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Recognising Psychiatric Symptoms

Relevance to the Diagnostic Process

Published online by Cambridge University Press:  02 January 2018

G. E. Berrios  and
E. Y. H. Chen
G. E. Berrios*
Affiliation:
Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge CB2 2QQ
E. Y. H. Chen
Affiliation:
University of Hong Kong, formerly Senior Registrar in Psychiatry, Department of Psychiatry, University of Cambridge
*
∗Correspondence
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Abstract

Current overemphasis on nosological diagnosis has led to a neglect of the process of symptom recognition. There is evidence, however, that the perception of the symptom alone does not guarantee symptom ascertainment since a decision-making component is also involved. To achieve the latter, additional information must be provided by the contextual cues implicit in the ongoing diagnostic hypothesis. Current diagnostic systems, however, still assume a two-stage model according to which symptom and disease recognition are independent cognitive events. This paper suggests that this model is inadequate and that descriptive psychopathology is not transparent. It then describes a neural network simulation to make various aspects of the problem explicit. This takes into account the multidimensional and probabilistic aspects of symptom recognition and is, from this point of view, superior to traditional algorithmic models. It also has the capacity to represent the different cognitive styles involved in symptom recognition.

Type
Papers
Information
The British Journal of Psychiatry , Volume 163 , Issue 3 , September 1993 , pp. 308 - 314
Copyright
Copyright © Royal College of Psychiatrists, 1993 

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