Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series

Moods in Clinical Depression Are More Unstable than Severe Normal Sadness

OBJECTIVE

Current descriptions in psychiatry and psychology suggest that depressed mood in clinical depression is similar to mild sadness experienced in everyday life, but more intense and persistent. We evaluated this concept using measures of average mood and mood instability (MI).

METHOD

We prospectively measured low and high moods using separate visual analog scales twice a day for seven consecutive days in 137 participants from four published studies. Participants were divided into a non-depressed group with a Beck Depression Inventory score of ≤10 (n = 59) and a depressed group with a Beck Depression Inventory score of ≥18 (n = 78). MI was determined by the mean square successive difference statistic.

RESULTS

Mean low and high moods were not correlated in the non-depressed group but were strongly positively correlated in the depressed group. This difference between correlations was significant. Low MI and high MI were weakly positively correlated in the non-depressed group and strongly positively correlated in the depressed group. This difference in correlations was also significant.

CONCLUSION

The results show that low and high moods, and low and high MI, are highly correlated in people with depression compared with those who are not depressed. Current psychiatric practice does not assess or treat MI or brief high mood episodes in patients with depression. New models of mood that also focus on MI will need to be developed to address the pattern of mood disturbance in people with depression.

An investigation of mental imagery in bipolar disorder: Exploring "the mind's eye"

OBJECTIVES

Mental imagery abnormalities occur across psychopathologies and are hypothesized to drive emotional difficulties in bipolar disorder (BD). A comprehensive assessment of mental imagery in BD is lacking. We aimed to test whether (i) mental imagery abnormalities (abnormalities in cognitive stages and subjective domains) occur in BD relative to non-clinical controls; and (ii) to determine the specificity of any abnormalities in BD relative to depression and anxiety disorders.

METHODS

Participants included 54 subjects in the BD group (depressed/euthymic; n=27 in each subgroup), subjects with unipolar depression (n=26), subjects with anxiety disorders (n=25), and non-clinical controls (n=27) matched for age, gender, ethnicity, education, and premorbid IQ. Experimental tasks assessed cognitive (non-emotional) measures of mental imagery (cognitive stages). Questionnaires, experimental tasks, and a phenomenological interview assessed subjective domains including spontaneous imagery use, interpretation bias, and emotional mental imagery.

RESULTS

(i) Compared to non-clinical controls, the BD combined group reported a greater impact of intrusive prospective imagery in daily life, more vivid and "real" negative images (prospective imagery task), and higher self-involvement (picture-word task). The BD combined group showed no clear abnormalities in cognitive stages of mental imagery. (ii) When depressed individuals with BD were compared to the depressed or anxious clinical control groups, no significant differences remained-across all groups, imagery differences were associated with affective lability and anxiety.

CONCLUSIONS

Compared to non-clinical controls, BD is characterized by abnormalities in aspects of emotional mental imagery within the context of otherwise normal cognitive aspects. When matched for depression and anxiety, these abnormalities are not specific to BD-rather, imagery may reflect a transdiagnostic marker of emotional psychopathology.

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

BACKGROUND

Traditionally, assessment of psychiatric symptoms has been relying on their retrospective report to a trained interviewer. The emergence of smartphones facilitates passive sensor-based monitoring and active real-time monitoring through time-stamped prompts; however there are few validated self-report measures designed for this purpose.

METHODS

We introduce a novel, compact questionnaire, Mood Zoom (MZ), embedded in a customised smart-phone application. MZ asks participants to rate anxiety, elation, sadness, anger, irritability and energy on a 7-point Likert scale. For comparison, we used four standard clinical questionnaires administered to participants weekly to quantify mania (ASRM), depression (QIDS), anxiety (GAD-7), and quality of life (EQ-5D). We monitored 48 Bipolar Disorder (BD), 31 Borderline Personality Disorders (BPD) and 51 Healthy control (HC) participants to study longitudinal (median±iqr: 313±194 days) variation and differences of mood traits by exploring the data using diverse time-series tools.

RESULTS

MZ correlated well (|R|>0.5,p<0.0001) with QIDS, GAD-7, and EQ-5D. We found statistically strong (|R|>0.3,p<0.0001) differences in variability in all questionnaires for the three cohorts. Compared to HC, BD and BPD participants exhibit different trends and variability, and on average had higher self-reported scores in mania, depression, and anxiety, and lower quality of life. In particular, analysis of MZ variability can differentiate BD and BPD which was not hitherto possible using the weekly questionnaires.

LIMITATIONS

All reported scores rely on self-assessment; there is a lack of ongoing clinical assessment by experts to validate the findings.

CONCLUSIONS

MZ could be used for efficient, long-term, effective daily monitoring of mood instability in clinical psychiatric practice.

Mental Imagery-Based Training to Modify Mood and Cognitive Bias in Adolescents: Effects of Valence and Perspective

Mental imagery has a powerful impact on emotion and cognitive processing in adults, and is implicated in emotional disorders. Research suggests the perspective adopted in mental imagery modulates its emotional impact. However, little is known about the impact of mental imagery in adolescence, despite adolescence being the key time for the onset of emotional dysfunction. We administered computerised positive versus mixed valence picture-word mental imagery training to male adolescent participants (N = 60, aged 11–16 years) across separate field and observer perspective sessions. Positive mood increased more following positive than mixed imagery; pleasantness ratings of ambiguous pictures increased following positive versus mixed imagery generated from field but not observer perspective; negative interpretation bias on a novel scrambled sentences task was smaller following positive than mixed imagery particularly when imagery was generated from field perspective. These findings suggest positive mental imagery generation alters mood and cognition in male adolescents, with the latter moderated by imagery perspective. Identifying key components of such training, such as imagery perspective, extends understanding of the relationship between mental imagery, mood, and cognition in adolescence.