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.