An evaluation of evidence on depressive classification and some alternative suggestions from physiology

The prevalence of symptoms of depression in an Australian General Population

The prevalence of depressive symptoms was estimated in a random sample of an Australian general population by administration of the Zung Self-Rating Depression Scale (S.D.S.). Rates, calculated according to criteria derived from a previously studied clinical sample, were somehwat higher in this population than had been reported in similar studies elsewhere. It was reasoned that this finding related to the relative laxity of criteria employed in the present study. Socio-demographic influences on the reporting of depressive symptoms were evident, the most prominent of these being the sex of the subject. It was suggested that these influences may underlie socio-demographic differences in rates of recognized depressive states occurring within clinical samples.

The effect of placebo and tricyclic antidepressants on cortical evoked potentials in depressed patients

Cortical evoked potentials in depressives were recorded in order to study stimulus intensity control in this group, and also to study the effect of treatment. In a sample of 33 psychiatric patients, the amplitudes of visual and auditory evoked potentials were found to be significantly greater during depression, than at recovery. The changes which appeared to be due to recovery were found not only in patients treated with tricyclic antidepressants (n = 22), but in those who had recovered following treatment with placebo (n = 11). The changes were most evident in the auditory system. In addition, no diagnostic predictors differentiated depressed patients who subsequently recovered on placebo from those who did not. It is concluded that: (i) cortical evoked potentials may change in amplitude with emotional state; (ii) placebo may have physiological consequences usually attributed to drugs alone.

A note on cluster analysis and depression: disparities in results produced by the application of different clustering methods

Cluster analysis is the most logically suited method for establishing psychiatric classifications. Different mathematical methods of clustering do, however, produce disparate results when applied to the same set of data. This study attempted to quantify the extent of such disparities, and found them to be marked. It was concluded that until cluster analysis has undergone further mathematical and statistical development, it should be used with caution.