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Measuring maladaptive personality traits with the Structured Clinical Interview for DSM‐IV Axis II Screening Questionnaire using a common metrics approach

The classification of personality disorder (PD) is undergoing a paradigm shift in which categorically defined specific PDs are being replaced by dimensionally defined maladaptive trait domains. To bridge the classificatory approaches, this study attempts to use items from the categorical PD model in...

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Bibliographic Details
Published in:Personality and mental health 2024-08, Vol.18 (3), p.191-203
Main Authors: Krasniqi, Cameri, Müller, Steffen, Wendt, Leon P., Fischer, Felix H., Spitzer, Carsten, Zimmermann, Johannes
Format: Article
Language:English
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Summary:The classification of personality disorder (PD) is undergoing a paradigm shift in which categorically defined specific PDs are being replaced by dimensionally defined maladaptive trait domains. To bridge the classificatory approaches, this study attempts to use items from the categorical PD model in DSM‐IV to measure the maladaptive trait domains described in DSM‐5 Section III/ICD‐11. A general population sample comprising 1228 participants completed the Screening Questionnaire of the Structured Clinical Interview for DSM‐IV Axis II (SCID‐II‐SQ), the Personality Inventory for DSM‐5 (PID‐5), and the anankastia scale of the Personality Inventory for ICD‐11 (PiCD). Using item response theory models and a psychometric linking technique, SCID‐II‐SQ items were evaluated for their contribution to measuring maladaptive trait domains. The best discriminating items were then selected to derive proxy scales. We found that convergent validity of these proxy scales was in a similar range to that of other self‐report measures for PD, except for the proxy scale for PiCD anankastia. However, only the proxy scale for negative affectivity showed acceptable reliability that would allow its application in research settings. Future studies should seek to establish a common metric between specific PDs and maladaptive trait domains using self‐report measures with higher specificity or semi‐structured interviews.
ISSN:1932-8621
1932-863X
1932-863X
DOI:10.1002/pmh.1607