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<p>The establishment of outcome measures that accurately reflect patient functioning is a significant challenge in psychiatry. The present study aims to compare the predictive utility of traditional ICD-10 categorical diagnoses with dimensional psychopathology for functional, social, and cognitive domains. A total of 206 psychiatric patients diagnosed with ICD-10 diagnoses (F10–F69) were assessed using a transdiagnostic battery of self-reports and clinician-administered tools. Exploratory Factor Analysis (EFA) identified four psychopathological dimensions: Dysregulation, Reality Distortion, Detachment and Substance Use. Bayesian ANCOVAs were used to compare these dimensions and categorical diagnoses with respect to their ability to predict outcomes, including the WHODAS-II and ICF-3&#xa0;F-AT. The utilisation of dimensional models has been demonstrated to have superior predictive utility for global functioning when compared to categorical diagnoses. Dysregulation emerged as the strongest predictor of functional impairment across all measures, followed by Detachment, which specifically predicted role execution and empathy. Bayesian analyses showed that neither dimensional nor categorical variables were able to robustly predict (socio-)cognitive performance. These findings highlight the clinical relevance of dimensional assessments, suggesting they warrant further investigation regarding their feasibility and implementation in clinical practice.</p>

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Dimensional psychopathology explains functional disability better than ICD-10 categories

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月31日

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  • Pauline Maria Nagel,
  • Kornelius Winds,
  • Wolfgang Aichhorn,
  • Martin Kronbichler,
  • Lisa Kronbichler

摘要

The establishment of outcome measures that accurately reflect patient functioning is a significant challenge in psychiatry. The present study aims to compare the predictive utility of traditional ICD-10 categorical diagnoses with dimensional psychopathology for functional, social, and cognitive domains. A total of 206 psychiatric patients diagnosed with ICD-10 diagnoses (F10–F69) were assessed using a transdiagnostic battery of self-reports and clinician-administered tools. Exploratory Factor Analysis (EFA) identified four psychopathological dimensions: Dysregulation, Reality Distortion, Detachment and Substance Use. Bayesian ANCOVAs were used to compare these dimensions and categorical diagnoses with respect to their ability to predict outcomes, including the WHODAS-II and ICF-3 F-AT. The utilisation of dimensional models has been demonstrated to have superior predictive utility for global functioning when compared to categorical diagnoses. Dysregulation emerged as the strongest predictor of functional impairment across all measures, followed by Detachment, which specifically predicted role execution and empathy. Bayesian analyses showed that neither dimensional nor categorical variables were able to robustly predict (socio-)cognitive performance. These findings highlight the clinical relevance of dimensional assessments, suggesting they warrant further investigation regarding their feasibility and implementation in clinical practice.