Development and Evaluation of a Smartphone-Based Measure of Social Rhythms for Bipolar Disorder

Mark Matthews, Saeed Abdullah, Elizabeth Murnane, Stephen Voida, Tanzeem Choudhury, Geri Gay, Ellen Frank

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Dynamic psychological processes are most often assessed using self-report instruments. This places a constraint on how often and for how long data can be collected due to the burden placed on human participants. Smartphones are ubiquitous and highly personal devices, equipped with sensors that offer an opportunity to measure and understand psychological processes in real-world contexts over the long term. In this article, we present a novel smartphone approach to address the limitations of self-report in bipolar disorder where mood and activity are key constructs. We describe the development of MoodRhythm, a smartphone application that incorporates existing self-report elements from interpersonal and social rhythm therapy, a clinically validated treatment, and combines them with novel inputs from smartphone sensors. We reflect on lessons learned in transitioning from an existing self-report instrument to one that involves smartphone sensors and discuss the potential impact of these changes on the future of psychological assessment.

Original languageEnglish (US)
Pages (from-to)472-483
Number of pages12
JournalAssessment
Volume23
Issue number4
DOIs
StatePublished - Aug 1 2016

All Science Journal Classification (ASJC) codes

  • Clinical Psychology
  • Applied Psychology

Fingerprint Dive into the research topics of 'Development and Evaluation of a Smartphone-Based Measure of Social Rhythms for Bipolar Disorder'. Together they form a unique fingerprint.

Cite this