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Experts have proposed removing obsessive-compulsive disorder (OCD) from the anxiety disorders section and grouping it with putatively related conditions in DSM-5. The current study uses co-morbidity and familiality data to inform these issues. Case family data from the OCD Collaborative Genetics Study (382 OCD-affected probands and 974 of their first-degree relatives) were compared with control family data from the Johns Hopkins OCD Family Study (73 non-OCD-affected probands and 233 of their first-degree relatives). Anxiety disorders (especially agoraphobia and generalized anxiety disorder), cluster C personality disorders (especially obsessive-compulsive and avoidant), tic disorders, somatoform disorders (hypochondriasis and body dysmorphic disorder), grooming disorders (especially trichotillomania and pathological skin picking) and mood disorders (especially unipolar depressive disorders) were more common in case than control probands; however, the prevalences of eating disorders (anorexia and bulimia nervosa), other impulse-control disorders (pathological gambling, pyromania, kleptomania) and substance dependence (alcohol or drug) did not differ between the groups. The same general pattern was evident in relatives of case versus control probands. Results in relatives did not differ markedly when adjusted for demographic variables and proband diagnosis of the same disorder, though the strength of associations was lower when adjusted for OCD in relatives. Nevertheless, several anxiety, depressive and putative OCD-related conditions remained significantly more common in case than control relatives when adjusting for all of these variables simultaneously. On the basis of co-morbidity and familiality, OCD appears related both to anxiety disorders and to some conditions currently classified in other sections of DSM-IV.

Obsessive–compulsive disorder (OCD) is a heterogeneous mental illness characterized by a variety of clinical manifestations and underlying neurobiological mechanisms. Modern research highlights the importance of identifying subtypes of OCD—separate categories that are characterized by specific phenotypic manifestations. This review provides a systematic integration of multi-level biomarker data (genetic, neuroimaging, neuropsychological) specifically aligned with the most consistently replicated, symptom-based subtypes of OCD. Our findings demonstrate that distinct OCD subtypes are underpinned by divergent neurobiological pathways, involving dysregulation across glutamatergic, serotonergic, dopaminergic, and neurotrophic systems, as well as distinct patterns of brain region engagement. The most extensive body of evidence currently exists for the contamination/cleaning and symmetry/ordering OCD subtypes. In contrast, other subtypes require more rigorous investigation. The findings from this study can provide theoretical prerequisites for future experimental studies involving larger cohorts of OCD patients, who can then be classified based on their detected biomarkers and tested accordingly.

Progress in understanding the underlying neurobiology of obsessive-compulsive disorder (OCD) has stalled in part because of the considerable problem of heterogeneity within this diagnostic category, and homogeneity across other putatively discrete, diagnostic categories. As psychiatry begins to recognize the shortcomings of a purely symptom-based psychiatric nosology, new data-driven approaches have begun to be utilized with the goal of solving these problems: specifically, identifying trans-diagnostic aspects of clinical phenomenology based on their association with neurobiological processes. In this review, we describe key methodological approaches to understanding OCD from this perspective and highlight the candidate traits that have already been identified as a result of these early endeavours. We discuss how important inferences can be made from pre-existing case-control studies as well as showcasing newer methods that rely on large general population datasets to refine and validate psychiatric phenotypes. As exemplars, we take ‘compulsivity’ and ‘anxiety’, putatively trans-diagnostic symptom dimensions that are linked to well-defined neurobiological mechanisms, goal-directed learning and error-related negativity, respectively. We argue that the identification of biologically valid, more homogeneous, dimensions such as these provides renewed optimism for identifying reliable genetic contributions to OCD and other disorders, improving animal models and critically, provides a path towards a future of more targeted psychiatric treatments.

This review examines recent functional neuroimaging research of resting-state regional connectivity between brain regions in anxiety disorders. Studies compiled in the PubMed–National Center for Biotechnology Information database targeting resting-state functional connectivity in anxiety disorders were reviewed. Diagnoses included posttraumatic stress disorder (PTSD), generalized anxiety disorder (GAD), social anxiety disorder (SAD), obsessive–compulsive disorder (OCD), panic disorder (PD), and specific phobia (SP). Alterations to network connectivity were demonstrated in PTSD, GAD, SAD, OCD, and PD in several resting-state investigations. Differences from control subjects were primarily observed in the default mode network within PTSD, SAD, and OCD. Alterations within the salience network were observed primarily in PTSD, GAD, and SAD. Alterations in corticostriatal networks were uniquely observed in OCD. Finally, alterations within somatosensory networks were observed in SAD and PD investigations. Resting-state studies involving SPs as a primary diagnosis (with or without comorbidities) were not generated during the literature search. The emerging use of resting-state paradigms may be an effective method for understanding associations between anxiety disorders. Targeted studies of PD and SPs, meta-analyses of the studies conducted to date, and studies of the impact of specific comorbid presentations, are recommended future research directions.

Many conditions we now call body-focused repetitive behaviors (BFRBs) have been subject to research for several decades, most notably trichotillomania and skin picking. However, the American Psychiatric Association did not combine these conditions into a single category, body-focused repetitive behavior disorders (BFRBDs), until the fifth edition of the DSM (2013). Several aspects of the disorder remain uncertain and controversial. For example, ongoing debate surrounds which specific conditions fall under this diagnostic category and how to best differentiate BFRBs from conditions such as nonsuicidal self-injury (NSSI). The current article presents results from a survey of experts' opinions on diagnostic criteria, with the goal of refining the diagnostic criteria. We contacted experts on BFRB via various sources and invited them to complete an online survey on the phenomenology, classification, and differential diagnosis of BFRB. We also inquired about possible alternative syndrome labels (e.g., body-focused habit). Data from the final sample of 50 experts demonstrates that most experts agree with the present classification of BFRB/BFRBD as an obsessive-compulsive and related disorder and recommend retaining the labels BFRB or BFRBD. The experts considered the following conditions BFRB, with an agreement of over 60%: trichotillomania, skin picking, dermatophagia, nail biting, and lip-cheek biting. Mixed results emerged for awake bruxism and thumb sucking in adults. Only a minority regarded night bruxism and knuckle cracking as BFRB. To differentiate BFRB from NSSI, the experts noted that the motive behind the urge (self-harm/injury versus release of tension) should be considered. Analyses of a sub-sample of experts with at least six years of clinical and/or research experience yielded results compatible with those of the entire sample. The survey supports the usefulness of the BFRBD diagnostic entity. However, some criteria require further refinement. Future editions of the DSM should more explicitly delineate which conditions qualify as BFRB. Furthermore, it is important to give more attention to the primary motivation behind BFRB to distinguish it from NSSI and potentially from stereotypic movement behavior. •The phenomenology, classification, and differential diagnosis of BFRBs remain under debate.•Experts concur that trichotillomania, skin picking, dermatophagia, nail biting, and lip-cheek biting are primary BFRBs.•The motive is considered an important criterion in distinguishing BFRB from other conditions.•Experts concur that BFRBs should continue to be categorized as an obsessive-compulsive and related disorder.

Although trichotillomania (TTM), skin picking (SP), and nail biting (NB) have been receiving growing scientific attention, the question as to whether these disorders can be regarded as separate entities or they are different manifestations of the same underlying tendency is unclear. Data were collected online in a community survey, yielding a sample of 2705 participants (66% women, mean age: 29.1, SD: 8.6). Hierarchical factor analysis was used to identify a common latent factor and the multiple indicators and multiple causes (MIMIC) modelling was applied to test the predictive effect of borderline personality disorder symptoms, impulsivity, distress and self-esteem on pathological grooming. Pearson correlation coefficients between TTM, SP and NB were between 0.13 and 0.29 (p < 0.01). The model yielded an excellent fit to the data (CFI = 0.992, TLI = 0.991, χ2 = 696.65, p < 0.001, df = 222, RMSEA = 0.030, Cfit of RMSEA = 1.000), supporting the existence of a latent factor. The MIMIC model indicated an adequate fit (CFI = 0.993, TLI = 0.992, χ2 = 655.8, p < 0.001, df = 307, RMSEA = 0.25, CI: 0.022-0.028, pclose = 1.000). TTM, SP and NB each were loaded significantly on the latent factor, indicating the presence of a general grooming factor. Impulsivity, psychiatric distress and contingent self-esteem had significant predictive effects, whereas borderline personality disorder had a nonsignificant predictive effect on the latent factor. We found evidence that the category of pathological grooming is meaningful and encompasses three symptom manifestations: trichotillomania, skin picking and nail biting. This latent underlying factor is not better explained by indicators of psychopathology, which supports the notion that the urge to self-groom, rather than general psychiatric distress, impulsivity, self-esteem or borderline symptomatology, is what drives individual grooming behaviours.

For the publication of DSM‐5, obsessive‐compulsive disorder (OCD) was the subject of significant revisions to its classification and diagnostic criteria. One of these significant changes was the placement of OCD in a new category, “Obsessive‐Compulsive and Related Disorders (OCRDs),” which also includes body dysmorphic disorder (BDD), trichotillomania (hair‐pulling disorder), excoriation (skin‐picking) disorder, hoarding disorder, substance/medication‐induced OCRD, OCRD due to another medical condition, and other specified OCRDs. Changes in the diagnostic criteria and grouping of these disorders may have significant clinical implications, and will be reviewed in this article.

Obsessive–compulsive disorder (OCD) is a chronic and disabling condition affecting approximately 3.5% of the global population, with diagnosis on average delayed by 7.1 years or often confounded with other psychiatric disorders. Advances in electroencephalography (EEG) analysis using machine learning hold promise for the development of OCD-specific biological markers. This systematic review aims to evaluate studies that classify individuals with OCD from other groups based on EEG data. Following PRISMA guidelines, we searched the Web of Science, Scopus, PubMed, and IEEE databases through February 2025; of 42 screened studies, 11 met inclusion criteria for final analysis. Data were extracted across four domains: general information, population characteristics, EEG features, and machine learning features. Results revealed extensive heterogeneity in study populations, associated symptoms, EEG preprocessing methods, validation strategies, and reporting of model accuracy, underscoring the need for harmonized standards. Notably, only a few studies provided statistical interpretation of their models. None of reviewed studies employed modern interpretability techniques such as SHAP or LIME methods that, beyond reducing “black-box” opacity, can inform optimal electrode placement for neurofeedback or transcranial electrical stimulation. Many studies were constrained by cultural limitations, small sample sizes and lack of demographic information e.g., age, gender, medication. This work represents the first systematic review of EEG-ML classification studies in OCD and emphasizes the urgent need for methodological standardization in this emerging field.

Obsessive–compulsive disorder (OCD) encompasses a broad range of symptoms representing multiple domains. This complex phenotype can be summarized using a few consistent and temporally stable symptom dimensions. The objective of this study was to assess the psychometric properties of the Dimensional Yale–Brown Obsessive–Compulsive Scale (DY-BOCS). This scale measures the presence and severity of obsessive–compulsive (OC) symptoms within six distinct dimensions that combine thematically related obsessions and compulsions. The DY-BOCS includes portions to be used as a self-report instrument and portions to be used by expert raters, including global ratings of OC symptom severity and overall impairment. We assessed 137 patients with a Diagnostic and Statistical Manual-IV diagnosis of OCD, aged 6–69 years, from sites in the USA, Canada and Brazil. Estimates of the reliability and validity of both the expert and self-report versions of the DY-BOCS were calculated and stratified according to age (pediatric vs. adult subjects). The internal consistency of each of the six symptom dimensions and the global severity score were excellent. The inter-rater agreement was also excellent for all component scores. Self-report and expert ratings were highly intercorrelated. The global DY-BOCS score was highly correlated with the total Yale–Brown Obsessive–Compulsive Scale score (Pearson r =0.82, P <0.0001). Severity scores for individual symptom dimensions were largely independent of one another, only modestly correlated with the global ratings, and were also differentially related to ratings of depression, anxiety and tic severity. No major differences were observed when the results were stratified by age. These results indicate that the DY-BOCS is a reliable and valid instrument for assessing multiple aspects of OCD symptom severity in natural history, neuroimaging, treatment response and genetic studies when administered by expert clinicians or their highly trained staff.

To (1) confirm whether the Habit, Reward, and Fear Scale is able to generate a 3-factor solution in a population of obsessive-compulsive disorder and alcohol use disorder (AUD) patients; (2) compare these clinical groups in their habit, reward, and fear motivations; and (3) investigate whether homogenous subgroups can be identified to resolve heterogeneity within and across disorders based on the motivations driving ritualistic and drinking behaviors. One hundred and thirty-four obsessive-compulsive disorder (n = 76) or AUD (n = 58) patients were assessed with a battery of scales including the Habit, Reward, and Fear Scale, the Yale-Brown Obsessive-Compulsive Scale, the Alcohol Dependence Scale, the Behavioral Inhibition/Activation System Scale, and the Urgency, (lack of ) Premeditation, (lack of ) Perseverance, Sensation Seeking, and Positive Urgency Impulsive Behavior Scale. A 3-factor solution reflecting habit, reward, and fear subscores explained 56.6% of the total variance of the Habit, Reward, and Fear Scale. Although the habit and fear subscores were significantly higher in obsessive-compulsive disorder (OCD) and the reward subscores were significantly greater in AUD patients, a cluster analysis identified that the 3 clusters were each characterized by differing proportions of OCD and AUD patients. While affective (reward- and fear-driven) and nonaffective (habitual) motivations for repetitive behaviors seem dissociable from each other, it is possible to identify subgroups in a transdiagnostic manner based on motivations that do not match perfectly motivations that usually described in OCD and AUD patients.