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Comparison of alternative models for personality disorders
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Background. The categorical classification system for personality disorder (PD) has been frequently criticized and several alternative dimensional models have been proposed. Method. Antecedent, concurrent and predictive markers of construct validity were examined for three models of PDs: the Five-Factor Model (FFM), the Schedule for Nonadaptive and Adaptive Personality (SNAP) model and the DSM-IV in the Collaborative Study of Personality Disorders (CLPS) sample. Results. All models showed substantial validity across a variety of marker variables over time. Dimensional models (including dimensionalized DSM-IV) consistently outperformed the conventional categorical diagnosis in predicting external variables, such as subsequent suicidal gestures and hospitalizations. FFM facets failed to improve upon the validity of higher-order factors upon cross-validation. Data demonstrated the importance of both stable trait and dynamic psychopathological influences in predicting external criteria over time. Conclusions. The results support a dimensional representation of PDs that assesses both stable traits and dynamic processes.
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“Dimensional representations of PDs have been shown to outperform categorical diagnoses in predicting external variables [28, 33]”
From Personality disorders are important risk factors for disability pensioning (2014) · cites this paper as [33]
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Metadata
- Authors
- MOREY, L. C., HOPWOOD, C. J., GUNDERSON, J. G., SKODOL, A. E., SHEA, M. T., YEN, S., STOUT, R. L., ZANARINI, M. C., GRILO, C. M., SANISLOW, C. A., & McGLASHAN, T. H.
- Affiliations
- Texas A&M University (US)
- Harvard University (US)
- New York State Psychiatric Institute (US)
- Brown University (US)
- Yale University (US)
- ORCID
- Venue
- Psychological Medicine
- Publisher
- Cambridge University Press (CUP)
- Published
- 2006-11-23
- Volume
- 37
- Issue
- 7
- Pages
- 983-994
- ISSN
- 0033-2917 (ISSN-L)
- 1469-8978
- OpenAlex
- W2136652875
- Cited by
- 204
- References
- 47
- Citations by year
- 2025: 2 · 2024: 5 · 2022: 3 · 2021: 8 · 2020: 26 · 2019: 8 · 2018: 11 · 2017: 8 · 2016: 6 · 2015: 10 · 2014: 13 · 2013: 16 · 2012: 23
- FWCI
- 8.47
- Type
- journal article
- Language
- en
- Open access
- green
- works.bepress.com
- Locations
- Psychological Medicine (publishedVersion)
- PubMed (publishedVersion)
- Wesleyan University Digital Collections (Wesleyan University) (submittedVersion)
- Wesleyan University Digital Collections (Wesleyan University) (submittedVersion, public-domain)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- WESLEYAN
- Funders
- National Institute of Mental Health (MH50850, MH01654, MH 50840, MH-50837, MH 50839, MH 50838, K23MH073708, R01MH050838, R01MH050837, R01MH050850, K23MH069904, K05MH001654)
- Topics
- Social Sciences › Psychology › Clinical Psychology › Personality Disorders and Psychopathology
- Social Sciences › Psychology › Clinical Psychology › Personality Traits and Psychology
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- personality disorders, dimensional models, categorical classification, Big Five personality traits, construct validity, suicidal gestures, hospitalization, trait stability, psychopathology
- MeSH terms
- Female, Humans, Male, Models, Psychological, Personality Disorders, Predictive Value of Tests, Reproducibility of Results, Diagnostic and Statistical Manual of Mental Disorders
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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