Background Problematic social media use (PSMU) is characterized by maladaptive behaviors and symptoms paralleling addiction. Despite rising prevalence, PSMU lacks formal diagnostic criteria, underscoring the need to investigate its underpinnings. The present study aimed to investigate both psychosocial and neurobiological features that underpin the six characteristics of PSMU (i.e. conflict, mood modifications, relapse, salience, tolerance, withdrawal). Methods A battery of psychometric scales and a magnetic resonance imaging (MRI) scan were administered to 79 individuals (n = 55 female) aged 15-35 years. One psychosocial PCA included mental health symptoms and eight social media behaviors. A second neurobiological PCA included the volume of six brain regions involved in reward. Principal components explaining the most variance (eigenvalue > 1) were extracted for regression analyses with total PSMU and the six characteristics. Results Psychosocial component one, which reflected negative mental health, was significantly associated (p<.001) with total PSMU (t = 6.74), and all six PSMU characteristics (conflict; t = 4.23, mood modifications; t = 4.43, relapse; t = 5.05, salience; t = 5.55, tolerance; t = 5.86, and withdrawal; t = 3.48). The six characteristics showed differing patterns of associations with psychosocial and neurobiological components. Withdrawal was the only PSMU characteristic significantly associated with a neurobiological component (t = 2.02, p<.05). Conclusion The present study is the first to use a biopsychosocial approach to explore PSMU characteristics, integrating social media behaviors, psychological factors, and structural brain patterns. These findings highlight the possibility of differing risk factors distinct to the six PSMU characteristics.

Background The current study examined associations between substance use (alcohol, cannabis, and simultaneous co-use of alcohol and cannabis) and eating behaviors (amount and type of food consumption). The aims of the current study were to assess (1) the frequencies of different eating behaviors on simultaneous co-use of alcohol and cannabis occasions, (2) typical substance use behaviors (alcohol-only, cannabis-only, and simultaneous co-use) among those who engage in different eating behaviors before and after simultaneous co-use, and (3) whether experiences of consequences on simultaneous co-use occasions differed between those who typically engaged in eating before or after simultaneous co-use. Method Participants were 155 undergraduate students who completed an online survey about their substance use frequency, food consumption before and after simultaneous co-use, frequency of junk food (i.e. low nutritional value) consumption after simultaneous co-use, frequency of food consumption later in the night after simultaneous co-use, and simultaneous co-use consequences. Results Frequencies indicated that students may exhibit different levels of food consumption before and after simultaneous co-use. Results revealed that participants who “always" ate junk food and “always” continued to eat after simultaneous co-use, reported greater alcohol use frequency. Results indicated that students who ate less food than usual before, more food than usual after simultaneous co-use, and those who ate more junk food than usual after simultaneous co-use, reported more simultaneous co-use consequences. Conclusion Simultaneous co-use may contribute to changes in eating behaviors among young adults.

Background The rapid expansion of legalized sports wagering may be particularly enticing to athletes, who report higher rates of problem gambling than non-athletes. This study aimed to identify latent classes of potential risk factors in athletes with problem gambling symptoms, guided by the Pathways Model of Problem Gambling. Method Epidemiological data were analyzed from 337 athletes at moderate or high risk for problem gambling from a representative sample of New Jersey adults. Latent class analysis incorporated continuous and binary indicators based on risk factors in the Pathways Model (e.g. depression, anxiety, antisociality) and others associated with problem gambling (e.g. exposure to gambling during childhood). Competing models were evaluated, and the optimal solution was selected. Post hoc analyses examined associations between class membership and demographic, gambling-related, mental health, and addiction variables. Results A three-class solution provided the best fit. Class 1 (‘Behaviorally Conditioned’; n = 110, 32.64%), reported the lowest levels of most indicators. Class 2 (‘Highly Internalizing’; n = 97, 28.78%), showed elevated mood problems and the lowest sport involvement. Class 3 (‘Internalizing-Externalizing’; n = 130, 38.58%) reported the highest levels of substance and addiction problems, sport involvement, gambling during childhood, gambling-related antisocial thoughts and behaviors, suicidality, and non-suicidal self-injury. Conclusions Athletes at moderate to high risk for problem gambling present as three distinct subgroups with implications for prevention, screening, and treatment. These findings extend the Pathways Model to athletes, underscoring the need for sport-specific frameworks to understand and address gambling-related harm in the current era.

Models of gambling disorder, along with other addiction-related conditions, identify impulsive traits as a key component to developing challenging behaviors. This is supported by empirical findings indicating that individuals with gambling disorder exhibit poorer response inhibition, a facet of impulsivity. However, studies on individual differences in inhibition often find weak correlations between different inhibition tasks, suggesting that cognitive processes other than a general inhibitory control ability may contribute to task performance, and by extension, to gambling. The current study applied cognitive modeling to dissociate the cognitive processes involved in response inhibition tasks and examined which cognitive processes are predictive of gambling severity. A total of 422 participants completed the Stroop, Go/No-go and Stop-Signal tasks alongside the Problem Gambling Severity Index (PGSI) questionnaire. The drift diffusion model was used to decompose traditional task performance data into parameters which were then grouped into four distinct cognitive processes: inhibitory control, general processing speed, response caution, and perceptual/motor speed. Preregistered regression analyses indicate that lower caution, rather than inhibition, is associated with higher gambling severity. Whereas previous research had focused on inhibitory control as a risk factor for gambling behaviors, as well as a target for potential interventions (e.g. training apps), these findings suggest rather that the strategic processes underlying decision making – caution – are important to consider.

Background Recovery from drug use is an individualized process that does not necessitate complete abstinence. Due to a growing literature base emphasizing that unmet holistic needs may hinder recovery efforts, some researchers advocate for a focus on quality of life (QoL) in recovery. There is, however, no consensus on its definition or measurement. Certain groups, such as individuals who are receiving opiate agonist treatment (OAT), may face unique experiences that influence their QoL. Method This study explored factors that literature and theory suggest are associated with QoL among individuals recovering from opioid use. Nine variables were chosen to represent three life domains: personal health, standard of living, and achievement. Data were collected from 782 adults (30.1% women) aged 23 to 77, who were receiving methadone or buprenorphine OAT from a recovery organization in the north of England. Results A multiple regression revealed significant associations between five variables and QoL: housing stability, mental health diagnosis, employment status, concurrent illicit substance, and duration in OAT (5 to 10 years). Conclusions It is possible the above variables are linked with increased strain, which could reduce overall satisfaction with life. Recovery services could provide interventions to enhance QoL in addition to those which support abstinence from substances. It is important to achieve consistency in definition and measurement, gather relevant data on theory-driven predictors, and incorporate the perspectives of individuals using recovery services.

Background Youth and young adult nicotine and cannabis users most commonly use multiple delivery methods (e.g. vaping plus combustible cigarette smoking). Vaping and combustible cigarette use are also associated with increased internalizing symptoms (i.e. anxiety, depression, suicidal ideation); however, it is unclear whether there are differential patterns of associations based on product use patterns. Therefore, the purpose of the current study was to examine user group differences in internalizing symptoms, how internalizing symptoms may impact use, and the perceived impact of vaping on internalizing symptoms. Method Participants were 1742 U.S. youth and young adults aged 13–24 (Mage = 18.04, SD = 3.46; 49.3% female; 74.9% White) who completed self-report measures online. Results Current users, regardless of the number of products used, were more likely to report clinically elevated anxiety and depression symptoms as well as suicidal ideation. Poly-product users also were more likely to endorse indicators of dependence. There were few group differences in terms of affect-related motivations to vape. Conclusions These findings suggest that youth and young adults reporting any use of nicotine or THC should be screened for internalizing symptoms and that cessation interventions for this age group target internalizing symptoms as well as dependence symptoms.

Background The Post-Traumatic Growth Inventory (PTGI) is a widely used measure of psychological growth following adversity, although not yet validated for use with those in recovery from substance addiction. The present study was designed to explore the latent structure, reliability, and validity of the inventory in this new population. Method The PTGI was completed by 485 adults (71.8% female) in recovery from addiction. Exploratory Factor Analysis, supported by parallel analysis, was used to explore the latent structure of the PTGI. Cronbach’s alpha reliability coefficients and item-total correlations were calculated to assess internal reliability of the PTGI. Concurrent and convergent validity were also examined by the relationship between the PTGI and measures of growth, social support and rumination. Results Analysis supported a two-factor structure including 18-items, explaining 60.28% of the common variance. The two subscales appeared to capture 1) intrapersonal growth and 2) interpersonal growth (including relationship with God). A strong positive correlation between the subscales in the two-factor solution, and the presence of a single-factor solution explaining 52.31% of the variance, also suggest the presence of a single latent ‘growth’ construct. All scales demonstrated excellent reliability, and concurrent and convergent validity. Conclusions This study supports the reliability and validity of the PTGI for use with those in addiction recovery. Evidence suggests psychological growth in this population can be experienced intra- and inter-personally, but likely has an underlying core.

Both physiological and epidemiological research suggest that certain psychoactive substances have a greater potential for abuse (e.g. heroin) than others (e.g. hallucinogens). The use of multiple substances is also associated with a higher risk of substance use disorder (SUD). The goal of the present study was to evaluate the association between the use of different substances and the risk of SUD while accounting for polysubstance use. Data from the 2021 National Survey on Drug Use and Health (n = 58,034, unweighted) were used. Eight different substances (i.e. Alcohol, Cannabis, Cocaine, Inhalants, Hallucinogens, Heroin, Methamphetamine, and Opiate Misuse) were compared with respect to their typical frequency of use; the prevalence of SUD among individuals using each substance; the odds of SUDs when controlling for polysubstance use; and the rate of other substance use among those with a substance-specific SUD. Notable differences were found regarding the frequency of use and the rate of SUD among individuals reporting past year use. Heroin and methamphetamine were associated with the highest risk of SUD across all analyses. In contrast, hallucinogens and inhalants were consistently identified as having the lowest risk. The present results confirm that certain substances appear to have an inherently greater association with SUD compared to other substances. While these findings are not fundamentally divergent from prior epidemiological studies or ranking systems, they provide a more solid empirical foundation for assumptions of differential risk.