Cited by 169Bipolar Disorder and TreatmentMental Health Research TopicsDigital Mental Health Interventions

Smartphone data as an electronic biomarker of illness activity in bipolar disorder

Faurholt‐Jepsen, Maria, Vinberg, Maj, Frost, Mads, Christensen, Ellen Margrethe, Bardram, Jakob E, Kessing, Lars Vedel·2015·Bipolar Disorders

Abstract

Objectives Objective methods are lacking for continuous monitoring of illness activity in bipolar disorder. Smartphones offer unique opportunities for continuous monitoring and automatic collection of real-time data. The objectives of the paper were to test the hypotheses that (i) daily electronic self-monitored data and (ii) automatically generated objective data collected using smartphones correlate with clinical ratings of depressive and manic symptoms in patients with bipolar disorder. Methods Software for smartphones (the MONARCA I system) that collects automatically generated objective data and self-monitored data on illness activity in patients with bipolar disorder was developed by the authors. A total of 61 patients aged 18-60 years and with a diagnosis of bipolar disorder according to ICD-10 used the MONARCA I system for six months. Depressive and manic symptoms were assessed monthly using the Hamilton Depression Rating Scale 17-item (HDRS-17) and the Young Mania Rating Scale (YMRS), respectively. Data are representative of over 400 clinical ratings. Analyses were computed using linear mixed-effect regression models allowing for both between individual variation and within individual variation over time. Results Analyses showed significant positive correlations between the duration of incoming and outgoing calls/day and scores on the HDRS-17, and significant positive correlations between the number and duration of incoming calls/day and scores on the YMRS; the numbe…

Integrity signals

Registry

Crossref · 10.1111/bdi.12332

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Digital mood-tracking applications allow individuals to track mood fluctuations, medication adherence, and sleep patterns, providing insights into treatment strategies.

    “These apps allow individuals to track mood fluctuations, medication adherence, and sleep patterns, providing insights into treatment strategies [58].”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Faurholt‐Jepsen, M., Vinberg, M., Frost, M., Christensen, E. M., Bardram, J. E., & Kessing, L. V.
Affiliations
  • Mental Health Services (DK)
  • IT University of Copenhagen (DK)
Corresponding author
Faurholt‐Jepsen, Maria
Venue
Bipolar Disorders
Publisher
Wiley
Published
2015-09-23
Volume
17
Issue
7
Pages
715-728
ISSN
  • 1398-5647 (ISSN-L)
  • 1399-5618
OpenAlex
W2171995598
Cited by
169
References
40
Citations by year
2026: 9 · 2025: 14 · 2024: 14 · 2023: 9 · 2022: 12 · 2021: 22 · 2020: 23 · 2019: 21 · 2018: 14 · 2017: 16 · 2016: 12 · 2015: 1 · 2014: 1
FWCI
11.65
Type
journal article
Language
en
Open access
closed
Locations
  • Bipolar Disorders (publishedVersion)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
  • Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion)
  • IT University Of Copenhagen (IT University of Copenhagen) (submittedVersion)
Funders
Seventh Framework Programme
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
Keywords
bipolar disorder, smartphone data, call duration, text messaging, self-monitoring, depressive symptoms, manic symptoms, real-time data acquisition
MeSH terms
Smartphone, Adolescent, Adult, Bipolar Disorder, Female, Humans, Interpersonal Relations, Male, Middle Aged, Monitoring, Physiologic, Psychiatric Status Rating Scales, Statistics as Topic, Diagnostic Self Evaluation, Patient Acuity

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review