ArticleEuropean child & adolescent psychiatry2021
Mood, activity, and sleep measured via daily smartphone-based self-monitoring in young patients with newly diagnosed bipolar disorder, their unaffected relatives and healthy control individuals.
Article in European child & adolescent psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A Clinical AI-Based System (MoodMon) for Affective Disorders: Algorithm Development and Validation.JMIR AI · 2026Article
- Sleep fluctuations precede self-reported mood changes in bipolar disorder: results from the BipoSense study.International journal of bipolar disorders · 2026Article
- The effect of smartphone-based monitoring and treatment including clinical feedback in progressed bipolar disorder: the SmartBipolar trial randomised controlled parallel-group trial.International journal of bipolar disorders · 2026Article
- Digital tools for assessing bipolar disorder: A scoping review of the current landscape.Neuroscience applied · 2026Article
- Mood and Activity Measured Using Smartphones in Unipolar Depressive Disorder.Frontiers in psychiatry · 2021Article
- Automatically Generated Smartphone Data in Young Patients With Newly Diagnosed Bipolar Disorder and Healthy Controls.Frontiers in psychiatry · 2021Article
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Authors and funding
11 authors.
Funding
Abstract
Diagnostic evaluations and early interventions of patients with bipolar disorder (BD) rely on clinical evaluations. Smartphones have been proposed to facilitate continuous and fine-grained self-monitoring of symptoms. The present study aimed to (1) validate daily smartphone-based self-monitored mood, activity, and sleep, against validated questionnaires and clinical ratings in young patients with newly diagnosed BD, unaffected relatives (UR), and healthy controls persons (HC); (2) investigate differences in daily smartphone-based self-monitored mood, activity, and sleep in young patients with newly diagnosed BD, UR, and HC; (3) investigate associations between self-monitored mood and self-monitored activity and sleep, respectively, in young patients with newly diagnosed BD. 105 young patients with newly diagnosed BD, 24 UR and 77 HC self-monitored 2 to 1077 days (median [IQR] = 65 [17.5-112.5]). There was a statistically significantly negative association between the mood item on Hamilton Depression Rating Scale (HAMD) and smartphone-based self-monitored mood (B = - 0.76, 95% CI - 0.91; - 0.63, p < 0.001) and between psychomotor item on HAMD and self-monitored activity (B = - 0.44, 95% CI - 0.63; - 0.25, p < 0.001). Smartphone-based self-monitored mood differed between young patients with newly diagnosed BD and HC (p < 0.001), and between UR and HC (p = 0.008) and was positively associated with smartphone-based self-reported activity (p < 0.001) and sleep duration (p < 0.001). The findings support the potential of smartphone-based self-monitoring of mood and activity as part of a biomarker for young patients with BD and UR. Smartphone-based self-monitored mood is better to discriminate between young patients with newly diagnosed BD and HC, and between UR and HC, compared with smartphone-based activity and sleep.Trial registration clinicaltrials.gov NCT0288826.
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