Due to 40% higher enzymatic activity of the Val compared to Met allele , homozygote carriers of the Val allele metabolize PFC DA at a more efficient rate, resulting in lower levels of DA in the synapse, whereas those with Met/Met genotype have the lowest rate of DA clearance, resulting in higher level of DA in the synapse. As METH substantially augments the concentration of extracellular DA, we hypothesized that COMT genotype would be a relevant predictor of brain consequences of METH exposure. COMT Val158Met has been examined in many contexts relevant to catecholamine function. With regard to cognition, it has been linked most consistently to differences in executive function , although some controversy remains about the replicability of findings . In healthy adults, the Val allele has been linked to executive dysfunction , whereas the Met allele is associated with enhanced executive function . Some evidence suggests this effect may be specific to men . The Met-associated cognitive advantage is likely due to higher DA bio-availability in the PFC resulting from slower clearance coded by Met. Other findings point to an inverted U-shape relationship between DA activity in the PFC and cognitive performance such that the relationship between COMT and PFC function is likely to be context dependent and more complex than a simple dichotomy in which a Val allele is harmful and a Met allele is protective. For example, under conditions of DA excess, such as after METH administration, the greater metabolic activity conferred by Val alleles may be more advantageous in restoring the brain to homeostasis. In an earlier study of COMT Val158Met and executive dysfunction in the context of HIV disease and METH dependence, we found that, regardless of HIV status,grow rack individuals with Met/Met genotype had better executive function compared to Val carriers, except if they were METH users, and this effect did not generalize to other cognitive domains .

Although increased bio-availability of cortical DA associated with the Met/Met genotype is thought to enhance executive function under physiologically normal conditions, in the hyperdopaminergic state induced by METH, slow DA clearance can result in neurotoxicity, possibly via DA auto-oxidation , thus attenuating any advantage, or posing a liability for executive function in METH-using Met/Met individuals. Here, we aim to examine whether variability in COMT Val158Met contributes to individual differences in executive deficits reported after heavy chronic METH exposure, with the goal to potentially identify genotype groups that are at higher risk of METH-associated executive dysfunction. In this investigation, we are focusing on a more homogenous sample than in our prior work, reducing variability associated with sex and racial background, as well as HIV status, since HIV can also affect dopaminergic circuitry. Our analyses will examine the main and interactive effects of COMT genotype and METH dependence on a three-test composite of executive function . Follow-up analyses will examine the effects of COMT genotype and METH dependence on each test of executive function. We hypothesize that, contrary to its effect in the general population, among individuals with METH dependence, slower DA clearance in the PFC conferred by the Met/Met genotype, in conjunction with METH induced dopaminergic excess, will be associated with worse executive function, while Val carriers will show comparatively better executive function. Participants were 85 METH dependent and 64 non-drug dependent comparison research volunteers evaluated at the University of California, San Diego All were HIV- non-Hispanic White men. We limited our sample to a demographically narrow group for the purpose of genetic analyses, as some sex and race differences in COMT effects and allele frequencies have been reported , and we did not have sufficient numbers of women or non-White participants to conduct separate analyses. Participants were excluded if: they met DSM-IV criteria for lifetime dependence on any drugs other than METH or cannabis within the last 5 years, or alcohol dependence within the last 12 months; they reported abuse of any substances other than METH within the last 12 months, with the exception of cannabis, alcohol and nicotine, given their high prevalence in this population; or they had a history of neurologic, psychiatric, or developmental disorders of sufficient severity to confound neuropsychological test results.

The Wide Range Achievement Test version 3 or 4 reading subtest was used as an estimate of preexisting cognitive ability. Participants who had WRAT reading scores below 80 were excluded to limit the confounding contribution of preexisting low intellectual functioning. Participants gave written informed consent prior to enrollment and collection of neuropsychological, neuropsychiatric, medical and genetic information. HIV status was determined using enzyme linked immunosorbent assays with a confirmatory test. Hepatitis C status was also determined and, while slightly more frequent in METH+, hepatitis C seropositivity did not differ significantly among the COMT genotypes. All procedures were approved by the Human Research Protection Program at UCSD.DNA for genotyping was isolated from 0.2 ml whole blood stored at −70°C using the Qiagen QIAamp DNA Mini Kit and QiaCube Robotic workstation for automated DNA purification. The COMT Val158Met SNP was assayed using an addiction-relevant gene array . All participants were genotyped for COMT Val158Met by standard procedures. Genotyping involved hybridization of a locus-specific oligonucleotide and two allele-specific oligonucleotides to target genomic DNA, extension and ligation reactions, followed by PCR with common dye-labeled PCR primers . The PCR products were hybridized to the universal array, and imaged using a high-resolution scanner. Finally, the images were analyzed using software for automated genotype clustering and calling within Bead Studio software. Participants completed three tests of executive function: Wisconsin Card Sorting Test 64-item-computerized version , Stroop Color-Word Test , and Trail Making Test Part B . The executive function composite consisted of number of perseverative responses on the WCST, reflecting untimed ability to perceive complex pattern set-shifting; score obtained in 45 seconds on the Stroop Color-Word interference condition, reflecting timed ability to selectively inhibit information and manage cognitive interference; and time to complete Trails B, reflecting timed ability to switch and maintain attention between ongoing sequences. Raw scores from the component tests were converted to T-scores adjusted for age, education, and gender according to published test norms, and then averaged across tests to form the EF composite T-score. Variables that differed significantly across the six groups were included as covariates in primary analyses.

Groups differed significantly by years of education, reading level , days since last alcohol use, and lifetime average drinks per day. Thus, these variables were included as covariates in subsequent models for executive function. Years of education was not included as a covariate given that the outcome variables of executive function are demo graphically adjusted for years of education. We used multi-variable linear regression analyses to examine the effects of COMT genotype, METH dependence, and their interaction on the executive function composite,greenhouse grow tables controlling for significant covariates. COMT genotype was coded with Val/Met as the reference group, given that it is the largest genotype group in our analyses and the most common in the general population, including White populations . In order to probe significant COMT*METH interactions and assess the differential influence of each predictor on executive function, we conducted follow-up analyses stratified by COMT genotype and separately, stratified by METH dependence. Similar analyses examined the same predictors in multi-variable linear regression analyses with the individual tests of executive function as outcomes. For these three individual tests, stratified analyses that followed-up on COMT*METH interaction effects were interpreted using a Bonferroni-adjusted α-threshold of .0167 .Participants were all non-Hispanic White men, ranged in age from 18 to 66 years old , and had an average of 12.6 years of formal education . Table 1 provides sample demographic and lifetime substance use characteristics by METH status and COMT genotype group. Across the six groups, METH+ participants had significantly fewer years of formal education, lower WRAT reading scores, more days since last alcohol use and higher average lifetime alcohol drinks per day compared to METH- participants. Importantly, within each METH group, COMT genotype groups had comparable background characteristics , substance use histories, and proportion of hepatitis C seropositivity . This risk is highest for large breed dogs and those over 10 years of age.Cancer and its treatments cause disruptions in nutritional status, such as loss of appetite and cachexia in many species. In humans undergoing or surviving beyond treatment, evidence for the effectiveness of dietary strategies is inconsistent, which might reflect the complexity of the relationships among various nutritional factors, cancer biology, and both general and cancer-specific outcomes. Overall, research data in humans suggest general healthy diet and lifestyle measures are beneficial after diagnosis and during treatment of cancer, including healthy weight management, exercise, increased fruit and vegetable consumption, and avoidance of red or processed meats.

Little evidence is available to support using specific nutritional strategies for dogs with cancer. Nonetheless, recommendations for specific commercial diets as well as home-prepared diet recipes for dogs with cancer are readily accessible by pet owners, although the latter do not typically meet nutritional standards.Dogs with cancer are more likely to receive home-prepared foods, with more than half of diet alterations after a cancer diagnosis involving the addition of home-prepared components. Owners of dogs with cancer are more likely to give supplements.Given the importance of nutrition in dogs with cancer, and because owners might change the diets after diagnosis, it is important that clinicians collect information on what owners are feeding their dogs and how a cancer diagnosis affects this. There is limited data on alterations relating to supplement usage or specific diet strategies, such as grain-free or organic. Diet history information, including supplement and treat use, is essential for performing the nutritional assessment, and understanding why certain changes are being made is important for client counseling and to develop sound treatment plans.This is especially relevant in cases where owners are switching to potentially unbalanced home-prepared diets or adding raw animal products that carry the risk of contamination with pathogenic bacteria.This study sought to determine how dog owners altered diet and supplement usage in response to a cancer diagnosis. Owners were surveyed on diets and supplements given both before and after diagnosis, in addition to current treat usage. Reasons for alterations as well as informational resources used by owners of dogs with cancer were also queried. Based on previous studies, we expected that the most common changes would involve the initiation of supplements as well as the reduction or discontinuation of commercial diet products in favor of home-prepared foods.Dog owners were surveyed if their dog presented, for the first time, to the UC Davis Veterinary Medical Teaching Hospital’s Oncology Service for the treatment or further diagnosis of a tumor between December of 2020 and March of 2022. Dogs presenting to the service for the first time with recurrence or that had a previous, different type of cancer were excluded. Surveys were sent out in groups every 2 to 3 weeks. During this period, we reviewed the appointment schedule for newly presenting dogs and sent out surveys to owners upon identifying recruitment eligibility. A link to the Qualtrics survey was distributed to eligible dog owners via the email address that they provided during registration of their dog at the hospital. Consent to participate was obtained through the first question of the survey. Participants were then asked if they would prefer to take the survey by telephone; if the participant selected this option, the online survey would end, and we attempted to collect responses via telephone call. Owners were excluded if they did not consent to the survey.An early draft of the survey was piloted with several dog owners. The final version of the survey had 62 possible questions, many of which were conditionally shown based on previous answers . Survey data were matched to each dog’s medical record to collect information regarding signalment, diagnosis, time from diagnosis to survey response, and estimated household income based on census tract. The bulk of the survey consisted of 3 sections: diet, supplements, and treats. All eligible responses with information on diet, supplements, or treats were retained for analysis. The diet section asked what owners were currently feeding their dogs, including specific characteristics and if the diets were commercially available, home prepared, or a combination of the 2. For commercial diets, the brand name and form of diet was collected.

The wave 2 questionnaire introduced the term “electronic nicotine products,” of which “ecigarettes ” was a subset. In this analysis, we considered the most inclusive electronic nicotine product wording at each wave as e-cigarette use. The first research question was used to assess parent or guardian knowledge or suspicion of their child’s tobacco use. Each wave, parents or guardians were asked, “Asfar as you know, has [child’s first name] ever smoked a cigarette or used other tobacco products, such as e-cigarettes, cigars, a pipe, a hookah, smokeless tobacco, dissolvable tobacco, bidis, or kreteks?” Parents were categorized as knowing or suspecting tobacco use if endorsing “you know that she/he has” or “you strongly suspect she/he has.” The responses “you don’t think she/he has” and “you are confident that she/ he has not” were categorized as not aware or suspicious. “Don’t know” responses were uncommon and were coded as not aware or suspicious. The second research question involved longitudinal analyses of youth tobacco use initiation. Parents or guardians and youth were independently asked to consider “rules about using tobacco inside your home” as applied to “everyone who might be in your home, including children, adults, visitors, guests, or workers.” Separate items referred to “tobacco products that are burned, such as cigarettes, cigars, pipes, or hookah” and “tobacco products that are not burned, like smokeless tobacco, dissolvable tobacco, and e-cigarettes.” Endorsing that product use “is not allowed anywhere or at any time inside my home” was classified as strict household rules, whereas endorsing “in some places or at some times,” “anywhere and at any time,” or “don’t know” was considered more permissive. Additionally, youth were asked, “In the past 12 months,cannabis dry rack have your parents or guardians talked with you, even once, about not using any type of tobacco product?” which we categorized as “yes” versus “no” or “don’t know.”

For both research questions, covariables included in multi-variable models were parent or guardian educational attainment ; the child’s age , sex, and race and/or ethnicity; whether anyone who now lives with the child uses tobacco ; and whether the child lives somewhere else with another parent . Models of parental knowledge or suspicion additionally included whether the parent or guardian was the child’s biological mother. Models of tobacco initiation additionally included child ever use of alcohol and cannabis, whether the child has a curfew , and the sensation seeking score.Of the total number of youth respondents in wave 1 , wave 2 , wave 3 , and wave 4 , the pseudo cross-sectional time-series analysis was limited to respondents with non-missing data for parent knowledge or suspicion of youth tobacco use . In this pseudo time-series, each cross sectional wave is weighted to be nationally representative, but some participants appear in multiple waves, resulting in n = 52 237 observations from n = 23 170 individuals. Longitudinal analyses were limited to youth who had never used any tobacco product as of wave 1. We assessed the outcome, initiation of tobacco use, at waves 2, 3, and 4, defined as reporting ever use of $1 tobacco product as of the time point of interest, including youth who “aged-up” into the adult survey by reaching age 18 at follow-up . For the pseudo time-series analysis, parental knowledge or suspicion of their child’s tobacco use was modeled as the dependent variable by using logistic regression with wave-specific, cross-sectional, balanced repeated replicate weights, allowing each wave to be nationally representative despite participant overlap. Youth tobacco use category was the main predictor variable, with tobacco use 3 survey wave interaction terms added to assess wave-specific differences in parental knowledge or suspicion according to youth tobacco use status. For longitudinal analyses, youth tobacco initiation at waves 2, 3, and 4 were the dependent variables in separate logistic regression models with longitudinal weights. Wave 1 household tobacco rules and talking about not using tobacco were the main predictor variables. Household rules was specified as a 5-level categorical variable: both parent or guardian and child endorse more permissive rules on both product types, both endorse strict rules on burned tobacco , both endorse strict rules on not burned tobacco , parent and youth discordant on both product types, and both endorse strict rules on both products types.

As exploratory analyses, we examined several alternative model specifications. We hypothesized that changes in social environments as youth age could reduce any impact of household rules on tobacco initiation over time. Therefore, we explored interactions of household rules with baseline age. Additionally, we explored whether household rules may differentially impact initiation of different types of tobacco by specifying multinomial logistic regression models for a 4-level dependent variable: no initiation, initiation of combustible tobacco only, initiation of noncombustible tobacco only, initiation of both product types. Finally, given that exposures and covariables are potentially time varying, we specified a repeated measures model using generalized estimating equations for 1-year initiation outcomes, taking anyobservation of a youth tobacco never user in waves 1, 2, and 3. For all models, missing covariable values were multiply imputed . Although missingness was uncommon for any one tobacco use variable , missing tobacco responses were also imputed when examining parental knowledge or suspicion because missingness compounded when deriving categories: 7.7% of participant observations were missing $1 tobacco variable. Analyses were conducted by using Stata 16.0 . Results were considered statistically significant at P , .05.Tobacco poly use was the most common behavior among current youth tobacco users in waves 1 to 3; in wave 4, e-cigarette only use was most common . Among polytobacco users, 77% to 80% reported smoking cigarettes, depending on the survey wave. Social and demographic variables were similar in distribution over time . In all waves, parents or guardians were substantially less likely to report knowledge or suspicion that their children had used tobacco if their children reported use of only e-cigarettes, noncigarette combustible products, or smokeless tobacco compared with use of cigarettes or multiple tobacco products . In covariable adjusted models, other factors associated with greater parent knowledge or suspicion included lower parent educational attainment; the child being older, being male, identifying as non-Hispanic white, living with a tobacco user, or residing in another home; and the parent respondent being the child’s mother .Among wave 1 youth who reported never using tobacco, most parent child pairs mutually endorsed having strict household rules that prohibited use of any burned tobacco and not-burned tobacco .

Half of youth reported that a parent or guardian had talked with them about not using tobacco within the past 12 months. There was high percentage agreement between parent and youth responses regarding household rules , although interrater reliability was constrained under a high marginal prevalence of strict rules . Household rules and talking about tobacco were uncorrelated .Among wave 1 tobacco never users, 15% initiated use of $1 tobacco product by wave 2, 24% by wave 3, and 33% by wave 4. At all time points, children in households with the strictest rules prohibiting tobacco use had 20% to 26% lower odds of tobacco initiation compared with children in the most permissive households . Households with strict rules only for burned or not burned tobacco were also numerically associated with less initiation compared with the most permissive households, albeit not statistically significantly in these groups of smaller sample size. In contrast, youth who reported that their parent or guardian had talked with them about not using tobacco did not demonstrate lower odds of tobacco initiation; in fact, tobacco initiation was higher at waves 3 and 4 . Other factors positively associated with tobacco initiation in all waves were the child being older,trimming tray the child living with another tobacco user, the child residing at least part-time in another home, the child having used alcohol or cannabis, and greater sensation seeking . In exploratory analyses, although interaction by child age was not statistically significant overall, numerically, strict household rules were associated with lower odds of tobacco initiation among children who were younger at wave 1 . In multinomial models, strict household rules were associated with lower odds of noncombustible tobacco initiation at all 3 time points but not necessarily with lower odds of combustible tobacco initiation . However, initiation of only combustible tobacco was uncommon , which yielded imprecise estimates. In the repeated measures analysis, strict household rules remained associated with lower odds of tobacco initiation within a year .In this assessment, we identified substantial lapses in parents’ awareness of their children’s tobacco use. Most parents or guardians registered suspicion when their children smoked cigarettes or reported poly tobacco use . Only approximately half as many knew or suspected when their children used only e-cigarettes or noncigarette combustible products. Of parental strategies to prevent future tobacco use by their children, setting strict household rules that prohibit all forms of tobacco use by anyone within the home was associated with less youth tobacco initiation, whereas talking with children about tobacco was not. The percentage of parents aware or suspecting their children’s cigarette smoking was higher than in previous findings suggesting poor parental awareness of youth smoking.Greater awareness may be due to increasing social concern around youth smoking or survey measurement differences. However, low parental awareness of e-cigarette use belies rising public and media attention surrounding youth vaping.

Constantly changing e-cigarette device designs and terminology pose an increasing challenge for parents to recognize, whereas lack of smoke and odor enhance conceal ability.Notably, PATH Study data were collected before a 2019 outbreak of vaping-associated lung injury,which could heighten parental awareness going forward. Cigarette smoking youth smoke more frequently than e-cigarette users use e-cigarettes, potentially increasing parental awareness opportunities. Lower awareness for cigars and hookah, which do produce smoke and odors, suggests a wider need for parents to monitor for all tobacco products, including those they may perceive as less common or concerning. Findings related to tobacco-free households align with previous research revealing that home anti-smoking attitudes and rules contribute significantly to youth smoking prevention.The present work suggests that this benefit extends beyond cigarettes to include initiation of any tobacco product use. Creating home tobacco-free environments offers the additional advantage of protecting children from harmful secondhand smoke exposure and may also benefit household adults by aiding smoking cessation.Our results align with longitudinal findings revealing a benefit of household smoking bans, whether or not youth lived with smokers.Our finding that the benefits of strict household rules appear greatest at younger ages suggests a need for additional focused prevention when adolescents transition to young adulthood and potentially enter new social environments. Unexpectedly, strict household tobacco rules were more strongly associated with prevention of noncombustible tobacco use than combustible tobacco use. This result must be interpreted cautiously because many youth initiate use of both product types, and strong concordance between burned and not-burned household tobacco rules makes it difficult to isolate independent effects. Nonetheless, setting household tobacco use rules may be a promising tool against the rise in youth e-cigarette use. Contrary to rules governing tobacco use in the home, youth who reported that that their parent or guardian had talked with them about not using tobacco were at higher odds of initiating tobacco use after 2 or 3 years. An implication of this result is that telling children not to use tobacco does not benefit youth compared with setting norms and examples via tobacco-free rules that apply to everyone. Alternatively, it is possible that parents were more inclined to talk about tobacco with youth already at elevated risk of tobacco use on the basis of personality aspects not captured by study variables.In the current study, we did not measure the quality or frequency of parents’ anti tobacco communication: likely key elements of effectiveness.Therefore, although strong household rules appears to be a much more promising approach, it should not necessarily be concluded that all parental communication is unhelpful in youth tobacco use prevention. Advantageously, the current study features a large, prospective, nationally representative sample. To our knowledge, this analysis is the first to assess prospective outcomes of home tobacco use policies on youth initiation of cigarette and non-cigarette tobacco use and the first national study to assess parental awareness of their children’s use of multiple non-cigarette tobacco products. Numeric findings were robust to the length of follow-up and adjusted for an extensive suite of established youth tobacco use risk factors.

Examination of marijuana use in this context will improve our understanding of whether marijuana use lessens the efficacy of alcohol interventions, even when delivered sequentially in stepped care. Furthermore, it will inform future intervention efforts aimed at reducing both alcohol and marijuana use.Alcohol use was assessed using the Alcohol and Drug Use Measure at baseline and each follow-up. To determine if participants who completed Step 1 of the intervention would also complete Step 2, participants reported the number of times they engaged in heavy episodic drinking , defined as consumption of 5+ drinks for males , in the past month. The maximum number of drinks consumed during their highest drinking event in the past month and the amount of time spent drinking during this episode were used to calculate the students’ estimated peak blood alcohol concentration using the Matthews and Miller equation and an average metabolism rate of 0.017 g/dL per hour.Alcohol-related consequences were assessed using the Brief Young Adult Alcohol Consequences Questionnaire , a 24-item subset of the 48-item Young Adult Alcohol Consequences Questionnaire . Dichotomous items are summed for a total number of consequences experienced in the past month. The B-YAACQ is reliable and sensitive to changes in alcohol use over time and has demonstrated high internal consistency in research with college students . In this study, the B-YYACQ demonstrated good internal consistency at baseline, 6-week and follow-up assessments .First, distributions of outcome variables were examined, and outliers falling three standard deviations above the mean were recoded to the highest non-outlying value plus one , resolving initial non-normality in outcomes. Demographic information and descriptive statistics for the outcome variables were calculated . To examine marijuana users’ drinking behavior following BA for alcohol misuse ,greenhouse benches multiple regression models were run to predict each alcohol outcome variable at the 6- week assessment from baseline marijuana user status , controlling for gender and the corresponding alcohol outcome assessed at baseline.

To test hypotheses 2 and 3, hierarchical linear models were run in the HLM 7.01 program , using full maximum likelihood estimation. HLM is ideal for data nested within participants across time, for testing between-person effects and within-person effects on outcomes. An additional advantage of HLM is its flexibility in handling missing data at the within-person level, allowing us to retain for analysis any participant that contributed at least one follow-up assessment. We interpreted models that relied on robust standard errors in the determination of effect significance. All intercepts and slopes were specified as random in order to account for individual variation in both mean levels of the outcomes and time-varying associations. Fully unconditional HLM models were run first in order to determine intraclass correlations for each outcome. ICCs provided information on the percentage of variation in each outcome at both the between- and within-person level. Next, three dummy coded time components were created for inclusion at Level 1. The first was coded and therefore allowed examination of the impact of effects on change in the outcome variable from baseline to the first followup, the second was coded to model the impact of effects on change in the outcome variable from baseline to the second follow-up , and the third was coded in order to estimate the impact of effects on change in the outcome variable from the first to the third follow-up . In the context of these three dummy codes, effects on the intercept represent effects when all time effects are equal to 0 . Of note, as all participants received a BA session in the interim between the true baseline and 6-week assessment, marijuana user status at the 6-week assessment was used as the baseline for these analyses .To address hypothesis 2 , Level 2 effects for marijuana user status, treatment condition, and the interaction between marijuana user status and treatment condition were regressed on the three time components. Following recommendations of Aiken and West , prior to forming interactions, marijuana user status and treatment condition were recoded using effects coding , to remove collinearity with interaction terms so that all main effects of time could be evaluated in the context of models including interactions. To control for potential baseline group differences, we also regressed marijuana user status and treatment condition on the intercept.

To address hypothesis 3 [i.e., whether treatment group impacts marijuana use frequency at any of the three follow-up time points, among those who reported marijuana use at 6-week pre-BMI assessment], at Level 2, treatment condition was regressed on the Level 1 intercept and all three time effects of marijuana use frequency. In models for both hypotheses 2 and 3, at Level 2, gender also was included as a covariate.The purpose of the current study was to examine whether heavy drinking marijuana users demonstrate poorer response to two different alcohol-focused interventions compared to non-users and to examine the efficacy of an alcohol-focused BMI on marijuana use frequency among marijuana users receiving stepped care for alcohol use. Our findings indicated that marijuana users and nonusers evidenced equivalent treatment responses to the alcohol-focused BA session and reported similar alcohol-related outcomes following the BMI. Consistent with prior research , the alcohol-focused BMI did not significantly reduce marijuana use frequency in comparison to the assessment-only group. In our sample, marijuana users did report higher alcohol consumption and problems at baseline/pre-BMI regardless of condition, and these differences between users and nonusers persisted over time. The findings of the current study are somewhat consistent with studies indicating that marijuana use does not decrease the efficacy of alcohol interventions . Although marijuana use did not necessarily lessen the efficacy of the BA and BMI sessions on alcohol use and consequences, regardless of condition, marijuana users reported higher levels of alcohol consumption and consequences at baseline and the pre-BMI assessment. These patterns suggest that heavy drinking marijuana users may still benefit from alcohol use interventions. This is especially noteworthy because dual users typically report increased consequences related to their alcohol use and may have a higher likelihood of being referred to alcohol-focused treatment or mandated to receive intervention for alcohol-related sanctions. Although heavy drinking marijuana users may demonstrate reductions in alcohol consequences following an alcohol-focused intervention , their frequency of marijuana use did not change as a result of receiving a BMI.

We can posit several reasons for the participants’ continued use of marijuana, despite a decrease in alcohol-related consequences. First, the parent study found a reduction in alcohol consequences following the alcohol-focused BMI, but not a decrease in alcohol consumption. Prior research examining secondary effects of alcohol BMIs have noted a decrease in marijuana use when there was also a decrease in alcohol consumption . It could be that factors that result in students’ experiencing fewer alcohol-related consequences without changing their drinking differ from ones that would lead to reductions in alcohol or marijuana use. Although our study did not include a measure of marijuana-related consequences, future research should examine changes in marijuana consequences to investigate whether changes in alcohol-related consequences correspond with changes in marijuana consequences following alcohol-focused BMIs. Second, a lack of effects may be due to the fact that our BMI was focused solely on changing alcohol-related behaviors and did not discuss the participant’s marijuana use. Future research should examine process coding in BMIs that do discuss marijuana use to explore possible in-session processes that may be related to changes in marijuana use and can be targeted in future interventions3 . Similarly, although alcohol and marijuana use share similar predictors , they may differ in their mechanisms of change. For example, the underlying motives that drive these two behaviors may vary so changing one will not ultimately lead to changes in the other and existing BMIs may not be targeting or altering both. Third, the referral incident in this study may not have been severe enough to warrant an overall re-evaluation of substance use, as may have been the case for those who required a visit to the ED as a result of their alcohol use . Marijuana users may require a more focused intervention or a supplemental session that targets alternative substance free activities to facilitate changes in marijuana use . Finally,growers equipment with growing trends in decriminalization and legalization of marijuana in the US, the perceived risk of marijuana has decreased among college students . Marijuana use may be more entrenched in the college social environment and more difficult to change without a targeted marijuana specific intervention. The results of this study should be interpreted within the context of its limitations. First, our study is restricted by our measure of marijuana use, which was limited to frequency and did not assess for marijuana-related consequences. Future studies may include assessments of quantity, days smoked, and consequences to get a better of understanding of the severity of participants’ marijuana use. Although daily marijuana use is on the rise, with almost 6% of college students reporting daily use , marijuana users in our study were using about 13.7 times in the past month. This is fairly low compared to those seeking treatment for marijuana use or being seen in an emergency department. For example, Metrik et al. found that compared to lighter users, those who reported weekly marijuana use demonstrated a significant decrease in use following treatment. Furthermore, our measure of pBAC was derived from participants’ reported heaviest drinking event and may not be the best way to capture peak BAC levels. Additionally, the study sample was predominantly white which may limit our ability to generalize findings to other populations of interest. Finally, we relied on self-reported data collection that did not include corroborating measures. Research using collateral informants indicated that mandated students may under-report alcohol use . Despite these limitations, this study adds to the existing literature on the secondary effects of alcohol-focused BMIs. To our knowledge it is the first study to examine the influence of two different alcohol interventions on marijuana use in the context of stepped care. Furthermore, findings indicate that heavy drinking college students who also use marijuana may still benefit from alcohol treatment especially in reducing their alcohol related consequences.

From a theoretical perspective, our results suggest that changing one behavior does not necessarily mean changes in another will occur, at least with respect to marijuana. However, future work should examine other health behaviors that might change as a result of reducing alcohol consequences. For example, it may be that increases in substance free activities like exercising, volunteering, or academic related behaviors occur alongside changes in alcohol-related behaviors . Future research examining marijuana focused interventions of different intensity implemented in a stepped care approach may enhance our understanding of which interventions are most effective for college students with varying levels of involvement with marijuana.Humans support the growth and maintenance of diverse sets of microbes in niches in contact with the environment including skin, lungs, mouth and gut. Studies of these microbes in the gut and oral cavity have uncovered key interactions between bacteria and human hosts in a wide variety of normal and pathological states. Many of these interactions are inferred from correlations between the composition of the microbial populations and changes in health status. For example, in gingivitis, an increase in Gram negative and anaerobic bacteria causes inflammation in the mouth. Our understanding of the basis for changes in microbial composition, and of how these changes influence human phenotypes, is still a work in progress. Clearly environmental factors and host genetic factors have important influences, perhaps best demonstrated to date by studies in the gut. Candidate gene studies have been most effective at identifying human genetic influences on the microbiome. By this approach, informed hypotheses about human genes that may conceivably influence a particular microbiological phenotype are tested with family or population-based studies to identify human variants that are statistically consistent with the hypothesis. Examples include MHC genes, SLC11A1, the MEFV gene, FUT2 gene, and loci linked to susceptibility to infectious disease. While often successful, the candidate gene approach is limited by the ability to formulate hypotheses given current knowledge. They are neither comprehensive nor sufficient to identify the entire range of human genes involved in population changes associated with complex phenotypes or with maintenance of the composition of the “normal” microbiome. In addition the significant inter-individual variation in microbiome composition often masks specific effects of human genes if insufficient numbers of individuals are studied. Moreover, the microbiome of a niche includes complex mixtures of organisms and is in part defined by interactions among its members making the identification of a “microbial phenotype” complicated.

Two major kinase-mediated signaling pathways are activated following TLR4 stimulation by LPS. These include the MAPKs and IkB kinase complexes, which lead to activation of AP-1 and NF-kB transcription factors, respectively. Here we show that LPSup regulated expression of Dusp1 was significantly up regulated by CBD but not by THC. An increase in the expression of Dusp1 was also observed following incubation of resting BV-2 cells with CBD, but not with THC. A similar CBD mediated regulation of mRNA level was observed for Dusp8, another negative regulator of MAPKs. The IPA interactome analysis has linked this CBD-stimulated expression of Dusp8, via negative modulation of p38 MAPK, to the attenuation of LPS mediated induction of NFAT5, a member of the inflammatory transcription complex. On the other hand, the LPS-stimulated expression of Dusp2 , a key positive regulator of the inflammatory MAPKs signaling, was significantly repressed by CBD as well as by THC. Moreover, CBD but not THC decreased basal levels of Dusp2/Pac-1 mRNA in resting BV-2 cells. IPA and interactome analysis indicate that pretreatment with CBD, but less so with THC, result in attenuation of LPS stimulated activation of NF-kB and its dependent gene transcription pathways. Indeed, our previous data show that CBDdecreases the activity of the NFkB signaling pathway in BV-2 microglial cells via the partial reversal of the LPS-induced degradation of IRAK-1 intermediate kinase, thus reversing IkB degradation and reducing NF-kB p65 subunit phosphorylation. This effect of CBD in decreasing NF-kB signaling activity is in line with the CBD-induced diminished transcription of NF-kBdependent genes, e.g., IL-1b and IL-6. We and others previously reported that BV-2 cells express CB1, CB2, GPR55, GPR18 and TRPV2, G protein-coupled receptors and a channel that are known to interact with cannabinoids.

Using gene array analysis,procona florida container we have observed that the relative levels of CB1, CB2, GPR18 and TRPV2 as well as of the fatty acid amide hydrolase gene transcripts were not significantly affected by the cannabinoid treatments and their levels did not exceed the 2-fold induction or 50% reduction by either CBD or THC treatment. On the other hand, we show here that LPS markedly down regulates CB2 and GPR55 and that this down regulation is not affected by either CBD or THC pretreatment. This result is in agreement with our previous report showing that LPS markedly down regulates CB2 and GPR55 mRNAs in BV- 2 microglial cells and in microglial primary cultures.A relationship between CBD-mediated oxidative stress response and glutathione depletion was previously reported . More recently, we showed that CBD-specific gene expression profile in BV-2 cells displays changes normally occurring under either nutrient limiting conditions or proteasome inhibition, and that are attributed to activation of GCN2/eIF2a/ p8/ATF4/CHOP-Trib3 pathway leading to autophagy as well as to apoptotic cell death. The Trib3 gene product seem to be of high importance to the CBD effect due to its ability to serve as a master regulator of an array of pathways including AP-1, ER stress, Akt/PKB and NF-kB. Trib3 expression is significantly up regulated by CBD as well as by THC and as observed here, remains up regulated after LPS treatment . According to these gene array studies and the qPCR results, LPS by itself does not significantly affect the expression of Trib3 mRNA. IPA interactome analysis of the microarrays data reveals an interaction between the CBD-up regulated Trib3 and the NF-kB transcription factor pathway . This interaction seems to be responsible for the attenuation by CBD of the transcription of many proinflammatory genes. There are several indications suggesting interaction between these two pathways. First, a direct interaction between p65/RelA and Trib3 protein which induces inhibition of PKA dependent p65 phosphorylation, was described. Second, Trib3 protein can negatively regulate the serinethreonine kinase Akt/PKB, a downstream effector of PI3K that has been implicated in the potentiation of NF-kB-induced transcription of proinflammatory mediators.

This negative regulation of Akt activity by the highly induced Trib3 gene product could point to the mechanism for the CBD-mediated regulation of LPS-stimulated gene expression. Indeed, the effect of CBD treatment on a number of LPS-stimulated genes as reported here is reminiscent of the effects described for the PI3K inhibitor and for the NFkB inhibitor in the murine macrophage cell line RAW264.7 activated with LPS. Both PI3K and NFkB signaling pathways exert important roles in gene expression in response to LPS, but they are not overlapping. Specifically, treatment with CBD repressed a number of typical proinflammatory genes stimulated by LPS, which are known to be NFkB dependent and of other genes including Csf3, Il-1b, Il-1a and Cox2/Ptgs2, which are under the control of both PI3K and NFkB pathways. Finally, Trib3 was documented to interfere with the inflammatory MAPK signaling via direct interaction with MEK-1 and MKK7 leading to attenuation of AP-1 mediated transcriptional activity in cancer HeLa cells. AP-1 is a transcription factor involved in the regulation of inflammation-mediated cellular functions and has been shown to be inhibited by Nrf2-activating agents. Indeed, our IPA network analysis indicates that the observed decrease in mRNA levels for a number of genes is probably related to a reduction in AP-1 dependent transcription. Additionally, according to these IPA results, this repression is reinforced by combined treatments of CBD and LPS as observed by the induction of FosL1 gene product, another negative regulator of AP-1 . Trib3 has been shown to down regulate PPARc transcription and serve as a potent negative regulator of adipocyte differentiation and PPARc is a molecular target for CBD that could be involved in mediating transcriptional effects in BV-2 microglial cells. Indeed, CBD has been shown to bind to PPARc in vitro as well as to activate its transcriptional activity in 3T3L1 fibroblast and in HEK293 transfected cells. In addition, Necela et al., described a regulatory feedback loop in which PPARc represses NF-kB-mediated inflammatory signaling in unstimulated macrophages.

Moreover, they show that upon activation of TLR4 in LPS-stimulated macrophages, NF-kB drives down PPARc expression. These results are in agreement with our results showing that LPS highly down regulates the expression of Pparg1 and Pparg2 in BV-2 cells. The profiles of CBD-induced gene expression with either resting or LPS-activated BV-2 cells, show that CBD stimulates the transcription of several anabolic genes encoding amino acid bio-synthetic enzymes, amino acid transporters and aminoacyltRNA synthetases known to be activated by ATF4, a basic leucine zipper transcription factor, that is increased when cultured cells are deprived of amino acids or subjected to endoplasmic reticulum stress . The divergent types of stress converge on a single event—phosphorylation of the translation initiation factor eIF2a, resulting in a general translational pause followed by selective increase in ATF4 mRNA translation and subsequent stimulation of expression of ATF4 target genes. Many of the CBD-affected transcripts are indeed classified as Nrf2-mediated oxidative stress response genes, including enzymes involved in the biosynthesis of glutathione. Thus, the observed CBD-mediated induction of ATF4-dependent anabolic genes may serve to replenish the amino acids reduced during the elevated turnover of GSH . The mechanism underlying CBD action presumably engages generation of ROS which in turn depletes intracellular GSH. Perturbations in redox tone and GSH levels activate the ‘‘phase 2 response’’, a mechanism used by cells to mitigate oxidative stress. As we have previously shown, many of the ‘‘phase 2’’ gene products are significantly up regulated by CBD. Our present results show that CBD, and less so THC, have immunosuppressive and protective activities that are reminiscent of other clinically applied drugs such as glucocorticoids ,procona London container rexinoids and synthetic triterpenoids. GCs are immunomodulatory agents known to act as suppressive and protective mediators against inflammation. GCs are known to clear antigens by stimulating cell trafficking as well as scavenger systems and matrix metalloproteinases while they stop cellularimmune responses by inhibiting antigen presentation and T cell activation. Synthetic oleanane triterpenoids were shown to be highly effective in many in vivo models in the prevention and treatment of cancer and other diseases with an inflammatory component. Molecular targets of SO include KEAP1 , PPARc, IkB kinase, TGF-b signaling and STAT signaling. SO are among the most potent known inducers of the phase 2 response both in vivo and in vitro and affect the expression of several key cell cycle proteins . In some cancer cells, SO signal through PPARc to inhibit proliferation. The rexinoids bind almost exclusively to the RXRs and are involved in regulation of development, cell proliferation, differentiation and apoptosis. Because RXRs heterodimerize with other receptors , rexinoids modulate the actions of many steroid-like molecules that control metabolism and cellular energetics. In view of these results, triterpenoids and rexinoids are defined as multifunctional drugs. Their targets are either regulatory proteins that control the activity of transcription factors or transcription factors themselves . These complex modulatory activities exerted by GCs, rexinoids and SO display a panorama of effects that closely resembles the complex actions of CBD.Preventing and reducing risky opioid misuse among older adolescents and young adults is critical given that peak misuse rates and associated morbidity and mortality coincide with this developmental period.

Nationally, past-year prescription opioid use ranges from 19.7% for ages 16-17 to 28.2% for ages 26-29, whereas past-year opioid misuse ranges from 3.4% to 5.8%, for these age groups respectively.Nearly one in three adolescents who report prescription opioid misuse by age 18 transition to heroin use in young adulthood.AYAs who misuse opioids are at increased risk for adverse health outcomes6 such as fatal/non-fatal injury, overdose, and opioid use disorder, warranting approaches designed to mitigate these consequences. U.S. emergency departments have over 130 million visits annually and the ED is a key location to bridge the divide to increase access to services and connection to the larger health system among at-risk AYAs who often are not continually connected to healthcare providers.Despite the current US opioid crisis, early interventions for AYAs focused on preventing opioid misuse/opioid use disorder are generally lacking in healthcare settings and research has called for more robust strategies, including those that use health coaching, focused on opioids.Although ED-based brief motivational interventions delivered by counselors of varying training backgrounds reduce other substance use/consequences among AYAs, their impact when tailored for AYA opioid misuse remains to be seen, lending to the focus of this trial. Our emphasis on tailored motivational interventions is underscored by prior work finding primary efficacy of a single-session brief motivational intervention in reducing opioid misuse and overdose risk behaviors in adult ED patients.We also demonstrated the secondary efficacy of ED and primary care-based brief interventions on reducing AYAs’ prescription drug misuse . We blended and packaged the content from these promising interventions as an initial intervention strategy in this trial. Our delivery approach for this early intervention is designed to increase the likelihood of implementation in busy medical settings, by using remote health coaches , allowing for real-time personalization and maximizing shelf-life to adapt to this rapidly changing crisis, with limited impact on ED staff. Due to the short-term and modest effects of the prior interventions mentioned above, we are also testing a strategy wherein health coaches are providing MI-based interventions for 30 days post-ED visit using a chat-based web portal. This portal mirrors the messaging style, and increasingly the function, of health systems’ patient portals, which promotes future implementation and scalability. Indeed, our prior work demonstrated the potential of this approach by delivering motivational interviewing-based 23 content in a portal-like platform to enhance motivation to seek mental health services for suicide prevention and others have used a portal to deliver alcohol-related feedback.After evaluating feasibility and acceptability of our ED-initiated interventions among AYAs screening positive for recent prescription opioid use with at least one risk factor or prescription or illicit opioid misuse we initiated a 2 x 2 factorial randomized controlled trial . The primary aim of the RCT is to evaluate the efficacy of 1) an intake condition of a remote health coach-delivered single session brief motivational intervention vs. a control condition of an enhanced usual care community resource brochure; and, 2) post-intake health coach-delivered portal-like messaging via a web portal over 30 days or EUC delivered at 30 days post-intake. Testing the relative efficacy of the health coach session, health coach session combined with the portal, or the portal intervention alone has high potential for public health impact by identifying the most effective combination of strategies to reduce primary outcomes of opioid misuse severity.

Cognitive Behavioral Social Skills Training combines both social skills training and cognitive‐ behavioral therapy to improve real‐world functioning . In one RCT, individuals who engaged in CBSST demonstrated better rates of achieving functional milestones as compared to individuals who received goal‐ focused supportive contact . Participants also showed greater improvement in experiential negative symptoms and defeatist performance attitudes. In another RCT of middle‐aged and older adults with schizophrenia, individuals who received CBSST demonstrated superior self‐ reported community living skills and a lower dose of psychotropic medications at 12‐month follow‐up compared to treatment as usual . Here we present data from a recently developed CBSST‐based program for adult patients with primary psychotic disorders—the UCLA Thought Disorders Intensive Outpatient Program . In addition to CBSST, participants received group‐modality self‐care and life skills training, medication management, case coordination, and brief individual supportive psychotherapy. We aimed to assess the TD IOP’s feasibility from a program development perspective as well as to assess the impact of this program on improving participants’ psychotic symptoms.CBSST is delivered in three modules, each lasting 2 weeks. The group is limited to 10 participants. The program is expected to last at least 6 weeks, longer if more treatment is clinically indicated. The program is held 3 days weekly from 1 p.m. through 4 p.m. Each day consists of 1 hour of CBSST as well as 2 hours of additional group therapy. Group‐modality treatment focuses on sleep hygiene, self‐ esteem building, time management, medication side‐ effect management, diet, and mindfulness, among others. Social workers meet with participants at least weekly to address participant concerns and provide brief individual supportive psychotherapy as well as any case management needs. Participants also meet regularly with their psychiatrist for medication management. Nurses are available for consultation regarding diet and nutrition; they also regularly measure vital signs,vertical grow rack system including weight. Family meetings are held as indicated with the participant and his or her social worker and psychiatrist.

The primary measurement tool used to assess the effectiveness of the program was the Clinician‐Rated Dimensions of Psychosis Symptom Severity scale. The CRDPSS scale was developed by the American Psychiatric Association as a patient assessment tool to assist with evaluating severity of mental health symptoms important across psychotic disorders and monitoring treatment progress . Symptoms are categorized into eight domains , as follows: DI, hallucinations; DII, delusions; DIII, disorganized speech; DIV, abnormal psychomotor behavior; DV, negative symptoms; DVI, impaired cognition; DVII, depression; and DVIII, mania. Each domain is scored by the clinician on a scale of 0 through 4 . Detailed descriptors are included that correspond to each value on the scale. The scale was administered by licensed clinical social workers each week from intake through discharge. Demographics and clinical characteristics were obtained by chart review for each participant.Table 1 summarizes the demographic, psychiatric, and recruitment characteristics of the participants. Among the 92 enrolled participants, average age was 30.5 ± 10.7 years; 65.2% identified as male, 32.6% as female, and 2.2% as non‐ binary. Most of the participants were referred to the program from an inpatient psychiatric hospital, while 33.7% were referred from an outpatient practice. Diagnostically, 41.3% of participants were diagnosed with schizophrenia, 29.3% of with unspecified psychotic disorder, and 19.6% with schizoaffective disorder. The majority of those with unspecified psychotic disorder at the time of their participation in the program displayed features consistent with likely schizophrenia or schizoaffective disorder but due to length of symptoms and/or confounding presence of substance abuse, a precise diagnostic determination could not be made. Only 4.3% of participants had never been psychiatrically hospitalized; 64.1% reported two or more hospitalizations. A history of daily cannabis use was indicated by 41.3% of participants. Of the 92 participants enrolled, 71 completed the full program . Reasons for early termination included COVID‐19 , transfer to residential program due to worsening suicidal ideation , transfer to inpatient hospital due to acute decompensation , transfer to general intensive outpatient program , transportation issues , starting new employment , suicide , and patient preference or other reason . The average length‐of‐stay for all enrolled patients was 52 ± 30 days , or approximately 8 weeks.

No sociodemographic factors or baseline clinical factors predicted early termination as assessed by univariant logistic regression analysis . Given even early terminators completed an average of 3 weeks of the program, all participants with complete pre‐ and post‐treatment CRDPSS data were included for outcome analysis . As shown in Table 2, participants showed statistically significant improvement across five of eight psychosis symptom domains as measured by the CRDPSS scale, with mean scores on discharge improving over mean scores on admission for domains I , II , III , VII , and VIII . Effect sizes for DI, DII, and DVII ranged from ∼0.4 to 0.6, indicating moderate‐ large effects. For DIII and DVIII , effects sizes were ∼0.3, indicating small effect size. No significant changes were found for DIV , DV , and DVI . Mean antipsychotic dose did not differ significantly between admission and discharge for all included participants . Antipsychotic dose remained the same or was reduced for most of the program participants over the course of the program. Restricting the analysis to patients that completed the program did not alter the results .Participants improved an average of 2.6 domains and 80/86 experienced improvement in at least one domain. Domains II and VII were improved in approximately half of the participants . Univariate logistic regression analysis was performed to determine if age, gender, or education associated with improvement in each domain. Male gender associated with reduced odds of any domain I improvement and college education associated with increased odds of any domain II improvement and domain VIII improvement . Participant program feedback is summarized in Table 3 . Overall program satisfaction was high . Program strengths were noted to be socialization/support , therapy/skill building , and provider access . Suggested improvements included increasing group discussion and improving the educational materials. Most participants cited no barriers to attendance with 23.1% and 7.7% reporting driving and parking as barriers, respectively.The present study evaluated the impact of an intensive outpatient program designed specifically to treat individuals with thought disorders. Our study showed that participants demonstrated statistically significant improvement in five out of eight psychosis symptom domains, as measured by a clinician‐rated scale. Additionally, most participants completed the program either with a reduction or no change in antipsychotic dose, indicating improvements cannot be attributed to medication alone.

In addition, the program was simple in design, feasible to incorporate under the umbrella of an existing general intensive outpatient program, required minimal resources for training and planning, and was effectively implemented by Master’s‐level clinicians. Although cognitive therapy has been frequently included in recent years as a standard recommended treatment for psychosis , few studies have evaluated the effectiveness of cognitive therapy for psychotic patients in non‐research‐based community mental health settings. An effectiveness study from Australia did not find significant improvement in symptoms in those receiving CBT for psychosis compared with controls; this was thought to be due to several factors,vertical grow system including the high quality of mental health services received by controls . Other studies have shown more positive results. One study showed that individual cognitive therapy provided to adults with psychotic disorders by clinical psychologists or nurse therapists in a community setting was associated with statistically significant improvements in positive symptoms, general mental health problems, and depression . In another small study in a community setting, one‐third of patients receiving up to 13 cognitive therapy sessions reported reduction in delusional conviction . One UK‐based study showed that delivery of six CBT sessions to a community sample of schizophrenia patients by mental health nurses, who were trained in CBT over just a 10‐day period, resulted in statistically significant improvements in negative symptoms and insight at 1‐year follow‐up . Several randomized controlled trials have evaluated the role of CBSST in the treatment of adults with psychoticdisorders. One study showed that middle‐aged and older patients with schizophrenia performed activities related to social functioning significantly more frequently than those who received treatment as usual, with improved self‐ reported functioning at 12‐month follow‐up . In a study of non‐geriatric adults with schizophrenia or schizoaffective disorder, those randomly assigned to receive CBSST experienced significantly greater functional improvement as well as greater engagement in educational activities when compared with those receiving goal‐ focused supportive contact only . CBSST has also been shown to benefit a first‐episode population, with significant functional gains observed among young patients with schizophrenia who had received less than 6 months of treatment .

To our knowledge, ours is the first study to evaluate the delivery of CBSST in a community setting. In addition, our study adds to the evidence base showing the effectiveness of CBSST in treating adult, non‐geriatric patients in various stages of illness. Of particular interest from a cost reduction perspective is the potential decrease in healthcare costs associated with CBSST. Previous studies examining the cost‐ effectiveness of individual CBT for psychosis have shown mixed results, with one showing increased initial healthcare costs though savings over time due to decreased service utilization , two showing neither cost benefit nor deficit , and one showing higher cost though better outcome in the CBT group . As a group‐based modality, CBSST requires far fewer therapist hours in comparison with the equivalent delivery of individual therapy. Prior studies have shown that the “dose” of CBSST sessions required to provide results was fewer than anticipated. For example, in one study, number of CBSST sessions attended was not significantly associated with outcome, with participants receiving an average of only 12 out of 36 offered sessions ; in another, there was no significant benefit from repeating CBSST modules a second time . Our study showed that significant gains were achieved even without program completion, suggesting again that patients can benefit from even brief engagement in CBSST. Our study population was clinically acute, as 60% of participants were referred directly from an inpatient hospital and almost all had a history of at least one psychiatric hospitalization, with 64% having a history of two or more prior hospitalizations. Despite the acuity of our study population, most participants completed the program. Our population appears like that described in the study by Farhall et al., in which patients randomized to receive CBT for psychosis had a median of 25 inpatient days and an average of 2.2 inpatient admissions prior to baseline assessment. In that study, the acuity of the population was thought to contribute to no significant symptom change between the control and treatment as usual groups . In contrast, our study suggests that even very ill patients with psychotic disorders can benefit from intensive outpatient treatment built on talk‐based therapy. Furthermore, these patients endorsed high subjective satisfaction with the program. A major strength of our study is its naturalistic design. The TD IOP program at UCLA was conceived as an inclusive treatment option for adults of all ages and in all stages of a psychotic illness. Non‐naturalistic studies for talk therapy in psychosis tend to focus on specific populations, such as geriatric or non‐geriatric adults, or adults who are experiencing their first episode of psychosis. In addition, our CBSST providers were non‐doctoral level therapists, most of whom had no significant prior experience working with psychotic disorders, though they did have extensive knowledge of delivery of CBT. They were able to effectively work with the study population after only 11 h of training in CBSST. Given the primary barrier to program attendance related to transport, community implementation of CBSST programs would confer significant value. Our study had several limitations. The sample size was limited to a single treatment arm. As unblinded, there is the potential for rater bias towards positive study results. New as of DSM‐5, the inter‐rater reliability and convergent validity of the CRDPSS remains underexplored. One study found low inter‐rater reliability scores except for the delusions domain. Positive associations, however, were found between CRDPSS and Positive and Negative Syndrome Scale , indicating convergent validity . A self‐reported measure of psychosis is not included. We did not follow‐up individually with patients outside of chart review; as such, no conclusion may be drawn if gains achieved in the program persisted or if treatment resulted in reduced number of future inpatient admissions. Treatments that improve the quality of life of individuals with psychosis is a matter of great significance to public health. Our data indicate that improved socialization and functioning are concerns shared by affected individuals and clinicians alike.

Contrary to our hypothesis, staying in shelters or meeting criteria for depressive symptomatology or significant distress on the CES-D scale was not associated with current smoking. Given that the more than half the participants reported a shelter stay or depressive symptomatology, these characteristics may not have differentiated smokers and nonsmokers in our study sample. Persons who reported a jail or prison stay in the past 6 months at enrollment had a non-significantly higher likelihood of being a smoker than those without a history of incarceration. Consistent with our hypothesis and previous studies,use of illicit substances and alcohol use were associated with current smoking among participants in our study. Comorbid substance use disorders pose significant challenges to smoking cessation because the use of illicit substances may provide social cues to smoking and augment the pleasurable effects of nicotine.Given these findings, there is mounting evidence for the integration of treatment for nicotine dependence with that of substance use treatment.A meta-analysis showed that treating nicotine addiction during substance use treatment may enhance short-term smoking cessation and lead to prolonged abstinence from alcohol and other illicit substances.Lower cigarette consumption and prior quit attempts were associated with increased likelihood of a subsequent quit attempt at follow-up. Time to first cigarette after waking, a nicotine dependence measure predictive of smoking cessation,was not associated with making a quit attempt in adjusted analysis. Concurrent use of other tobacco products, which is common among homeless adults,may reduce reliance on cigarettes and may reduce the predictive validity of time to first cigarette after waking as a predictor of cigarette quit attempts.Contrary to our hypothesis and previous studies that have shown an association with depression and decreased quit attempts,ebb flow table our results showed a higher likelihood of quit attempts among those who with depressive symptomatology .

In post hoc analysis we found that persons with depressive symptomatology showed a non-statistically significant higher likelihood of having received advice from a healthcare provider to quit smoking, suggesting that these individuals may have been both more engaged in health care and more likely to receive advice to quit and/ or other resources for smoking cessation. Staying in a shelter was associated with an increased likelihood of a quit attempt. Shelters may provide a more stable environment than unsheltered environments to engage in smoking cessation. Shelters have smoke-free policies that may motivate individuals to make quit attempts.Few shelters offer on-site resources, but most provide referrals to community-based resources for smoking cessation.These factors may also encourage quit attempts among homeless clients. Previous research has shown that the majority of smokers who attempt to quit smoking relapse back to smoking,but the longer the duration of smoking abstinence, the higher the likelihood of successful quitting.In a study of former smokers in the general population, only 12% of those who had abstained from smoking for less than 1 month at baseline were continuously abstinent from smoking at follow-up 1 year later; almost 50% had resumed smoking at follow-up.Only three participants reported sustained abstinence at 6 months follow-up. The results of this study highlight the difficulty of quitting smoking successfully, a task that is much more challenging when faced with the stress of material resource constraints and social disorganization common in homelessness.Given that a significant proportion of the sample was engaged in quitting behaviors during the study interval, our findings highlight the need for more effective therapies that increase the rate of successful quitting among older homeless smokers.Previous studies have identified limited access or poor adherence to smoking cessation aids, depression, lack of access to smoke-free homes, illicit substance use, and stress from social stressors as factors associated with relapse.Despite being socioeconomically disadvantaged, about one-fourth of the participants in the current study reported that they had used NRT or FDA-approved medications during the last quit attempt, a proportion that is similar to the general population.Although a minority of our study population reported achieving 30-day or 90-day abstinence, use of cessation medications was not associated with abstinence.

We may have been under powered to detect a meaningful difference in abstinence rates between those who did and did not use NRT, highlighting a need for studies that explore the efficacy of NRT for smoking cessation in this population. Other factors may influence the efficacy of NRT for smoking cessation in the homeless population including intensity of smoking,use of concurrent tobacco products, frequency of use of NRT, and access to other treatments for cessation; these factors merit further exploration. Examining access to smoke-free living environments, identifying messages to convey smoking-related health effects, and identifying perceptions of current tobacco control strategies may provide additional insights into developing effective interventions for smoking cessation among this population. Our study had several limitations. As in our previous work,we relied on self-reports of tobacco cessation behaviors, potentially leading to recall bias and over- or under-estimation of cessation rates. The lack of biomarker-verified measures of abstinence could result in potential inaccuracies in the estimates of prolonged abstinence. The slightly lower 6-month follow-up rate among smokers than nonsmokers may have led to a potential differential misclassification bias in estimates of tobacco cessation at follow-up. While we were able to assess whether participants switched to other tobacco products for cigarette smoking cessation, we were unable to assess concurrent use of other tobacco products with cigarette smoking. We were unable to determine whether receipt of tobacco cessation services in homeless shelters could have influenced sheltered participants’ decision to make a quit attempt. Our study sample that included predominantly African American participants may not be generalizable to other populations of older homeless adults across the United States. However, given the increased tobacco-related disease burden among African American smokers,our study provides insight into smoking cessation behaviors that might guide intervention development for this population. Despite these limitations, this is among the first studies on tobacco use and cessation to focus specifically on older homeless adults.

The high prevalence of smoking and the low rates of successful quitting highlight numerous opportunities to intervene to increase quitting rates among this population. Among these, increasing access to smoke-free living environments and identifying effective cessation therapies will be critical to reducing tobacco-related disease burden among older homeless adults.There were over 2 million incident cases of bacterial sexually transmitted infections in the United States in 2017.Surveillance data suggest dramatic increases in the incidence of syphilis, chlamydia, and gonorrhoea despite overall declining rates of new HIV infections.Preliminary estimates comparing new STI diagnoses between 2013 and 2017 indicate a 76% increase in syphilis, a 67% increase in gonorrhoea, and a 21% increase in chlamydia.These substantial increases have raised concerns about the spread of treatment-resistant gonorrhoea, increased morbidity from untreated infections, and other serious public health consequences . There is also uncertainty regarding whether the high incidence of STIs will compromise the long-term success of antiretroviral therapy -based prevention strategies such as pre-exposure prophylaxis and treatment as prevention .4 Although ART-based prevention will likely remain effective even in the presence of STIs,available data are not sufficient to rule out the possibility that STI-induced genital inflammation can facilitate local shedding of HIV despite systemic control.People with HIV , particularly men who have sex with men , are among the most severely impacted by the STI epidemic. For example, county surveillance data from San Francisco, California, indicate that between 2011 and 2014, the number of new STI cases among PWH increased by over 38% from 992 to 1372.Unhealthy alcohol use and drug use are prevalent among PWH,hydroponic grow table and place individuals at even greater risk for STIs as these have been associated with risk-taking behaviours and worse health outcomes.Unhealthy alcohol use refers to a range of drinking behaviors that increase the risk of negative health consequences.Previous studies have found that unhealthy alcohol use and drug use are associated with condomless sex and poor medication adherence and retention in care.Given the burden of STIs in this medically vulnerable population, it is critical to identify subgroups of PWH at greatest STI risk to target resources and optimize screening and early treatment. In this study, we examined the prevalence of bacterial STIs and associated correlates, including alcohol and drug use and partner PrEP use, among a primary care-based cohort of PWH with unhealthy alcohol use in an integrated healthcare system.

During the 24-month follow-up interview, participants were asked whether any of their partners in the last year used PrEP . Participants could respond with either “Yes,” “No,” “All my partners have been HIV-positive,” or “Don’t know/refuse.” Those who had no partners in the previous year were automatically marked as “Don’t know/refuse.” Participant responses were categorized by partner HIV status and PrEP use into mutually exclusive categories: HIV-positive partners only ; HIV-negative partners with at least one on PrEP; and HIV-negative none on PrEP . Participants with responses coded as “Don’t know/refuse” were excluded from our analyses to avoid misclassification as this group potentially included individuals who were not sexually active in the previous year. Participants were also asked about condom use during anal and/or vaginal sex and total number of partners in the last six months. Additional data collected included stimulant use , opiate use , cannabis use, and use of other drugs in the last year, as well as any alcohol and/or drug use before sex in the last six months. Drug and alcohol use were assessed using an interviewer-administered questionnaire . Severity of alcohol use was measured using the Alcohol Use Disorder Identification Test .AUDIT scores were interpreted based on standard cut-offs: <7 indicated low risk for alcohol use disorder; indicated hazardous use; suggested high risk for alcohol use disorder; and scores 20 or greater suggested a likelihood for alcohol use disorder.Interview responses were combined with laboratory data regarding most recent HIV viral load and positive STI tests in the prior year from the KPNC electronic health record. HIV viral suppression was defined as most recent viral load <75 copies/mL. Our outcome of interest was prevalence of any laboratory-confirmed bacterial STI in the year prior to the 24-month follow-up interview. STI testing was completed as part of routine clinical care. Extragenital testing was based on patient and provider discretion, and results were included in our analysis if tests returned positive. Syphilis was tested using a rapid plasma reagin and a treponemal IgG and IgM antibody test. Syphilis infections that occurred within the study period were identified based on a 4-fold increase in RPR titers.Those who had no positive results were assumed not to have an STI because PWH are screened for those STIs frequently in our healthcare delivery system, with quarterly testing recommended for most of those who are sexually active. Participant characteristics, including viral load, were summarized using descriptive statistics. The Kruskal-Wallis test was used to evaluate differences in median number of sex partners between PWH who had HIV-positive partners only, those who had at least one partner on PrEP, and those who did not report any partner PrEP use. Differences in condom use across partner groups were evaluated using chi-square tests. We estimated prevalence ratios to evaluate the association between alcohol and drug use and partner PrEP use with STIs using Poisson regression models fitted with robust variance estimators. Covariates were selected a priori using clinical judgment and all variables in the unadjusted models were used in the final adjusted model. Variance inflation factor was used to test for collinearity between all of the predictor variables. Analyses were completed using Stata 14 . This study was approved by the Institutional Review Boards at KPNC and at the University of California, San Francisco . Of the 614 PWH in the parent study, 553 participants completed 24-month interviews; of those, 88 did not provide partner information and were excluded from this analysis. Participant characteristics are summarized in Table 1. Of the 465 PWH in this analysis, median age was 52 years . Most were white , college educated , and MSM . Thirty-two percent of participants had HIV-positive partners only, 31% had at least one HIV-negative partner in the previous year who took PrEP, and 37% had HIV-negative partners without reported PrEP use. Approximately 94% of all participants were virologically suppressed. Of the 318 PWH with HIV negative partners, most were either suppressed or reported partner PrEP use in the prior year. The majority of participants had low risk alcohol use. However, self-reported drug use in the past year was common.

A recent follow-up of this cohort reported that PS at age 11 were associated not only with a diagnosis of schizophrenia at age 38 7.24) but also with diagnoses of Post Traumatic Stress Disorder , substance dependence , depression , and anxiety . Higher rates of PS at age 11 further predicted suicide/ suicide attempts at age 38, even when controlling for other psychiatric disorders at age 11 [the 15-year follow-up study of the Dunedin cohort at age 26 reported very similar findings ]. It is important to note, however, that PS were assessed with the Diagnostic Interview Schedule for Children, an instrument that includes only 5 questions on positive PS. The Avon Longitudinal Study of Parents and Children , with over 13,000 study participants, includes a total of 68 assessment points between birth and age 18. Niarchou et al. reported that, similar to results from the Dunedin cohort, PS at age 12 were predictive of a psychotic disorder at age 18 12.7. Interestingly, nonspecific symptoms such as depersonalization and sub-psychotic unusual experiences were predictive of a psychotic disorder and depression at age 18 . Even though, ALSPaC also assessed only positive PS, the semi-structured PLIKSi instrument covers the three major domains of positive PS, i.e., hallucinations, delusions, and bizarre thinking, and therefore reflects a broader spectrum of PS . Overall, in the general population it appears that PS during childhood and adolescence increase the risk of later development of a broad range of psychiatric illnesses . PS in help-seeking individuals fulfilling CHR criteria may be more specific in terms of predicting psychosis onset even though rates of co-occurring nonpsychotic disorders are also higher in these cohorts relative to the general population . Although their etiology is not well understood,grow tray PS throughout life are often preceded and accompanied by emotional and behavioral problems, which in turn are often associated with life adversities.

Findings from the ALSPaC sample further confirmed previously described risk factors. In particular, early neurodevelopmental problems such as autism spectrum symptoms, asphyxia during birth, lower IQ, and delayed early motor development were specifically associated with PS in adolescence . Bolhuis et al. highlighted emotional and behavioral problems at age 3 and 6 as the earliest significant predictors of PS at age 10. These encompassed depressive symptoms, aggressive behavior, anxiety, sleep difficulties, attention problems, and somatic complaints. Interestingly, emotional and behavioral problems also partially explained the association between previously described risk factors such as autistic traits and childhood adversities and PS, rendering it likely that emotional problems are a core risk factor or precursor for later PS. Further, the authors hypothesize that PS can manifest differently across the lifespan, ranging from emotional problems in early childhood to sub-clinical PS in late childhood and adolescence, and severe mental illness in adulthood. However, difficulties in validly assessing PS in younger children could lead to a distortion of the true association between childhood emotional problems and PS . A twin study further supports an association between childhood emotional and behavioral problems and adolescent PS by showing a modest genetic overlap across these phenotypes . Further, lack of certain personal resources such as low optimism, low self-esteem, and high avoidance, in addition to emotional problems, have been reported as significant predictors of PS during adolescence . Early life stress and childhood adversities are associated with emotional and behavioral problems not only in childhood and adolescence but across the lifespan . In the largest population-based study to date, the World Health Organization Mental Health Survey , McGrath and colleagues confirmed that childhood adversities are associated with an at least two-fold increased risk for developing PS, in a dose-response relationship . Childhood adversities characterizing ‘maladaptive family functioning’ posed a somewhat stronger association with later onset of PS than ‘other childhood adversities’ .

Interestingly, when adjusting for other mental illnesses with onset prior to PS, the association between childhood adversities and PS onset during adolescence became non-significant. This finding suggests that childhood adversities are not only a risk factor for adolescent-onset PS, but also other psychopathological symptoms with onset prior to adolescence, which in turn may lead to PS. Finally, an often-discussed risk factor for the consecutive development of PS is cannabis use; longitudinal results from the Netherlands Mental Health and Incidence Study reported that baseline cannabis use predicted PS at follow-up . Recent publications conclude that the evidence for this association is sufficient for policy makers to take this risk into consideration when further discussing legalizing cannabis . Recently, genetic studies have made great progress in elucidating the genetic architecture of severe mental illnesses. In the majority of cases, risk for severe mental illnesses appears to be attributable to the cumulative impact of multiple genes, where each gene individually explains only a small amount of variance, but the sum of risk alleles across all identified variants accounts for up to 18% of variance in schizophrenia diagnosis . As such, investigation of poly genic risk scores , based on effect sizes of common variants associated with schizophrenia and other disorders has become increasingly common in population-based studies. Studies applying PRS to developmental cohorts have recently emerged. For example, in the ALSPaC cohort schizophrenia PRS was significantly associated with negative symptoms and anxiety during adolescence, but not with positive symptoms, again suggesting that the genetic basis of PS may present differently across development . In line with behavioral studies, Riglin et al. highlighted associations between schizophrenia PRS and diverse problems of childhood development at ages 7 to 9, such as lower IQ and poor social and language skills . A recent study combined three major population-based cohorts [ALSPaC, TEDS , and CATSS ], identifying significant associations between schizophrenia PRS and different symptom domains: hallucinations and paranoia , anhedonia, cognitive disorganization, and parent-rated negative symptoms . Interestingly, bipolar disorder PRS was also significantly associated with hallucinations and paranoia, even when including individuals who scored zero on this scale.

PRS for major depression was further associated with anhedonia and parent-reported negative symptoms. In a follow-up study taking a multivariate factor analytic approach, Jones et al. found schizophrenia PRS was significantly associated with multiple psychopathology factors . However, these specific effects vanished when including a general psychopathology factor, suggesting that psychopathology during adolescence may be explained with one broad factor. PS during adolescence are rather non-specific and pose risk for a variety of severe mental illnesses. Loohuis and colleagues therefore utilized a novel multi-trait approach including PRS of a broad range of psychiatric disorders, including neurodevelopmental disorders as well as brain and cognitive traits, to assess the association between these genetic risk factors and PS in youth. Interestingly, the ADHD PRS was the only significant predictor of PS in youth of European-American ancestry in the PNC , even after removing individuals endorsing any ADHD symptoms to avoid confounds related to phenotypic overlap . This finding was replicated in a sample of help-seeking CHR individuals. Further, the association between PS and ADHD PRS was age-dependent, such that the association was strongest in younger children . It is noteworthy that for individuals < 12 years only collateral information on psychopathology was available, which could affect the results. In addition to polygenic risk ,hydroponic trays recent exome sequencing studies have also found that rare and ultra-rare variants contribute to the genetic risk of schizophrenia . Overall, findings from these studies highlight the complex association between genetic risk and PS during adolescence. While such symptoms may be non-specific, and presage later severe mental illnesses, polygenic risk may be indexing global psychopathology as well as risk for specific diagnostic entities. Importantly, because PRS are currently derived from almost entirely European cohorts, their application to non-European ethnic groups is problematic ; collection of ethnically diverse samples is a research imperative. Further, while PRS are far from clinical utility in the general population, as ever-increasing GWAS size improves the strength of these associations, these risk scores may approach clinical utility in enriched populations in the near future. Examples of publicly available population-based datasets in youth that include multimodal imaging and neurocognitive assessments are the PNC and the Adolescent Brain Cognitive Development study. These samples offer unprecedented opportunities for the neuroscience community to study complex brain-behavior interactions during development. In particular, longitudinal data will allow for unique investigations of developmental trajectories. Given the young age of ABCD participants at study baseline it has the potential to capture earliest signs of emotional and behavioral problems associated with subsequent severe mental illnesses. Table 2 summarizes large scale epidemiological cohorts with multi-modal imaging. The PNC has led to a wealth of new findings regarding structural and functional brain alterations in youth experiencing PS; 1,445 youth aged 8 to 21 years were recruited from the greater Philadelphia area and underwent genotyping, multi-modal imaging, and neuropsychological testing. This sample was not ascertained for specific neuropsychiatric problems and includes multi-ethnic youth from various socio-economic backgrounds.

Exclusion criteria were limited, and included significant medical problems, intellectual disability, neurological and/or endocrine conditions, and general MRI contraindications .Importantly, all studies on PS in the PNC applied the same diagnostic criteria, offering comparability across studies . Furthermore, neuroimaging data were acquired with a single MRI scanner, reducing artifacts and heterogeneity due to scanner and study site variability. Reductions in local gray matter volume in youth experiencing PS relative to typically developing youth were observed in bilateral medial temporal lobes, and were also associated with PS severity . Further, a significant age by group interaction suggested that these local reductions in gray matter volume only became apparent in mid-adolescence in youth experiencing PS. This pattern of volume reductions in medial temporal regions mirrors a wealth of such findings not only in individuals with chronic schizophrenia, but also in individuals with first episode psychosis as well as in individuals at clinical high-risk for developing psychosis . Given that the medial temporal lobe in this study included both the amygdala as well as parahippocampal cortex, this finding was followed up with a more detailed parcellation of the temporal lobe: whereas decreased volume of the left amygdala was associated with positive PS, decreased volume of the left entorhinal cortex was correlated with impaired cognition as well as more severe negative and disorganized symptoms , suggesting that variation in these brain structures may contribute to distinct symptom domains. Jalbrzikowski et al. subsequently investigated whole-brain morphology differences in cortical thickness, surface area, and sub-cortical volume in PS youth in this cohort, relative to both youth with bipolar mood symptoms and typically developing youth . This study found thalamic volume reductions that were specific to PS. Again, these findings parallel those observed in individuals with overt psychosis and those at CHR , highlighting the role of the thalamus in neural system disruptions in psychosis. In terms of white matter micro-structure, youth with PS also exhibited reduced fractional anisotropy in the retrolenticular internal capsule and the superior longitudinal fasciculus , possibly reflecting altered axonal diameter and/or myelination . Development of the SLF was associated with cognitive maturation in typically developing youth, an effect that was absent in youth experiencing PS. Overall, alterations of brain morphology observed in these non-clinically ascertained cohorts of youth experiencing subthreshold PS can be interpreted as further evidence for a psychosis continuum, given qualitatively similar alterations observed in individuals with overt illness and those at CHR for psychosis.In terms of functional MRI, task-based brain function and resting state functional connectivity have both been investigated in population-based studies of PS. In the PNC, two MRI paradigms have been acquired: an n-back task probing different working memory loads and an emotion identification task. Working memory is viewed as a function of higher cognitive/ executive functioning consistently shown to be impaired in schizophrenia . Similarly, a wealth of evidence exists for impaired emotional processing in schizophrenia . Wolf et al. found reduced activation in the executive control network in response to increasing working memory demands, concomitant with worse performance, in PS youth relative to typically developing peers . Amygdala activation in response to threatening facial expressions was increased in PS youth compared to unaffected youth and was also positively correlated with positive symptom severity .

Animal studies suggest that prenatal alcohol exposure affects DNA methylation through antagonistic effects on methyl donors, such as folate, and via long-lasting changes in gene expression . Preliminary evidence from studies of children with fetal alcohol spectrum disorder show genome-wide differences in DNA methylation . Further research is required to examine epigenetic markers and their role in adverse outcomes among exposed youths; DNA methylation or other epigenetic markers could potentially provide objective indicators of prenatal alcohol exposure. Limitations of our study include potential maternal under reporting of alcohol use during pregnancy, imprecise retrospective data on the timing, amount, and frequency of alcohol exposure, and absence of data on trimester-specific alcohol exposure. The effects of under reporting by mothers who indicated alcohol use during pregnancy may have inflated the observed associations, while under reporting by mothers who indicated no alcohol use when they did in fact consume alcohol would have attenuated the associations toward the null. Furthermore, data were not available on mothers who regularly consumed less than a full unit of alcohol. Therefore, youths exposed to this pattern of drinking would have been included in the unexposed group, potentially diluting outcome effects. Despite the large sample size, there were relatively few cases of youths exposed to stable light drinking throughout pregnancy, and too few cases of stable heavier drinking or increased consumption throughout pregnancy, to examine the impact on offspring. There is a larger body of existing evidence based on the consequences of heavier alcohol exposure . The small sample size of youths exposed to light, stable drinking throughout pregnancy resulted in wider variance in outcome measures and may underestimate the true impact. Other notable explanatory variables of early life that may influence the observed associations between prenatal alcohol exposure and neurobehavioral outcomes include childhood adversity and quality of parental care. These variables may contribute to mediating effects of neurodevelopment and possible epigenetic modifications .

The baseline ABCD Study protocol did not capture these variables,vertical growing system although future waves will. Longitudinal analyses of this cohort should consider these variables as possible confounding factors. In addition, we did not examine the effect of preconception paternal alcohol exposure on preadolescent brain structure, and this should be explored in future studies. In conclusion, relatively light levels of prenatal alcohol exposure were associated with small yet significantly greater psychological and behavioral problems, including internalizing and externalizing psychopathology, attention deficits, and impulsiveness. These outcomes were linked to differences in cerebral and regional brain volume and regional surface area among exposed youths ages 9 to 10 years. Examination of dose-dependent relationships and light alcohol exposure patterns during pregnancy shows that children with even the lowest levels of exposure demonstrate poorer psychological and behavioral outcomes as they enter adolescence. Associations preceded offspring alcohol use and were robust to the inclusion of potential confounding factors and during stringent demographic matching procedures, increasing the plausibility of the findings. Women should continue to be advised to abstain from alcohol consumption from conception throughout pregnancy.The opioid crisis in the United States continues to worsen, with the number of opioid related deaths continuing to rise. Increases in deaths have come in multiple waves. The first was overdoses related primarily to prescription opioid pills; the second was driven by heroin-related overdoses; and the third has been driven by overdoses due to use of illicitly manufactured fentanyl and its analogs . Deaths related to synthetic opioids other than methadone, primarily fentanyl and its analogs, have recently increased from 9,580 in 2015 to 36,359 in 2019 , and provisional counts from 2020 suggest that the number has continued to increase . Given that the opioid crisis has continued to shift, it is important for research to continue to examine trends related to fentanyl use and overdose in order to most effectively inform prevention and harm reduction efforts. Centers for Disease Control and Prevention National Vital Statistics Systems mortality data have been the official source of information on opioid-related deaths in the US; however, results are typically lagged by about nine months . These data also tend to lack extensive information on characteristics or circumstances of overdoses, and information regarding nonfatal overdoses is not collected. In light of these limitations, alternate sources of national data could help further inform researchers and the public regarding characteristics of the ever-shifting opioid crisis which is currently driven by fentanyl use.

Even though reports of fatal fentanyl exposures are exponentially higher via NVSS mortality data as these reports are believed to count all or almost all related deaths in the US , we believe Poison Control data can help complement this information. Specifically, Poison Control data are uploaded in almost real time and therefore, depending on data availability, they can be used as an informative source for surveillance . National Poison Control also collects more extensive data on circumstances of exposures , and the majority of National Poison Control data are cases involving nonfatal overdoses – events that are currently lacking data at the national level. Therefore, National Poison Control data can elucidate risk factors for severity of fentanyl exposure outcomes, and determine how severity of outcomes and other circumstances of use shift over time. In this analysis, we examine trends in characteristics of fentanyl exposures in the US using National Poison Control data and we also delineate correlates of cases experiencing major adverse effects or death. We intend for these analyses not only to complement national mortality data but also to inform prevention and harm reduction efforts as the opioid crisis continues to shift.This study is based on a collaboration through the National Institute on Drug “Abuse” National Drug Early Warning System with the Researched “Abuse” Diversion and Addiction-Related Surveillance System. Poison Control data were obtained via the RADARS System Poison Center Program. Participating Poison Control Centers provided all cases involving pre-identified Micromedex codes to RADARS System staff who then reviewed select cases for accuracy. Poison Control provides treatment advice to the public and to healthcare staff treating people with suspected poisonings involving drugs, chemicals, and plants. Information about the patient and poisoning circumstances are recorded by individual PCCs as per standards set by the American Association of Poison Control Centers and stored in an electronic database overseen by the National Poison Data System. RADARS System obtained data on poisonings reported to involve fentanyl between January 2015 and December 2021.

Data were available from PCCs in all US states other than Utah prior to 2017 and North Carolina . With respect to patient characteristics, age and sex of the patient were obtained by PCC staff from the caller to the poison center, which may be the patient, health care provider, or other contact. With regard to characteristics of reported exposures, PCCs obtained information on the reason or intention for exposure, whether other drugs were co-used, the route of administration, the management site, and severity of the outcome from the caller. Reasons for use included substance “abuse,” substance “misuse,” suspected suicide attempt, therapeutic error, and various other categories of intentional and unintentional exposure. Unintentional exposure does not involve intentional use of another drug and typically refers to exposure among children. “Abuse” was defined by PCC as exposure resulting from intentional improper or incorrect use of a drug in which the patient was attempting to acquire a high,how to dry cannabis a euphoric effect, or some other psychotropic effect . “Misuse” was defined by PCC as intentional improper or incorrect, or otherwise non-medical use but for reasons other than acquiring a psychotropic effect. Information on reason was collected by specialists in poison information from PCC contacts and reviewed by RADARS System staff. SPIs are instructed to determine whether the results were due to a purposeful action or not . Based on coding guidelines provided by the AAPCC , they select the most appropriate reason for use within these categories. SPIs are instructed to record the rationale for this selection in case notes which are reviewed by RADARS System staff. In instances in which the patient is not conscious, this may impact the ability to obtain this information or create a bias due to reliance on other persons reporting. Routes of administration included ingestion, dermal administration, injection, inhalation, and other method. It cannot be determined, however, whether inhalation referred to insufflation or smoking. Patients were able to report multiple routes. Co-drug use was also queried, and we focused on reported co-use of alcohol, cannabis, cocaine, methamphetamine, gabapentin, benzodiazepines, and prescription opioids . Drug use was based on self-report and toxicology test results were considered when available. All information recorded by PCC staff was reviewed for accuracy by trained RADARS System staff. Management site was the site in which the call about the exposure to the PCC was made, and this was coded as taking place at a hospital center, on site , or patient referral. Finally, medical outcome was defined by PCC staff as none, mild, moderate, major, or death . Mild effects were defined as minimally bothersome effects, moderate effects were defined as more pronounced or prolonged effects, and major effects were defined as life-threatening or permanently disabling effects.

Deaths indicate that the patient was believed to have died in relation to use of the drug. Specifically, exposure related death was either directly determined by PCC staff involved with case management, or from death reports obtained from a medical examiner or other source . In the latter case, an AAPCC faculty review team then judged whether deaths were in fact likely responsible or at least contributory regarding the reported exposure . First, we examined trends in characteristics of fentanyl exposures. We described the prevalence of characteristics of fentanyl exposures within each separate year and then calculated absolute and relative changes in prevalence between 2015 and 2021. We also estimated whether there were changes in the proportion of each category of each covariate by time by examining whether there were linear, quadratic, or cubic trends using logistic regression. Next, we examined correlates of exposures resulting in a major effect or death. Covariates were fit into a multi-variable generalized linear model using Poisson and log link to estimate adjusted prevalence ratios for each covariate. We imputed missing data for independent variables in the multi-variable model. Multiple imputation was implemented via chained equations to handle missingness; predictors included all variables in the case complete model. We imputed 10 datasets for the multi-variable model and combined results using Rubin’s Rules . We also conducted sensitivity tests in which we repeated all analyses excluding cases reported from Connecticut. This was done because beginning in 2018, Connecticut became the only state to mandate emergency medical service providers suspecting fentanyl overdoses to report such cases to local poison control . All statistics were conducted using Stata SE 17 . This secondary analysis was exempt from review by New York University Langone Medical Center’s institutional review board. In this analysis of fatal and nonfatal fentanyl-related exposures reported to PCCs in the US, we detected significant shifts in characteristics of cases between 2015 and 2021. We also determined correlates of exposures resulting in major adverse effects or death. There were many shifts in proportion of various age groups exposed across time. Exposures among individuals in all age groups between age 13 and 39 increased in proportion over time, especially adolescents . We also determined that children, adolescents, and adults ages 50–69 were at higher risk for experiencing a major effect or death, suggesting these age groups are at particularly high risk for experiencing morbidity after exposure. The finding about increased exposures among children and adolescents is relatively unique. Although previous studies of mortality related to synthetic opioids suggest that there were increases among all age groups from 2011 through 2016, with a 93.9% increase among those age 15–24, increases were larger among those aged 35–44 and 25–34 . As such, our findings regarding children and adolescents being at increased risk for more severe outcomes may require more focus. Also, with respect to patient characteristics, the proportion of exposures increased among males. These results corroborate mortality data which suggests that since 2013, deaths related to use of synthetic opioids have increased at a faster rate then for females . In fact, in 2018, the rate of males who died from synthetic opioids was 14.2 per 100,000 compared to 5.5 per 100,000 females .

The application of digital technologies to better assess, understand and treat substance use disorders is a particularly promising and vibrant area of scientific research . Among the many applications of digital technologies, digital tools may be useful in the screening and assessment of SUD. Indeed, research evaluating the use of electronic screeners has demonstrated that individuals more accurately report risk behavior, including substance use and sexual risk behavior, when responding to questions posed by an electronic screener instead of by another individual . Embedding standardized, validated clinical assessments of SUD into electronic health records may also facilitate the assessment and treatment of SUDs as part of the routine clinical workflow in a wide variety of clinical settings . Digital health interventions are interactive, self-directed software tools that can overcome some of the striking disparities in treatment access and treatment quality evident in healthcare settings across the globe . For example, digital therapeutics can teach people effective, scientifically validated skills to recognize and change unhealthy thoughts and behavior and provide tools to help people apply these skills to their everyday lives. Digital therapeutics can be available 24/7 and thus allow for “on-demand” access to therapeutic support, thereby creating unprecedented models of intervention delivery and reducing barriers to accessing care. Telehealth, the use of telecommunication technologies to deliver long-distance clinical care, may also allow SUD expert clinicians to deliver care in communities where SUD treatment needs are high but SUD workforce capacity is limited . Telehealth can be used in concert with digital therapeutics to provide real-time distance communication with SUD clinicians via video technology, complemented by digital therapeutic software that does not rely on synchronous communication with another individual but rather can be available at all times. Digital therapeutics and telehealth models of care may be transformative in the treatment of SUDs in many ways .

As most persons with SUDs spend the majority of their time outside of a treatment facility,cannabis dryer digital technologies can extend the reach and impact of treatment by offering anytime/anywhere SUD care. Digital tools can function like a therapist “in your pocket” and can be accessible at times when individuals struggling with SUDs may be in greatest need of therapeutic support. Additionally, a large part of care offered in SUD treatment settings does not reflect the state of the science of SUD care . Digital therapeutics can ensure the delivery of SUD care with fidelity to the most evidence-based practices. Further, the behavioral health clinician workforce cannot meet the large population-level needs for SUDs or offer anytime/anywhere care . Digital therapeutics provide science based, scalable solutions to meet SUD needs at a population-level. This may be particularly relevant in tackling the current U.S. opioid crisis, in which the number of Americans with an opioid use disorder has surged, especially in rural communities, while the trained SUD workforce has not grown at a comparable rate , 2019. Digital technologies also afford new opportunities to examine clinical trajectories and identify novel digital biomarkers within-individuals through intensive collection of individual-level data using mobile devices, wearable sensors, and mapping digital footprints. Indeed, digital tools may capture information about individual’s physiology “in vivo” as they live their daily lives . Specifically, mobile technologies enable ecological momentary assessment a method that prompts individuals to respond to queries on mobile devices, and which enables near real-time monitoring, of individuals’ behavior while they engage in daily activities. Because EMA allows for intensive longitudinal assessment in naturalistic contexts, these data offer promise to enhance our understanding of mechanisms of health behavior, including drug-taking behavior . Digital technologies also enable passive sensing and inference from smartphones or sensing devices worn on the body, which is transforming how we understand human behavior . Mobile sensing allows for the continuous measurement of physiological and behavioral data in the real world.

This sensor data can be streamed to a smartphone and processed immediately to infer information about a person’s health behavior, physiology, and context. These data from sensors can be combined with data from self-report EMA assessments to enhance an understanding of the individual’s behavior in context . This information can then be used to trigger the delivery of interventions in real time . Further, the use of social media sites has exploded in recent years. Social media enables multi-directional communication anywhere and anytime. Social media may be leveraged to recruit individuals into research, often allowing for rapid, cost-effective recruitment of national and hard-to-reach populations . Social media data have also been used to predict many phenomena, ranging from purchasing patterns to disease epidemics , and a growing body of literature shows how social media data may enable a rich understanding of the topology and functioning of social networks and their relationships to health/risk behavior . For example, social media has been shown to contain signals of depression among individuals, such as decreased social activity, increased negative affect, highly clustered egocentric networks, and heightened concerns about relations and medications . Also, data derived from social media has been shown to predict a range of sensitive personal attributes including sexual orientation, political views, personality traits, and use of addictive substances . Digitally-derived data offer great potential to refine and advance our understanding of health behavior, including SUDs. These granular-level data captured in daily life allow for the development of dynamic models of SUDs to understand behavior in real-time and in response to changing environmental, social, physiological, and intrapersonal factors . And, they can help us understand when individuals may be most receptive to interventions , with a goal of providing the right type/amount of therapeutic support at the right time by adapting to an individual’s changing internal and contextual state . Collectively, these digital technologies enable an entirely new offering of tools for collecting rich data about individuals’ behavior, health, and environment, provide personalized interventions and resources based on individuals’ needs and preferences, and enable dynamic computational models to predict and characterize individuals’ changing needs and health trajectories over time.

The National Drug Abuse Treatment Clinical Trials Network , launched in 1999 by the U.S. National Institute on Drug Abuse , has supported a growing line of research that leverages digital technologies to glean new insights into SUDs and provide science based therapeutic tools to a diverse array of persons with SUDs. The CTN is a unique research infrastructure for conducting practical, rigorous, and highly impactful trials focused on improving the treatment of SUDs and promoting widespread implementation and sustainability of effective and accessible SUD care in community systems across the nation. Among its many contributions, the CTN has supported a broad array of innovative and impactful research projects that have leveraged digital health. This manuscript provides an overview of the digital health portfolio of the CTN and outlines a vision for the many future opportunities to leverage the unique national CTN research network to scale-up the science on digital health to examine optimal strategies to increase the reach of, and reduce barriers in access to science-based SUD service delivery models both within and outside of healthcare. Note that we recognize that additional, rigorous research supported by NIDA focused on the application of digital health to SUDs has been conducted outside of the CTN ; however, consistent with the focus of this journal Special Issue, this article focuses on the breadth of work within the CTN. Collectively, this research within the CTN is focused on addressing important scientific questions such as how to use digital health to routinize and standardize validated SUD screening in health care settings; how to use digital health to detect substance use in real time and in “the wild”; how to implement and scale up effective SUD treatment; and how to leverage social media for recruitment and intervention. The majority of digital health studies in the CTN have focused on the use of electronic health records for SUD screening and/or assessment. One of the earliest projects in this area was the development and validation of a brief screening and assessment instrument, the Tobacco, Alcohol, Prescription Medication, and Other Substance Use Tool,vertical farming systems for use in primary care patients . The TAPS tool is comprised of a 4-item screening survey, followed by a more detailed, substance-specific assessment of risk for any substances for which an individual has a positive initial screen . An early multi-site CTN trial with 2000 adult patients in 5 adult primary care clinics compared an interviewer-administered version of the TAPS tool to a version of the tool that was self administered on a tablet computer . Results demonstrated that the interviewer- and self-administered versions of the TAPS tool had comparable diagnostic characteristics, but the self-administered version yielded higher rates of reporting of past year alcohol, illicit drug and prescription medication misuse . The most notable discrepancy was for reports of prescription medication misuse, such that disclosure rates were 50% higher on the self-administered version. In addition, the tool showed promising sensitivity and specificity for detecting several types of substance use disorders, including tobacco and alcohol. It also identified adult primary care patients with high risk scores on the World Health Organization’s Alcohol, Smoking and Substance Involvement Screening Test as well as moderate risk scores for tobacco, alcohol and marijuana . Overall, the TAPs tool showed a more modest ability to identify some illicit and prescription medication SUDs in comparison to the ASSIST.

Despite this, the TAPS tool is much briefer than the ASSIST and provides primary care providers with information about current substance use, thus underscoring its strong appeal for use in primary care. Given that visits to primary care represent an important window of opportunity to systematically screen and identify SUDs among a broad population , the TAPS tool is an example of a validated, brief and practical resource that can be routinely delivered, including in a digital format, in general medical settings. The CTN’s work has extended beyond development and validation of the TAPS SUD screening tool to evaluate the feasibility of embedding SUD screeners into EHRs in primary care and integrating screening into the primary care workflow. One trial evaluated how implementation of drug screening in primary care impacts rates of SUD assessment and subsequent care and demonstrated that screening led to an increase in SUD diagnoses, particularly cannabis use disorder diagnoses . Another multi-site study being conducted in both urban primary care and rural Federally Qualified Health Centers has identified barriers and facilitators of embedding screening into these settings and underscored the importance of clearly communicating with patients about the goals of screening to counteract stigma, addressing staff concerns regarding time and workflow, and providing SUD education and treatment resources to primary care clinicians . Several ongoing CTN projects have further extended this work to evaluate the feasibility, usability, acceptability and impact of OUD clinical decision support tools embedded in EHRs to help guide primary care providers in evidence-based treatment of OUD. Of considerable promise, and influenced by the research conducted within the CTN, the U.S. Preventive Services Task Force has just released a draft recommendation to screen for drug use among adults in general medical settings , 2019.The CTN has had a marked impact in the field of digital therapeutics for SUDs — interactive software used to treat SUDs. The most impactful clinical trial with a digital therapeutic conducted within the CTN evaluated the clinical effectiveness of the web-based Therapeutic Education System  . TES is a web-based, self-directed version of the strongly evidence-based Community Reinforcement Approach to behavior therapy developed by Azrin . This intensive behavioral treatment is designed to teach individuals with SUDs how to better understand and disrupt harmful behaviors and cognitions related to their drug-taking behavior and to develop new skills to restructure their lives. In this pivotal CTN trial, the CRA-based behavioral treatment was offered along with incentives targeting drug abstinence and treatment participation. In this trial, conducted in partnership with 10 SUD treatment sites, individuals in outpatient SUD treatment were randomly assigned to receive either 12 weeks of standard outpatient SUD treatment or a treatment model in which TES partially replaced 2 hours of patient-clinician therapy time or psychoeducation . This study found that participants who received TES as part of their care model had a markedly lower rate of treatment dropout and a higher rate of drug abstinence , an effect that was most evident among patients who had a drug-positive urine and/or alcohol-positive breath screen at the time of entering the study .

One summary measure from each test was chosen a priori as the best estimate of the function of that test. We factor analyzed the test battery to reduce the number of variables. Supplementary text and Table S1 provide extensive detail on the battery. We examined missing data prior to implementing multiple imputation. From a sample of 1043, 953 received baseline neurocognitive testing . Of the CHR sample that transitioned to psychosis during the two-year follow-up , 89 received testing . Overall data completeness for the tested sample was 96.6% for 19 test variables. After MI, we conducted a FA of the 19 neurocognitive variables . All analyses were done with SPSS, version 23.Groups were HCs, CHR converters and non-converters . T-tests, Kolmogorov-Smirnov Z and Chi Square tests were used to assess demographic comparability. Due to differences in age and maternal education, we controlled for both using MANCOVA and also controlled for site as a random effects factor with a linear mixed model. We covaried for estimated and premorbid IQ to test the role of general intellectual ability in cognitive dysfunctions. We compared medicated vs. Non-medicated groups of CHR +C vs HC, and CHR+C vs CHR-NC by conducting MANOVA with planned comparisons using residualized factor scores generated from the linear mixed models. To examine group cognitive profiles we residualized out age and maternal education from all neurocognitive indices . Area under the curve was calculated by the ROC program in SPSS. Prediction of conversion to psychosis and time to conversion was assessed by logistic and Cox regression. Covariates were selected based on similar prediction analyses conducted in NAPLS-164 and NAPLS-245 and entered into the model if they were associated with survival time and predicted conversion status in logistic regression. Survival time was time to the last SIPS interview or conversion, ebb and flow rolling benches whichever occurred first. Candidate covariates were added to the model as a block then subjected to backward selection with a criterion p value of 0.10. Candidates that survived at p ≤ .05 within domain were entered into an omnibus model.

ESs were calculated with Cohen’s d. Bonferroni corrected significance for mean comparisons was set for individual tests at p<. 00263 and for factors at p< .0125 .In the largest and most detailed study of CHR prodromal cases, using a multi-site, case control design and standardized assessments, we demonstrated that individuals at CHR were impaired in virtually all neurocognitive dimensions compared to controls, and this could not be accounted for by premorbid or current general cognitive ability, current depression, medications, alcohol or cannabis abuse. ESs in comparison to HCs for Declarative Memory and Attention/WM were large for CHR+C participants. Compared to CHR-NC, CHR+C participants were significantly impaired in Attention/WM and Declarative Memory, the latter significantly predicting conversion to psychosis and time to event in concert with positive symptoms. Comparable impairments were observed in never-medicated and currently unmedicated CHR-NCs and CHR+C’s. These data demonstrate the sensitivity of neurocognitive function as a component risk marker for psychosis.Our findings support theoretical models hypothesizing Attention/WM impairments, and even more strongly, impaired Declarative Memory, as central to the CHR stage.The results are consistent with NAPLS-1, in which Declarative Memory had the largest ES decrement and roughly the same magnitude in CHR+C.The distinct profile of performance across domains, especially in CHR+C, suggests that at the incipient psychotic phase, specific forms of neurocognition are affected and are predictive of later psychosis. Within CHR participants, there was considerable variability in neurocognitive performance. CHR-NC’s impairments , were on the order of other psychiatric disorders in young people, such as attention-deficit/hyperactivity disorder. CHR+Cs impairments were approximately 57% larger, although smaller than those observed in first episode schizophrenia . Analyses of individual variability and longitudinal analyses are needed to identify how profile and severity differ according to comorbid disorders, final diagnoses and pre- and post-conversion. A key question was how neurocognitive deficits are associated with medication status. Psychotropic-naive and unmedicated subgroups had significant impairments comparable to the overall CHR subgroups. Treated groups, including with antipsychotic medications, were largely comparable to those without treatment, except they had somewhat greater Attention/WM impairment.

These observations emphasize the essential nature of neurocognitive impairment in the CHR stage and de-emphasize the role of medications as confounders in our results. Our design precludes conclusions about causality and future work should study the effect of medications on neurocognition in CHR populations in a prospective design. There were a number of other potentially important observations. The unexpectedly higher Verbal score that was retained in logistic and Cox regressions in concert with impaired Declarative Memory was not a significant predictor in univariate comparisons. This pattern of high verbal premorbid ability and impaired memory, coupled with P1/P2 composite appears to be a pernicious combination predicting conversion and needs replication. Importantly, the BVMT-R showed comparably large impairments as the two verbal memory tasks, highlighting that Declarative Memory deficits in CHR are not solely verbal, and that Declarative Memory impairments are key neurocognitive risk markers . Neurocognitive tests used in concert with other clinical and psychobiological measures may enhance prediction of psychosis or functional outcome. For example, in analyses limited to two tests selected from literature review14 prior to these neuropsychological analyses, NAPLS-2 investigators found that the HVLT-R and BACS Symbol Coding added modest but significant independent predictive power above the clinical measures in a risk calculator algorithm for psychosis conversion and this was replicated in an independent non-NAPLS sample. Similar results have been observed in other studies. In this study, we showed that other tests, including BVMT-R, PAM, and ACPT QA Vigil added significant independent variance beyond P1-P2 symptoms, augmenting the importance of neurocognitive markers. NAPLS-2, because of its large sample from diverse geographical areas, extensive neurocognitive coverage, remarkably complete neurocognitive dataset, and large never medicated sample, allowed for a strong confirmation of neurocognitive hypotheses. The NAPLS-2 study built upon and improved the NAPLS-1 assessment, confirming and expanding prior results . This broad range of measures expanded the scope of what is known about CHR neurocognition. Limitations include the fact that most of these tests and factors are complex. Thus, while Declarative Memory is clearly affected, the tasks tapping this domain cannot parse the specific mechanisms underlying the deficits.

Further research with more molecular measures of cognition, such as those developed by CENTRACS, may allow specification of the cognitive processes underlying the deficits. We did not randomize or counterbalance the order of tests, so we cannot rule out order effects. However, the most impaired tasks were spread out across the battery from the sixth to the last tests in the battery so there is no obvious fatigue effect. Adolescence is a developmental period between childhood and adulthood characterized by marked physiological, psychological, and behavioral changes. Adolescents experience rapid physical growth, sexual maturation,rolling grow benches and advances in cognitive and emotional processing . These changes coincide with increases in substance use, with alcohol being the most widely used illegal substance among adolescents . National survey data indicate that 33% of 8th grade students have tried alcohol, and this percentage increases to 70% among 12th graders . Of greater concern is the increase in heavy episodic drinking where prevalence rates increase from 6% to 22% for 8th and 12th grades, respectively , as heavy episodic drinking during adolescence is associated with numerous negative effects on adolescent health and well being, including risky sexual behaviors , hazardous driving , and alterations in adolescent brain development . During adolescence, the brain undergoes significant changes, and a recent longitudinal neuroimaging study suggests that heavy episodic drinking during this developmental period alters brain functioning . Squeglia and colleagues examined the effects of heavy episodic drinking on brain function during a visual working memory task, comparing brain activity in adolescents at baseline and again at follow-up to compare brain activity in those who transitioned into heavy drinking during adolescence to demographically matched adolescents who remained nondrinkers. Adolescents who initiated heavy drinking exhibited increasing brain activity in frontal and parietal brain regions during a visual working memory task compared to adolescents who remained nondrinkers through follow-up, who showed decreasing frontal activation, consistent with studies in typical development . Thus, adolescent heavy episodic drinking may alter brain functioning involved in working memory; however, additional longitudinal studies are needed to explore the effects of alcohol on neural correlates of other vital cognitive processes, such as response inhibition.

Response inhibition refers to the ability to withhold a prepotent response in order to select a more appropriate, goal-directed response . The neural circuitry underlying response inhibition develops during adolescence , and as such, brain response during inhibition changes during adolescence . Briefly, cross-sectional research indicates that brain activation during response inhibition transitions from diffuse prefrontal and parietal activation to localized prefrontal activation . Longitudinal studies report that atypical brain responses during response inhibition, despite comparable performance, is predictive of later alcohol use , substance use and dependence symptoms , and alcohol-related consequences . Together, these findings indicate that neural substrates associated with response inhibition change over time and abnormalities in development may contribute to later substance use. To this end, the current longitudinal fMRI study examined the effects of initiating heavy drinking during adolescence on brain activity during response inhibition. We examined blood oxygen level dependent response during a go/no-go response inhibition task prior to alcohol initiation , then again on the same scanner approximately 3 years later, after some adolescents had transitioned into heavy drinking. Based on our previous findings , we hypothesized that adolescents who transition into heavy drinking would show reduced BOLD response during response inhibition prior to initiating heavy drinking followed by increased activation after the onset of heavy episodic drinking, as compared to adolescents who remained non-users. By identifying potential neurobiological antecedents and consequences of heavy episodic drinking, this study will extend previous research on the effects of alcohol on brain function and point to risk factors for heavy episodic drinking during adolescence.Table 1 provides baseline and follow-up descriptive information for Heavy Drinkers and Controls. Of note, the ability to inhibit prepotent responses improved with age with no differences in this improvement between groups . The no-go versus go contrast at baseline revealed activations consistent with meta-analyses of response inhibition showing significant clusters of activation in inferior, superior, and medial frontal gyri, and in parietal, temporal, cerebellar, and subcortical areas . Because Heavy Drinkers reported significantly more substance use than Controls at followup, a lifetime substance use composite and biological sex were included as covariates. A repeated measures ANCOVA revealed significant group × time interactions in 5 regions: the bilateral middle frontal gyri, right inferior parietal lobule, left putamen, and left cerebellar tonsil . At baseline, Heavy Drinkers showed significantly less no-go BOLD contrast than Controls in all 5 clusters . Across adolescence, Heavy Drinkers exhibited increasing response inhibition BOLD contrast, and Controls showed attenuated response in clusters. At follow-up, Heavy Drinkers showed significantly greater response inhibition activity than Controls in 4 brain regions : bilateral middle frontal gyri, right inferior parietal lobule, and left cerebellar tonsil. Exploratory post-hoc analyses examined whether BOLD response contrast change over time correlated with subsequent alcohol involvement in Heavy Drinkers . BOLD response contrast during no-go relative to go trials over time in the right middle frontal gyrus positively correlated with follow-up lifetime number of drinks . Follow-up hierarchical linear regressions revealed BOLD response contrast at baseline did not predict follow-up alcohol consumption after controlling for baseline alcohol, biological sex, and follow-up age at our conservative, corrected threshold . The present longitudinal neuroimaging study examined the effects of initiating heavy drinking during adolescence on brain responses during response inhibition. We hypothesized, based on previous findings , that adolescents who transition into heavy drinking would show reduced BOLD response during response inhibition prior to initiating heavy drinking followed by increased activation after the onset of heavy episodic drinking, as compared to adolescents who remained non-drinkers. Examining a longitudinal neuroimaging sample of youth both preand post-alcohol use initiation allowed us to address the etiology of neural pattern differences. Although group × time effect sizes were small, our findings suggest that differential neural activity patterns predate alcohol initiation and also arise as a consequence of heavy drinking.