Experiences of remote mood and activity monitoring in bipolar disorder: A qualitative study

Eur Psychiatry. 2017 Mar:41:115-121. doi: 10.1016/j.eurpsy.2016.11.005. Epub 2017 Jan 27.

Abstract

Background: Mobile technology enables high frequency mood monitoring and automated passive collection of data (e.g. actigraphy) from patients more efficiently and less intrusively than has previously been possible. Such techniques are increasingly being deployed in research and clinical settings however little is known about how such approaches are experienced by patients. Here, we explored the experiences of individuals with bipolar disorder engaging in a study involving mood and activity monitoring with a range of portable and wearable technologies.

Method: Patients were recruited from a wider sample of 50 individuals with Bipolar Disorder taking part in the Automated Monitoring of Symptom Severity (AMoSS) study in Oxford. A sub-set of 21 patients participated in a qualitative interview that followed a semi-structured approach.

Results: Monitoring was associated with benefits including increased illness insight, behavioural change. Concerns were raised about the potential preoccupation with, and paranoia about, monitoring. Patients emphasized the need for personalization, flexibility, and the importance of context, when monitoring mood.

Conclusions: Mobile and electronic health approaches have potential to lend new insights into mental health and transform healthcare. Capitalizing on the perceived utility of these approaches from the patients' perspective, while addressing their concerns, will be essential for the promise of new technologies to be realised.

Keywords: Activity; Ambulatory monitoring; Bipolar disorder; Mood monitoring; Wearable devices.

MeSH terms

  • Adult
  • Affect*
  • Bipolar Disorder / psychology*
  • Bipolar Disorder / therapy
  • Female
  • Humans
  • Male
  • Mental Health
  • Middle Aged
  • Mobile Applications
  • Qualitative Research
  • Self Report*
  • Self-Assessment
  • Telemedicine / methods*