ArticleBipolar disorders2020
A comparative study of engagement in mobile and wearable health monitoring for bipolar disorder.
Article in Bipolar disorders, 2020. 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 24 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
24 citing papers in PubMed, 4 syntheses or guidelines pooled it, 50 citations in OpenAlex.
- Mood Monitoring, Mood Tracking, and Ambulatory Assessment Interventions in Depression and Bipolar Disorder: Systematic Review and Meta-Analysis of Randomized Controlled Trials.JMIR mental health · 2026Pooled it
- Barriers and Facilitators of User Engagement With Digital Mental Health Interventions for People With Psychosis or Bipolar Disorder: Systematic Review and Best-Fit Framework Synthesis.JMIR mental health · 2025Pooled it
- Smartphone-based interventions in bipolar disorder: Systematic review and meta-analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force.Bipolar disorders · 2022Pooled it
- Feasibility of mHealth interventions for depressive symptoms in Latin America: a systematic review.International review of psychiatry (Abingdon, England) · 2021Pooled it
- Engagement With a Remote Symptom-Tracking Platform Among Participants With Major Depressive Disorder: Randomized Controlled Trial.JMIR mHealth and uHealth · 2024Trial
- Digital tools for assessing bipolar disorder: A scoping review of the current landscape.Neuroscience applied · 2026Article
- 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 phenotyping in bipolar disorder: Using longitudinal Fitbit data and personalized machine learning to predict mood symptomatology.Acta psychiatrica Scandinavica · 2025Article
- MoodMon: novel optimization of bipolar disorder monitoring through patient-driven voice parameter submission and AI technology.Postepy psychiatrii neurologii · 2024Article
- Mobile Acceptance and Commitment Therapy in Bipolar Disorder: Microrandomized Trial.JMIR mental health · 2023Article
- Remote Patient Monitoring for Neuropsychiatric Disorders: A Scoping Review of Current Trends and Future Perspectives from Recent Publications and Upcoming Clinical Trials.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2022Article
- A systematic review of engagement reporting in remote measurement studies for health symptom tracking.NPJ digital medicine · 2022Review
- Article
- Behavioral and Self-reported Data Collected From Smartphones for the Assessment of Depressive and Manic Symptoms in Patients With Bipolar Disorder: Prospective Observational Study.Journal of medical Internet research · 2022Observational
- A Mixed-Methods Analysis of Mobile ACT Responses From Two Cohorts.Frontiers in digital health · 2022Article
- Exploring the Effects of In-App Components on Engagement With a Symptom-Tracking Platform Among Participants With Major Depressive Disorder (RADAR-Engage): Protocol for a 2-Armed Randomized Controlled Trial.JMIR research protocols · 2021Article
- A digital self-report survey of mood for bipolar disorder.Bipolar disorders · 2021Article
- Dynamics of data-driven microstates in bipolar disorder.Journal of psychiatric research · 2021Article
- Patients' adherence to smartphone apps in the management of bipolar disorder: a systematic review.International journal of bipolar disorders · 2021Review
- Monitoring Sleep Changes via a Smartphone App in Bipolar Disorder: Practical Issues and Validation of a Potential Diagnostic Tool.Frontiers in psychiatry · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesSelf-monitoring is recommended for individuals with bipolar disorder, with numerous technological solutions available. This study aimed to identify basic components of these solutions that increase engagement with self-monitoring.
methodsParticipants with bipolar disorder (n = 47) monitored their symptoms with a Fitbit and a smartphone app and were randomly assigned to either review or not review recorded symptoms weekly. We tested whether individuals would better adhere to and prefer monitoring with passive monitoring with an activity tracker compared to active monitoring with a smartphone app and whether individuals would better adhere to self-monitoring if their recorded symptoms were reviewed with an interviewer.
resultsMonitoring with a smartphone app achieved similar adherence and preference to Fitbit (P > .85). Linear mixed effects modeling found adherence decreased significantly more over the study for the Fitbit (12% more, P < .001) even though more participants reported they would use the Fitbit over a year compared to the app (72.3% vs 46.8%). Reviewing symptoms weekly did not improve adherence, but most participants reported they would prefer to review symptoms with a clinician (74.5%) and on monthly basis (57.5%) compared to alternatives. Participants endorsed sleep as the most important symptom to monitor, forgetfulness as the largest barrier to self-monitoring, and raising self-awareness as the best reason for self-monitoring.
conclusionsWe recommend a combined strategy of wearable and mobile monitoring that includes reminders, targets raising self-awareness, and tracks sleep. A clinician may want to review symptoms on a monthly basis.
trial registrationClinicalTrials.gov NCT03358238.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.