Aims: Due to the increasing evidence of shared vulnerabilities between addictive behaviors and excessive food intake, the concept of food addiction in specific clinical populations has become a topic of scientific interest. The aim of this study was to validate the Yale Food Addiction Scale (YFAS) 2.0 in a Spanish sample. We also sought to explore food addiction and its clinical correlates in eating disorder (ED) and gambling disorder (GD) patients.Methods: The sample included 301 clinical cases (135 ED and 166 GD), diagnosed according to DSM-5 criteria, and 152 healthy controls (HC) recruited from the general population.Results: Food addiction was more prevalent in patients with ED, than in patients with GD and HC (77.8, 7.8, and 3.3%, respectively). Food addiction severity was associated with higher BMI, psychopathology and specific personality traits, such as higher harm avoidance, and lower self-directedness. The psychometrical properties of the Spanish version of the YFAS 2.0 were excellent with good convergent validity. Moreover, it obtained good accuracy in discriminating between diagnostic subtypes.Conclusions: Our results provide empirical support for the use of the Spanish YFAS 2.0 as a reliable and valid tool to assess food addiction among several clinical populations (namely ED and GD). The prevalence of food addiction is heterogeneous between disorders. Common risk factors such as high levels of psychopathology and low self-directedness appear to be present in individuals with food addiction.

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This study cross-sectionally examines in the elderly population: (a) the association of type 2 diabetes with executive function (EF); (b) the effect of BMI on both type 2 diabetes and EF; (c) the association between glycaemia control and EF in type 2 diabetes. 6823 older individuals with overweight/obesity and metabolic syndrome participating in the PREDIMED-PLUS study, were assessed with a battery of cognitive tests and a medical interview. ANOVA showed a significantly worse performance on EF in type 2 diabetes vs. non-diabetic individuals. Two complementary models were displayed: (1) in the whole sample, the presence of type 2 diabetes, depressive symptoms and BMI had a direct negative effect on EF, while apnoea had an indirect negative effect; (2) in the diabetes subsample, higher illness duration was associated with worse performance in EF. Participants with type 2 diabetes and HbA1c<53 mmol/mol displayed better cognitive performance when compared to those with HbA1c≥53 mmol/mol. Our results provide a controlled comprehensive model that integrates relevant neuropsychological and physical variables in type 2 diabetes. The model suggests that, to improve treatment adherence and quality of life once diabetes has been diagnosed, cognitive decline prevention strategies need to be implemented while monitoring depressive symptoms, BMI and glycaemia control.

Background and aimsThe recent growth of Internet use has led to an increase of potentially problematic behaviors that can be engaged online, such as online gambling or Internet gaming. The aim of this study is to better conceptualize Internet gaming disorder (IGD) by comparing it with gambling disorder (GD) patients who only gamble online (online GD).MethodsA total of 288 adult patients (261 online GD and 27 IGD) completed self-reported questionnaires for exploring psychopathological symptoms, food addiction (FA), and personality traits.ResultsBoth clinical groups presented higher psychopathological scores and less functional personality traits when compared with a normative Spanish population. However, when comparing IGD to online GD, some singularities emerged. First, patients with IGD were younger, more likely single and unemployed, and they also presented lower age of disorder onset. In addition, they displayed lower somatization and depressive scores together with lower prevalence of tobacco use but higher FA scores and higher mean body mass index. Finally, they presented lower novelty seeking and persistence traits.DiscussionGD is fully recognized as a behavioral addiction, but IGD has been included in the Appendix of DSM-5 as a behavioral addiction that needs further study. Our findings suggest that IGD and online GD patients share some emotional distress and personality traits, but patients with IGD also display some differential characteristics, namely younger age, lower novelty seeking scores and higher BMI, and FA scores.ConclusionsIGD presents some characteristics that are not extensive to online GD. These specificities have potential clinical implications and they need to be further studied.

Our results point to an association between food addiction severity levels and impairments in decision-making and attentional capacity in individuals with OB. Given the heterogeneity found in OB, it stands to reason that this subset of patients with food addiction could potentially benefit from interventions targeting neuropsychological deficits.

Impulsivity is a multidimensional construct. Although gambling disorder (GD) has been associated with high impulsivity, impulsivity across multiple domains has not been thoroughly investigated in this population. We first aimed to examine whether associations between three facets of impulsivity (response impulsivity, choice impulsivity and impulsive tendency) varied between GD patients and healthy controls (HC). We next aimed to evaluate relationships between these three types of impulsivity, as proposed by theoretical models of impulsivity, and their associations with GD severity. The sample included 97 treatment-seeking adult men with GD, diagnosed according to DSM-5 criteria, and 32 male HCs recruited from the general population. Greater impulsivity in all three domains was found in men with GD in comparison to men without GD. Associations between impulsivity facets were found in both groups, with response impulsivity being the only domain associated with GD severity. Our findings confirm that multiple domains of impulsivity are relevant in GD. Future studies should examine the extent to which treatments aimed at targeting specific aspects of impulsivity improve outcomes. Although impulsivity has been proposed as a multifactorial construct 1 , there is still a lack of consensus regarding its definition and the independence of impulsivity domains 2. Impulsivity has been defined as a tendency to respond with little forethought, often with disregard to the negative consequences to the impulsive individual or others 3. Impulsivity has been found to factor into multiple forms, including response and choice forms, that can be measured across species 4-7. While multiple theoretical models have been proposed different types of impulsivity, the proposal by MacKillop et al. 8 is widely used and validated in different populations. This model posits that impulsivity can be partitioned into three main domains: response impulsivity, choice impulsivity and impulsive tendencies. Response impulsivity, also termed impulsive action or motor impulsivity, involves impairments in delaying, withholding or interrupting inappropriate responses 4,9. High levels of this type of impulsivity have been associated with gambling disorder (GD), with GD participants demonstrating differences in response impulsivity in comparison with healthy control (HC) participants 10 , including within treatment-seeking samples 11. Multiple studies suggest gambling severity is positively correlated with motor impulsivity 9,12,13 and one recent meta-analysis found GD to be associated with significant impairments in motor and attentional inhibition 14. Delay discounting relates to impulsive choice and the extent to which an individual prefers a smaller-sooner over a larger-later reward 5,15. In the case of GD, cognitive disturbances related to risk-reward decision making have been reported 16,17 , and individuals with GD tend to discount rewards more steeply than controls 18-21. Increasing evidence supports that people with gambling problems prefer to obtain ...

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To identify Gambling Disorder (GD) subtypes, in a population of men seeking treatment for GD, according to specific executive function domains (i.e., cognitive flexibility, inhibition and working memory as well as decision making) which are usually impaired in addictive behaviors. A total of 145 males ranging from 18 to 65 years diagnosed with GD were included in this study. All participants completed: (a) a set of questionnaires to assess psychopathological symptoms, personality and impulsivity traits, and (b) a battery of neuropsychological measures to test different executive functioning domains. Two clusters were identified based on the individual performance on the neuropsychological assessment. Cluster 1 [n = 106; labeled as Low Impaired Executive Function (LIEF)] was composed by patients with poor results in the neuropsychological assessment; cluster 2 patients [n = 46; labeled as High Impaired Executive Function (HIEF)] presented significantly higher deficits on the assessed domains and performed worse than the ones of LIEF cluster. Regarding the characterization of these two clusters, patients in cluster 2 were significantly older, unemployed and registered higher mean age of GD onset than patients in cluster 1. Additionally, patients in cluster 2 also obtained higher psychopathological symptoms, impulsivity (in both positive and negative urgency as well as sensation seeking) and some specific personality traits (higher harm avoidance as well as lower self-directedness and cooperativeness) than patients in cluster 1. The results of this study describe two different GD subtypes based on different cognitive domains (i.e., executive function performance). These two GD subtypes display different impulsivity and personality traits as well as clinical symptoms. The results provide new insight into the etiology and characterization of GD and have the potential to help improving current treatments.