Background Several behaviors, besides psychoactive substance ingestion, produce short-term reward that may engender persistent behavior despite knowledge of adverse consequences, i.e., diminished control over the behavior. These disorders have historically been conceptualized in several ways. One view posits these disorders as lying along an impulsive-compulsive spectrum, with some classified as impulse control disorders. An alternate, but not mutually exclusive, conceptualization considers the disorders as non-substance or “behavioral” addictions. Objectives Inform the discussion on the relationship between psychoactive substance and behavioral addictions. Methods: We review data illustrating similarities and differences between impulse control disorders or behavioral addictions and substance addictions. This topic is particularly relevant to the optimal classification of these disorders in the forthcoming fifth edition of the American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders. Results Growing evidence suggests that behavioral addictions resemble substance addictions in many domains, including natural history, phenomenology, tolerance, comorbidity, overlapping genetic contribution, neurobiological mechanisms, and response to treatment, supporting the DSM-V Task Force proposed new category of Addiction and Related Disorders encompassing both substance use disorders and non-substance addictions. Current data suggest that this combined category may be appropriate for pathological gambling and a few other better studied behavioral addictions, e.g., Internet addiction. There is currently insufficient data to justify any classification of other proposed behavioral addictions. Conclusions and Scientific Significance Proper categorization of behavioral addictions or impulse control disorders has substantial implications for the development of improved prevention and treatment strategies.

Background: There is growing concern about possible cognitive consequences of COVID-19, with reports of 'Long COVID' symptoms persisting into the chronic phase and case studies revealing neurological problems in severely affected patients. However, there is little information regarding the nature and broader prevalence of cognitive problems post-infection or across the full spread of disease severity. Methods: We sought to confirm whether there was an association between cross-sectional cognitive performance data from 81,337 participants who between January and December 2020 undertook a clinically validated web-optimized assessment as part of the Great British Intelligence Test, and questionnaire items capturing self-report of suspected and confirmed COVID-19 infection and respiratory symptoms. Findings: People who had recovered from COVID-19, including those no longer reporting symptoms, exhibited significant cognitive deficits versus controls when controlling for age, gender, education level, income, racial-ethnic group, pre-existing medical disorders, tiredness, depression and anxiety. The deficits were of substantial effect size for people who had been hospitalised (N = 192), but also for non-hospitalised cases who had biological confirmation of COVID-19 infection (N = 326). Analysing markers of premorbid intelligence did not support these differences being present prior to infection. Finer grained analysis of performance across sub-tests supported the hypothesis that COVID-19 has a multi-domain impact on human cognition. Interpretation: Interpretation. These results accord with reports of 'Long Covid' cognitive symptoms that persist into the early-chronic phase. They should act as a clarion call for further research with longitudinal and neuroimaging cohorts to plot recovery trajectories and identify the biological basis of cognitive deficits in SARS-COV-2 survivors.

This article is a critical review of risk factors for pathological gambling categorized by demographics, physiological and biological factors, cognitive distortions, comorbidity and concurrent symptoms, and personality symptoms and characteristics. There is also a varia section (availability, parents playing, sensory characteristics, schedules of reinforcement, age of onset, and playing duration). The review found very few well established risk factors for pathological gambling (i.e. more than two studies to support the conclusions). Well established risk factors included demographic variables (age, gender), cognitive distortions (erroneous perceptions, illusion of control), sensory characteristics, schedules of reinforcement, comorbid disorders (OCD, drug abuse), and delinquency/illegal acts. An understanding of risk factors for pathological gambling should enhance prevention and treatment approaches.

clinicaltrials.gov Identifier: NCT00354770.

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