A digital self-report survey of mood for bipolar disorder

Objectives Bipolar disorder (BP) is commonly researched in digital settings. As a result, standardized digital tools are needed to measure mood. We sought to validate a new survey that is brief, validated in digital form, and able to separately measure manic and depressive severity. Methods We introduce a 6-item digital survey, called digiBP, for measuring mood in BP. It has three depressive items (depressed mood, fidgeting, fatigue), two manic items (increased energy, rapid speech), and one mixed item (irritability); and recovers two scores (m and d) to measure manic and depressive severity. In a secondary analysis of individuals with BP who monitored their symptoms over 6 weeks (n = 43), we perform a series of analyses to validate the digiBP survey internally, externally, and as a longitudinal measure. Results We first verify a conceptual model for the survey in which items load onto two factors (manic and depressive). We then show weekly averages of m and d scores from digiBP can explain significant variation in weekly scores from the Young Mania Rating Scale (R-2 = 0.47) and SIGH-D (R-2 = 0.58). Lastly, we examine the utility of the survey as a longitudinal measure by predicting an individual's future m and d scores from their past m and d scores. Conclusions While further validation is warranted in larger, diverse populations, these validation analyses should encourage researchers to consider digiBP for their next digital study of BP.

Automated summary

This study introduces a brief digital survey, digiBP, for measuring mood in patients with bipolar disorder and validates its internal, external, and longitudinal measurement properties through various analyses. The results demonstrate that the scores from digiBP can effectively explain variation in mood scores and serve as a longitudinal measurement tool.