Research
Print page Print page
Switch language
The Capital Region of Denmark - a part of Copenhagen University Hospital
Published

Daily estimates of clinical severity of symptoms in bipolar disorder from smartphone-based self-assessments

Research output: Contribution to journalJournal articleResearchpeer-review

  1. Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

    Research output: Contribution to journalJournal articleResearchpeer-review

  2. Polygenic risk score, psychosocial environment and the risk of attention-deficit/hyperactivity disorder

    Research output: Contribution to journalJournal articleResearchpeer-review

  3. Genetic stratification of depression in UK Biobank

    Research output: Contribution to journalJournal articleResearchpeer-review

  4. Improvement in indices of cellular protection after psychological treatment for social anxiety disorder

    Research output: Contribution to journalJournal articleResearchpeer-review

  1. Daily mobility patterns in patients with bipolar disorder and healthy individuals

    Research output: Contribution to journalJournal articleResearchpeer-review

  2. The impact of the trajectory of bipolar disorder on global cognitive function: A one-year clinical prospective case-control study

    Research output: Contribution to journalJournal articleResearchpeer-review

  3. Bipolar disorders

    Research output: Contribution to journalReviewResearchpeer-review

  4. Norms for the Screen for Cognitive Impairment in Psychiatry and cognitive trajectories in bipolar disorder

    Research output: Contribution to journalJournal articleResearchpeer-review

View graph of relations

Currently, the golden standard for assessing the severity of depressive and manic symptoms in patients with bipolar disorder (BD) is clinical evaluations using validated rating scales such as the Hamilton Depression Rating Scale 17-items (HDRS) and the Young Mania Rating Scale (YMRS). Frequent automatic estimation of symptom severity could potentially help support monitoring of illness activity and allow for early treatment intervention between outpatient visits. The present study aimed (1) to assess the feasibility of producing daily estimates of clinical rating scores based on smartphone-based self-assessments of symptoms collected from a group of patients with BD; (2) to demonstrate how these estimates can be utilized to compute individual daily risk of relapse scores. Based on a total of 280 clinical ratings collected from 84 patients with BD along with daily smartphone-based self-assessments, we applied a hierarchical Bayesian modelling approach capable of providing individual estimates while learning characteristics of the patient population. The proposed method was compared to common baseline methods. The model concerning depression severity achieved a mean predicted R2 of 0.57 (SD = 0.10) and RMSE of 3.85 (SD = 0.47) on the HDRS, while the model concerning mania severity achieved a mean predicted R2 of 0.16 (SD = 0.25) and RMSE of 3.68 (SD = 0.54) on the YMRS. In both cases, smartphone-based self-reported mood was the most important predictor variable. The present study shows that daily smartphone-based self-assessments can be utilized to automatically estimate clinical ratings of severity of depression and mania in patients with BD and assist in identifying individuals with high risk of relapse.

Original languageEnglish
Article number194
JournalTranslational psychiatry
Volume10
Issue number1
Pages (from-to)194
ISSN2158-3188
DOIs
Publication statusPublished - 18 Jun 2020

ID: 60949487