Evaluation of changes in depression, anxiety, and social anxiety using smartphone sensor features: Longitudinal cohort study

Jonah Meyerhoff, Tony Liu, Konrad P. Kording, Lyle H. Ungar, Susan M. Kaiser, Chris J. Karr, David C. Mohr*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Background: The assessment of behaviors related to mental health typically relies on self-report data. Networked sensors embedded in smartphones can measure some behaviors objectively and continuously, with no ongoing effort. Objective: This study aims to evaluate whether changes in phone sensor-derived behavioral features were associated with subsequent changes in mental health symptoms. Methods: This longitudinal cohort study examined continuously collected phone sensor data and symptom severity data, collected every 3 weeks, over 16 weeks. The participants were recruited through national research registries. Primary outcomes included depression (8-item Patient Health Questionnaire), generalized anxiety (Generalized Anxiety Disorder 7-item scale), and social anxiety (Social Phobia Inventory) severity. Participants were adults who owned Android smartphones. Participants clustered into 4 groups: Multiple comorbidities, depression and generalized anxiety, depression and social anxiety, and minimal symptoms. Results: A total of 282 participants were aged 19-69 years (mean 38.9, SD 11.9 years), and the majority were female (223/282, 79.1%) and White participants (226/282, 80.1%). Among the multiple comorbidities group, depression changes were preceded by changes in GPS features (Time: R=-0.23, P=.02; Locations: R=-0.36, P<.001), exercise duration (r=0.39; P=.03) and use of active apps (r=-0.31; P<.001). Among the depression and anxiety groups, changes in depression were preceded by changes in GPS features for Locations (r=-0.20; P=.03) and Transitions (r=-0.21; P=.03). Depression changes were not related to subsequent sensor-derived features. The minimal symptoms group showed no significant relationships. There were no associations between sensor-based features and anxiety and minimal associations between sensor-based features and social anxiety. Conclusions: Changes in sensor-derived behavioral features are associated with subsequent depression changes, but not vice versa, suggesting a directional relationship in which changes in sensed behaviors are associated with subsequent changes in symptoms.

Original languageEnglish (US)
Article numbere22844
JournalJournal of medical Internet research
Volume23
Issue number9
DOIs
StatePublished - Sep 2021

Keywords

  • Anxiety
  • Depression
  • Digital biomarkers
  • Digital phenotyping
  • Digital phenotyping
  • Ecological momentary assessment
  • Internet technology
  • Mental health assessment
  • Mobile device
  • Mobile phone
  • Mobile phone
  • Passive sensing
  • Personal sensing
  • Psychiatric disorders
  • mHealth

ASJC Scopus subject areas

  • Health Informatics

Fingerprint

Dive into the research topics of 'Evaluation of changes in depression, anxiety, and social anxiety using smartphone sensor features: Longitudinal cohort study'. Together they form a unique fingerprint.

Cite this