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 We analyzed real-world data from patients ( N = 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.