Attentional Biases and Their Association with Substance-Use-Related Problems and Addictive Behaviors: The Utility of a Gamified Value-Modulated Attentional Capture Task.

Background: Attentional biases towards reward stimuli have been implicated in substance use-related problems. The value-modulated attentional capture (VMAC) task assesses such reward-related biases. The VMAC task widely used in lab studies tends to be monotonous and susceptible to low effort. We therefore tested a gamified online version of the VMAC that aimed to increase participant engagement. Our goal was to examine how VMAC is associated with substance use-related problems and addictive behaviors, and whether this association is moderated by cognitive control. Methods: We recruited 285 participants from an online community, including heavy alcohol users. All participants completed a novel gamified version of the VMAC task, measures of substance use and addictive behaviors (addictive-like eating behavior, problematic smartphone use), the WebExec measure of problems with executive functions, and the Stroop Adaptive Deadline Task (SDL) as a measure of cognitive control. Results: The gamified VMAC task successfully identified value-modulated attentional capture effects towards high-reward stimuli. We found no significant associations between VMAC scores, problematic alcohol or cannabis use, addictive behaviors, or any moderation by a behavioral measure of cognitive control. Exploratory analyses revealed that self-reported cognitive problems were associated with more alcohol-, and cannabis-related problems, and addictive behaviors. Greater attentional capture (VMAC) was associated with more cannabis use-related problems among individuals with higher levels of self-reported cognitive problems. Conclusions: Our study is one of the first to demonstrate the utility of the gamified version of the VMAC task in capturing attentional reward biases. Self-reported problems with cognitive functions represent a key dimension associated with substance use-related problems and addictive behaviors.

The neurocognitive correlates of non-substance addictive behaviors.

Neurocognitive deficits have been implicated as transdiagnostic risk markers of substance use disorders. However, these have yet to be comprehensively evaluated in other, non-substance addictions. In a large, general community sample (N = 475) the present study evaluated the neurocognitive correlates of problem alcohol use and three non-substance-related addictive behaviors: addictive eating (AE), problematic pornography use (PPU), and problematic use of the internet (PUI), to identify potential shared and distinct neurocognitive correlates. A sample of Australian residents (54.4 % female M[SD] age = 32.4[11.9] years) completed a comprehensive online assessment of neurocognitive tasks tapping into eight distinct expert-endorsed domains purportedly associated with addiction. Multiple linear regressions with bootstrapping were used to examine associations among each addictive behavior of interest and neurocognition, trait impulsivity, and compulsivity, as well as key covariates. Neurocognition was differentially associated with each addictive behavior. None of the neurocognitive domains were significantly associated with problematic alcohol use or AE (p >.05), poorer performance monitoring was significantly associated with higher levels of PPU and PUI (ß = -0.10, p =.049; ß = -0.09, p =.028), and a preference for delayed gratification was associated with more severe PUI (ß = -0.10, p =.025). Our findings have theoretical implications for how we understand non-substance addiction and suggest the need for a more nuanced approach to studying addictive behaviors that take into account the underlying neurocognitive mechanisms associated with each type of addiction.

A Novel, Expert-Endorsed, Neurocognitive Digital Assessment Tool for Addictive Disorders: Development and Validation Study.

BACKGROUND: Many people with harmful addictive behaviors may not meet formal diagnostic thresholds for a disorder. A dimensional approach, by contrast, including clinical and community samples, is potentially key to early detection, prevention, and intervention. Importantly, while neurocognitive dysfunction underpins addictive behaviors, established assessment tools for neurocognitive assessment are lengthy and unengaging, difficult to administer at scale, and not suited to clinical or community needs. The BrainPark Assessment of Cognition (BrainPAC) Project sought to develop and validate an engaging and user-friendly digital assessment tool purpose-built to comprehensively assess the main consensus-driven constructs underpinning addictive behaviors. OBJECTIVE: The purpose of this study was to psychometrically validate a gamified battery of consensus-based neurocognitive tasks against standard laboratory paradigms, ascertain test-retest reliability, and determine their sensitivity to addictive behaviors (eg, alcohol use) and other risk factors (eg, trait impulsivity). METHODS: Gold standard laboratory paradigms were selected to measure key neurocognitive constructs (Balloon Analogue Risk Task [BART], Stop Signal Task [SST], Delay Discounting Task [DDT], Value-Modulated Attentional Capture [VMAC] Task, and Sequential Decision-Making Task [SDT]), as endorsed by an international panel of addiction experts; namely, response selection and inhibition, reward valuation, action selection, reward learning, expectancy and reward prediction error, habit, and compulsivity. Working with game developers, BrainPAC tasks were developed and validated in 3 successive cohorts (total N=600) and a separate test-retest cohort (N=50) via Mechanical Turk using a cross-sectional design. RESULTS: BrainPAC tasks were significantly correlated with the original laboratory paradigms on most metrics (r=0.18-0.63, P<.05). With the exception of the DDT k function and VMAC total points, all other task metrics across the 5 tasks did not differ between the gamified and nongamified versions (P>.05). Out of 5 tasks, 4 demonstrated adequate to excellent test-retest reliability (intraclass correlation coefficient 0.72-0.91, P<.001; except SDT). Gamified metrics were significantly associated with addictive behaviors on behavioral inventories, though largely independent of trait-based scales known to predict addiction risk. CONCLUSIONS: A purpose-built battery of digitally gamified tasks is sufficiently valid for the scalable assessment of key neurocognitive processes underpinning addictive behaviors. This validation provides evidence that a novel approach, purported to enhance task engagement, in the assessment of addiction-related neurocognition is feasible and empirically defensible. These findings have significant implications for risk detection and the successful deployment of next-generation assessment tools for substance use or misuse and other mental disorders characterized by neurocognitive anomalies related to motivation and self-regulation. Future development and validation of the BrainPAC tool should consider further enhancing convergence with established measures as well as collecting population-representative data to use clinically as normative comparisons.

Neurocognitive predictors of addiction-related outcomes: A systematic review of longitudinal studies.

It is well-established that addiction is typically associated with a distinct pattern of neurocognitive functioning with a consensus that it is typified by impaired top-down executive control and aberrant risk-reward processing. Despite a consensus that neurocognition plays an important role in characterizing and maintaining addictive disorders, there is a lack of systematic, bottom-up synthesis of quantitative evidence showing that neurocognition predicts addictive behaviors, and which neurocognitive constructs have the best predictive validity. This systematic review aimed to assess whether cognitive control and risk-reward processes as defined by the Research Domain Criteria (RDoC) predict the development and maintenance of addictive behaviors specifically, consumption, severity, and relapse. The findings from this review expose the substantial lack of evidence for neurocognition predicting addiction outcomes. However, there is evidence that suggests reward-related neurocognitive processes may be important for the detection of early risk for addiction, as well as a potentially viable target for designing novel, more effective interventions.

Lifestyle risk factors for obsessive-compulsive symptoms and related phenomena: What should lifestyle interventions target?

OBJECTIVE: Understanding the impact of lifestyle on mental illness symptoms is important for informing psycho-education and developing interventions which target mental and physical comorbidities. Obsessive-compulsive and related disorders can have a significant impact on health-related quality of life and physical health. However, our understanding of the impact of lifestyle on obsessive-compulsive symptoms and broader compulsive and impulsive problematic repetitive behaviours is limited. AIMS: We investigated whether lifestyle factors predicted change in obsessive-compulsive symptoms and problematic repetitive behaviours in a general population sample over a 3-month period. METHODS: Eight hundred thirty-five participants completed an online questionnaire battery assessing lifestyle and mental health. Of these, 538 participants completed the same battery 3 months later. We conducted negative binomial regressions to analyse the association of lifestyle factors at baseline with future (1) obsessive-compulsive symptoms, (2) compulsive problematic repetitive behaviours and (3) impulsive problematic repetitive behaviours, adjusting for baseline obsessive-compulsive symptoms and problematic repetitive behaviours. RESULTS: Lower vegetable (p = 0.020) and oily fish (p = 0.040) intake and lower moderate intensity physical activity (p = 0.008) predicted higher obsessive-compulsive symptoms at follow-up. Higher intake of high-fat foods (p < 0.001) predicted higher compulsive problematic repetitive behaviours at follow-up. No lifestyle factors significantly predicted impulsive problematic repetitive behaviours at follow-up. CONCLUSION: Our results speak to the potential importance of lifestyle quality screening, education and lifestyle interventions (e.g. an anti-inflammatory diet) for individuals experiencing compulsivity-related behaviours and/or symptoms. Further research into potential mechanisms of action will allow for more targeted approaches to lifestyle interventions for transdiagnostic compulsive behaviours.

Distress-driven impulsivity interacts with trait compulsivity in association with problematic drinking: A two-sample study.

Objective: Problematic drinking is highly prevalent among the general population, oftentimes leading to significant negative consequences, including physical injury, psychological problems and financial hardship. In order to design targeted early interventions for problematic drinking, it is important to understand the mechanisms that render individuals at risk for and/or maintain this behavior. Two candidate drivers of problematic drinking are distress-driven impulsivity and trait compulsivity, with recent research suggesting these constructs may interact to enhance risk for addictive behaviors. The current study examined whether individual differences in distress-driven impulsivity and trait compulsivity interact in relation to problematic drinking. Method: Distress-driven impulsivity (indexed by the S-UPPS-P negative urgency subscale), trait compulsivity (indexed by the CHIT scale) and problematic drinking (indexed by the BATCAP alcohol scale) were assessed in two independent online samples (Sample 1, n = 117; Sample 2, n = 474). Bootstrapped moderation analysis was conducted to examine whether trait compulsivity moderated the relationship between distress-driven impulsivity and problematic drinking. Results: In both samples, there was a significant interaction between distress-driven impulsivity and trait compulsivity in relation to problematic drinking. Follow-up tests revealed that, in both samples, higher distress-driven impulsivity was associated with more problematic drinking behaviors among participants with high trait compulsivity only. Conclusions: The current findings add to the growing literature supporting an interactive relationship between impulsivity and compulsivity-related traits in relation to addictive behaviors and have implications for informing early detection of risk and targeted early interventions.

The Moderating Role of Psychological Flexibility on the Association between Distress-Driven Impulsivity and Problematic Internet Use.

BACKGROUND: Problematic internet use is receiving increasing attention in the addiction field, yet the mechanisms driving such behaviours remain unclear. Previous research has shown that impulsivity- and compulsivity-related constructs may interactively contribute to a range of problematic behaviours. The current study examined whether distress-driven impulsivity and psychological flexibility may interactively contribute to problematic internet use, which has not been addressed in prior literature. METHOD: Two hundred and one participants completed an online survey. Bootstrapped moderation analysis was conducted to examine the collected data on distress-driven impulsivity, psychological flexibility, and their interaction in relation to problematic internet use. RESULTS: The interaction between distress-driven impulsivity and psychological flexibility was significantly related to problematic internet use. Simple slope tests confirmed that distress-driven impulsivity was associated with problematic internet use among individuals with low flexibility levels. CONCLUSIONS: Our findings highlight the moderating role of psychological inflexibility in the association between distress-driven impulsivity and problematic internet use. Prevention and/or early interventions for problematic internet use should consider targeting psychological inflexibility and distress-driven impulsivity.

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 psychological distress in the relationship between lifestyle and compulsivity: An analysis of independent, bi-national samples.

BACKGROUND: Poor mental health is a state of psychological distress that is influenced by lifestyle factors such as sleep, diet, and physical activity. Compulsivity is a transdiagnostic phenotype cutting across a range of mental illnesses including obsessive-compulsive disorder, substance-related and addictive disorders, and is also influenced by lifestyle. Yet, how lifestyle relates to compulsivity is presently unknown, but important to understand to gain insights into individual differences in mental health. We assessed (a) the relationships between compulsivity and diet quality, sleep quality, and physical activity, and (b) whether psychological distress statistically contributes to these relationships. METHODS: We collected harmonized data on compulsivity, psychological distress, and lifestyle from two independent samples (Australian n = 880 and US n = 829). We used mediation analyses to investigate bidirectional relationships between compulsivity and lifestyle factors, and the role of psychological distress. RESULTS: Higher compulsivity was significantly related to poorer diet and sleep. Psychological distress statistically mediated the relationship between poorer sleep quality and higher compulsivity, and partially statistically mediated the relationship between poorer diet and higher compulsivity. CONCLUSIONS: Lifestyle interventions in compulsivity may target psychological distress in the first instance, followed by sleep and diet quality. As psychological distress links aspects of lifestyle and compulsivity, focusing on mitigating and managing distress may offer a useful therapeutic approach to improve physical and mental health. Future research may focus on the specific sleep and diet patterns which may alter compulsivity over time to inform lifestyle targets for prevention and treatment of functionally impairing compulsive behaviors.

The place of obsessive-compulsive and related disorders in the compulsive-impulsive spectrum: a cluster-analytic study.

BACKGROUND: The extent to which obsessive-compulsive and related disorders (OCRDs) are impulsive, compulsive, or both requires further investigation. We investigated the existence of different clusters in an online nonclinical sample and in which groups DSM-5 OCRDs and other related psychopathological symptoms are best placed. METHODS: Seven hundred and seventy-four adult participants completed online questionnaires including the Cambridge-Chicago Compulsivity Trait Scale (CHI-T), the Barratt Impulsiveness Scale (BIS-15), and a series of DSM-5 OCRDs symptom severity and other psychopathological measures. We used K-means cluster analysis using CHI-T and BIS responses to test three and four factor solutions. Next, we investigated whether different OCRDs symptoms predicted cluster membership using a multinomial regression model. RESULTS: The best solution identified one "healthy" and three "clinical" clusters (ie, one predominantly "compulsive" group, one predominantly "impulsive" group, and one "mixed"-"compulsive and impulsive group"). A multinomial regression model found obsessive-compulsive, body dysmorphic, and schizotypal symptoms to be associated with the "mixed" and the "compulsive" clusters, and hoarding and emotional symptoms to be related, on a trend level, to the "impulsive" cluster. Additional analysis showed cognitive-perceptual schizotypal symptoms to be associated with the "mixed" but not the "compulsive" group. CONCLUSIONS: Our findings suggest that obsessive-compulsive disorder; body dysmorphic disorder and schizotypal symptoms can be mapped across the "compulsive" and "mixed" clusters of the compulsive-impulsive spectrum. Although there was a trend toward hoarding being associated with the "impulsive" group, trichotillomania, and skin picking disorder symptoms did not clearly fit to the demarcated clusters.

Distress-driven impulsivity interacts with cognitive inflexibility to determine addiction-like eating.

BACKGROUND: Researchers are only just beginning to understand the neurocognitive drivers of addiction-like eating behaviours, a highly distressing and relatively common condition. Two constructs have been consistently linked to addiction-like eating: distress-driven impulsivity and cognitive inflexibility. Despite a large body of addiction research showing that impulsivity-related traits can interact with other risk markers to result in an especially heightened risk for addictive behaviours, no study to date has examined how distress-driven impulsivity interacts with cognitive inflexibility in relation to addiction-like eating behaviours. The current study examines the interactive contribution of distress-driven impulsivity and cognitive inflexibility to addiction-like eating behaviours. METHOD: One hundred and thirty-one participants [mean age 21 years (SD = 2.3), 61.8% female] completed the modified Yale Food Addiction Scale, the S-UPPS-P impulsivity scale, and a cognitive flexibility task. A bootstrap method was used to examine the associations between distress-driven impulsivity, cognitive inflexibility, and their interaction with addiction-like eating behaviours. RESULTS: There was a significant interaction effect between distress-driven impulsivity and cognitive flexibility (P = 0.03). The follow-up test revealed that higher distress-driven impulsivity was associated with more addiction-like eating behaviours among participants classified as cognitively inflexible only. CONCLUSION: The current findings shed light on the mechanisms underlying addiction-like eating behaviours, including how traits and cognition might interact to drive them. The findings also suggest that interventions that directly address distress-driven impulsivity and cognitive inflexibility might be effective in reducing risk for addiction-like eating and related disorders.

The Influence of Trait Compulsivity and Impulsivity on Addictive and Compulsive Behaviors During COVID-19.

Background: The COVID-19 pandemic has resulted in high levels of psychological distress worldwide, with experts expressing concern that this could result in corresponding increases in addictive behaviors as individuals seek to cope with their distress. Further, some individuals may be at greater risk than others for developing problematic addictive behaviors during times of high stress, such as individuals with high trait impulsivity and compulsivity. Despite the potential of such knowledge to inform early detection of risk, no study to date has examined the influence of trait impulsivity and compulsivity on addictive behaviors during COVID-19. Toward this aim, the current study examined the association between impulsive and compulsive traits and problematic addictive and compulsive behaviors during the first COVID-19 lockdown in Australia. Methods: Eight hundred seventy-eight adults completed a cross-sectional online survey during the first lockdown, between late May to June 2020. Participants completed scales for addictive and compulsive behaviors for the period prior to and during lockdown for problematic eating, pornography, internet use, gambling, drinking, and obsessive-compulsive behaviors. Negative binomial regressions examined the associations between impulsivity, compulsivity, and their interaction with problematic behaviors during lockdown, controlling for age, gender, sample, psychological distress, exposure to COVID-related stressors, and pre-COVID problems. Results: Greater trait compulsivity was associated with more problematic obsessive-compulsive behaviors (p < 0.001) and less problematic drinking (p = 0.038) during lockdown. Further, trait compulsivity interacted with trait impulsivity in relation to problematic eating behaviors (p = 0.014) such that greater trait compulsivity was associated with more problems among individuals with low impulsivity only (p = 0.030). Finally, psychological distress and/or exposure to COVID-related stressors were associated with greater problems across all addictive and compulsive behaviors, as was severity of pre-COVID problems. Discussion: Trait compulsivity was associated with addictive and compulsive behaviors in different ways. Further, the finding that stress-related variables (psychological distress and COVID-related stressors) were associated with greater problems across all lockdown behaviors supports the idea that stress may facilitate, or otherwise be associated with, problematic behaviors. These findings highlight the need for interventions that enhance resilience to stress, which in turn may reduce risk for addictive and compulsive disorders.

Habitual versus affective motivations in obsessive-compulsive disorder and alcohol use disorder.

OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Neurocognitive functioning predicts suicidal behaviour in young people with affective disorders.

BACKGROUND: Neurocognitive impairment is recognised as a risk factor for suicidal behaviour in adults. The current study aims to determine whether neurocognitive deficits also predict ongoing or emergent suicidal behaviour in young people with affective disorders. METHODS: Participants were aged 12-30 years and presented to early intervention youth mental health clinics between 2008 and 2018. In addition to clinical assessment a standardised neurocognitive assessment was conducted at baseline. Clinical data was extracted from subsequent visits using a standardised proforma. RESULTS: Of the 635 participants who met inclusion criteria (mean age 19.6 years, 59% female, average follow up 476 days) 104 (16%) reported suicidal behaviour during care. In 5 of the 10 neurocognitive domains tested (cognitive flexibility, processing speed, working memory, verbal memory and visuospatial memory) those with suicidal behaviour during care were superior to clinical controls. Better general neurocognitive function remained a significant predictor (OR=1.94, 95% CI 1.29- 2.94) of suicidal behaviour in care after controlling for other risk factors. LIMITATIONS: The neurocognitive battery used was designed for use with affective and psychotic disorders and may not have detected some deficits more specific to suicidal behaviour. CONCLUSION: Contrary to expectations, better neurocognitive functioning predicts suicidal behaviour during care in young people with affective disorders. While other populations with suicidal behaviour, such as adults with affective disorders or young people with psychotic disorders, tend to experience neurocognitive deficits which may limit their capacity to engage in some interventions, this does not appear to be the case for young people with affective disorders.

Modelling change in neurocognition, symptoms and functioning in young people with emerging mental disorders.

Mental disorders and their functional impacts evolve dynamically over time. Neurocognition and clinical symptoms are commonly modelled as predictors of functioning, however, studies tend to rely on static variables and adult samples with chronic disorders, with limited research investigating change in these variables in young people with emerging mental disorders. These relationships were explored in a longitudinal clinical cohort of young people accessing early intervention mental health services in Australia, around three-quarters of whom presented with a mood disorder (N = 176, aged 12-30 at baseline). Bivariate latent change score models quantified associations between neurocognition (a latent variable of working memory, verbal memory, visuospatial memory, and cognitive flexibility), global clinical symptoms, and functioning (self- and clinician-rated) and their relative change over follow-up (median = 20 months). We found that longitudinal changes in functioning were coupled with changes in global clinical symptoms (ß = -0.43, P < 0.001), such that improvement in functioning was related to improvement in clinical symptoms. Changes in neurocognition were not significantly associated with changes in functioning or clinical symptoms. Main findings were upheld in three sensitivity analyses restricting the sample to: (a) adults aged 18-30; (b) participants with 12-24 months of follow-up; and (c) participants without a psychotic disorder. Our findings show that global symptom reduction and functional improvement are related in young people with emerging mental disorders. More work is needed to determine the temporal precedence of change in these variables. Future studies should apply this methodology to intervention studies to untangle the causal dynamics between neurocognition, symptoms, and functioning.

Reward-related attentional capture and cognitive inflexibility interact to determine greater severity of compulsivity-related problems.

BACKGROUND AND OBJECTIVES: Neurocognitive processes are key drivers of addictive and compulsive disorders. The current study examined whether reward-related attentional capture and cognitive inflexibility are associated with impulsive and/or compulsive personality traits, and whether these cognitive characteristics interact to predict greater compulsivity-related problems across obsessive-compulsive and drinking behaviors. METHODS: One-hundred and seventy-three participants (mean age = 34.5 years, S.D = 8.4, 42% female) completed an online visual search task to measure reward-related attentional capture and its persistence following reversal of stimulus-reward contingencies. Participants also completed questionnaires to assess trait impulsivity, compulsivity, alcohol use, and obsessive-compulsive behaviors. RESULTS: Greater reward-related attentional capture was associated with trait compulsivity, over and above all impulsivity dimensions, while greater cognitive inflexibility was associated with higher negative urgency (distress-elicited impulsivity). Reward-related attentional capture and cognitive inflexibility interacted to predict greater compulsivity-related problems among participants who reported obsessive-compulsive behaviors in the past month (n = 57) as well as current drinkers (n = 88). Follow-up analyses showed that, for OCD behaviors, this interaction was driven by an association between higher reward-related attentional capture and more problematic behaviors among cognitively inflexible participants only. For drinking, the same pattern was seen, albeit at trend level. LIMITATIONS: This study includes a non-clinical, online sample and is cross-sectional, thus its findings need to be interpreted with these limitations in mind. CONCLUSIONS: Reward-related attentional capture and cognitive flexibility are related to trait compulsivity and impulsivity (negative urgency) respectively, and interact to determine more problematic behaviors.

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.

Transdiagnostic neurocognitive subgroups and functional course in young people with emerging mental disorders: a cohort study.

BACKGROUND: Neurocognitive impairments robustly predict functional outcome. However, heterogeneity in neurocognition is common within diagnostic groups, and data-driven analyses reveal homogeneous neurocognitive subgroups cutting across diagnostic boundaries. AIMS: To determine whether data-driven neurocognitive subgroups of young people with emerging mental disorders are associated with 3-year functional course. METHOD: Model-based cluster analysis was applied to neurocognitive test scores across nine domains from 629 young people accessing mental health clinics. Cluster groups were compared on demographic, clinical and substance-use measures. Mixed-effects models explored associations between cluster-group membership and socio-occupational functioning (using the Social and Occupational Functioning Assessment Scale) over 3 years, adjusted for gender, premorbid IQ, level of education, depressive, positive, negative and manic symptoms, and diagnosis of a primary psychotic disorder. RESULTS: Cluster analysis of neurocognitive test scores derived three subgroups described as 'normal range' (n = 243, 38.6%), 'intermediate impairment' (n = 252, 40.1%), and 'global impairment' (n = 134, 21.3%). The major mental disorder categories (depressive, anxiety, bipolar, psychotic and other) were represented in each neurocognitive subgroup. The global impairment subgroup had lower functioning for 3 years of follow-up; however, neither the global impairment (B = 0.26, 95% CI -0.67 to 1.20; P = 0.581) or intermediate impairment (B = 0.46, 95% CI -0.26 to 1.19; P = 0.211) subgroups differed from the normal range subgroup in their rate of change in functioning over time. CONCLUSIONS: Neurocognitive impairment may follow a continuum of severity across the major syndrome-based mental disorders, with data-driven neurocognitive subgroups predictive of functional course. Of note, the global impairment subgroup had longstanding functional impairment despite continuing engagement with clinical services.

Modelling associations between neurocognition and functional course in young people with emerging mental disorders: a longitudinal cohort study.

Neurocognitive impairment is commonly associated with functional disability in established depressive, bipolar and psychotic disorders. However, little is known about the longer-term functional implications of these impairments in early phase transdiagnostic cohorts. We aimed to examine associations between neurocognition and functioning at baseline and over time. We used mixed effects models to investigate associations between neurocognitive test scores and longitudinal social and occupational functioning ("Social and Occupational Functioning Assessment Scale") at 1-7 timepoints over five-years in 767 individuals accessing youth mental health services. Analyses were adjusted for age, sex, premorbid IQ, and symptom severity. Lower baseline functioning was associated with male sex (coefficient -3.78, 95% CI -5.22 to -2.34 p < 0.001), poorer verbal memory (coefficient 0.90, 95% CI 0.42 to 1.38, p < 0.001), more severe depressive (coefficient -0.28, 95% CI -0.41 to -0.15, p < 0.001), negative (coefficient -0.49, 95% CI -0.74 to -0.25, p < 0.001), and positive symptoms (coefficient -0.25, 95% CI -0.41 to -0.09, p = 0.002) and lower premorbid IQ (coefficient 0.13, 95% CI 0.07 to 0.19, p < 0.001). The rate of change in functioning over time varied among patients depending on their sex (male; coefficient 0.73, 95% CI 0.49 to 0.98, p < 0.001) and baseline level of cognitive flexibility (coefficient 0.14, 95% CI 0.06 to 0.22, p < 0.001), such that patients with the lowest scores had the least improvement in functioning. Impaired cognitive flexibility is common and may represent a meaningful and transdiagnostic target for cognitive remediation in youth mental health settings. Future studies should pilot cognitive remediation targeting cognitive flexibility while monitoring changes in functioning.