Determining essential dimensions for the clinical approximation of personality disorder severity - a multimethod study Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.31234/osf.io/rg5pf_v2
Background: Decades of research on the dimensional nature of personality disorder (PD) have led to the replacement of categorical PD diagnoses by a dimensional assessment of PD severity (PDS) in ICD-11, which essentially corresponds to personality functioning in the alternative DSM-5 model for PDs. Besides advancing the focus in the diagnosis of PD on impairments in self and interpersonal functioning, this shift also urges clinicians and researchers worldwide to get familiar with new diagnostic approaches. Aims: This study investigated which PDS dimensions among different assessment methods and conceptualizations have the most predictive value for overall PDS. Methods: Using semi-structured interviews and self-reports of personality functioning, personality organization, and personality structure in clinical samples of different settings in Switzerland and Germany (n = 534), we calculated a latent general factor for PDS (g-PDS) by applying a correlated trait correlated method – 1 model. Results: Our results showed that four interview-assessed PDS dimensions - defense mechanisms, desire and capacity for closeness, sense of self, and comprehension and appreciation of others’ experiences and motivations account for 91.1% of variance of g-PDS, with a combination of either two of these four dimensions already explaining between 81.7% and 88.9%. Regarding self-reports, the dimensions depth and duration of connections, self-perception, object perception, and attachment capacity to internal objects predicted 61.3% of the variance of a latent interview-based score, with all investigated self-reported dimensions together adding up to 65.2% variance explanation. Conclusions: Taken together, our data suggest that focusing on specific dimensions, such as intimacy and identity, in time-limited settings might be viable in determining PDS efficiently.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.31234/osf.io/rg5pf_v2
- https://osf.io/rg5pf_v2/download
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- gold
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- OpenAlex ID
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https://openalex.org/W4409009759Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.31234/osf.io/rg5pf_v2Digital Object Identifier
- Title
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Determining essential dimensions for the clinical approximation of personality disorder severity - a multimethod studyWork title
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preprintOpenAlex work type
- Language
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enPrimary language
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2025Year of publication
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2025-03-31Full publication date if available
- Authors
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André Kerber, Caroline Macina, Ludwig Ohse, Leonie Kampe, O. Busch, Michael Rentrop, Christine Knaevelsrud, Johannes Wrege, Susanne Hörz‐SagstetterList of authors in order
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https://doi.org/10.31234/osf.io/rg5pf_v2Publisher landing page
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https://osf.io/rg5pf_v2/downloadDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://osf.io/rg5pf_v2/downloadDirect OA link when available
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Psychology, Personality, Clinical psychology, Social psychologyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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