PubMed · 5217616
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S Kashiwagi. 1965. Geometric vector orthogonal rotation method in multiple-factor analysis.. https://doi.org/10.1007/bf02289541
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OBJECTIVE: The DSM-IV classification of personality disorders has not proven satisfying to either researchers or clinicians. Incremental changes to categories and criteria using structured interviews may no longer be useful in attempting to refine axis II. An alternative approach that quantifies clinical observation may prove useful in developing a clinically rich, useful, empirically grounded classification of personality pathology. METHOD: A total of 496 experienced psychiatrists and psychologists used the Shedler-Westen Assessment Procedure-200 (SWAP-200) to describe current patients diagnosed with axis II personality disorders. The SWAP-200 is an assessment tool that allows clinicians to provide detailed, clinically rich descriptions of patients in a systematic and quantifiable form. A statistical technique, Q-analysis, was used to identify naturally occurring groupings of patients with personality disorders, based on shared psychological features. The resulting groupings represent an empirically derived personality disorder taxonomy. RESULTS: The analysis found 11 naturally occurring diagnostic categories, some of which resembled current axis II categories and some of which did not. The findings suggest that axis II falls short in its attempt to "carve nature at the joints": In some cases it puts patients who are psychologically dissimilar in the same diagnostic category, and in others it makes diagnostic distinctions where none likely exist. It also fails to recognize a large category of patients best characterized as having a dysphoric personality constellation. The empirically derived classification system appears to be more faithful to the clinical data and to avoid many problems inherent in the current axis II taxonomy. CONCLUSIONS: The approach presented here may be helpful in refining the existing taxonomy of personality disorders and moving toward a system of classification that lies on a firmer clinical and empirical foundation. In addition, it can help to bridge the gap that often exists between research and clinical approaches to personality pathology.
Dimensions of hearing aid outcome are explored in this paper. First, a variety of hearing aid outcome measures is defined including objective and subjective performance, objective and subjective benefit, satisfaction, and use. Following the definition of these terms, factor analysis is described as a statistical tool that can be of assistance in establishing the number and nature of the relevant dimensions of hearing aid outcome. Next, the results from three recent studies that included a variety of measures of hearing aid outcome are examined and factor analysis is applied to the data from each study. This examination leads to the conclusion that hearing aid outcome is a multidimensional construct, rather than unidimensional. The most complete description of hearing aid outcome will be obtained when including at least one measure of aided speech recognition performance, one or more measures of objective benefit in speech recognition, one or two subjective measures of sound quality or listening effort, and one measure of either subjective benefit, satisfaction, or use.
BACKGROUND: Previous factor analytic studies of patients with schizophrenia have consistently demonstrated the presence of 3 psychopathological domains labeled positive, negative, and disorganized. This study examined whether similar domains can be seen in disorders other than schizophrenia, and the degree to which such domains are independent of diagnostic categorization. METHODS: Data from the Diagnostic and Statistical manual of Mental Disorders, Fourth Edition (DSM-IV) field trial involving 221 patients with schizophrenia and 189 patients with nonschizophrenia diagnoses were factor analyzed to study the nature of psychopathological domains in the 2 groups. Differential associations between each domain and selected clinical variables were assessed. RESULTS: Factor analysis yielded a similar 3-factor model of positive, negative, and disorganization domains for patients with schizophrenia as well as other diagnoses. Differential associations found between individual domains and clinical variables (premorbid functioning and negative domain; absence of remissions and disorganization domain) were similar in both schizophrenia and nonschizophrenia groups. CONCLUSIONS: The 3 psychopathological domains previously described in schizophrenia are not specific for that diagnosis. Differential associations found between individual domains and clinical variables were not limited by diagnostic categorization. The results suggest that these domains are not unique to schizophrenia and may each correspond to a discrete pathophysiologic condition.