Daily mood monitoring of symptoms using smartphones in bipolar disorder: A pilot study assessing the feasibility of ecological momentary assessment

Abstract

Background Personal device technology has facilitated gathering data in real-time using Ecological momentary assessment (EMA). We hypothesized that using smartphones to measure symptoms in auto-generated surveys twice a day would be feasible in a group with bipolar disorder (BD). A second exploratory objective of this study was to compare potential differences in core symptoms between BD and healthy control (HC) groups. Methods A two-arm, parallel group, observational study was designed to measure completion rates of surveys of symptoms of mood, energy, speed of thought, impulsivity, and social stress in BD (N=10) and HC (N=10) participants. The surveys were auto-generated twice a day for fourteen days, and subjects could also perform self-generated surveys. Completion rates were compared between BD and HC groups. Scores were averaged for each participant over the 14 day period, and group medians were compared. Results Median completion rates did not differ between groups: 95% in BD, 88% in HC (p=0.68); the median completion rate of auto-generated surveys in the BD group was 79% and in the HC group was 71% (p=0.22). The BD group had significantly lower median mood score (p=0.043) and energy score (p=0.007) than the HC group. Median scores of speed of thoughts (p=0.739), impulsivity (p=0.123) and social stress (p=0.056) did not significantly differ between BD and HC. The BD group had significantly higher range of variability of group median mood (p=0.043), speed of thoughts (p=0.002) and impulsivity (p=0.005) scores over the course of 14 days than HC, while range of variability of energy (p=0.218) and social stress (p=0.123) scores did not differ. Results were not significantly different between auto-generated and self-generated surveys for BD or HC. Limitations This pilot study was conducted for a short time and with a small sample. Conclusions This study demonstrates feasibility of using EMA with a smartphone to gather data on BD symptoms.

Immediate Mood Scaler: Tracking Symptoms of Depression and Anxiety Using a Novel Mobile Mood Scale

“…The results of this study support similar findings in the recent literature that have shown the significance of remote, in-the-moment (and real-world) approaches to the evaluation of mood state [12,13,17,48]. The feasibility of this approach is supported by the growing usage of mobile devices by patients with mood disorders [9,10,49] and studies that have shown good compliance with mobile monitoring strategies [47,49,79].…”

Daily longitudinal self-monitoring of mood variability in bipolar disorder and borderline personality disorder

“…Monitoring of mood states is often used in the assessment and management of mood disorders. Traditionally, self-monitoring of mood using Patient Reported Outcome Measures (PROMs) was achieved using paper-based and more recently computer-based questionnaires ( Bopp, 2010 , Malik, 2012 ) but in recent years the ubiquity of mobile networks and the rapid evolution of smartphone technology have led to an increasing focus on the use of mobile applications ( Faurholt-Jepsen et al, 2015 , Schärer et al, 2015 , Schwartz et al, 2016 ). This approach has advantages because mood states can be reported in real time without the inconvenience of logging to a computer and thus self-ratings should be less prone to recall bias ( Proudfoot et al, 2010 ).…”

“…We present results from a relatively large number of participants in the context of longitudinal mood monitoring, tracking their mood variation for multiple months , as opposed to other studies that were confined to a few weeks (e.g. Holmes et al, 2016 , Schwartz et al, 2016 ), and using multiple questionnaires (most previous studies focus on a single questionnaire to investigate symptom variation, e.g. depression, for example Bonsall et al, 2012 , Moore et al, 2014 , Bonsall et al, 2015 , Holmes et al, 2016 ).…”

Variability in phase and amplitude of diurnal rhythms is related to variation of mood in bipolar and borderline personality disorder

“…Increased mood variability in euthymic BD patients compared to healthy controls has been shown through retrospective questionnaires, indicating BD is not restricted to episodes of depression and mania but is also associated with mood instability between episodes 6 . More recent studies have used more continuous daily monitoring of mood in BD with smartphones, again finding increased mood variability in inter-episodic periods 7 , 8 . Patients with BPD are not as widely studied, however similar affective lability has been described in BPD 9 .…”