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The Use of Clustering Techniques for the Classification of Psychiatric Patients

Published online by Cambridge University Press:  29 January 2018

John S. Strauss
Affiliation:
Psychiatric Assessment Section, National Institute of Mental Health, Bethesda, Maryland, and Clinical Psychiatry Research Programs, Rochester University School of Medicine, 260 Crittenden Boulevard, Rochester, New York 14642
John J. Bartko
Affiliation:
Mathematical Statistician, Biometry Branch, National Institute of Mental Health, Bethesda, Maryland
William T. Carpenter Jr.
Affiliation:
Psychiatric Assessment Section, National Institute of Mental Health, Bethesda, Maryland

Extract

There has been a reawakening of interest in the classification of psychiatric patients. Clinicians and researchers alike have realized that it is impossible to evaluate methods of treatment, determine aetiology, or measure the course of illness of psychiatric disorders without adequate methods for diagnosis. On the other hand, it has been shown that conventional clinical methods for making psychiatric diagnoses are of distressingly low reliability, except for the broadest categories, and have only marginal relationships to such criteria of validity as common aetiology, common response to treatment, and common prognosis (Baldessarini, 1970; Beck et al., 1962; Jenkins, 1966). Klein (1967) has shown that the usual clinical diagnoses, because of low validity, can actually obscure important relationships between types of psychopathology and such crucial variables as response to treatment.

Type
Research Article
Copyright
Copyright © Royal College of Psychiatrists, 1973 

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References

Baldessarini, R. J. (1970). ‘Frequency of diagnoses of schizophrenia versus affective disorders from 1944 to 1968.American Journal of Psychiatry, 127, 759–63.Google Scholar
Bartko, J., Strauss, J., and Carpenter, W. T. (1971). ‘An evaluation of taxometric techniques for psychiatric data.Classification Society Bulletin, 2, 128.Google Scholar
Beck, A. T., Ward, C H., Mendelson, M., Mock, J. E., and Erbauoh, J. K. (1962). ‘Reliability of psychiatric diagnoses: 2. A study of consistency of clinical judgements and ratings.American Journal of Psychiatry, 119, 351–7.Google Scholar
Fleiss, J. Unpublished data.Google Scholar
Fleiss, J. and Zubin, J. (1969). ‘On the methods and theory of clustering.Multivariate Behavioral Research, 4, 235–50.CrossRefGoogle ScholarPubMed
Grinker, R. R., Werble, B., and Bryce, R. E. (1968). The Borderline Syndrome. New York: Basic Books.Google Scholar
Jenkins, R. L. (1966). ‘Psychiatric syndromes in children and their relation to family background.American Journal of Orthopsychiatry, 36, 450–7.Google Scholar
Katz, M., Cole, J. O., and Lowery, H. A. (1969). ‘Studies of the diagnostic process.American Journal of Psychiatry, 125, 937–47.CrossRefGoogle Scholar
Klein, D. (1967). ‘Importance of psychiatric diagnosis in prediction of clinical drug effects.Archives of General Psychiatry, 16, 118–26.CrossRefGoogle ScholarPubMed
Lorr, M. (1966). Explorations in Typing Psychotics. Oxford: Pergamon Press.Google Scholar
Lorr, M. and Radhakrishnan, B. K. (1967). ‘A comparison of two methods of cluster analysisEducational and Psychological Measurement, 27, 4753.CrossRefGoogle Scholar
Marriot, F. C. (1971). ‘Practical problems in a method of cluster analysis.Biometrics, 27, 501–14.Google Scholar
McKeon, J. J. (1967). Hierarchical Cluster Analysis. George Washington University Biometrics Laboratory.Google Scholar
Paykel, E. S. (1971). ‘Classification of depressed patients: A cluster analysis derived grouping.British Journal of Psychiatry, 118, 275–88.CrossRefGoogle ScholarPubMed
Pilowski, I., Levine, S., and Bouton, D. M. (1969). ‘The classification of depression by numerical taxonomy.British Journal of Psychiatry, 115, 937–45.Google Scholar
Report of the Collaborating Investigators Vol. 1. International Pilot Study of Schizophrenia. World Health Organization, Geneva (in press).Google Scholar
Rubin, J., and Friedman, H. P. (1967). A Cluster Analysis and Taxonomy System for Grouping and Classifying Data. New York: I.B.M. New York Scientific Center.Google Scholar
Sokal, R. R., and Sneath, P. H. A. (1963). Principles of Numerical Taxonomy. San Francisco: W. H. Freeman.Google Scholar
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