BACKGROUND:Problematic social media use (PSMU) and mindfulness are consistently negatively associated, but longitudinal evidence on their directional relationship remains limited. This study examined whether mindfulness prospectively predicts lower later PSMU (protection pathway), whether PSMU predicts lower later mindfulness (erosion pathway), or whether their longitudinal association is bidirectional. METHODS:Participants were 246 early adolescents from German-speaking Switzerland (48.4 % girls), aged 10 to 13 years (M = 10.93, SD = 0.51), assessed approximately one year apart in spring 2024 and spring 2025. After establishing longitudinal measurement invariance, a two-wave latent cross-lagged panel model was estimated to examine temporal stability and prospective associations between the constructs. RESULTS:PSMU and mindfulness were moderately and negatively associated within both waves, and both constructs showed temporal stability. Cross-lagged effects were asymmetric: baseline mindfulness did not predict later PSMU, whereas higher baseline PSMU predicted lower mindfulness at follow-up (β = - 0.188). Supplementary analyses showed no evidence of sex differences, and sensitivity analyses supported the same directional pattern. CONCLUSIONS:Findings suggest that, in early adolescence, PSMU may be more likely to undermine later mindfulness than mindfulness is to protect against later PSMU. This pattern provides initial support for an erosion pathway during an early phase of social media uptake and highlights mindfulness as a possible outcome of digital behavior.
Alcohol use remains a significant problem among young adults (YAs), and growing evidence suggests exposure to alcohol-related content (ARC) on social media may contribute to increased alcohol use. ARC often portrays drinking as rewarding and/or normative, potentially shaping drinking motives, which are key predictors of alcohol use. Therefore, the present study sought to longitudinally examine if drinking motives mediate the associations between (a) exposure to peers' ARC on social media and (b) perceived number of friends posting ARC and YA alcohol use over an 8-week period. A sample of N = 266 YAs (ages 18-30) in the US who reported consuming ≥8 drinks per week completed baseline, 4- and 8-week follow-up surveys assessing ARC exposure, perceived number of peers posting ARC, drinking motives, and alcohol use. Eight longitudinal mediated growth curve models were tested, evaluating drinking motives (social, enhancement, coping, conformity) as mediators. Both ARC exposure and perceived ARC posting were significantly associated with all four motives, with each predicting baseline alcohol use, however, none predicted longitudinal change in alcohol use. Coping and enhancement motives significantly mediated the association between ARC exposure and baseline alcohol use. All four motives significantly mediated the association between perceived number of friends posting ARC and baseline alcohol use, suggesting proximal peer cues may be especially influential. Findings highlight the roles of coping and enhancement motives in linking ARC exposure to YA drinking. Programs targeting motivational pathways and perceived peer norms and challenging social media-driven alcohol motivations may help reduce YA alcohol use.
Background Rates of methamphetamine use and methamphetamine-related harms are increasing. Many people who use methamphetamine have concurrent non-amphetamine substance use disorders (SUDs). This study evaluated the prevalence of methamphetamine use in records of people receiving treatment for non-amphetamine SUDs, stratified by primary SUD. Methods Repeat cross-sectional analysis of treatment records for alcohol, crack/cocaine, opioid, and cannabis use disorders in the United States (US). Data was obtained from the Treatment Episode Dataset–Discharges (TEDS-D), which contains information on individuals receiving care at publicly funded addiction treatment facilities in most US states. The prevalence of methamphetamine use was tabulated for each year between 2015 and 2022, stratified by primary SUD. Differences in the prevalence of methamphetamine use over time and by primary SUD were evaluated using a multivariable logistic regression model. Results Rates of methamphetamine use increased between 2015 and 2022 across all primary SUDs. The increase in methamphetamine use was most pronounced among treatment records for opioid use disorder, where the annual prevalence increased from 8.61% in 2015 to 19.22% in 2022. The prevalence of methamphetamine use among treatment records for cannabis use disorder increased from 9.68% in 2015 to 14.28% in 2022, which represented a higher baseline rate and temporal change than that observed among treatment records for alcohol or crack/cocaine use disorders. Conclusion Rates of methamphetamine use increased in treatment records for individuals with non-amphetamine SUDs and this increase was most pronounced for opioid and cannabis use disorders. Developing treatment and harm reduction strategies for individuals who combine methamphetamine/opioids and methamphetamine/cannabis will be an important future direction.
Prevalence of addictive behaviors is commonly associated with alterations in the brain's reward circuitry, leading to the upholding of a maladaptive pattern of reward-seeking behavior despite aversive consequences. The main objective of this systematic review was to provide a broad overview of the literature on electrophysiological correlates of anticipation and reward processing in addiction, including substance use disorders (SUD), as well as behavioral addictions. Reward processing in addiction has been investigated using electroencephalography (EEG) studies employing a cue-reward experimental design, with event-related potentials (ERPs) as the outcome measure. Relevant studies were identified by searching scientific databases: PubMed, APA PsycINFO, Web of Science, and Scopus in April 2026. The terms used to search the databases covered EEG/ERP markers of reward processing in substance and behavioral addictions. The inclusion criteria comprised peer-reviewed ERP studies employing a cue-reward paradigm in adults with addictive behaviors and healthy controls, published in English between 2000 and 2026. Forty-two studies were reviewed (SUD: 23; behavioral addictions: 19). Reward anticipation was indexed by cue-P300, contingent negative variation (CNV), and stimulus-preceding negativity (SPN). Reward processing was examined in distinct early (feedback-related negativity (FRN) and reward positivity (RewP)) and late (P300 and late positive potential (LPP)) reward outcome phases. Altered neural responses were observed across multiple stages of reward processing in both substance and behavioral addictions, consistent with disruptions in the generation, evaluation, and updating of reward expectations. Despite these convergent patterns, methodological heterogeneity limits the strength of current conclusions and highlights the need for greater standardization in future research.
INTRODUCTION:Smoking prevalence in Germany has remained high in recent years, with around 30 % of the population smoking. Related nicotine products, such as e-cigarettes, are increasingly popular, especially among youth. Unlike previous generations, for whom nicotine use typically began with traditional cigarettes, initiation pathways may now increasingly involve these related nicotine products. METHODS:Data from 1,164 participants aged 14 years and older were collected between August and September 2022 through the DEBRA study (German Study on Tobacco Use), using computer-assisted household interviews. Descriptive statistics analysed the frequency of nicotine initiation products, grouped into traditional tobacco products (tobacco cigarettes, pipes/cigars/cigarillos) and related tobacco and nicotine products (heated tobacco products, e-cigarettes with nicotine, waterpipes, chewing tobacco/snuff, nicotine pouches/snus and cannabis mixed with tobacco). Associations between initiation product category and sociodemographic factors (age, sex, migration background, education, and income) were analysed using univariate binary logistic regression. RESULTS:Tobacco cigarettes were the most common nicotine initiation product, reported by 84.3 % of individuals with ever use of nicotine containing products. Initiation with related products was more common among younger and higher educated individuals: ages 14-17 (OR = 17.42, 95 %CI = 4.6-66.02), ages 18-25 (OR = 10.95, 95 %CI = 5.24-22.89) compared with those aged 65 and older, and among individuals with high vs. low educational attainment (OR = 1.93, 95 %CI = 1.24-3.02). DISCUSSION:Traditional cigarettes remain the most common nicotine initiation product in Germany. However, younger and higher educated individuals are more likely to initiate with related products. These findings highlight changing initiation patterns and underscore the importance of considering alternative nicotine products when addressing pathways into nicotine dependence and their long-term public health implications.
BACKGROUND:The Interaction of Person-Affect-Cognition-Execution model suggests that impulsivity and specific gaming motives contribute to the development of gaming disorder (GD). However, it remains unclear whether these factors interact synergistically or operate independently. This study investigated the additive versus interactive effects of specific impulsivity facets, gaming motives, and behavior automatization on GD symptom severity. METHOD:A sample of 377 adult gamers (338 male, 38 female, 1 diverse; age 18-58 years, M = 25.44, SD = 5.51) was assessed using the Barratt Impulsiveness Scale, Motives for Online Gaming Questionnaire, and the Assessment of Criteria of Specific Internet-use Disorders (ACSID-11) screening for GD symptom severity. Depression and anxiety were also assessed via self-report. We conducted hierarchical moderated regression analyses and exploratory cluster analysis. RESULTS:The non-planning impulsivity dimension significantly predicted GD symptom severity in the final models. Escape motive and behavior automatization emerged as robust predictors, explaining substantial additional variance. Contrary to initial hypotheses, no significant interaction effects were found. Depression and anxiety served as strong covariates across all models. Cluster analysis identified four distinct profiles: Unproblematic-Adaptive, Social-Recreational, Impulsive-Automatical, and Problematic-Clinical. CONCLUSION:The findings support a predominantly additive model, indicating that impulsivity traits, maladaptive motives (specifically escape), and automatization contribute cumulatively to GD severity rather than through complex interactions. The identification of distinct gamer profiles suggests a need for personalized clinical interventions: the Impulsive-Automatical cluster may benefit from interventions targeting planning deficits and behavioral disinhibition, while the Problematic-Clinical cluster requires comprehensive treatment addressing comorbid affective psychopathology alongside gaming behavior.
Memory loss from alcohol ("blackout") is common among young adults who drink and associated with significant alcohol-related harm. Despite longstanding evidence distinguishing fragmentary (transient) and en bloc (permanent) blackouts, a measure distinguishing these two forms of blackout (the Alcohol-Induced Blackout Measure-2 [ABOM-2]) was only recently developed and has not been psychometrically evaluated among young adults with a history of alcohol-induced blackouts. The present study evaluated the psychometric properties of the ABOM-2, particularly its longitudinal measurement invariance and prospective predictive validity, among 169 heavy-drinking young adults (ages 18-30) with a history of blackout. Confirmatory factor analyses at baseline (T1) and one-month follow-up (T2) supported previous research showing the ABOM-2 items are best represented by two correlated factors. Both factors, en bloc and fragmentary, demonstrated convergent validity, showing significant associations with hazardous drinking, alcohol consumption, and alcohol-related consequences. In concurrent convergent and prospective predictive regression models that accounted for relevant covariates and included both types of blackouts, en bloc (but not fragmentary) blackouts significantly predicted hazardous drinking, alcohol consumption, and consequences across time. Longitudinal measurement invariance testing provided evidence for configural, metric, and scalar invariance across T1 and T2, supporting the measurement equivalence of ABOM-2 over time. Findings reinforce the distinction between en bloc and fragmentary blackouts, support the convergent and predictive validity of the ABOM-2, and highlight the clinical and research utility of the ABOM-2 as a reliable tool for assessing blackout across time. En bloc blackouts, in particular, serve as a robust marker of alcohol-related risk among young adults.
Objective Social media marketing of oral nicotine pouches (ONPs) has expanded rapidly since their U.S. introduction in 2016, particularly among young adults. It remains unclear whether ONP use-status influences cognitive, emotional, and behavioral responses to influencer-generated ONP marketing, including ONP interest and comparative harm perceptions. Methods A 2 (ONP use-status: people who use ONPs vs. people who do not use ONPs) x 2 (paid partnership disclosure: present vs. absent) between-participants experiment was conducted with young adults (N = 193; Mage = 20.19 years). Participants viewed a TikTok influencer advertisement promoting ONPs while psychophysiological responses were recorded, followed by self-report measures. Results Paid partnership disclosures increased ONP interest among both people who use ONPs and people who do not use ONPs (p < 0.001, ηp2 = 0.07), with people who use ONPs reporting greater overall interest than people who do not use ONPs (p < 0.001, ηp2 = 0.53). Controlling for baseline comparative harm perceptions, disclosure effects varied by baseline comparative harm perceptions and ONP use-status (p < 0.001, ηp2 = 0.14). Compared with people who do not use ONPs, people who use ONPs allocated fewer cognitive resources to the ONP advertisements over time (b = 0.01, p = 0.03), exhibited greater physiological arousal over time (b = 0.0004, p = 0.04), and showed less negative emotional responding when disclosures were present (b = -0.53, p = 0.02). Conclusions Paid partnership disclosures increased ONP interest but produced divergent effects on comparative harm perceptions, cognitive processing, physiological arousal, and emotional responding according to ONP use-status.
Background Major depressive disorder (MDD) and internet addiction (IA) are closely linked in adolescents, yet the neurobiological mechanisms underlying their relationship remain unclear. This study aimed to explore the role of abnormal functional connectivity (FC) between theta oscillation and the default mode network (DMN) in IA development among adolescent MDD patients. Methods A total of 183 drug-naive first-episode adolescent MDD patients and 93 healthy controls (HC) were enrolled. Clinical assessments were conducted using the HAMD-24, HAMA, and Young Internet Addiction Scale, with MDD patients divided into IA and MDD subgroups. Resting-state EEG data were collected for time–frequency analysis, brain electrical source reconstruction, and FC analysis, with statistical tests performed via SPSS 22.0. Results The IA group had higher scores in depression, anxiety, anhedonia, and IA severity than the MDD and HC groups. Theta band power spectral density (PSD) was lower in the IA group than in the MDD group, while both MDD groups exhibited higher theta PSD than HCs. IA was associated with abnormal intra-DMN connections; theta oscillation mediated the relationship between anhedonia and IA severity. HC subjects had stronger DMN FC across Delta, Theta, Alpha, and Gamma bands than MDD patients, and the MDD group showed stronger theta-band DMN FC than the IA group. Conclusions Abnormal theta oscillation-DMN network correlates with IA in adolescent MDD patients, and the mediating role of theta oscillation provides a new perspective for understanding the neural mechanism of this comorbidity.
Background This study examined which characteristics of substance use disorder (SUD) treatment facilities and their surrounding areas are associated with offering overdose education and naloxone (OEN). Methods We linked data from eight national sources regarding 12,146 SUD treatment facilities (from the 2024 National Directory of Drug and Alcohol Use Treatment Facilities) and the communities and states where they operate. Regression analyses tested whether facility OEN provision was associated with facility type (with cluster analysis used to group facilities based on services offered) and selected facility, ZIP code, and state characteristics. Findings In a generalized linear mixed model, odds of OEN provision were higher in facilities that: used medications for opioid use disorder (Adjusted Odds Ratio [AOR] 7.21; 95% Confidence Interval [CI] 5.97–8.71); offered testing for HIV/hepatitis (AOR 2.39; 95% CI, 2.00–2.86); were government-operated (AOR 2.37; 95% CI, 1.81–3.11) vs. private for-profit; accepted Medicaid (AOR 2.36; 95% CI, 2.01–2.77); or were in metropolitan (vs. non-metropolitan) areas (AOR 1.27; 95% CI, 1.06–1.53). In facility cluster analysis (based on 191 facility characteristics/services), adjusted odds of OEN provision were lowest in the cluster characterized by outpatient services, low use of medications for opioid use disorder, and few social/medical/tailored services. Odds of OEN provision were highest in the cluster characterized by offering “detoxification,” residential care, buprenorphine and naltrexone, and comprehensive medical and social services. Conclusions OEN provision is lowest in SUD treatment facilities that do not use medications for opioid use disorder, offer relatively few social or medical services, and/or are located in non-metropolitan areas.
AIM:To identify longitudinal trajectories of cannabis, alcohol, and cigarette use from ages 18-24 and examine whether trajectory-group membership is associated with non-prescribed opioid use during young adulthood. METHODS:Data were drawn from restricted Monitoring the Future (MTF) panel data. Participants completed the base year survey and at least one of three follow-up surveys. Individuals reporting non-prescribed opioid use at baseline were excluded. The analytic sample included 62,223 participants from 42 US base year cohorts (1976-2018). Group-based trajectory modeling identified patterns of past-year cannabis, alcohol, and cigarette use. The outcome was any past-year non-prescribed opioid use reported at follow-up through ages 23/24. Weighted logistic regression models estimated associations between trajectory-group membership and non-prescribed opioid use, adjusting for background characteristics; sex-stratified models were also estimated. RESULTS:Five trajectory groups emerged: (1) no cannabis and cigarette/low-to-moderate alcohol use (14.7%); (2) no cannabis and cigarette/high alcohol use (32.7%); (3) high use of all substances (21.2%); (4) low cannabis use/moderate-to-high cigarette use/high alcohol use (19.6%); and (5) high-to-moderate cannabis use/moderate-decreasing-to-low cigarette use/high alcohol use (11.8%). Compared with Group 1, all other groups had higher adjusted odds of non-prescribed opioid use (p-values <0.01). Patterns were generally similar by sex. CONCLUSION:Compared with young adults characterized by no cannabis or cigarette use and low-to-moderate alcohol use, those in trajectory groups characterized by high use of one or more substances had higher odds of non-prescribed opioid use during young adulthood. Findings suggest that non-prescribed opioid use during young adulthood often occurs within a broader pattern of polysubstance use involving cannabis, alcohol, and cigarette use.
Housing hardship is increasingly recognized as a risk factor for substance use, yet little is known about whether entering and exiting hardship are differentially associated with addictive behaviors or whether these associations vary by gender. Drawing on stress-coping theory and the self-medication hypothesis, this study examines how housing hardship transitions are associated with smoking frequency (number of days smoked in the past 30 days), binge drinking frequency (days per month), and marijuana use (any use in the past 30 days) among young adults. Using data from Waves III (aged 18-27, M = 21.9) and IV (aged 24-34, M = 28.4) of the National Longitudinal Study of Adolescent to Adult Health (N = 12,965), we employ asymmetric fixed-effects models that separately estimate associations for entering and exiting housing hardship and formally test whether they differ in magnitude. Standard fixed-effects models indicate positive associations between housing hardship and all three substance use outcomes. However, asymmetric models reveal significant asymmetry for smoking: entering housing hardship is associated with increases in smoking, whereas exiting is not associated with corresponding reductions, consistent with the persistence of nicotine dependence. Binge drinking and marijuana use display largely symmetric responses. Gender interaction analyses indicate that increases in smoking and marijuana use associated with hardship entry are more pronounced among men, while reductions in binge drinking associated with hardship exit are stronger among men. These findings suggest potential substance-specific differences in the reversibility of stress-induced use and may inform gender-responsive approaches to addiction treatment and housing support.
BACKGROUND:Cannabis cessation or reduction may increase cross-substance substitution in response to craving or reduced use. Evidence for substitution is mixed, and treatment effects remain unclear. This exploratory study examined alcohol and tobacco substitution within clinical trials of cannabis cessation. DESIGN:Data were pooled from 829 participants (Mage = 27.1, SD = 9.1; 31 % female; 63 % White; 13 % Latine/Hispanic) across seven pharmacologic cannabis use disorder (CUD) trials. Weekly cannabis, alcohol, and cigarette use were assessed (cigarettes in six trials). Longitudinal mixed-effects models tested whether cannabis use or craving predicted next-week alcohol and cigarette outcomes, with treatment condition included as a moderator. RESULTS:No significant three-way interactions with treatment emerged. Cannabis craving interacted with cannabis frequency to predict modest increases in next-week alcohol quantity (b = 0.009, p = 0.04970497), although not drinking frequency. Higher cannabis quantity predicted lower next-week cigarette quantity (b = - 0.009, p = 0.042). There was limited evidence of a treatment × craving interaction for cigarette frequency (b = - 0.008, p = 0.04990499), with higher craving associated with fewer smoking days in the active treatment arm. CONCLUSIONS:Alcohol findings were consistent with complementary use patterns, whereas cigarette smoking showed evidence of both concurrent coco-use and prospective substitution with cannabis. Pharmacotherapy did not broadly alter these relationships; however, among participants receiving active treatment, greater cannabis craving was associated with fewer smoking days. These findings provide initial evidence supporting monitoring of polysubstance use during CUD treatment and consideration of how cessation efforts may differentially affect alcohol and tobacco use.
BACKGROUND:Smoking susceptibility predicts subsequent tobacco use, yet most research has treated it as static, measured at a single time point. How susceptibility develops over adolescence and how distinct patterns relate to multi-product tobacco use remain unclear in East Asian contexts. METHODS:Five annual waves (2019-2023) of the nationally representative Korean Youth Health Behaviour Panel Survey (n = 5045) were analyzed, following adolescents from grade 6 (age 11-12) to grade 10 (age 15-16). Susceptibility was assessed with a four-point willingness-to-smoke measure. Latent class growth analysis was applied to the five repeated susceptibility measures to identify trajectory classes. Associations with wave 5 lifetime use of cigarettes, e-cigarettes, and heated tobacco products (HTPs) were examined using the Bolck-Croon-Hagenaars method. Multinomial logistic regression identified baseline predictors, including peer smoking, parental disapproval, household smoking, perceived harm, media exposure, gender, academic performance, and socioeconomic status. RESULTS:Three trajectory classes emerged: low-stable (88.4 %), increasing (5.6 %), and high-decreasing (6.0 %); entropy was 0.812. Both the increasing and high-decreasing classes showed significantly higher lifetime use of cigarettes, e-cigarettes, and HTPs than the low-stable class. Lower parental disapproval, lower perceived harm, greater media exposure, male gender, and lower academic performance distinguished these two trajectories from the low-stable trajectory. CONCLUSIONS:Smoking susceptibility follows heterogeneous developmental trajectories during adolescence, and a small but identifiable subgroup shows escalating susceptibility associated with elevated risk for multi-product tobacco use. Findings highlight parental attitudes, harm perceptions, and media exposure as modifiable targets for early prevention.
BACKGROUND:Alcohol use disorder and alcohol withdrawal syndrome impose substantial clinical and economic burdens, with repeated hospitalizations being common. We aimed to systematically review readmission rates following inpatient detoxification, assess variation across study designs and hospital settings, and identify key risk and protective factors. METHODS:We performed a literature search in Embase and Pubmed on 10/04/2026 focusing on studies assessing in hospital alcohol detoxification. Exclusion criteria included studies on substance use other than alcohol and outpatient or residential treatment. Main outcome was rehospitalization, and meta-analysis was performed to estimate pooled readmission proportions. Secondary outcomes were risk factors and protective factors influencing the rate of rehospitalization. RESULTS:Twenty-five studies were included. The pooled proportion of readmissions following alcohol detoxification was estimated at 17% (95% CI: 14%-21%; 13 studies, n = 287,896) within 1 month, increasing to 44% (95% CI: 36%-52%; 8 studies, n = 2,877) at 1 year. Substantial between-study heterogeneity was observed. Subgroup analyses found no significant differences by hospital setting or time period. Findings for study aim and study design were mixed and based on limited data A small number of studies suggested associations with housing stability, employment, and treatment engagement. CONCLUSIONS:This meta-analysis suggests that approximately one in six patients are readmitted within 1 month and nearly half within 1 year after inpatient alcohol detoxification. However, readmission rates varied considerably across settings and populations. Future research should evaluate targeted interventions to reduce readmissions among high-risk patient groups.
BACKGROUND:Even with the most effective smoking cessation pharmacotherapies (i.e., varenicline or combination nicotine replacement [C-NRT]), the majority of people ultimately return to smoking. This research explored how to optimize the use of varenicline and C-NRT to promote smoking cessation. METHODS:Primary care patients participated in a 2x2x2x2 factorial experiment that evaluated 4 factors: 1) Medication Type (Varenicline vs. C-NRT [patch + mini-lozenge]), 2) Preparation (pre-quit) Medication (4 Weeks vs. Standard); 3) Medication Duration (Extended [24 weeks] vs. Standard [12 weeks]); and 4) Counseling Type (Cessation Counseling [4 sessions] vs. Referral Support [2 sessions focused on use of referral resources]). This study was discontinued prior to reaching the proposed sample size (N = 608) due to pandemic-related budgetary constraints. RESULTS:Participants (N = 496) were 55% women and 45.6% Black individuals. There were no statistically significant main effects of the 4 factors on abstinence at 12, 26 or 52 weeks. There was a 3-way interaction between Medication Type, Preparation Medication, and Counseling Type (p = 0.04) predicting the primary outcome of biochemically confirmed abstinence at 52 weeks; cessation counseling vs. referral support improved varenicline quit rates when 4 weeks versus 1 week of pre-quit medication was offered. For C-NRT, counseling type did not significantly improve quit rates regardless of the use of preparation medication. CONCLUSIONS:There was no robust evidence that enhanced pre-quit or extended duration of varenicline or C-NRT increased abstinence rates. More intensive counseling may support cessation for different pharmacotherapy regimens. Given the lack of consistent findings, this research should be viewed as exploratory to guide future research.
