitoring symptoms of BP, including the strategies of using activity trackers compared with self-reports and reviewing recorded symptoms weekly with an interviewer.
methodsA total of 50 individuals with BP will be recruited from the Prechter Longitudinal Study of Bipolar Disorder at the University of Michigan to participate in a 6-week study. Participants will monitor their symptoms through an activity tracker (Fitbit Alta HR) and a mobile phone app designed for this study. In addition to monitoring symptoms, participants have a 50-50 chance of being assigned to an arm that reviews self-reports and activity information weekly. Statistical tests will be performed to test hypotheses that participants adhere to activity tracking significantly more than self-reporting, prefer activity tracking significantly more than self-reporting, and better adhere to both activity tracking and self-reporting when reviewing collected information weekly.
resultsRecruitment commenced in November 2017. The first group of participants began the study in January 2018.
conclusionsThis study aims to establish strategies to engage individuals with BP in monitoring their symptoms with mobile and wearable technology. Better engagement strategies are expected to aid current efforts in bipolar research and clinical care, from the development of new mobile phone apps to providing the right intervention to the right individual at the right moment.
trial registrationClinicalTrials.gov NCT03358238; https://clinicaltrials.gov/ct2/show/NCT03358238 (Archived by WebCite at http://www.webcitation.org/6yebuNfz5). REGISTERED REPORT IDENTIFIER: RR1-10.2196/9899.
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