Psychometric evaluation of the DSM-5-TR-Level 1 Cross-Cutting Symptom Measure: transdiagnostic factor analysis in a real-world psychiatric outpatient sample

Background: Dimensional approaches to psychiatric assessment are increasingly used to complement categorical diagnoses. The DSM-TR Level 1 Cross-Cutting Symptom Measure (DSM-XC) assesses symptoms across psychopathology domains, but its latent structure remains unexplored in large, real-world psychiatric outpatient populations, limiting guidance on how clinicians interpret and apply results. Methods: = 3,101) using the Osmind platform who completed the DSM-XC as part of measurement-based care (the systematic collection of patient-reported outcomes to guide clinical decision-making). Exploratory factor analysis was conducted in half of the sample, and confirmatory factor analysis tested two models in the remaining half: a 6-factor general model, a 5-factor bifactor model with a general psychopathology factor. A third confirmatory model based on Caspi et al's framework was also evaluated using the full sample. Results: The 6-factor general model identified domains of 'Mood', 'Anxiety', 'Depression', 'Psychosis', 'Substance Use', and 'Distress and Disconnection'. The 5-factor bifactor model demonstrated a strong general psychopathology factor. The Caspi-inspired model showed acceptable fit but weaker support for the specific dimensions. These results underscore the DSM-XC's capacity to capture both shared and domain-specific dimensions of psychopathology, highlighting its relevance for dimensional assessment. Conclusion: By clarifying its latent structure, this study identified clinically meaningful symptom dimensions which helps facilitate interpretation and application of the DSM-XC in the real-world. As dimensional and measurement-based approaches continue to expand in psychiatry, clearer understanding of tools such as the DSM-XC may support their integration into clinical practice and future research.