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The Capital Region of Denmark - a part of Copenhagen University Hospital
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Daily mobility patterns in patients with bipolar disorder and healthy individuals

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BACKGROUND: Alterations in energy and activity in bipolar disorder (BD) differ between affective states and compared with healthy control individuals (HC). Measurements of activity could discriminate between BD and HC and in the monitoring of affective states within BD. The aims were to investigate differences in 1) passively collected smartphone-based location data (location data) between BD and HC, and 2) location data in BD between affective states.

METHODS: Daily, patients with BD and HC completed smartphone-based self-assessments of mood for up to nine months. Location data reflecting mobility patterns, routine and location entropy was collected daily. A total of 46 patients with BD and 31 HC providing daily data was included.

RESULTS: A total of 4,859 observations of smartphone-based self-assessments of mood and mobility patterns were available from patients with BD and 1,747 observations from HC. Patients with BD had lower location entropy compared with HC (B= -0.14, 95% CI= -0.24; -0.034, p=0.009). Patients with BD during a depressive state were less mobile compared with a euthymic state. Patients with BD during an affective state had lower location entropy compared with a euthymic state (p<0.0001). The AUC of combined location data was rather high in classifying patients with BD compared with HC (AUC: 0.83).

LIMITATIONS: Individuals willing to use smartphones for daily self-monitoring may represent a more motivated group.

CONCLUSION: Alterations in location data reflecting mobility patterns may be a promising measure of illness and illness activity in patients with BD and may be used to monitor the effects of treatments.

Original languageEnglish
JournalJournal of Affective Disorders
Volume278
Pages (from-to)413-422
Number of pages10
ISSN0165-0327
DOIs
Publication statusPublished - 1 Jan 2021

    Research areas

  • Bipolar disorder, Digital phenotyping, Mobile sensing, Mobility, Mood

ID: 61340165