Understanding the factors influencing alcohol use disorder (AUD) treatment outcomes is essential. More knowledge about patient characteristics that predict treatment outcomes can help personalise interventions, improve treatment planning and address the needs of specific subgroups. The frequency of treatment attendance may also affect drinking outcomes after treatment. Despite research efforts, uncertainty remains about how patient factors and treatment attendance influence treatment outcomes.

To examine how patient factors and treatment attendance predict high- or low-risk drinking at the end of treatment.

We used data (N = 92) from a multisite observational study of treatment-seeking individuals with AUD attending group treatment. Sociodemographic measures, alcohol and substance use measures, cognitive functioning, psychological distress, personality functioning and quality of life were screened in univariate analyses. Significant variables were entered into a binary logistic regression model.

Individuals with a higher percentage of treatment attendance (odds ratio 0.96 [95% CI 0.93, 0.96]) and with greater responsiblity scores on the Severity Indices of Personality Functioning (odds ratio 0.30 [95% CI 0.14, 0.64]) had a decreased likelihood of high-risk drinking at treatment end. Substance use, psychological distress and cognitive functioning were not associated with drinking levels at the end of treatment.

A higher percentage of treatment attendance has a minor effect on drinking levels. Being more responsible, as reflected in higher scores on the responsibility domain, reduces the likelihood of high-risk drinking at the end of treatment. Clinicians are encouraged to screen and assess personality functioning when planning treatment for individuals with AUD.

This study examines the prospective associations of alcohol and drug misuse with suicidal behaviors among service members who have left active duty. We also evaluate potential moderating effects of other risk factors and whether substance misuse signals increased risk of transitioning from thinking about to attempting suicide.

US Army veterans and deactivated reservists (N = 6,811) completed surveys in 2016–2018 (T1) and 2018–2019 (T2). Weights-adjusted logistic regression was used to estimate the associations of binge drinking, smoking/vaping, cannabis use, prescription drug abuse, illicit drug use, alcohol use disorder (AUD), and drug use disorder (DUD) at T1 with suicide ideation, plan, and attempt at T2. Interaction models tested for moderation of these associations by sex, depression, and recency of separation/deactivation. Suicide attempt models were also fit in the subgroup with ideation at T1 (n = 1,527).

In models controlling for socio-demographic characteristics and prior suicidality, binge drinking, cannabis use, prescription drug abuse, illicit drug use, and AUD were associated with subsequent suicidal ideation (AORs = 1.42–2.60, ps < .01). Binge drinking, AUD, and DUD were associated with subsequent suicide plan (AORs = 1.23–1.95, ps < .05). None of the substance use variables had a main effect on suicide attempt; however, interaction models suggested certain types of drug use predicted attempts among those without depression. Additionally, the effects of smoking/vaping and AUD differed by sex. Substance misuse did not predict the transition from ideation to attempt.

Alcohol and drug misuse are associated with subsequent suicidal behaviors in this population. Awareness of differences across sex and depression status may inform suicide risk assessment.

Externalizing and internalizing pathways may lead to the development of substance use behaviors (SUBs) and substance use disorders (SUDs), which are all heritable phenotypes. Genetic correlation studies have indicated differences in the genetic susceptibility between SUBs and SUDs. We investigated whether these substance use phenotypes are differently related to externalizing and internalizing problems at a genetic level.

We analyzed data from genome-wide association studies (GWAS) of four SUBs and SUDs, five externalizing traits, and five internalizing traits using the bivariate causal mixture model (MiXeR) to estimate genetic overlap beyond genetic correlation.

Two distinct patterns were found. SUBs demonstrated high genetic overlap but low genetic correlation of shared variants with internalizing traits, suggesting a pattern of mixed effect directions of shared genetic variants. Conversely, SUDs and externalizing traits exhibited considerable genetic overlap with moderate to high positive genetic correlation of shared variants, suggesting concordant effect direction of shared risk variants.

These results highlight the importance of the externalizing pathway in SUDs as well as the limited role of the internalizing pathway in SUBs. As MiXeR is not intended for the identification of specific genes, further studies are needed to reveal the underlying shared mechanisms of these traits.

The prevalence of alcohol use disorder among older adults is increasing, with this population being particularly vulnerable to alcohol’s detrimental effects. While knowledge of preventative factors is scarce, physical activity has emerged as a potential modifiable protective factor. This study aimed to examine associations between alcohol consumption and physical activity in a large-scale, multi-national prospective study of the older adult population.

Longitudinal data from the SHARE study on physical activity, alcohol consumption, demographic, socioeconomic, and health variables, were analyzed in older adults. Individual-level data were examined using logistic regression models. Both cross-sectional and longitudinal models were calculated to account for potential latency in the association between physical activity and alcohol consumption.

The study included 3133 participants from 13 countries. Higher physical activity levels were significantly associated with higher alcohol consumption in cross-sectional (p = 0.0004) and longitudinal analyses (p = 0.0045) over a median follow-up of 6 years. While the presence of depressive symptoms and higher educational attainment were associated with higher alcohol consumption, female sex and persons with lower perceived health showed lower frequency of alcohol consumption. Additionally, the country of residence also proved to be a relevant factor for alcohol consumption.

Higher levels of physical activity showed an association with higher alcohol consumption in older adults. Future research should investigate whether this association is causal and underpinned by neurobiological, social, or methodological factors.

Extant literature implicates the role of glucagon-like peptide-1 (GLP-1) and GLP-1 receptor agonists (GLP-1RAs) on modulating alcohol-associated behaviours, with a particular emphasis of these agents on neural circuits subserving reward and appetite control. Herein, we explore the potential effects of GLP-1RAs on alcohol-associated behaviours in brain regions implicated in reward processing facilitating the repurposing of these agents for the treatment and prevention of problematic drinking. Understanding how GLP-1’s analogues interact with alcohol-related behaviours may underscore the development of therapeutic strategies for alcohol use disorder (AUD) and those with comorbid metabolic disorders.

A systematic review was conducted, wherein relevant literature was identified through Web of Science, PubMed, and OVID (MedLINE, Embase, AMED, PsycInfo, JBI EBP) from database inception to October 27th, 2024. Preclinical and clinical studies examining the association between GLP-1RAs and alcohol-related behaviours were assessed.

Preclinical studies (n = 19) indicate that GLP-1RAs attenuate alcohol-related behaviours, with exenatide demonstrating significant dose-dependent effects in high alcohol-consuming phenotypes. Semaglutide and liraglutide are associated with reduced alcohol intake, though their effects were often transient. In human studies (n = 2) with AUD, semaglutide significantly reduced alcohol consumption, while exenatide showed mixed results, with reductions in alcohol drinking within high BMI subpopulations.

Extant preclinical and clinical literature provides preliminary support for the potential therapeutic role of GLP-1RAs in attenuating alcohol consumption and preference. There is a need for large well controlled studies evaluating the effect of GLP-1RAs as a treatment strategy for behavioural modifications in individuals living with alcohol use disorder.

Associations between childhood trauma, neurodevelopment, alcohol use disorder (AUD), and posttraumatic stress disorder (PTSD) are understudied during adolescence.

Using 1652 participants (51.75% female, baseline Mage = 14.3) from the Collaborative Study of the Genetics of Alcoholism, we employed latent growth curve models to (1) examine associations of childhood physical, sexual, and non-assaultive trauma (CPAT, CSAT, and CNAT) with repeated measures of alpha band EEG coherence (EEGc), and (2) assess whether EEGc trajectories were associated with AUD and PTSD symptoms. Sex-specific models accommodated sex differences in trauma exposure, AUD prevalence, and neural development.

In females, CSAT was associated with higher mean levels of EEGc in left frontocentral (LFC, ß = 0.13, p = 0.01) and interhemispheric prefrontal (PFI, ß = 0.16, p < 0.01) regions, but diminished growth in LFC (ß = −0.07, p = 0.02) and PFI (ß = −0.07, p = 0.02). In males, CPAT was associated with lower mean levels (ß = −0.17, p = 0.01) and increased growth (ß = 0.11, p = 0.01) of LFC EEGc. Slope of LFC EEGc was inversely associated with AUD symptoms in females (ß = −1.81, p = 0.01). Intercept of right frontocentral and PFI EEGc were associated with AUD symptoms in males, but in opposite directions. Significant associations between EEGc and PTSD symptoms were also observed in trauma-exposed individuals.

Childhood assaultive trauma is associated with changes in frontal alpha EEGc and subsequent AUD and PTSD symptoms, though patterns differ by sex and trauma type. EEGc findings may inform emerging treatments for PTSD and AUD.

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.

Problematic drinking frequently co-occurs with depression among young adults, but often remains unaddressed in depression treatment. Evidence is insufficient on whether digital alcohol interventions can be effective in this young comorbid population. In a randomized controlled trial, we examined the effectiveness of Beating the Booze (BtB), an add-on digital alcohol intervention to complement depression treatment for young adults.

Participants were randomized to BtB + depression treatment as usual (BTB + TAU, n = 81) or TAU (n = 82). The primary outcome was treatment response, a combined measure for alcohol and depression after 6-month follow-up. Secondary outcomes were number of weekly drinks (Timeline Follow-back) and depressive symptoms (Center for Epidemiologic Studies Depression scale). Treatment response was analyzed using generalized linear modeling and secondary outcomes using robust linear mixed modeling.

Low treatment response was found due to lower than expected depression remission rates. No statistically significant between-group effect was found for treatment response after 6-month follow-up (odds ratio 2.86, p = 0.089, 95% confidence interval [CI] 0.85–9.63). For our secondary outcomes, statistically significant larger reductions in weekly drinks were found in the intervention group after 3-month (B = −4.00, p = 0.009, 95% CI −6.97 to −1.02, d = 0.27) and 6-month follow-up (B = −3.20, p = 0.032, 95% CI −6.13 to −0.27, d = 0.23). We found no statistically significant between-group differences on depressive symptoms after 3-month (B = −0.57, p = 0.732, 95% CI −3.83 to 2.69) nor after 6-month follow-up (B = −0.44, p = 0.793, 95% CI −3.69 to 2.82).

The add-on digital alcohol intervention was effective in reducing alcohol use, but not in reducing depressive symptoms and treatment response among young adults with co-occurring depressive disorders and problematic alcohol use.

Pre-registered on October 29, 2019 in the Overview of Medical Research in the Netherlands (OMON), formerly the Dutch Trial Register(https://onderzoekmetmensen.nl/en/trial/49219).

Although the link between alcohol involvement and behavioral phenotypes (e.g. impulsivity, negative affect, executive function [EF]) is well-established, the directionality of these associations, specificity to stages of alcohol involvement, and extent of shared genetic liability remain unclear. We estimate longitudinal associations between transitions among alcohol milestones, behavioral phenotypes, and indices of genetic risk.

Data came from the Collaborative Study on the Genetics of Alcoholism (n = 3681; ages 11–36). Alcohol transitions (first: drink, intoxication, alcohol use disorder [AUD] symptom, AUD diagnosis), internalizing, and externalizing phenotypes came from the Semi-Structured Assessment for the Genetics of Alcoholism. EF was measured with the Tower of London and Visual Span Tasks. Polygenic scores (PGS) were computed for alcohol-related and behavioral phenotypes. Cox models estimated associations among PGS, behavior, and alcohol milestones.

Externalizing phenotypes (e.g. conduct disorder symptoms) were associated with future initiation and drinking problems (hazard ratio (HR)⩾1.16). Internalizing (e.g. social anxiety) was associated with hazards for progression from first drink to severe AUD (HR⩾1.55). Initiation and AUD were associated with increased hazards for later depressive symptoms and suicidal ideation (HR⩾1.38), and initiation was associated with increased hazards for future conduct symptoms (HR = 1.60). EF was not associated with alcohol transitions. Drinks per week PGS was linked with increased hazards for alcohol transitions (HR⩾1.06). Problematic alcohol use PGS increased hazards for suicidal ideation (HR = 1.20).

Behavioral markers of addiction vulnerability precede and follow alcohol transitions, highlighting dynamic, bidirectional relationships between behavior and emerging addiction.

Alcohol or drug (AOD) problems are a significant health burden in the UK population, and understanding pathways to remission is important.

To determine the UK population prevalence of overcoming an AOD problem and the prevalence and correlates of ‘assisted’ pathways to problem resolution.

Stage 1: a screening question was administered in a national telephone survey to provide (a) an estimate of the UK prevalence of AOD problem resolution; and (b) a demographic profile of those reporting problem resolution. Stage 2: social surveying organisation YouGov used the demographic data from stage 1 to guide the administration of the UK National Recovery Survey to a representative subsample from its online panel.

In stage 1 (n = 2061), 102 (5%) reported lifetime AOD problem resolution. In the weighted sample (n = 1373) who completed the survey in stage 2, 49.9% reported ‘assisted’ pathway use via formal treatment (35.0%), mutual help (29.7%) and/or recovery support services (22.6%). Use of an assisted pathway was strongly correlated with lifetime AOD diagnosis (adjusted odds ratio [AOR] = 9.54) and arrest in the past year (AOR = 7.88) and inversely correlated with absence of lifetime psychiatric diagnosis (AOR = 0.17). Those with cocaine (AOR = 2.44) or opioid problems (AOR = 3.21) were more likely to use assisted pathways compared with those with primary alcohol problems.

Nearly three million people have resolved an AOD problem in the UK. Findings challenge the therapeutic pessimism sometimes associated with these problems and suggest a need to learn from community-based self-change that can supplement and enhance existing treatment modalities.

The relationship between migraine and alcohol consumption is unclear. We assessed the association between chronic migraine and alcohol use disorder(AUD), relative to chronic disease controls, and in conjunction with common comorbidities.

We conducted a retrospective, observational study. The primary outcome was the odds ratio for AUD in patients with chronic migraine or with chronic migraine and additional comorbidities relative to controls.

A total of 3701 patients with chronic migraine, 4450 patients with low back pain, and 1780 patients with type 2 diabetes mellitus met inclusion criteria. Patients with chronic migraine had a lower risk of AUD relative to both controls of low back pain (OR 0.37; 95% CI: 0.29–0.47, p < 0.001) and type 2 diabetes mellitus (OR 0.39; 95% CI: 0.29–0.52, p < 0.001). Depression was associated with the largest OR for AUD in chronic migraine (OR 8.62; 95% CI: 4.99–14.88, p < 0.001), followed by post-traumatic stress disorder (OR 6.63; 95% CI: 4.13–10.64, p < 0.001) and anxiety (OR 3.58; 95% CI: 2.23–5.75, p < 0.001).

Patients with chronic migraine had a lower odds ratio of AUD relative to controls. But in patients with chronic migraine, those with comorbid depression, anxiety, or PTSD are at higher risk of AUD. When patients establish care, comorbid factors should be assessed and for those at higher risk, AUD should be screened for at every visit.

To determine whether genetic risk factors for major depression (MD) and alcohol use disorder (AUD) interact with a potent stressor – death of spouse, parent, and sibling – in predicting episodes of, respectively, MD and AUD.

MD and AUD registrations were assessed from national Swedish registries. In individuals born in Sweden 1960–1970, we identified 7586, 388 459, and 34 370 with the loss of, respectively, a spouse, parent, and sibling. We started following subjects at age 18 or the year 2002 with end of follow-up in 2018. We examined time to event – a registration for MD within 6 months or AUD within a year – on an additive scale, using the Nelson–Aalen estimator. Genetic risk was assessed by the Family Genetic Risk Score (FGRS).

In separate models controlling for the main effects of death of spouse, parent, and sibling, FGRS, and sex, significant interactions were seen in all analyses between genetic risk for MD and death of relative in prediction of subsequent MD registration. A similar pattern of results, albeit with weaker interaction effects, was seen for genetic risk for AUD and risk for AUD registration. Genetic risk for bipolar disorder (BD) and anxiety disorders (AD) also interacted with event exposure in predicting MD.

Genetic risk for both MD and AUD act in part by increasing the sensitivity of individuals to the pathogenic effects of environmental stressors. For prediction of MD, similar effects are also seen for genetic risk for AD and BD.