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[Undetected psychiatric disorders in primary health care. A need for psychotherapy]. | LitMetric

[Undetected psychiatric disorders in primary health care. A need for psychotherapy].

Cesk Psychiatr

Psychiatrické centrum Praha.

Published: November 1992

In joint collaboration of both Institutes the Leipzig-south survey of need of psychotherapy was replicated in a representative sample (N = 1708) of patients waiting one year to be examined and/or treated in out-patient departments of general practitioners and other specialists (gynaecology, orthopaedic surgery and internal medicine) in one district of Prague City (N = 1461) and a rural district in Kromĕríz (N = 247). In a preceding pilot study (N = 207) the zero hypothesis of unspecificity of the Leipzig methodology was rejected. Roughly corresponding proportions of three classes of the need of psychotherapy (defined by means of cluster analysis) were found in the geographic areas, compared in waiting rooms of all out-patient departments except the evidently lower need of psychotherapy found in the rural GP's waiting rooms. Highest rates were those in waiting rooms of gynaecologists and orthopedic surgeons. The GHQ-60 and the Leipzig classifications were compared in both CS samples: 35.1% of male and 30.6% of female respondents did not need psychotherapy and very probably were not psychiatric cases. In 32.5% of males and 36.9% of females the need of generally oriented psychotherapy was combined with suspected hidden psychopathology. 3.8% male and 6.9% female respondents were very probably hidden psychiatric cases and in need of specifically oriented psychotherapy. Predictors of both measures of hidden psychopathology used were obtained from descriptions of personality, demographic background and health care need and attitudes case history by means of multivariate statistical techniques. 12 of 23 descriptors explained 48.8% variance of the global GHQ-60 score. An agreement of 62.9% of the need of psychotherapy back classification was attained by discriminant function using 11 of 23 descriptors. In both procedures the factor analysis derived dimensions of personality were found to be the most potent class of predictors.

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