| Nonlinear Dynamics, Psychology, and Life Sciences, Vol. 14, Iss. 1, Jan, 2010, pp. 15-25 @2010 Society for Chaos Theory in Psychology & Life Sciences Evidence of Reduced Complexity in Self-report Data from Patients with Medically Unexplained Symptoms Abstract: Physical symptoms which cannot be adequately explained by organic
disease are a common problem in all fields of medicine. Reduced complexity,
shown using nonlinear dynamic analysis, has been found to be associated with
a wide range of illnesses. These methods have been applied to short time series
of mood but not to self-rated physical symptoms. We tested the hypothesis that
self-reported medically unexplained physical symptoms display reduced complexity
by measuring the approximate entropy of self-reported emotions and physical
symptoms collected twice daily over 12 weeks and comparing the results with
series-specific surrogate data. We found that approximate entropy (ApEn) was
lower for actual data series than for surrogate data. There was no significant
difference in entropy between different types of symptoms and no significant
correlation between entropy and the diurnal variation of the data series.
Future studies should concentrate on specific symptoms and conditions,
and evaluate the effect of treatment on the entropy of symptom patterns. Keywords: affective disorders, approximate entropy, models, nonlinear dynamics, somatoform disorders |