Examining the unique relationships between problematic use of the internet and impulsive and compulsive tendencies: network approach.

BACKGROUND: Both impulsivity and compulsivity have been identified as risk factors for problematic use of the internet (PUI). Yet little is known about the relationship between impulsivity, compulsivity and individual PUI symptoms, limiting a more precise understanding of mechanisms underlying PUI. AIMS: The current study is the first to use network analysis to (a) examine the unique association among impulsivity, compulsivity and PUI symptoms, and (b) identify the most influential drivers in relation to the PUI symptom community. METHOD: We estimated a Gaussian graphical model consisting of five facets of impulsivity, compulsivity and individual PUI symptoms among 370 Australian adults (51.1% female, mean age = 29.8, s.d. = 11.1). Network structure and bridge expected influence were examined to elucidate differential associations among impulsivity, compulsivity and PUI symptoms, as well as identify influential nodes bridging impulsivity, compulsivity and PUI symptoms. RESULTS: Results revealed that four facets of impulsivity (i.e. negative urgency, positive urgency, lack of premeditation and lack of perseverance) and compulsivity were related to different PUI symptoms. Further, compulsivity and negative urgency were the most influential nodes in relation to the PUI symptom community due to their highest bridge expected influence. CONCLUSIONS: The current findings delineate distinct relationships across impulsivity, compulsivity and PUI, which offer insights into potential mechanistic pathways and targets for future interventions in this space. To realise this potential, future studies are needed to replicate the identified network structure in different populations and determine the directionality of the relationships among impulsivity, compulsivity and PUI symptoms.

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.

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.

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.

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.

Fear driven compulsive behaviour is associated with worse long-term outcome in obsessive-compulsive disorder.

OBJECTIVES: In this retrospective study of patients with obsessive-compulsive disorder (OCD), we assessed the relationship between different motivational drivers of compulsive behaviours and the response to naturalistic treatments (based mostly on high dose serotonin reuptake inhibitors [SRIs]). METHODS: Seventy-six OCD patients were assessed with a structured diagnostic interview; the Habit, Reward and Fear Scale-Revised (HRFS-R); the Yale-Brown Obsessive-Compulsive Scale (YBOCS); the Beck Depression Inventory (BDI); and the OCD Retrospective Assessment of Treatment Response (RATS), which includes information on SRIs administration (e.g., dose and duration of their use), augmentation strategies (such as antipsychotic use or exposure and response prevention intervention), and pre-treatment YBOCS scores. Patients were naturalistically followed up for a mean of 7.28 (SD 5.51) years. RESULTS: Analysis revealed that the fear subscore of the HRFS was the only significant predictor (among a detailed battery of demographic, clinical and treatment factors) independently associated with greater delta (pre-treatment minus post-treatment) YBOCS scores. CONCLUSIONS: In contrast to predictions (based on existing models), poorer treatment response was not associated with increased habit scores in the HRFS. Future longitudinal studies are needed to confirm whether increased fear as a driver for ritualistic behaviours is able to predict worse outcomes in OCD samples.

The relationship between obsessive-compulsive disorder and anxiety disorders: A question of diagnostic boundaries or simply severity of symptoms?

BACKGROUND: A growing number of studies are questioning the validity of current DSM diagnoses, either as "discrete" or distinct mental disorders and/or as phenotypically homogeneous syndromes. In this study, we investigated how symptom domains in patients with a main diagnosis of obsessive-compulsive disorder (OCD), panic disorder (PD) and social anxiety disorder (SAD) coaggregate. We predicted that symptom domains would be unrelated to DSM diagnostic categories and less likely to cluster with each other as severity increases. METHODS: One-hundred eight treatment seeking patients with a main diagnosis of OCD, SAD or PD were assessed with the Dimensional Obsessive-Compulsive Scale (DOCS), the Social Phobia Inventory (SPIN), the Panic and Agoraphobia Scale (PAS), the Anxiety Sensitivity Index-Revised (ASI-R), and the Beck Depression and Anxiety Inventories (BDI and BAI, respectively). Subscores generated by each scale (herein termed "symptom domains") were used to categorize individuals into mild, moderate and severe subgroups through K-means clusterization and subsequently analysed by means of multiple correspondence analysis. RESULTS: Broadly, we observed that symptom domains of OCD, SAD or PD tend to cluster on the basis of their severities rather than their DSM diagnostic labels. In particular, symptom domains and disorders were grouped into (1) a single mild "neurotic" syndrome characterized by multiple, closely related and co-occurring mild symptom domains; (2) two moderate (complicated and uncomplicated) "neurotic" syndromes (the former associated with panic disorder); and (3) severe but dispersed "neurotic" symptom domains. CONCLUSION: Our findings suggest that symptoms domains of treatment seeking patients with OCD and anxiety disorders tend to be better conceptualized in terms of severity rather than rigid diagnostic boundaries.

A study on the correlates of habit-, reward-, and fear-related motivations in alcohol use disorder.

OBJECTIVE: We assessed self-reported drives for alcohol use and their impact on clinical features of alcohol use disorder (AUD) patients. Our prediction was that, in contrast to "affectively" (reward or fear) driven drinking, "habitual" drinking would be associated with worse clinical features in relation to alcohol use and higher occurrence of associated psychiatric symptoms. METHODS: Fifty-eight Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) alcohol abuse patients were assessed with a comprehensive battery of reward- and fear-based behavioral tendencies. An 18-item self-report instrument (the Habit, Reward and Fear Scale; HRFS) was employed to quantify affective (fear or reward) and non-affective (habitual) motivations for alcohol use. To characterize clinical and demographic measures associated with habit, reward, and fear, we conducted a partial least squares analysis. RESULTS: Habitual alcohol use was significantly associated with the severity of alcohol dependence reflected across a range of domains and with lower number of detoxifications across multiple settings. In contrast, reward-driven alcohol use was associated with a single domain of alcohol dependence, reward-related behavioral tendencies, and lower number of detoxifications. CONCLUSION: These results seem to be consistent with a shift from goal-directed to habit-driven alcohol use with severity and progression of addiction, complementing preclinical work and informing biological models of addiction. Both reward-related and habit-driven alcohol use were associated with lower number of detoxifications, perhaps stemming from more benign course for the reward-related and lack of treatment engagement for the habit-related alcohol abuse group. Future work should further explore the role of habit in this and other addictive disorders, and in obsessive-compulsive related disorders.

A Systematic Meta-Review of Impulsivity and Compulsivity in Addictive Behaviors.

It is well established that poor inhibitory control confers both a vulnerability to, and maintenance of, addictive behaviors across the substance and behavioral spectrums. By comparison, the role of compulsivity in addictive behaviors has received less research focus. The neurocognitive literature to date is vast, and it is unclear whether there are any convincing lines of systematic evidence delineating whether and how aspects of impulsivity and compulsivity are shared and unique across different substance and behavioral addictive disorders. Such information has significant implications for our understanding of underlying mechanisms and clinical implications for assessing and treating neurocognitive deficits across addictions. Here, we conducted a systematic meta-review of the quantitative meta-analyses to date, specifically examining the neurocognitive functions central to impulsive-compulsive behaviors transdiagnostically across addictive behaviors. Out of 1186 empirical studies initially identified, six meta-analyses met inclusion criteria examining alcohol, cannabis, cocaine, MDMA, methamphetamine, opioid and tobacco use, as well as gambling and internet addiction. The pooled findings across the systematic meta-analyses suggest that impulsivity is a core process underpinning both substance and behavioral addictive disorders, although it is not equally implicated across all substances. Compulsivity-related neurocognition, by comparison, is important across alcohol and gambling disorders, but has yet to be examined systematically. The gestalt of findings to date suggests that both impulsivity and compulsivity are core constructs linked to addictive behaviors and may not be solely the secondary sequelae associated with the effects of prolonged substance exposure.