Mental health diagnostics is undergoing a transformation, with a shift away from traditional categorical systems like the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), and the International Classification of Diseases, 11th Revision (ICD-11), and toward innovative frameworks like the Hierarchical Taxonomy of Psychopathology (HiTOP) and the Research Domain Criteria (RDoC). These emerging models prioritize dimensional and biobehavioral approaches in order to overcome limitations such as oversimplification, comorbidity and heterogeneity. This editorial explores the challenges of implementing these paradigms, such as the need for empirical validation, interdisciplinary collaboration and clinician training. It highlights the importance of advanced tools, biomarkers and technological integration to improve precision in diagnosis and treatment. Future research directions include creating reliable dimensional assessment methods, conducting longitudinal studies and fostering interdisciplinary networks. By bridging traditional and emerging frameworks, the field can progress toward personalized, biologically informed mental health treatment. This transition necessitates collaboration among researchers, clinicians and policymakers to improve diagnostic accuracy and treatment outcomes for those affected by mental health disorders.
Keywords: Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5); Hierarchical Taxonomy of Psychopathology (HiTOP); International Classification of Diseases 11th Revision (ICD-11); Research Domain Criteria (RDoC); precision medicine.