Dimensional psychopathology profiling during psychiatric intake: implementation and preliminary clinical target mapping

Introduction

Categorical diagnoses remain essential for clinical communication, but may underrepresent comorbidity, dimensional severity and transdiagnostic treatment targets. The Hierarchical Taxonomy of Psychopathology Self-Report (HiTOP-SR) provides dimensional profiling across spectra and lower-order symptom constructs [1,2]. Its translation into psychiatric intake may support formulation, symptom prioritisation and measurement-based care; clinical integration and symptom-based treatment planning have been proposed, but real-world implementation data remain limited [3,4].

Aims

To describe the implementation of dimensional psychopathology profiling in a multidisciplinary outpatient psychiatric intake workflow and characterise preliminary treatment-relevant target domains emerging from patient self-report profiles.

Methods

We conducted a pragmatic single-site implementation study at MODRA Psiquiatria, an outpatient multidisciplinary mental health group in Argentina. Between 1 February 2025 and 1 February 2026, patients completing intake were invited to complete the Spanish self-report assessment through Qualtrics before or around psychiatric evaluation. Raw exports were processed through a reproducible pipeline. Incomplete, non-clinical/test and earlier likely duplicate submissions were excluded. Prefer-not-to-answer responses coded as 888 were treated as item-level missingness. Validated rows were mapped into a formula-corrected local scoring workflow and patient-specific workbooks were generated. For aggregate target mapping, item-based raw scale scores were computed using the official item mapping and reverse scoring where required. Outcomes were completion, retention after quality control, missingness, successful report generation and number of raw dimensional scale means >=3/4. Statistical analysis used descriptive statistics.

Results

The raw export contained 111 submissions; 71 were complete (64.0%). After quality control, 67 unique clinical cases were retained (94.4% of complete submissions). Mean age was 34.2 years (SD=10.9; median=32; range=20-70), and median completion time was 58.2 minutes (IQR=47.9-100.2). Effective core missingness was low (median=0%; maximum=8.0%). Sixty-seven patient-specific workbooks were generated; validation showed no structural or response-integrity failures, and sampled cross-checking against independent official item-mapping scores showed 456/456 scale comparisons within tolerance. Sixty patients (89.6%) had at least one dimension with raw mean >=3/4; 42 (62.7%) had at least five. Patients showed a median of 7 elevated dimensions (IQR=2-12) and elevations across a median of 3 spectra (IQR=2-3.5). The spectra most often containing an elevated dimension were internalising (79.1%), externalising (70.1%), detachment (61.2%), somatoform (32.8%) and thought disorder (19.4%). The most frequent target domains were distress-dysphoria (52.2% >=3), cognitive problems and non-persistence (40.3% >=3 each), insomnia and perfectionism (35.8% >=3 each), body dissatisfaction (31.3% >=3), hyperdeliberation (29.9% >=3) and somatic preoccupation (19.4% >=3).

Conclusions

Dimensional psychopathology profiling was feasible in this outpatient psychiatric intake workflow and identified multiple potentially treatment-relevant transdiagnostic targets per patient. Profiles highlighted affective distress, cognitive/executive problems, sleep disturbance, perfectionism and body-related symptoms, supporting their relevance for personalised formulation, symptom-target prioritisation and measurement-based follow-up. These data describe a heterogeneous clinical intake population rather than a diagnostically selected sample. The assessment should complement, not replace, clinical judgement; prospective clinician-rated utility remains an important next step.

References

Kotov, R., Krueger, R.F., Watson, D., et al., 2017. The Hierarchical Taxonomy of Psychopathology (HiTOP): a dimensional alternative to traditional nosologies. J. Abnorm. Psychol. 126 (4), 454-477. https://doi.org/10.1037/abn0000258
Conway, C.C., Forbes, M.K., Forbush, K.T., et al., 2019. A Hierarchical Taxonomy of Psychopathology can transform mental health research. Perspect. Psychol. Sci. 14 (3), 419-436. https://doi.org/10.1177/1745691618810696
Ruggero, C.J., Kotov, R., Hopwood, C.J., et al., 2019. Integrating the Hierarchical Taxonomy of Psychopathology (HiTOP) into clinical practice. J. Consult. Clin. Psychol. 87 (12), 1069-1084. https://doi.org/10.1037/ccp0000452
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