Maria Faurholt-Jepsen1, Jonas Busk2, Maj Vinberg3, Ellen Margrethe Christensen4, Mads Frost5, Jakob E Bardram2, Lars Vedel Kessing6. 1. Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Rigshospitalet, Blegdamsvej 9, DK- 2100 Copenhagen, Denmark; Monsenso Aps, Langelinie Alle 47, Copenhagen, Denmark. Electronic address: maria@faurholt-jepsen.dk. 2. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark; Monsenso Aps, Langelinie Alle 47, Copenhagen, Denmark. 3. Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Rigshospitalet, Blegdamsvej 9, DK- 2100 Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen; Psychiatric Research Unit, Psychiatric Centre North Zealand, Hilleroed; Monsenso Aps, Langelinie Alle 47, Copenhagen, Denmark. 4. Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Rigshospitalet, Blegdamsvej 9, DK- 2100 Copenhagen, Denmark; Monsenso Aps, Langelinie Alle 47, Copenhagen, Denmark. 5. Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen; Monsenso Aps, Langelinie Alle 47, Copenhagen, Denmark. 6. Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Rigshospitalet, Blegdamsvej 9, DK- 2100 Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen; Monsenso Aps, Langelinie Alle 47, Copenhagen, Denmark.
Abstract
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.
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.
Authors: John Torous; Sandra Bucci; Imogen H Bell; Lars V Kessing; Maria Faurholt-Jepsen; Pauline Whelan; Andre F Carvalho; Matcheri Keshavan; Jake Linardon; Joseph Firth Journal: World Psychiatry Date: 2021-10 Impact factor: 49.548