This study was designed to examine whether proactive and reactive aggression are meaningful distinctions at the variable-and person-based level, and to determine their associated behavioral profiles. Data from 587 adolescents (mean age 15.6; 71.6 % male) from clinical samples of four different sites with differing levels of aggression problems were analyzed. A multi-level Latent Class Analysis (LCA) was conducted to identify classes of individuals (personbased) with similar aggression profiles based on factor scores (variable-based) of the Reactive Proactive Questionnaire (RPQ) scored by self-report. Associations were examined between aggression factors and classes, and externalizing and internalizing problem behavior scales by parent report (CBCL) and self-report (YSR). Factor-analyses yielded a three factor solution: 1) proactive aggression, 2) reactive aggression due to internal frustration, and 3) reactive aggression due to external provocation. All three factors showed moderate to high correlations. Four classes were detected that mainly differed quantitatively (no 'proactive-only' class present), yet also qualitatively when age was taken into account, with reactive aggression becoming more severe with age in the highest affected class yet diminishing with age in the other classes. Findings were robust across the four samples. Multiple regression analyses showed that 'reactive aggression due to internal frustration' was the strongest predictor of YSR and CBCL internalizing problems. However, results showed moderate to high overlap between all three factors. Aggressive behavior can be distinguished psychometrically into three factors in a clinical sample, with some differential associations. However, the clinical relevance of these findings is challenged by the person-based analysis showing proactive and reactive aggression are mainly driven by aggression severity.

The basic concepts underlying compulsive, impulsive and addictive behaviours overlap, which may help explain why laymen use these expressions interchangeably. Although there has been a large research effort to better characterize and disentangle these behaviours, clinicians and scientists are still unable to clearly differentiate them. Accordingly, obsessive-compulsive disorder (OCD), impulse control disorders (ICD) and substance-related disorders (SUD) overlap on different levels, including phenomenology, co-morbidity, neurocircuitry, neurocognition, neurochemistry and family history. In this review we summarize these issues with particular emphasis on the role of the opioid system in the pathophysiology and treatment of OCD, ICD and SUD. We postulate that with progression and chronicity of OCD, the proportion of the OCD-related behaviours (e.g. checking, washing, ordering and hoarding, among others) that are driven by impulsive 'rash' processes increase as involvement of more ventral striatal circuits becomes prominent. In contrast, as SUD and ICD progress, the proportion of the SUD- and ICD-related behaviours that are driven by compulsive 'habitual' processes increase as involvement of more dorsal striatal circuits become prominent. We are not arguing that, with time, ICD becomes OCD or vice versa. Instead, we are proposing that these disorders may acquire qualities of the other with time. In other words, while patients with ICD/SUD may develop 'compulsive impulsions', patients with OCD may exhibit 'impulsive compulsions'. There are many potential implications of our model. Theoretically, OCD patients exhibiting impulsive or addictive features could be managed with drugs that address the quality of the underlying drives and the involvement of neural systems. For example, agents for the reduction or prevention of relapse of addiction (e.g. heavy drinking), which modulate the cortico-mesolimbic dopamine system through the opioid (e.g. buprenorphine and naltrexone), glutamate (e.g. topiramate), serotonin (e.g. ondansetron) or γ-aminobutyric acid (e.g. baclofen and topiramate) systems, may prove to show some benefit in certain forms of OCD. Based on the available evidence, we suggest that the treatment of patients with these disorders must account for alterations in the underlying motivations and neurobiology of the condition. We provide an initial guide to the specific treatments that future clinical trials might consider in patients with OCD. For example, it might be wise to test naltrexone in patients with co-morbid SUD and ICD, topiramate in patients with co-morbid ICD and eating disorders, and baclofen in patients with co-morbid Tourette's syndrome. These trials could also include scales aimed at assessing underlying impulsivity (e.g. Barratt Impulsiveness Scale) to check whether this construct might predict response to drugs acting on the reward system.

ObjectiveImpulsivity and compulsivity have been implicated as important transdiagnostic dimensional phenotypes with potential relevance to addiction. We aimed to develop a model that conceptualizes these constructs as overlapping dimensional phenotypes and test whether different components of this model explain the co-occurrence of addictive and related behaviors.MethodsA large sample of adults (N = 487) was recruited through Amazon’s Mechanical Turk and completed self-report questionnaires measuring impulsivity, intolerance of uncertainty, obsessive beliefs, and the severity of 6 addictive and related behaviors. Hierarchical clustering was used to organize addictive behaviors into homogenous groups reflecting their co-occurrence. Structural equation modeling was used to evaluate fit of the hypothesized bifactor model of impulsivity and compulsivity and determine the proportion of variance explained in the co-occurrence of addictive and related behaviors by each component of the model.ResultsAddictive and related behaviors clustered into 2 distinct groups: Impulse-Control Problems, consisting of harmful alcohol use, pathological gambling, and compulsive buying, and Obsessive-Compulsive-Related Problems, consisting of obsessive-compulsive symptoms, binge eating, and internet addiction. The hypothesized bifactor model of impulsivity and compulsivity provided the best empirical fit, with 3 uncorrelated factors corresponding to a general Disinhibition dimension, and specific Impulsivity and Compulsivity dimensions. These dimensional phenotypes uniquely and additively explained 39.9% and 68.7% of the total variance in Impulse-Control Problems and Obsessive-Compulsive-Related Problems.ConclusionA model of impulsivity and compulsivity that represents these constructs as overlapping dimensional phenotypes has important implications for understanding addictive and related behaviors in terms of shared etiology, comorbidity, and potential transdiagnostic treatments.