DSM Disorders Disappear in Statistical Clustering of Psychiatric Symptoms Author: Awais Aftab Date: March 9, 2024 Source: Psychiatry at the Margins --- Overview A recent study by Miri Forbes et al. published in Clinical Psychological Science profoundly challenges traditional DSM categorizations by statistically analyzing individual psychiatric symptoms. Using a large, diverse sample (14.8K participants) and symptom-level questionnaires based on DSM-5 items asked in random order, the study applies rigorous clustering methods (iclust and Ward’s hierarchical clustering) to identify natural groupings ("syndromes") and higher-order structures in psychopathology. Key Findings Symptom Clusters vs. DSM Disorders: Instead of reproducing DSM diagnoses as cohesive syndromes, the analysis revealed 139 statistically homogeneous clusters and 81 solo symptoms, organized into 8 spectra: Externalizing Harmful Substance Use Mania/Low Detachment Thought Disorder Somatoform Eating Pathology Internalizing Neurodevelopmental and Cognitive Difficulties The study emphasized a general psychopathology factor dubbed the “Big Everything”, paralleling the known "p-factor". Traditional DSM disorders, like Major Depressive Disorder (MDD), Generalized Anxiety Disorder (GAD), and PTSD, do not appear as discrete syndromes. Instead, their symptom heterogeneity causes them to: Break down into smaller, more homogeneous symptom clusters. Merge into broader subfactors and spectra. Detailed Insights on Depression MDD symptoms (e.g., SIGECAPS symptoms, PHQ-9 items) dissolve into multiple clusters such as: Depressed mood and anhedonia Self-derogation and suicidality Guilt/shame proneness Emotional lability Dysregulated sleep (morning depression) Cognitive difficulties and psychomotor impairments Patients with MDD diagnoses vary widely in symptom presentations, reflecting diverse combinations of these clusters rather than a single homogenous disorder. This variability means: MDD is an index of multiple varying syndrome combinations, not a fixed entity. Each instance of MDD represents an overlapping but different symptom subset. This heterogeneity contributes to low diagnostic reliability in official DSM field trials. Implications The traditional DSM framework may reify diagnostic criteria as disorders themselves, but this study supports viewing DSM diagnoses as indexes of symptom subsets, not singular coherent entities. The study aligns partly with the Hierarchical Taxonomy of Psychopathology (HiTOP) model, but reveals areas where revisions might be needed based on empirical data. Clinical understanding and diagnostic categories may need to shift toward recognizing these symptom clusters and spectra rather than relying on strict DSM categories. Methodological Notes and Limitations Study relied entirely on self-reported symptoms without clinician observations. Symptoms were assessed over a uniform 12-month timeframe, potentially conflating symptom patterns appearing at different timescales. Contextual factors (e.g., cause of insomnia) were not distinguished. Future research should incorporate multi-method, multi-informant approaches and diverse samples to verify and extend these findings. Expert Commentary Historical reviews indicate DSM criteria emphasize a narrowed symptom scope, omitting several cognitive, physical, and psychomotor features important in classic depression descriptions. The study authors and commentators highlight a problematic trend of DSM reification, calling for an approach acknowledging the complexity and heterogeneity of psychiatric conditions. Theoretical perspectives like Borsboom's network theory argue no centralized disease mechanisms exist for mental disorders; instead, disorders emerge from dynamic symptom interactions and context. Summary