Abstract
Treatment innovation for bipolar disorder has been hampered by a lack of techniques to capture a hallmark symptom: ongoing mood instability. Mood swings persist during remission from acute mood episodes and impair daily functioning. The last significant treatment advance remains Lithium (in the 1970s), which aids only the minority of patients. There is no accepted way to establish proof of concept for a new mood-stabilizing treatment. We suggest that combining insights from mood measurement with applied mathematics may provide a step change: repeated daily mood measurement (depression) over a short time frame (1 month) can create individual bipolar mood instability profiles. A time-series approach allows comparison of mood instability pre- and post-treatment. We test a new imagery-focused cognitive therapy treatment approach (MAPP; Mood Action Psychology Programme) targeting a driver of mood instability, and apply these measurement methods in a non-concurrent multiple baseline design case series of 14 patients with bipolar disorder. Weekly mood monitoring and treatment target data improved for the whole sample combined. Time-series analyses of daily mood data, sampled remotely (mobile phone/Internet) for 28 days pre- and post-treatment, demonstrated improvements in individuals' mood stability for 11 of 14 patients. Thus the findings offer preliminary support for a new imagery-focused treatment approach. They also indicate a step in treatment innovation without the requirement for trials in illness episodes or relapse prevention. Importantly, daily measurement offers a description of mood instability at the individual patient level in a clinically meaningful time frame. This costly, chronic and disabling mental illness demands innovation in both treatment approaches (whether pharmacological or psychological) and measurement tool: this work indicates that daily measurements can be used to detect improvement in individual mood stability for treatment innovation (MAPP).
Highlights
For any disease or disorder, an essential part of treatment development is the ability to measure and assess key clinical outcomes
Anxiety in bipolar disorder should be of particular interest if, as we have proposed, it contributes to depressed mood instability via an ‘emotional amplifier’ effect of anxiety-laden mental imagery.[39]
Subsyndromal mood instability is a key clinical factor impacting on the long-term course of bipolar disorder; it has remained a neglected treatment target, and techniques to measure mood instability are lacking
Summary
For any disease or disorder, an essential part of treatment development is the ability to measure and assess key clinical outcomes. In the absence of appropriate techniques, innovation will be slow. One example of where this problem has hampered treatment development is bipolar disorder. Bringing together ideas from several areas of science—here psychology, psychiatry and applied mathematics—may provide an opportunity for treatment advances. Bipolar disorder (formerly ‘manic depression’) is characterized by repeated episodes of depression with at least one (hypo)manic episode of elevated mood and overactivity.[1] The clinical picture is that depression tends to dominate; depressed mood fluctuations present the focus of this paper. Co-morbid anxiety is common, fuelling depression, and relates to poorer prognosis.[2]
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