Among those with common mental health disorders (e.g. mood, anxiety, and stress disorders), comorbidity of substance and other addictive disorders is prevalent. To simplify the seemingly complex relationships underlying such comorbidity, methods that include multiple measures to distill which specific addictions are uniquely associated with specific mental health disorders rather than due to the co-occurrence of other related addictions or mental health disorders can be used.

In a general population sample of Jewish adults in Israel (N = 4002), network analysis methods were used to create partial correlation networks of continuous measures of problematic substance (non-medical use of alcohol, tobacco, cannabis, and prescription sedatives, stimulants, and opioid painkillers) and behavioral (gambling, electronic gaming, sexual behavior, pornography, internet, social media, and smartphone) addictions and common mental health problems (depression, anxiety, and post-traumatic stress disorder [PTSD]), adjusted for all variables in the model.

Strongest associations were observed within these clusters: (1) PTSD, anxiety, and depression; (2) problematic substance use and gambling; (3) technology-based addictive behaviors; and (4) problematic sexual behavior and pornography. In terms of comorbidity, the strongest unique associations were observed for PTSD and problematic technology-based behaviors (social media, smartphone), and sedatives and stimulants use; depression and problematic technology-based behaviors (gaming, internet) and sedatives and cannabis use; and anxiety and problematic smartphone use.

Network analysis isolated unique relationships underlying the observed comorbidity between common mental health problems and addictions, such as associations between mental health problems and technology-based behaviors, which is informative for more focused interventions.

Different components of the endocannabinoid (eCB) system such as their most well-known endogenous ligands, anandamide (AEA) and 2-arachidonoylglycerol (2-AG), have been implicated in brain reward pathways. While shared neurobiological substrates have been described among addiction-related disorders, information regarding the role of this system in behavioral addictions such as gambling disorder (GD) is scarce.

Fasting plasma concentrations of AEA and 2-AG were analyzed in individuals with GD at baseline, compared with healthy control subjects (HC). Through structural equation modeling, we evaluated associations between endocannabinoids and GD severity, exploring the potentially mediating role of clinical and neuropsychological variables.

The sample included 166 adult outpatients with GD (95.8% male, mean age 39 years old) and 41 HC. Peripheral blood samples were collected after overnight fasting to assess AEA and 2-AG concentrations (ng/ml). Clinical (i.e., general psychopathology, emotion regulation, impulsivity, personality) and neuropsychological variables were evaluated through a semi-structured clinical interview and psychometric assessments.

Plasma AEA concentrations were higher in patients with GD compared with HC (p = .002), without differences in 2-AG. AEA and 2-AG concentrations were related to GD severity, with novelty-seeking mediating relationships.

This study points to differences in fasting plasma concentrations of endocannabinoids between individuals with GD and HC. In the clinical group, the pathway defined by the association between the concentrations of endocannabinoids and novelty-seeking predicted GD severity. Although exploratory, these results could contribute to the identification of potential endophenotypic features that help optimize personalized approaches to prevent and treat GD.

Addictive behaviors on the workplace are a real public health problem because of its consequences not only on workers but also on productivity at work.

To explore the relationship between addictive behaviors and productivity at work among employees of a Tunisian oil rig.

A cross-sectional study was conducted in the first half of 2018. The assessment of work productivity was done using the validated WPAI-GH questionnaire. Smoking dependence was assessed via the Fagerström score and alcohol abuse by the FACE questionnaire.

It was 94 employees working in an onshore oil field with an average age of 41.1 years. Average job seniority was 14.3 years. Active smoking was noted in 34.7% of cases. Alcohol consumption was noted in 19.1% of cases. In the 7 days preceding the survey, the average percentage of absenteeism was 3.64 ± 21.7% and the presenteeism was 17.66 ± 25.58%. The average decline in productivity was 14.8 ± 43.7% and the average decline in daily activities was 20.21 ± 31.45%. These parameters were not correlated with smoking and alcoholism.

Addictive behaviors in the workplace still a denied reality.Increasing awareness and clarifying expectations can be a good first step in order to ameliorate employee functioning and decrease productivity problems.