Literature DB >> 32743692

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.

Sigurd Arne Melbye1,2, Sharleny Stanislaus3, Maj Vinberg3,4,5, Mads Frost4, Jakob Eyvind Bardram4,6,7, Kimie Sletved3, Klara Coello3, Hanne Lie Kjærstad3, Ellen Margrethe Christensen3, Maria Faurholt-Jepsen3, Lars Vedel Kessing3,4.   

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.
© 2020. The Author(s).

Entities:  

Keywords:  Activity; Bipolar disorder; Mood; Sleep; Smartphones

Year:  2020        PMID: 32743692     DOI: 10.1007/s00787-020-01611-7

Source DB:  PubMed          Journal:  Eur Child Adolesc Psychiatry        ISSN: 1018-8827            Impact factor:   4.785


  41 in total

1.  Validity and repeatability of the EPIC-Norfolk Physical Activity Questionnaire.

Authors:  Nicholas J Wareham; Rupert W Jakes; Kirsten L Rennie; Jo Mitchell; Susie Hennings; Nicholas E Day
Journal:  Int J Epidemiol       Date:  2002-02       Impact factor: 7.196

2.  Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication.

Authors:  Ronald C Kessler; Patricia Berglund; Olga Demler; Robert Jin; Kathleen R Merikangas; Ellen E Walters
Journal:  Arch Gen Psychiatry       Date:  2005-06

3.  Is smartphone-based mood instability associated with stress, quality of life, and functioning in bipolar disorder?

Authors:  Maria Faurholt-Jepsen; Mads Frost; Jonas Busk; Ellen Margrethe Christensen; Jakob Eyvind Bardram; Maj Vinberg; Lars Vedel Kessing
Journal:  Bipolar Disord       Date:  2019-05-27       Impact factor: 6.744

4.  Mood instability as a predictor of clinical and functional outcomes in adolescents with bipolar I and bipolar II disorder.

Authors:  Lisa A O'Donnell; Alissa J Ellis; Margaret M Van de Loo; Jonathan P Stange; David A Axelson; Robert A Kowatch; Christopher D Schneck; David J Miklowitz
Journal:  J Affect Disord       Date:  2018-04-09       Impact factor: 4.839

5.  Sleep disturbances in bipolar disorder during remission.

Authors:  Julie St-Amand; Martin D Provencher; Lynda Bélanger; Charles M Morin
Journal:  J Affect Disord       Date:  2012-08-11       Impact factor: 4.839

6.  Do young adults with bipolar disorder benefit from early intervention?

Authors:  Lars Vedel Kessing; Hanne Vibe Hansen; Ellen Margrethe Christensen; Henrik Dam; Christian Gluud; Jørn Wetterslev
Journal:  J Affect Disord       Date:  2013-10-10       Impact factor: 4.839

7.  Subsyndromal symptoms assessed in longitudinal, prospective follow-up of a cohort of patients with bipolar disorder.

Authors:  Glenda M MacQueen; Michael Marriott; Helen Begin; Janine Robb; Russell T Joffe; L Trevor Young
Journal:  Bipolar Disord       Date:  2003-10       Impact factor: 6.744

8.  Effects of treatment latency on response to maintenance treatment in manic-depressive disorders.

Authors:  Ross J Baldessarini; Leonardo Tondo; Christopher J Baethge; Beatrice Lepri; Irene M Bratti
Journal:  Bipolar Disord       Date:  2007-06       Impact factor: 6.744

9.  Mood instability is a common feature of mental health disorders and is associated with poor clinical outcomes.

Authors:  Rashmi Patel; Theodore Lloyd; Richard Jackson; Michael Ball; Hitesh Shetty; Matthew Broadbent; John R Geddes; Robert Stewart; Philip McGuire; Matthew Taylor
Journal:  BMJ Open       Date:  2015-05-21       Impact factor: 2.692

10.  Assessment of the Functioning Levels and Related Factors in Patients with Bipolar Disorder during Remission.

Authors:  Yunus Hacimusalar; Esra Sezgin Doğan
Journal:  Noro Psikiyatr Ars       Date:  2019-07-16       Impact factor: 1.339

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