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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.
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.
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.
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.
Obsessions, compulsions and related phenomena occur across a wide spectrum of neuropsychiatric disorders. The boundaries between obsessive-compulsive disorder (OCD) and other psychopathological phenomena, such as delusions, impulsions and habits, remain unclear. Further, the subclinical symptoms of OCD are highly prevalent, causing significant impact but yet are poorly understood. To help address these limitations, recent debates have highlighted the importance of a transdiagnostic approach to psychiatry. This book integrates what is currently known about obsessionality, compulsivity and the boundaries of OCD and related disorders and unveils areas that are worthy of future research. Using a transdiagnostic framework, it provides a comprehensive review of the key issues to understanding the diagnosis and evaluation of OCD and related disorders, as well as describing how the clinician can treat OCD and its manifold presentations. Edited by leading specialists in the field, this book offers a global perspective to the diagnosis and treatment of these disorders.
Impulsivity 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.
A 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.
Addictive 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.
A 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.
Lithium and quetiapine are considered standard maintenance agents for bipolar disorder yet it is unclear how their efficacy compares with each other.
To investigate the differential effect of lithium and quetiapine on symptoms of depression, mania, general functioning, global illness severity and quality of life in patients with recently stabilised first-episode mania.
Maintenance trial of patients with first-episode mania stabilised on a combination of lithium and quetiapine, subsequently randomised to lithium or quetiapine monotherapy (up to 800 mg/day) and followed up for 1 year. (Trial registration: Australian and New Zealand Clinical Trials Registry – ACTRN12607000639426.)
In total, 61 individuals were randomised. Within mixed-model repeated measures analyses, significant omnibus treatment × visit interactions were observed for measures of overall psychopathology, psychotic symptoms and functioning. Planned and post hoc comparisons further demonstrated the superiority of lithium treatment over quetiapine.
In people with first-episode mania treated with a combination of lithium and quetiapine, continuation treatment with lithium rather than quetiapine is superior in terms of mean levels of symptoms during a 1-year evolution.
We aimed to determine whether individuals with obsessive-compulsive disorder (OCD) and demographically matched healthy individuals can be clustered into distinct clinical subtypes based on dimensional measures of their self-reported compulsivity (OBQ–44 and IUS–12) and impulsivity (UPPS–P).
Participants (n=217) were 103 patients with a clinical diagnosis of OCD; 79 individuals from the community who were “OCD-likely” according to self-report (Obsessive-Compulsive Inventory–Revised scores equal or greater than 21); and 35 healthy controls. All data were collected between 2013 and 2015 using self-report measures that assessed different aspects of compulsivity and impulsivity. Principal component analysis revealed two components broadly representing an individual's level of compulsivity and impulsivity. Unsupervised clustering grouped participants into four subgroups, each representing one part of an orthogonal compulsive-impulsive phenotype.
Clustering converged to yield four subgroups: one group low on both compulsivity and impulsivity, comprised mostly of healthy controls and demonstrating the lowest OCD symptom severity; two groups showing roughly equal clinical severity, but with opposing drivers (i.e., high compulsivity and low impulsivity, and vice versa); and a final group high on both compulsivity and impulsivity and recording the highest clinical severity. Notably, the largest cluster of individuals with OCD was characterized by high impulsivity and low compulsivity. Our results suggest that both impulsivity and compulsivity mediate obsessive-compulsive symptomatology.
Individuals with OCD can be clustered into distinct subtypes based on measures of compulsivity and impulsivity, with the latter being found to be one of the more defining characteristics of the disorder. These dimensions may serve as viable and novel treatment targets.
In this work, we built all sky index files from Gaia DR1 catalogue for the high-precision astrometric field solution and the precise WCS coordinates of the moving objects. For this, we used build-astrometry-index program as a part of astrometry.net code suit. Additionally, we added astrometry.net's WCS solution tool to our previously developed software which is a fast and robust pipeline for detecting moving objects such as asteroids and comets in sequential FITS images, called A-Track. Moreover, MPC module was added to A-Track. This module is linked to an asteroid database to name the found objects and prepare the MPC file to report the results. After these innovations, we tested a new version of the A-Track code on photometrical data taken by the SI-1100 CCD with 1-meter telescope at TÜBİTAK National Observatory, Antalya. The pipeline can be used to analyse large data archives or daily sequential data. The code is hosted on GitHub under the GNU GPL v3 license.
To determine the rates and associated illness characteristics of obsessive-compulsive disorder (OCD) patients who describe their symptoms as either rewarding or habitual.
Seventy-three treatment-seeking OCD patients had their dominant compulsive behavior assessed with a structured interview (the Temporal Impulsive-Compulsive Scale–Revised) to track the progression of rewarding (ie, gain in positive affect), aversive (ie, decrease in negative affect), and neutral (or non-affective) states and a self-report scale (the Self-Report Habit Index) to evaluate their habitual features. Additional measures included structured diagnostic interviews for axis I and II disorders, measures of OCD symptoms severity, and a battery of instruments to comprehensively assess relevant aspects of sensitivity to reward and fear.
Almost half (49%) of our OCD patients (particularly washers) endorsed that they anticipated obtaining a reward (ie, positive affect) from the enactment of their dominant compulsive behavior. Washers stood out in that their positive affects during and after compulsive behaviors were highly (and positively) correlated with duration of illness. In contrast, habit strength did not differ between washers, checkers, and arrangers, although it also correlated with duration of illness among checkers. Furthermore, the severity of OCD and comorbidity with impulse control disorders predicted up to 35% of the variance in the habit strength of OCD behaviors.
Compulsive washing may be more clearly characterized by problems in reward processing. In contrast, duration of checking, severity of OCD, and comorbidity with impulse control disorders shape compulsive behaviors by imparting them with habitual tendencies.
The aetiological boundary between obsessive–compulsive related disorders
(OCRDs) including obsessive–compulsive disorder (OCD) and anxiety
disorders is unclear and continues to generate debate.
To determine the genetic overlap and the pattern of causal relationships
among OCRDs and anxiety disorders.
Multivariate twin modelling methods and a new regression analysis to
infer causation were used, involving 2495 male and female twins.
The amount of common genetic liability observed for OCD symptoms was
higher when considering anxiety disorders and OCRDs in the model
v. modelling OCRD symptoms alone. OCD symptoms
emerged as risk factors for the presence of generalised anxiety, panic
and hoarding symptoms, whereas social phobia appeared as a risk factor
for OCD symptoms.
OCD represents a complex phenotype that includes important shared
features with anxiety disorders and OCRDs. The novel patterns of risk
identified between OCD and anxiety disorder may help to explain their
We investigated the morphology of multiple brain regions in a rare sample of
15 very heavy cannabis users with minimal psychiatric comorbidity or
significant exposure to other substances (compared with 15 age- and
IQ-matched non-cannabis-using controls) using manual techniques. Heavy
cannabis users demonstrated smaller hippocampus and amygdala volumes, but no
alterations of the orbitofrontal and anterior- and paracingulate cortices,
or the pituitary gland. These findings indicate that chronic cannabis use
has a selective and detrimental impact on the morphology of the