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

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.

Associations between mood instability and emotional processing in a large cohort of bipolar patients.

BACKGROUND: Aberrant emotional biases have been reported in bipolar disorder (BD), but results are inconsistent. Despite the clinical relevance of chronic mood variability in BD, there is no previous research investigating how the extent of symptom fluctuations in bipolar disorder might relate to emotional biases. This exploratory study investigated, in a large cohort of bipolar patients, whether instability in weekly mood episode symptoms and other clinical and demographic factors were related to emotional bias as measured in a simple laboratory task. METHOD: Participants (N = 271, BDI = 206, BDII = 121) completed an 'emotional categorization and memory' task. Weekly self-reported symptoms of depression and mania were collected prospectively. In linear regression analyses, associations between cognitive bias and mood variability were explored together with the influence of demographic and clinical factors, including current medication. RESULTS: Greater accuracy in the classification of negative words relative to positive words was associated with greater instability in depressive symptoms. Furthermore, greater negative bias in free recall was associated with higher instability in manic symptoms. Participants diagnosed with BDII, compared with BDI, showed overall better word recognition and recall. Current antipsychotic use was associated with reduced instability in manic symptoms but this did not impact on emotional processing performance. CONCLUSIONS: Emotional processing biases in bipolar disorder are related to instability in mood. These findings prompt further investigation into the underpinnings as well as clinical significance of mood instability.