On the meaning and measurement of affective instability: clues from chaos theory

Background: “Affective instability” describes affective shifts occurring over hours to days that are associated with clinically significant impairment or distress. Since patients with this condition are clinically “chaotic,” we undertook to study affective instability relative to normal affective variability using the tools of chaos theory. Methods: Patients and controls generated time series data over 90 days using a visual analog mood scale to capture daily affective means and extremes. The series were analyzed using the Mean Squared Successive Difference (MSSD), Power Spectral Density (PSD), and Fractal Dimension (FD). Results: Patients demonstrated substantially more variability than controls on the MSSD, but less complexity as measured by the FD. The PSD revealed that power varied with frequency (f) in a 1fα relationship, wherein the α for patients was double that for controls. Conclusions: Despite the “chaotic” clinical presentation of affective instability patients, affective instability itself was found to be less complex from a chaos-theoretic perspective than normal affective variability. Of particular interest is the α ratio of order 2 between patients and controls seen in both our study and a similar but much longer study of mood in rapid-cycling bipolar disorder; an observation suggesting that pathological affect may be distinguishable from normal affective variability by a scale-invariant parameter.