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Validating the German version of the Personality Disorder Severity-ICD-11 Scale using nominal response models.

Johannes ZimmermannCarl F FalkLeon P WendtCarsten SpitzerFelix H FischerBo BachMartin SellbomSascha Müller
Published in: Psychological assessment (2022)
The International Classification of Diseases (ICD-11) features a new classification of personality disorders (PD), focusing on the severity of PD. Although there are numerous self-report measures that assess PD severity, to date only the Personality Disorder Severity- ICD-11 ( PDS -ICD-11 ) is based on ICD-11 's operationalization of PD. Initial results indicated that the PDS- ICD-11 measures a unidimensional construct, but the assumptions made for scoring its bipolar items had not been fully examined. The aim of this study is to fill this gap and investigate the latent structure of the German version of the PDS- ICD-11 using nominal response models (NRM), which allow for testing these assumptions. We applied the PDS- ICD-11 together with other self-report measures in a sample of 1,228 individuals from the general population. NRM indicated an acceptable fit of a unidimensional model, with only few deviations from the theoretically imposed scoring scheme. The total score was sufficiently reliable and correlated meaningfully with other self-report measures of PD severity. Regarding Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and ICD-11 maladaptive trait domains, the total score was found to be most strongly associated with negative affectivity, whereas associations with antagonism and anankastia were small or nonsignificant. We conclude that the proposed scoring scheme of the PDS- ICD-11 items is acceptable, and the examined psychometric properties of the German version largely correspond to the results from the English-language development study. The total score, however, depicts more internalizing than externalizing personality pathology. Future studies should investigate the diagnostic efficiency of the PDS -ICD-11 scale using multiple methods and time points as well as clinical and forensic samples. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Keyphrases
  • psychometric properties
  • machine learning
  • emergency department
  • gene expression
  • dna methylation