Compulsivity is measurable across distinct psychiatric symptom domains and is associated with familial risk and reward-related attentional capture.

BACKGROUND: Compulsivity can be seen across various mental health conditions and refers to a tendency toward repetitive habitual acts that are persistent and functionally impairing. Compulsivity involves dysfunctional reward-related circuitry and is thought to be significantly heritable. Despite this, its measurement from a transdiagnostic perspective has received only scant research attention. Here we examine both the psychometric properties of a recently developed compulsivity scale, as well as its relationship with compulsive symptoms, familial risk, and reward-related attentional capture. METHODS: Two-hundred and sixty individuals participated in the study (mean age = 36.0 [SD = 10.8] years; 60.0% male) and completed the Cambridge-Chicago Compulsivity Trait Scale (CHI-T), along with measures of psychiatric symptoms and family history thereof. Participants also completed a task designed to measure reward-related attentional capture (n = 177). RESULTS: CHI-T total scores had a normal distribution and acceptable Cronbach's alpha (0.84). CHI-T total scores correlated significantly and positively (all p < 0.05, Bonferroni corrected) with Problematic Usage of the Internet, disordered gambling, obsessive-compulsive symptoms, alcohol misuse, and disordered eating. The scale was correlated significantly with history of addiction and obsessive-compulsive related disorders in first-degree relatives of participants and greater reward-related attentional capture. CONCLUSIONS: These findings suggest that the CHI-T is suitable for use in online studies and constitutes a transdiagnostic marker for a range of compulsive symptoms, their familial loading, and related cognitive markers. Future work should more extensively investigate the scale in normative and clinical cohorts, and the role of value-modulated attentional capture across compulsive disorders.

Transdiagnostic phenotypes of compulsive behavior and associations with psychological, cognitive, and neurobiological affective processing.

Compulsivity is a poorly understood transdiagnostic construct thought to underlie multiple disorders, including obsessive-compulsive disorder, addictions, and binge eating. Our current understanding of the causes of compulsive behavior remains primarily based on investigations into specific diagnostic categories or findings relying on one or two laboratory measures to explain complex phenotypic variance. This proof-of-concept study drew on a heterogeneous sample of community-based individuals (N = 45; 18-45 years; 25 female) exhibiting compulsive behavioral patterns in alcohol use, eating, cleaning, checking, or symmetry. Data-driven statistical modeling of multidimensional markers was utilized to identify homogeneous subtypes that were independent of traditional clinical phenomenology. Markers were based on well-defined measures of affective processing and included psychological assessment of compulsivity, behavioral avoidance, and stress, neurocognitive assessment of reward vs. punishment learning, and biological assessment of the cortisol awakening response. The neurobiological validity of the subtypes was assessed using functional magnetic resonance imaging. Statistical modeling identified three stable, distinct subtypes of compulsivity and affective processing, which we labeled "Compulsive Non-Avoidant", "Compulsive Reactive" and "Compulsive Stressed". They differed meaningfully on validation measures of mood, intolerance of uncertainty, and urgency. Most importantly, subtypes captured neurobiological variance on amygdala-based resting-state functional connectivity, suggesting they were valid representations of underlying neurobiology and highlighting the relevance of emotion-related brain networks in compulsive behavior. Although independent larger samples are needed to confirm the stability of subtypes, these data offer an integrated understanding of how different systems may interact in compulsive behavior and provide new considerations for guiding tailored intervention decisions.

The role of Experiential Avoidance in transdiagnostic compulsive behavior: A structural model analysis.

Compulsivity is recognized as a transdiagnostic phenotype, underlying a variety of addictive and obsessive-compulsive behaviors. However, current understanding of how it should be operationalized and the processes contributing to its development and maintenance is limited. The present study investigated if there was a relationship between the affective process Experiential Avoidance (EA), an unwillingness to tolerate negative internal experiences, and the frequency and severity of transdiagnostic compulsive behaviors. A large sample of adults (N = 469) completed online questionnaires measuring EA, psychological distress and the severity of seven obsessive-compulsive and addiction-related behaviors. Using structural equation modelling, results indicated a one-factor model of compulsivity was superior to the two-factor model (addictive- vs OCD-related behaviors). The effect of EA on compulsivity was fully mediated by psychological distress, which in turn had a strong direct effect on compulsivity. This suggests distress is a key mechanism in explaining why people with high EA are more prone to compulsive behaviors. The final model explained 41% of the variance in compulsivity, underscoring the importance of these constructs as likely risk and maintenance factors for compulsive behavior. Implications for designing effective psychological interventions for compulsivity are discussed.

The Influence of Aerobic Exercise on Hippocampal Integrity and Function: Preliminary Findings of a Multi-Modal Imaging Analysis.

Aerobic exercise (AE) interventions represent promising therapeutic approaches in disorders that compromise hippocampal integrity, but a more comprehensive account of the neural mechanisms stimulated by AE in the human brain is needed. We conducted a longitudinal pilot-study to assess the impact of a 12-week AE intervention on hippocampal structure and function in 10 healthy, human participants (50% females; 25-59 years). Using a novel combination of multimodal MRI techniques, we found significant increases in left hippocampal volume, Cornu Ammonis subfield area 1, NAA concentration and immediate verbal recall performance. Our preliminary findings highlight the utility of a multimodal approach in assessing hippocampal integrity.

Cannabis-related hippocampal volumetric abnormalities specific to subregions in dependent users.

RATIONALE: Cannabis use is associated with neuroanatomical alterations in the hippocampus. While the hippocampus is composed of multiple subregions, their differential vulnerability to cannabis dependence remains unknown. OBJECTIVES: The objective of the study is to investigate gray matter alteration in each of the hippocampal subregions (presubiculum, subiculum, cornu ammonis (CA) subfields CA1-4, and dentate gyrus (DG)) as associated with cannabis use and dependence. METHODS: A total of 35 healthy controls (HC), 22 non-dependent (CB-nondep), and 39 dependent (CB-dep) cannabis users were recruited. We investigated group differences in hippocampal subregion volumes between HC, CB-nondep, and CB-dep users. We further explored the association between CB use variables (age of onset of regular use, monthly use, lifetime use) and hippocampal subregions in CB-nondep and CB-dep users separately. RESULTS: The CA1, CA2/3, CA4/DG, as well as total hippocampal gray matter were reduced in volume in CB-dep but not in CB-nondep users, relative to HC. The right CA2/3 and CA4/DG volumes were also negatively associated with lifetime cannabis use in CB-dep users. CONCLUSIONS: Our results suggest a regionally and dependence-specific influence of cannabis use on the hippocampus. Hippocampal alteration in cannabis users was specific to the CA and DG regions and confined to dependent users.