The ways in which perceived harm due to substance use affects relationships between psychotic and suicidal experiences are poorly understood. The goal of the current study was to redress this gap by investigating the moderating effects of harm due to substance use on pathways involving positive psychotic symptoms, the perceived cognitive-emotional sequelae of those symptoms, and suicidal ideation.

The design was cross-sectional. Mediation and moderated mediation pathways were tested. The predictor was severity of positive psychotic symptoms. Cognitive interpretative and emotional characteristics of both auditory hallucinations and delusions were mediators. Suicidal ideation was the outcome variable. General symptoms associated with severe mental health problems were statistically controlled for.

There was evidence of an indirect pathway between positive psychotic symptom severity and suicidal ideation via cognitive interpretation and emotional characteristics of both auditory hallucinations and delusions. Harm due to drug use, but not alcohol use, moderated the indirect pathway involving delusions such that it was most prominent when harm due to drug use was at medium-to-high levels. The components of suicidal ideation that were most strongly affected by this moderated indirect pathway were active intent, passive desire, and lack of deterrents.

From both scientific and therapy development perspectives, it is important to understand the complex interplay between, not only the presence of auditory hallucinations and delusions, but the ensuing cognitive and emotional consequences of those experiences which, when combined with harm associated with substance use, in particular drug use, can escalate suicidal thoughts and acts.

Machine learning could predict binge behavior and help develop treatments for bulimia nervosa (BN) and alcohol use disorder (AUD). Therefore, this study evaluates person-specific and pooled prediction models for binge eating (BE), alcohol use, and binge drinking (BD) in daily life, and identifies the most important predictors.

A total of 120 patients (BN: 50; AUD: 51; BN/AUD: 19) participated in an experience sampling study, where over a period of 12 months they reported on their eating and drinking behaviors as well as on several other emotional, behavioral, and contextual factors in daily life. The study had a burst-measurement design, where assessments occurred eight times a day on Thursdays, Fridays, and Saturdays in seven bursts of three weeks. Afterwards, person-specific and pooled models were fit with elastic net regularized regression and evaluated with cross-validation. From these models, the variables with the 10% highest estimates were identified.

The person-specific models had a median AUC of 0.61, 0.80, and 0.85 for BE, alcohol use, and BD respectively, while the pooled models had a median AUC of 0.70, 0.90, and 0.93. The most important predictors across the behaviors were craving and time of day. However, predictors concerning social context and affect differed among BE, alcohol use, and BD.

Pooled models outperformed person-specific models and the models for alcohol use and BD outperformed those for BE. Future studies should explore how the performance of these models can be improved and how they can be used to deliver interventions in daily life.

Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians.

In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance.

Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12.

Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.

Recreational drug use has become more and more accepted in society. Availability and purity are rising and new psychoactive substances (NPS) are popping up.

The aim of this study was to provide objective data on illicit drug use at a Belgian festival in order to report on arising trends. This may provide additional information to help develop preventive strategies.

A cross-sectional study took place during a music festival in the summer of 2019, where 43 samples of pooled urine were collected at four different locations and at different moments of the day. Analysis was performed using gas chromatography with a flame ionization detector (GC-FID) to determine ethanol concentrations. Drugs of abuse were quantified using liquid chromatography-tandem mass spectrometry. A qualitative analysis was performed using high-resolution mass spectrometry.

Median ethanol concentration was 0.88g/L. Cocaine, 3,4-methylenedioxymethamphetamine (MDMA), amphetamines, ketamine, and cannabis were detected in almost every sample and often in high concentrations. Furthermore, two NPS were detected and a variety of over-the-counter medication and adulterants were also found.

The findings were largely in-line with trends outlined in the European Drug Report. Striking were the relatively high concentrations of MDMA and ketamine and detection of two synthetic cathinones. Two possible adulterants of cocaine were detected, namely flecainide and amlodipine.

Music festivals are considered a high-risk setting for alcohol consumption and illicit drug use. Analysis of pooled urine samples at a festival therefore provides a valuable method to evaluate trends and to screen for new substances. Wide-spread use of classical drugs and identification of two NPS were observed during a major international music festival in Belgium. Results need to be interpreted carefully, taking into account the possibilities and limitations of the used techniques and a standardized sampling is required.

The survey assessed changes in tobacco, alcohol and other substance use during the COVID-19 pandemic.

The survey was carried out in Moscow and Nizhegorodskaya Oblast in December, 2020 - February, 2021 and included 650 medical organizations’ employees and 344 individuals with harmful alcohol or other substances use.

The instrument included ASSIST, Kessler-10 and IES-R tests modified for self-reporting about different pandemic periods.

Among medical workers 36.8% smoked last 12 months; during the COVID-19 pandemic 13% maintained usual cigarette smoking level, 2.4% increased smoking during incidence rises. 71.2% drank alcohol last 12 months; during incidence rises 20.4% drank as usual, 15.0% drank less frequently; 2.4% increased frequency of drinking, 1.8% volumes on drinking days, 1.3% frequency of heavy episodic drinking. In harmful substance use group 61.9% smoked last 12 months; during COVID-19 incidence rises 40% kept their usual level of smoking; 13.4% increased their smoking during the first and 8.7% during the second ‘wave’ of the pandemic. 90.1% drank alcohol last 12 months; during incidence rises 49% kept drinking as usual, 20% reduced drinking and 17.3% increased drinking frequency, 21.0% volumes on drinking days, 16.4% heavy episodic drinking frequency. Wastewater-based epidemiology analysis performed in Moscow Oblast location demonstrated significant increase during COVID-19 pandemic, compared to same period 2 years earlier: inhaled nicotine use by average of 40%, ethanol consumption by average of 49%.

Changes in cigarette smoking and alcohol use during the COVID-19 pandemic had significant variation. Increases were more likely to occur during the pandemic ‘waves’ among individual from harmful users’ group.

No significant relationships.

No significant relationships.

The influence of sexual hormones on mental disorders have been extensively reported. In fact, recent studies suggest that sex hormones may play a relevant role in the pathophysiology of psychosis, may be a precipitant when exogenously administered or even be used as a treatment agent of psychotic disorders.

To describe the case of a patient with a recent diagnosis of delusional disorder (DD) with an onset in the perimenopausal period.

Case report and narrative review focused on the impact of sexual hormones on depressive symptoms and alcohol use comorbidity during perimenopause in DD women by using PubMed database.

Case report: A 48-year-old woman diagnosed with DD. The clinical assessment of climacteric symptoms, as well as the gonadotropins (elevated levels of follicle-stimulating hormone -FSH- and luteinizing hormone -LH-) and estrogen levels monitoring (variations on 17-β-estradiol -E2-) enabled to link the endocrine changes with the onset and course of the psychiatric disorder. During the development of the disease, the patient also presented comorbid depressive symptoms and alcohol use disorder. Review: Estrogen depletion seems to increase the risk of psychosis, while scientific literature is not conclusive in establishing a definitive relationship between depressive symptoms and hormonal imbalance in DD. Alcohol use disorder is a common comorbidity in both perimenopausal women and patients with DD.

Multiaxial management of the case helped clinicians to achieve clinical stabilization. Sex differences as well as hormonal pattern disturbances should receive special attention due to the seminal implications in pharmacotherapy and clinical outcomes.

No significant relationships.

It remains unclear whether substance use in youth could be associated with a lower likelihood of accessing employment.

To examine prospectively associations between substance use and the risk of not getting employed among young people.

From the French population-based CONSTANCES cohort, 2,873 students who never worked were included between 2012 and 2018 and followed-up for 2.7 years in average. Generalized estimating equations computed the odds of being unemployed versus employed according to substance use at baseline controlling for sociodemographic factors and depressive state. Tobacco use (smoking status and number of cigarettes), cannabis use frequency, and at-risk alcohol use according to the Alcohol Use Disorder Identification Test (total score >7) were introduced separately in the models.

Tobacco use wasn’t significantly associated with employment. Cannabis use at least weekly, and at-risk alcohol use, were associated with increased odds of being unemployed (OR=1.85, 95%CI(1.29, 2.64)) and OR=1.34, 95%CI(1.04, 1.71)), respectively. Additional analyses on sub-scores of alcohol use suggested that the association was mainly driven by alcohol dependence rather than frequency of use.

Public health campaigns must target youth by advising them of the detrimental roles of regular cannabis use and at-risk alcohol use and their lower chances of getting employed.

No significant relationships.

Responses to the COVID-19 pandemic have included lockdowns and social distancing with considerable disruptions to people's lives. These changes may have particularly impacted on those with mental health problems, leading to a worsening of inequalities in the behaviours which influence health.

We used data from four national longitudinal British cohort studies (N = 10 666). Respondents reported mental health (psychological distress and anxiety/depression symptoms) and health behaviours (alcohol, diet, physical activity and sleep) before and during the pandemic. Associations between pre-pandemic mental ill-health and pandemic mental ill-health and health behaviours were examined using logistic regression; pooled effects were estimated using meta-analysis.

Worse mental health was related to adverse health behaviours; effect sizes were largest for sleep, exercise and diet, and weaker for alcohol. The associations between poor mental health and adverse health behaviours were larger during the May lockdown than pre-pandemic. In September, when restrictions had eased, inequalities had largely reverted to pre-pandemic levels. A notable exception was for sleep, where differences by mental health status remained high. Risk differences for adverse sleep for those with the highest level of prior mental ill-health compared to those with the lowest were 21.2% (95% CI 16.2–26.2) before lockdown, 25.5% (20.0–30.3) in May and 28.2% (21.2–35.2) in September.

Taken together, our findings suggest that mental health is an increasingly important factor in health behaviour inequality in the COVID era. The promotion of mental health may thus be an important component of improving post-COVID population health.

Academic procrastination is a specific sub-type of procrastination, assessing the tendency to delay academic tasks in connection with the preparation of courses or exams.

To determine the impact of academic procrastination on studies and academic performances and identify associated factors.

We conducted a cross-sectional descriptive study in students from three different universities: a medical school, a law school and an engineering school. Socio-demographic, clinical and academic data were collected. Procrastination was assessed using the Academic Procrastination Scale. We further administered the Short Version of the impulsive behaviour scale, the Satisfaction with Life Scale, the Perfectionism scale, and the one item Self-esteem Scale.

Our sample consisted of 1019 students. The mean age was 22 ± 2.25 years, and 62% were females. About one third of study participants used tobacco or alcohol, and 10% used drugs (cannabis or others). We found a significant positive correlation between procrastination and academic failure (r=0.22 p= 0.00) and a negative correlation with academic success (r= -0.27 p=0.00). Multivariate regression analysis showed the following risk factors for academic procrastination: alcohol consumption (ORa= 1.74 [1.14; 2.67]), study field (with reference to medicine: law ORa= 1.50 [1.02; 2.19], engineering studies ORa= 2.01 [1.34; 3.02]), and impulsivity (ORa= 2.11 [1.55; 2.86]).

Academic procrastination has a negative impact on academic achievement and performance. This impact appears to differ depending on the field of study. It also seems closely related to impulsiveness and alcohol use. Our findings might contribute to find new ways of helping students to improve academic performance.

No significant relationships.

No significant relationships.

Alcohol consumption, smoking and mood disorders are leading contributors to the global burden of disease and are highly comorbid. Yet, their interrelationships have remained elusive. The aim of this study was to examine the multi-cross-sectional and longitudinal associations between (change in) smoking and alcohol use and (change in) number of depressive symptoms.

In this prospective, longitudinal study, 6646 adults from the general population were included with follow-up measurements after 3 and 6 years. Linear mixed-effects models were used to test multi-cross-sectional and longitudinal associations, with smoking behaviour, alcohol use and genetic risk scores for smoking and alcohol use as independent variables and depressive symptoms as dependent variables.

In the multi-cross-sectional analysis, smoking status and number of cigarettes per day were positively associated with depressive symptoms (p < 0.001). Moderate drinking was associated with less symptoms of depression compared to non-use (p = 0.011). Longitudinally, decreases in the numbers of cigarettes per day and alcoholic drinks per week as well as alcohol cessation were associated with a reduction of depressive symptoms (p = 0.001–0.028). Results of genetic risk score analyses aligned with these findings.

While cross-sectionally smoking and moderate alcohol use show opposing associations with depressive symptoms, decreases in smoking behaviour as well as alcohol consumption are associated with improvements in depressive symptoms over time. Although we cannot infer causality, these results open avenues to further investigate interventions targeting smoking and alcohol behaviours in people suffering from depressive symptoms.

Structural variation in subcortical brain regions has been linked to substance use, including the most commonly used substances nicotine and alcohol. Pre-existing differences in subcortical brain volume may affect smoking and alcohol use, but there is also evidence that smoking and alcohol use can lead to structural changes.

We assess the causal nature of the complex relationship of subcortical brain volume with smoking and alcohol use, using bi-directional Mendelian randomisation.

Mendelian randomisation uses genetic variants predictive of a certain ‘exposure’ as instrumental variables to test causal effects on an ‘outcome’. Because of random assortment at meiosis, genetic variants should not be associated with confounders, allowing less biased causal inference. We used summary-level data of genome-wide association studies of subcortical brain volumes (nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen and thalamus; n = 50 290) and smoking and alcohol use (smoking initiation, n = 848 460; cigarettes per day, n = 216 590; smoking cessation, n = 378 249; alcoholic drinks per week, n = 630 154; alcohol dependence, n = 46 568). The main analysis, inverse-variance weighted regression, was verified by a wide range of sensitivity methods.

There was strong evidence that liability to alcohol dependence decreased amygdala and hippocampal volume, and smoking more cigarettes per day decreased hippocampal volume. From subcortical brain volumes to substance use, there was no or weak evidence for causal effects.

Our findings suggest that heavy alcohol use and smoking can causally reduce subcortical brain volume. This adds to accumulating evidence that alcohol and smoking affect the brain, and likely mental health, warranting more recognition in public health efforts.