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Diagnostic boundaries, reasoning and depressive disorder, II. Application of a probabilistic model to the OPCS general population survey of psychiatric morbidity in Great Britain

Published online by Cambridge University Press:  01 July 1997

P. G. SURTEES ,
N. W. J. WAINWRIGHT ,
W. R. GILKS ,
T. S. BRUGHA ,
H. MELTZER  and
R. JENKINS
P. G. SURTEES
Affiliation:
MRC Biostatistics Unit, Institute of Public Health, University of Cambridge; the Department of Psychiatry, University of Leicester; the Office for National Statistics and the Department of Health, London
N. W. J. WAINWRIGHT
Affiliation:
MRC Biostatistics Unit, Institute of Public Health, University of Cambridge; the Department of Psychiatry, University of Leicester; the Office for National Statistics and the Department of Health, London
W. R. GILKS
Affiliation:
MRC Biostatistics Unit, Institute of Public Health, University of Cambridge; the Department of Psychiatry, University of Leicester; the Office for National Statistics and the Department of Health, London
T. S. BRUGHA
Affiliation:
MRC Biostatistics Unit, Institute of Public Health, University of Cambridge; the Department of Psychiatry, University of Leicester; the Office for National Statistics and the Department of Health, London
H. MELTZER
Affiliation:
MRC Biostatistics Unit, Institute of Public Health, University of Cambridge; the Department of Psychiatry, University of Leicester; the Office for National Statistics and the Department of Health, London
R. JENKINS
Affiliation:
MRC Biostatistics Unit, Institute of Public Health, University of Cambridge; the Department of Psychiatry, University of Leicester; the Office for National Statistics and the Department of Health, London
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Abstract

Background. Reliable prevalence and risk estimation of psychiatric disorder is a cornerstone to achieving objectives in public health psychiatry. Research strategies have increasingly depended, therefore, upon the progressive evolution and refinement of diagnostic approaches designed to reflect better current knowledge concerning prognosis, course and outcome but essentially the need to improve agreement between users of the various schemes.

Methods. This paper contrasts a conventional with a probabilistic approach to the diagnosis of depression based upon the OPCS United Kingdom National survey of psychiatric morbidity. The probabilistic approach, while designed to mimic current diagnostic practice in relation to the depressive disorders, naturally includes provision for the allocation of respondents on a scale of diagnostic uncertainty according to the severity of their presenting condition.

Results. Findings are reported arising from the application of the probabilistic method to three areas of research interest in public health psychiatry, namely; an evaluation of additivity of event exposure and depressive morbidity, secondly use of the approach for investigating psychosocial models of depressive disorder and thirdly for assessing the agreement between depressive disorder when classified according to competing diagnostic schemes.

Conclusions. The results show application of the probabilistic approach to provide a firm basis for achieving gains in both the stability and precision of risk profile estimation for depressive conditions.

Type
Research Article
Information
Psychological Medicine , Volume 27 , Issue 4 , July 1997 , pp. 847 - 860
Copyright
1997 Cambridge University Press

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