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Additional research using other national samples is needed to replicate our findings

However variation in study recruitment strategies between sites may also contribute to the observed differences as some venue based recruitment may have targeted drug users at risk for HIV-infection. Reported reasons for marijuana use were similar to previous studies, with stress reduction and appetite stimulation as the most commonly reported reasons for use.While many women report using marijuana for social and relaxation reasons, marijuana use for symptom relief was also noted as an important motivator among these HIV-infected women. Reasons for marijuana use in this study were also consistent with previously reported studies showing appetite stimulation, reduction of pain, relaxation/social use, anxiety reduction, and help with sleep.Research supports the utility of marijuana in reducing these symptoms with improvements in appetite, nausea, anxiety, depression, tingling, weight loss and tiredness reported from marijuana use in other observational studies of HIV-infected individuals. If cannabanoids are proven to reduce these ART-related side effects, medicinal marijuana use may become an increasingly important option for HIV-infected individuals, where laws allow its use. Indeed, recent randomized placebo controlled trials of HIV-infected individuals demonstrated significant reduction in neuropathy-associated pain and improved appetite from smoked cannabis, supporting its utility. As more HIV-infected individuals initiate ART treatment early and remain on treatment for long periods, reduction of ART-associated morbidity is increasingly important. Adherence to ART was lower among current marijuana users than non-users in this study,flood and drain table consistent with previous research.However, ART adherence was not reduced among the more consistent daily marijuana users. These results are similar to those observed by a previous study of 168 HIV-infected patients on ART in California who reported an increase in ART adherence among daily marijuana users despite decreased adherence among marijuana users overall.

It appears that for some women, regular marijuana use reduces HIV associated symptoms, and does not impair adherence to ART. Multiple patterns of use are present in the cohort, ranging from highly adherent regular marijuana users, to higher risk women whose marijuana use may be associated with use of other drugs and higher risk sexual behaviors. The association of recent sexual behavior and drug use with recent marijuana use observed in this study has been shown in many other studies,as risk behaviors are often correlated. The fact that sex and drug use behavior were not associated with daily marijuana use in this study underscores the different nature of daily marijuana use and is consistent with the interpretation that some of daily marijuana use is medicinal rather than recreational. There are several limitations and strengths to the current study. Validity of self-reported drug use has supported in multiple studies,although some studies suggest risk behaviors are under-reported compared to use of computer-assisted self interview.Whether marijuana use was medicinal or recreational was only specifically asked in 2009 and therefore the trend in medicinal marijuana use could not be evaluated. However, earlier surveys did ask about other questions related to reasons for marijuana use and as the frequency of marijuana use was collected longitudinally the trends in daily marijuana use could be explored. Marijuana abuse/dependence was not assessed. In addition, this was an observation study so marijuana users were self selected and this study did not assess the efficacy or safety of marijuana use. Further, we analyzed changes in marijuana use at cohort level , we can not rule out the possibility that immigrative or emmigrative selection bias might in part explain the changes in marijuana use observed in the cohort. Our study demonstrates that marijuana use is common among a representative group of U.S. women living with HIV, and that daily marijuana use did not decrease ART adherence. Further, marijuana use was reported by many users to alleviate HIV-related symptoms. Given this pattern, which appears to be part of a broad trend towards use of marijuana in chronic illness, additional research is needed on the optimal formulation, efficacy, effectiveness and safety of this patient led treatment.

Cannabis, which is often referred to as marijuana, is the most commonly used illicit drug in the United States, and its use has increased over the past decade. In 2010, for example, 11.5% of Americans aged 12 or older were past-year marijuana users. Less than a decade later, in 2018, 16% of the country’s population—nearly 44 million Americans— reported being past-year users , 2020a. Each day, there are approximately 8,400 new marijuana users. While marijuana’s therapeutic benefit has been demonstrated for selected indications , there is general consensus that it adversely effects the developing brain and should be avoided by pregnant women and children/adolescents . A variety of health, social, legal, and financial problems have been associated with high frequency marijuana use—for example, respiratory conditions , social problems , other illicit drug use . In the United States, the population of marijuana users is expected to grow given states’ marijuana policy environments, which are changing rapidly with an overall movement toward liberalization . To date, 36 states and the District of Columbia have legalized medical marijuana, and 15 states and DC have legalized it for adult recreational use. More states are considering such actions drawing on early adopters and lessons from alcohol and tobacco legislation in their approaches In addition to the positive impact these policies have on patients’ access to marijuana for treatment, the trend toward legalization is an effort to respond to the social justice concerns among disadvantaged, minority populations that have shouldered a disproportionate amount of the burden associated with marijuana prohibition . In establishing their policies, states have distinguished between medical and recreational marijuana ; however, it is not understood whether marijuana users make this same distinction. A few studies have compared the characteristics or patterns of marijuana consumption between medical and recreational users; however, limitations in their designs and samples have introduced confounding or limited generalizability . Other studies have relied on data from the early 2000s when far fewer states had legalized marijuana for medical or recreational purposes . Using data from 2017-2019, our study addresses these limitations and advances what is known about why adults use marijuana. Specifically, by comparing users by their reasons for use—medical, recreational, or both—and by identifying the correlates of each subgroup, we were able to develop past-month marijuana user profiles by reasons for use.

Additionally, given the effect states’ policy environments have on attitudes towards and use of marijuana —some research has demonstrated that residents in states that have legalized recreational marijuana more commonly attribute some benefit to marijuana and more commonly use all forms and multiple forms of marijuana —we control for state policy environment. In this way, our findings establish a baseline against which post legalization outcomes can be compared as states’ environments shift. Finally, our study makes use of 2017-2019 data from Behavioral Risk Factor Surveillance System , a national probability sample survey,rolling bench which enabled us to produce national estimates. To our knowledge, this is the first time these national data were used to compare marijuana users by their reasons for use. We used the most current data available from the BRFSS, which is the nation’s premier system of health-related telephone surveys that collect state data from U.S. residents, 18 years and older, about their health-related risk behaviors, chronic health conditions, and use of preventive services , 2020a, 2020b, 2019, 2018a, 2018b, 2018c, 2018d, 2017. Established in 1984, the BRFSS is currently collected in all 50 states, the District of Columbia, and two U.S. territories . More than 400,000 adult interviews are completed each year. In 2016, BRFSS added an optional marijuana module, which included questions about past month marijuana use and routes of administration . In 2017, the question about routes of administration was changed from asking about all routes of administration to the primary route of administration, and a question about respondents’ reasons for marijuana use was added—“When you used marijuana or hashish during the past 30 days, was it for medical reasons to treat or decrease symptoms of a health condition, or was it for non-medical reasons to get pleasure or satisfaction —with five response options: only medical reasons to treat or decrease symptoms of a health condition; non-medical purposes to get pleasure or satisfaction; both medical and non-medical reasons; don’t know/not sure; refused. Since its introduction, the number of states including the optional marijuana module has grown. See Supplemental Table S1 in the online version of this article. For our analysis, we combined the last three years of BRFSS data for the 20 states that asked about respondents’ reasons for using marijuana any of the three years. During the study period, the median, annual response rate among all participating states and territories was 45.9% in 2017, 49.8% in 2018, and 49.4% in 2019 , 2020a, 2018a.The dependent variable of greatest interest was marijuana users’ reasons for use, which was drawn directly from the BRFSS question and had three response categories: medical versus recreational versus both reasons .

Additionally, because several prior studies had categorized marijuana users’ reasons for use differently—for example, comparing those who reported only recreational reasons for use to a category, which combined those who reported only medical with those who reported both reasons for use, referred to as “any medical reason” —we also created two alternative, binary specifications representing these constructs—specifically, medical reasons only versus any recreational and recreational reasons only versus any medical . To capture states’ policy environments, we created separate, binary variables reflecting the status of medical and recreational marijuana legalization from 2017-2019 in each state. See Supplemental Table S1 in the online version of this article. For all but three states, marijuana laws were stable throughout the study period. In Oklahoma, Utah, and West Virginia, medical marijuana laws were enacted and implemented in August 2018, December 2018, and June 2019, respectively. In these cases, the values of the policy variable was adjusted to reflect the month and year of legalization. After examining trends in legalization, we also created an alternative categorical specification, which combined the legal and recreational statuses by each state-year .We estimated overall and state-level percentages of the U.S. adult population who reported past-month marijuana use by reasons for use. We used bivariate analyses to examine the demographic characteristics, health status, and risk behaviors of the sample and the population from which the sample was drawn by reasons for marijuana use . Using multi-variable regression analyses, we tested the relationship between an array of predictors and each reason for marijuana use. Because the outcome of primary interest was categorical—i.e., respondents reported using marijuana for medical reasons only, recreational reasons only, or both reasons—we used multinomial logistic regression and estimated adjusted relative risk ratios. Based on underlying theory and previous research, we incorporated a multitude of covariates for statistical control. Ultimately, the final model included: gender, age, race, ethnicity, marital status, education, employment status, income, number of past-month days of poor mental and physical health, frequency of use , route of administration, tobacco use, binge drinking, and the categorical marijuana policy variable. All models were also adjusted for state and year fixed effects. Because the interpretation of multinomial logistic regression parameter estimates is not straightforward , we made two adjustments. First, we estimated the average marginal effects for each explanatory variable—that is, how an incremental change in each risk factor affects the predicted probability of reporting past-month marijuana use by each reason for use. To explore the relationship between states’ legal environments and marijuana users’ reasons for use, we created user profiles— i.e., hypothetical observations with illustrative values —and varied the legal environment. In each case, we estimated the average predicted probability of reporting each reason for use and compared those probabilities in states that were fully legal versus fully illegal. Additionally, we used the binary version of the dependent variable —i.e., recreational only versus any medical— and used logistic regression to re-estimate the relationships between each covariate and reporting only recreational reasons for marijuana use. To provide nationally representative and generalizable results, all estimates were adjusted for sampling weights and BRFSS’ complex survey design; confidence intervals were based on standard errors computed using the linearized variance estimator. We followed the CDC’s guidelines for combining multiple years of BRFSS data and data reliability/ suppression , 2020b, 2019, 2018b; Klein et al., 2002. Stata/SE version 15.1 was used for all analyses .

Adverse events by symptom category did not significantly differ between medication groups

To assess the effect of medication on alcohol-induced changes in mood and craving, three-level models were run for each positive mood, negative mood, craving, and urge scores, as predicted by medication condition, time and a medication × time interaction. Two sets of exploratory analyses were conducted. First, to explore how medication effects might impact drinking outcomes, we tested whether ibudilast moderated the effect of stimulation/ sedation on same-day drinking during the trial, given support for these variables as strong predictors of alcohol use . As such, a within-subject cross-level interaction of medication × stimulation or sedation was added with random slopes, and same-day number of drinks served as the outcome. In a similar fashion, we also tested whether ibudilast moderated the effect on stimulation/ sedation on next-day drinking using cross-lagged logistic models; this analysis served to test whether subjective response predicted future drinking behaviors. Second, given the trial’s a priori interest in a withdrawal-related dysphoria characteristic, we tested whether dysphoria would moderate ibudilast’s effects on alcohol-induced changes in mood and craving. A three-way interaction was added to models estimating the outcomes- positive mood, negative mood, urge, and craving . Stimulation and sedation variables were limited to a single time point and were thus excluded from analyses testing before to during drinking changes.The final sample of randomized participants who completed at least one DDA, consisted of 50 non-treatment seeking individuals with current AUD . Overall, 66% of the sample reported their sex as male, 68% reported an annual household income < $60,000, and the average age was 32.7 years . Regarding race, participants most frequently identified as White ,cannabis grow racks followed by 14% Black or African American, and 12% mixed race. In addition, 24% of the sample identified as Hispanic/ Latinx. Participants had an average of 5.6 DPDD in the month prior to their baseline visit. Medication adherence was high, as both medication groups exceeded 97% adherence rates.

In this secondary analysis, we tested bio-behavioral mechanisms of ibudilast, a neuroimmune modulator, through naturalistic daily reporting of subjective response to alcohol collected during a two-week RCT enrolling 50 non-treatment seeking participants with AUD. Electronic DDAs were administered each morning to participants to capture their previous day drinking behaviors and subjective alcohol response measures. First, we were interested in understanding whether ibudilast altered average levels of stimulation and sedation during drinking episodes. Results showed that ibudilast treatment did not significantly change average levels of stimulation nor sedation during the trial compared with placebo. These findings are consistent with an initial safety trial in which ibudilast did not significantly affect any subjective response variables during an experimentally controlled alcohol infusion in the laboratory . Relatedly, a trial combining laboratory and EMA methods showed that topiramate reduced drinking-related craving but not the stimulant or sedative effects of alcohol . However, animal literature shows that apremilast, another PDE inhibitor, did alter a wide range of ethanol-induced effects in mice, such as reducing acute functional tolerance and increasing the sedative, intoxicating effects, and aversive properties of ethanol . Perhaps unlike certain pharmacotherapies for AUD such as naltrexone, neuroimmune modulators, like ibudilast may not reduce drinking by robustly suppressing alcohol’s stimulant properties or amplifying its sedative effects. Rather, ibudilast may more directly alter other central mechanisms like alcohol craving or may exert a wider range of effects on multiple mechanisms that cumulatively impact drinking outcomes. Second, we tested a related exploratory aim examining the moderating effect of ibudilast on alcohol-related stimulation and sedation and same-day number of drinks consumed. Participants on ibudilast reported a significant, positive relationship between their stimulation and sedation ratings and same-day drinking levels, neither of which was observed in the placebo condition. This suggests that participants randomized to ibudilast consumed more alcohol on days when they retrospectively reported feeling more stimulated during a drinking episode than on days when they felt less stimulated . Yet for those on placebo, we did not detect a significant relationship between one’s feelings of stimulation or sedation and alcohol use. These findings are consistent with EMA data showing that naltrexone potentiated participant’s subjective “high” across rising levels of estimated BrAC . Similarly, topiramate was shown to strengthen the association between mean positive affect and frequency of cannabis use .

These results are also in line with a secondary analysis of our lab’s initial efficacy trial, whereby ibudilast potentiated the association between mood states and one’s craving for alcohol following a stress exposure paradigm compared with placebo . Mechanistically, PDE4 inhibitors attenuate alcohol-induced neuroimmune activation and dysregulation of GABAergic signaling . These important processes are connected to behavioral responses to ethanol . Thus, micro-longitudinal reports collected during the current trial helped to elucidate dynamic, day-to-day associations between within-person subjective effects and drinking, such that ibudilast seemed to moderate these relationships for a given individual, rather than by altering average subjective response levels across participants. For our second primary aim, we assessed whether ibudilast, compared with placebo, attenuated daily alcohol-induced changes in positive mood, negative mood, urge, and craving . Among the full sample, we found that ibudilast significantly dampened within-person alcohol-induced increases in craving seen under the placebo condition, but not other subjective response indicators. This suggests that one of the mechanisms by which ibudilast exerts its effects on drinking outcomes, such as reductions in heavy drinking ), may be by diminishing one’s desire to continue drinking during an episode. Considering its immunomodulatory actions, ibudilast may reduce the acute and chronic proinflammatory effects of alcohol, either indirectly through suppression of peripheral inflammation or directly by altering cAMP signaling pathways and suppressing cytokine expression and in the brain . In return, acute alcohol-induced increases in craving are blunted. Supporting these findings is research on methamphetamine use disorder . An RCT for inpatients with MUD showed that ibudilast significantly blunted the rewarding effects of methamphetamine during an infusion in the laboratory and similarly diminished drug-induced increases in proinflammatory levels during infusion . Continuing, previous results from our group implicate ibudilast in the reduction of tonic craving and neural alcohol-cue reactivity, as evidenced by attenuation of cue-elicited activation in the ventral striatum compared with placebo .

It is thus plausible that reductions in alcohol craving and reward, across these contexts, represent a primary mechanism of action of ibudilast for AUD. Craving likely represents a more proximal determinant of alcohol use than stimulation and sedation, which are shown to indirectly influence alcohol self-administration through craving . An additional exploratory aim was to test whether a characteristic of AUD severity, withdrawal-related dysphoria, moderated ibudilast’s effects on daily alcohol-induced changes in mood and craving. Notably, we found that individuals without a reported history of withdrawal-related dysphoria who were treated with ibudilast showed attenuation of alcohol-induced changes in craving, urge, and positive mood when compared to placebo. This tempering of alcohol’s effects may reflect ibudilast’s enhancement of anti-inflammatory and neurotrophic factors suspected to impact dopaminergic signaling in rewards regions,cannabis grow system such as the nucleus accumbens, where PDE4 and PDE10 are highly expressed . However, individuals who endorsed this withdrawal-dysphoric profile did not appear to benefit from treatment via this mechanism, such that ibudilast did not significantly blunt acute rewarding and reinforcing effects of alcohol. Although intriguing, these moderation findings should be interpreted with caution given the limited sample size, particularly the subgroup of individuals reporting experiences with withdrawal-related dysphoria . Despite these findings, preliminary analyses from this two-week RCT show that withdrawal dysphoria did not moderate clinical response to ibudilast regarding rates of heavy drinking or drinks per drinking day. Notably, these subjective response results are somewhat in contrast to what might be expected for individuals with a history of withdrawal and experiencing the “dark side of addiction”, such that these individuals may potentially show greater dysfunction of the immune system and thus may be predicted to have better response to an anti-inflammatory treatment, such as ibudilast. However, it is suspected that other mechanisms may be central to the maintenance of AUD among individuals with withdrawal dysphoria, beyond the enhancing effects of alcohol. Namely, these individuals may primarily drink to feel ‘normal’ and alleviate physiological or psychological distress, particularly during early abstinence , which was not the focus on the current study. The present findings also differ somewhat from our laboratory’s initial efficacy trial of ibudilast, in which individuals with higher levels of depression showed attenuation of alcohol-induced increases in positive mood and ‘wanting’ during intravenous alcohol administration . A relevant difference between these studies is that participants enrolled in the efficacy trial were likely in a state of early abstinence, as they were asked to refrain from drinking for safety reasons; yet those enrolled in the present trial were not asked to change their drinking behaviors and consumed alcohol on roughly 60% of trial days and around 6 DPDD on average. In preclinical models, withdrawal increases the expression of innate immune markers in brain regions regulating autonomic and emotional states and while speculative, may thus represent a unique condition with the potential to impact ibudilast’s therapeutic effects. For instance, ibudilast reduced opioid withdrawal symptoms among individuals with heroin dependence and another PDE4 inhibitor, rolipram, diminished withdrawal-induced behaviors indicative of negative affect in rodents . Future research evaluating the impact of withdrawal states on immune signaling in larger clinical samples is needed to advance understanding of these complex processes and immune intervention. These findings should be considered in the context of the study’s strengths and limitations. One limitation is that DDAs were reported retrospectively once daily, which is less temporally accurate than EMA designs. As such, items on subjective response and drinking were reported by participants concurrently the morning following a drinking episode and did not capture one’s subjective response level at a specific BrAC or blood alcohol curve limb. As such, this weakens our ability to draw a causal link between the effect of subjective response on alcohol intake and may introduce recall bias. Next, participants with more non-drinking days and incomplete DDAs during the trial are suspected to have greater error variance in their data given the lower number of observations with subjective response data. The lack of daily pre-drinking data on stimulation and sedation prevented us from examining daily changes in these variables, such that we could not account for pre-drinking levels. The sample was comprised of non-treatment seeking individuals with moderate AUD on average and the majority did not fall in the withdrawal-related dysphoria category. Future work with ibudilast in more diverse and treatment-seeking samples with more significant experiences of withdrawal-related dysphoria is needed. This study’s strengths include a clinical AUD sample enrolled in a rigorous double-blind RCT testing a promising novel pharmacotherapy. This trial displayed strong medication adherence rates and tolerability. Further, DDAs had high completion rates and the data comprise a substantial number of drinking episodes . Morning reports are also less likely to be affected by the intoxicating effects of alcohol that may lend to reporting errors, as could be seen with EMA or nightly reports. Finally, to our knowledge, this is the first study on the effect of immune modulation on subjective alcohol response in the natural environment. In closing, this daily diary study complements findings from our previous reports of ibudilast treatment for AUD by examining medication effects on subjective response during real-world drinking episodes. The nuanced nature of the findings, including the distinction among those with and without withdrawal-related dysphoria and within vs. between person subjective response effects, speak to the heterogeneity of AUD and dynamic mechanisms maintaining alcohol use. Ibudilast’s effects on subjective alcohol responses, such as positive mood and craving, appear to be nuanced and perhaps most salient for individuals drinking for positive reinforcement as opposed to normalizing. Treatment with ibudilast potentiated the within-person relations between stimulation/ sedation and alcohol intake in this trial, such that an individual’s quantity of consumption on a given day appears to be more tightly connected to subjective response. The ecologically valid nature of these DDA, through retrospective reports of past day drinking and subjective responses to alcohol, provide a clinically useful window into how individuals experience and recall alcohol’s effects while taking ibudilast, compared to placebo.

Half of these CBIs have not been included in previous reviews

These CBIs typically mentioned use of a specific theoretical construct without reference to a broader theory, or intervention technique. In addition, sometimes a specific construct or intervention technique can be associated with more than one theory. For example, several of these CBIs mentioned that the goal of the intervention was to improve “self-efficacy”, a specific construct that is most often associated with Social Cognitive Theory, but is also incorporated within other theories such as the Theory of Reasoned Action. We applied the same classification system to these CBIs with regard to mention, application and measure for the construct and/or techniques. For each CBI listed in Tables 1 and 2, the use of the theory or construct/technique are classified as mentioned, applied, or measured .As noted above, a CBI was classified as “applied” if any one of the associated articles provided some description of how the theory/construct was used in the CBI. Of the 21 CBIs that mentioned use of a broad theory, all provided at least some information about how the theory was applied to the intervention . However, the quality of the description explaining how the theory was applied varied considerably across the CBIs. Tables 1 provides a brief summary of how the articles, associated with each CBI, applied theory. There were a number of articles that provided a strong description of how the theory was applied to the intervention . Another intervention, the Life Skills Training CD-ROM, was derived from an evidence-based comprehensive in-person curriculum with a strong basis in Social Learning/Cognitive Theory. The Life Skills Training CD-ROM, like the original face-to face curriculum, contains a number of modules that articulate the specific linkages between theory and intervention approaches. Other articles described how one or two aspects of the theory were applied to the CBI, but not the overall theoretical pathway that would inform behavior change In contrast, the majority of articles lacked sufficient information to understand how theory informed the development of the intervention. For the CBIs listed that did not mention use of a broad theory , but mentioned using a specific construct or technique,vertical grow system all provided a description of how it was applied in the intervention ; however the amount and quality of information provided about the application of the construct/techniques varied considerable across this group of CBIs.Of the 21 CBIs that mentioned use/application of theory , all but two included at least one measure of a construct associated with the theory.

If a CBI mentioned use of a theory, it was more likely to include a measure of specific constructs associated with the theory compared to CBIs that did not mention use of a broad theory. Specifically, of the CBIs, that did not explicitly mention use of a theory, but did include a specific construct, only five included corresponding measures of the theoretical construct . Tables 1 and 2 lists the classification of each CBI and provides a list of the measure associated with the theory, construct or intervention technique.The measures listed in Table 3 and 4 are primary outcome measures and, in many cases, are different from those listed in Tables 1 and 2 which lists the measures of theoretical constructs which were often secondary rather than primary outcomes. For the outcomes listed in Tables 3 and 4, an asterisk denotes statistical significance indicating that the intervention showed more favorable results than the comparator Of the 42 CBIs, all but one demonstrated improvements in alcohol knowledge and/or attitudes. In addition to these knowledge or attitude outcomes, the majority of the CBIs showed significant reductions in alcohol related behaviors. The proportion of CBIs reporting significant behavioral outcomes was greater among those that used a broad theoretical framework compared to those that targeted a specific theoretical construct and/or intervention technique .This study identified 100 unique articles covering 42 unique computer-based interventions aimed at preventing or reducing alcohol use among adolescents and young adults.Thus, this review includes a total of 21 new CBIs and 43 new articles. This review is the first to provide an in-depth examination of how CBI’s integrate theories of behavior change to address alcohol use among adolescents and young adults. While theories of behavior change are a critical component of effective interventions that have been developed and evaluated over the past several decades, attention to the application of theory in CBIs has been limited. We utilized a simple classification system to examine if theories were mentioned, applied or measured in any of the publications that corresponded with the CBIs. Only half of the CBIs reviewed mentioned use of an overarching, established theory of behavior change. The other half mentioned used of a single construct and/or intervention technique but did not state use of a broader theory. CBIs that were based on a broad theoretical framework were more likely to include measures of constructs associated with the theory than those that used a discrete construct or intervention technique.

However, greater attention to what theory was used, articulating how theory informed the intervention and including measures of the theoretical constructs is critical to assess and understand the causal pathways between intervention components/mechanisms and behavioral outcomes . When mentioning the use of a theory or construct, almost all provided at least some description of how it informed the CBI; however, the amount and quality of information about how the theory was applied to the intervention varied considerably. Greater attention to what is inside the “black box” is critical in order to improve our understanding of not only what works, but why it works. While a few articles provided detailed information about the application of theory, the majority included limited information to examine the pathway between intervention approach and outcomes. There are a number of reasons why there may be limited information on the use of theory in CBIs. Some researchers/intervention developers may not fully appreciate how theory can be used to inform intervention approaches. There is an emphasis on outcomes/effectiveness of interventions and less attention is placed on their development. In addition, to our knowledge, there are no publication guidelines/standards for describing the use of theoretical frameworks in intervention studies and the inclusion of this information is often up to individual authors and reviewers. Given the importance of theory in guiding interventions, greater emphasis on the selection and application of theory is needed in publications. The classification system used in this review provided some form of personalized normative feedback and applied it relatively consistently across the CBIs. Personalized normative feedback is designed to correct misperceptions about the frequency and acceptability of alcohol use among peers. It typically involves an assessment of a youth’s perceptions of peer norms around alcohol attitudes and use followed by tailored information about actual norms. In addition, some interventions have recently incorporated personal feedback to address individual’s motivations to change through assessing and providing feedback on drinking motives or in decisional balance exercises. The widespread use of personalized normative feedback in CBIs may be because it has been widely documented as an effective strategy and because it lends itself readily to an interactive, personalized computer-based intervention. Motivational interviewing was also used in several of the CBIs and is an effective face-to-face counseling technique. In contrast, this technique was applied to CBIs in a number of different ways, such as exercises designed to clarify goals and values, making both the description of how it was applied even more essential to examine differential effectiveness across various CBIs. This study builds on the growing evidence supporting the use of CBIs as a promising intervention approach. We found most of the CBIs improved knowledge, attitudes and reduced alcohol use among adolescents and young adults. In addition, this study suggests CBIs that use overarching theories more frequently reported significant behavioral outcomes than those that use just one specific construct or intervention technique . This finding is consistent with prior studies examining the use of theory in face to-face interventions targeting alcohol use in adolescents.

However, it is important to acknowledge the wide variation across the CBIs not only in their use of theory, but in scope, the targeted populations,mobile grow systems duration/dosage, and measured outcomes. It is encouraging that even brief/targeted CBIs demonstrated some effectiveness and thus can play an important role in improving knowledge and attitudes, which are important contributors to changes in behavior. There are limitations to this study. As discussed previously, many articles did not explicitly describe how theory was applied in the CBI. It is therefore possible that the theoretical pathways for the intervention were further developed than we have noted, and possibly included in other documents, such as logic models and/or funding applications; however, such information is not readily accessible and was outside the scope of this review. Thus, lack of mention of the name of a theory or construct or its application does not mean that the intervention did not integrate the theory in the intervention, only that the article did not provide information about its application. Thus, due to variations in the described use of theory along with the wide range of CBIs, it was not possible to draw comparisons about the relative effectiveness of CBIs according to the theory used. The ability to make such comparisons is further limited by the wide time frame in which CBIs were developed. This review spanned articles published between 1995 and 2014. During this period, CBIs to address health issues have been rapidly evolving due to major advancements in technological innovations . These advancements coupled with greater interest and investments from federal agencies and philanthropic foundations. Over time one would expect these factors to further contribute to the effectiveness of CBIs.Marijuana use is common among persons living with HIV as studies have reported prevalence rates of current marijuana use between 24 and 56 % as compared to approximately 7 % in the general United States population. Men who have sex with men report higher rates of current and past-year marijuana use than their heterosexual counterparts. Several studies report that persons living with HIV use marijuana to alleviate stress, anxiety, depression, HIV-related symptoms and side effects of antiretroviral therapy. In one recent study, among HIV-seropositive persons who inject drugs and who recently seroconverted, heavy cannabis use was associated with lower plasma viral load levels. The therapeutic effects of marijuana are proposed to be mediated via the actions of active cannabinoid chemicals in marijuana—cannabidiol—at specific receptor sites: cannabinoid receptors located mainly on cells and tissues of the immune system. In contrast the primary psychoactive cannabinoid in marijuana: tetrahydrocannabidiol binds to and activates another receptor site: cannabinoid receptor located mainly in areas of the brain to produce the euphoric and cognitive impairing effects of marijuana. Accordingly, there are concerns that marijuana use may be associated with poorer HIV treatment outcomes. Previous studies have found marijuana use to be associated with decreased cognitive function as well as reduced ART adherence, which is crucial for persons living with HIV as optimal adherence to ART medications is required for long-term viral suppression. Effective prevention strategies to reduce unhealthy or harmful marijuana use require an in depth understanding of subgroups with different patterns of use. Despite the published evidence that marijuana use is common among HIV+ individuals and MSM and the potential adverse health outcomes associated with its use in these populations, very little is known about the patterns of marijuana use or how patterns of marijuana use may change over time in these populations. Developmental research suggests different rather than similar pathways via which individuals initiate and progress to unhealthy or problem substance use over the life course. For instance, individuals who start using substances at an early age have increased risk of progressing to problem use and developing use disorders. Among HIV+ women, depressive symptoms and the presence of hepatitis C infection was associated with a pattern of persistent heavy drinking over time. Another study found that low income and concurrent substance use were factors that predicted consistent hazardous drinking among HIV + MSM. Therefore, understanding the natural history of marijuana use and the identification of different trajectories of use over time is important in order for intervention programs to be most effective. For instance, the identification of different patterns of marijuana use over time can help characterize subgroups of individuals with the greatest risk of progressing to heavy patterns of marijuana use and reveal unique predictors of such patterns of use which can be used to inform targeted intervention programs.

Understanding and addressing these exposures offers an opportunity for primary prevention

Interventions focused on diabetes, hypertension, and drug or alcohol dependence/abuse across the county may be effective for preterm birth reduction. We identified several modifiable risk and resilience factors across the reproductive life course that can be addressed to reduce preterm birth rates. Given the complex clinical and social determinants that influence preterm birth, cross-sector collaborative efforts that take into account place-based contextual factors may be helpful and are actively being pursued in Fresno County. Ultimately, refining our understanding of risk and resilience and how these factors vary across a geography are fundamental steps in pursuing a precision public health approach to achieve health equity. Individuals with psychotic disorders were for many decades not considered appropriate candidates for psychotherapy. The first case reports detailing the use of cognitive behavioral techniques to treat psychosis were published in the 1980s , while the first randomized controlled trial of cognitive‐behavioral therapy for psychosis originated in the United Kingdom in the 1990s . Presently, CBT is listed as a preferred treatment for psychosis by the Schizophrenia Patient Outcome Research Team in the United States, a set of strictly evidenced‐based treatment guidelines . A combination of anti-psychotics and structured therapy has been shown to improve both positive and negative symptoms and result in global functional improvement . The CBT focus on cognitive restructuring, normalizing, behavioral self‐monitoring, and activity scheduling promotes social engagement . In one community‐based study, CBT improved positive symptoms, general mental health problems, and depression, as well as reduced admission rates following treatment . The PORT guidelines also recommend social skills training , which targets social cognitive processes, psycho‐education,life management skills , and relapse prevention skills . Cognitive Behavioral Social Skills Training combines both social skills training and cognitive‐ behavioral therapy to improve real‐world functioning . In one RCT,wholesale indoor plant grow rack 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, 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.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 anti-psychotic 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, 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 schizo affective 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,grow table 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 under explored. 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. CBSST appears to be an effective intervention to address these concerns that requires minimal resources and a relatively brief treatment interval, making it ideally suited to adaptation to a variety of clinical settings. Future studies will compare CBSST to standard outpatient care with a focus on additional outcomes, including quality of life and healthcare utilization.The acute respiratory distress syndrome affects at least 10% of patients in the intensive care unit and carries a high mortality rate of approximately 40%.1 There have been effective advances in supportive care, but there are as yet no consistently proven effective pharmacologic treatments for ARDS.2 One approach to addressing this problem is to target the heterogeneity of ARDS by understanding patient factors that impact response to treatment once ARDS has already developed. For example, secondary analyses of randomized clinical trials demonstrate that ARDS sub-phenotypes respond differentially to simvastatin therapy.Another important facet is early intervention in hospitalized patients at risk of ARDS.However, clinicians and researchers should also focus on identifying preventable patient exposures that increase the risk for ARDS, as demonstrated by a growing body of research. This review summarizes the current literature on environmental exposures and ARDS development and outcomes, discusses underlying mechanisms, and outlines the implications for patient management and policy-guided solutions.According to the World Health Organization, the pollutants with the greatest effect on human health are ozone, sulfur dioxide , nitrogen dioxide , and particulate matter .

Marginalization on the basis of sexual orientation increases the risk for problematic substance use

For example, GBM men were approximately one and half times more likely to have reported being diagnosed with a substance use disorder during their lifetime than heterosexual men , and one and a half times more likely to have been dependent onalcohol or other substances in the past year . GBM also have higher rates of mental health issues than their heterosexual counterparts . In a review of 10 studies, Meyer found that gay men were twice as likely to have experienced a mental disorder during their lives as heterosexual men. More specifically, gay men were approximately two and a half times more likely to have reported a mood disorder or an anxiety disorder than heterosexual men. A review by King and colleagues found that lesbian, gay, and bisexual individuals were more than twice as likely as heterosexuals to attempt suicide over their lifetime and one and a half times more likely to experience depression and anxiety disorders in the past year, as well as over their lifetime.Few Canadian studies have explored population-based estimates for mental health outcomes among GBM. In one cross-sectional study of Canadian gay/“homosexual” and bisexual men using 2003 Canadian Community Health Survey data, Brennan and colleagues found participants were nearly three times as likely to report a mood or anxiety disorder than heterosexual men. Pakula & Shoveller conducted a more recent cross-sectional analysis that used 2007–2008 Canadian Community Health Survey data and found again that GBM were 3.5 times more likely to report a mood disorder compared with heterosexual males. These analyses used government-run population-based study data, which may limit self-disclosure of sexual minority status,marijuana growing racks and further relied on a single identity variable to measure sexual orientation, which ignores same-sex sexual behaviors. There is an inextricable yet varied relationship between an individual’s mental health and substance use. Substance use may lead to poorer mental health or, inversely, poor mental health may lead to increased substance use .

A variety of substances have been shown to be associated with negative mental health events or symptoms. For example, Clatts, Goldsamt, and Li found that a third of young MSM who used club drugs on a regular basis reported having attempted suicide, and almost half of those who had attempted suicide, did so multiple times over their lifetime. They also found that more than half of regular club drugs users had high levels of depressive symptoms. McKirnan and colleagues found that GBM who showed signs of depression were nearly twice as likely to smoke. Stall and colleagues identified a “dose-response” relationship between self-rated mental well being and alcohol related problems: GBM who self-rated their mental well-being as low were approximately three times more likely to have alcohol related problems and those who rated it as moderate were nearly twice as likely to have alcohol related problems. Respondents who scored as depressed were also one and half times more likely to report using multiple drugs and nearly twice as likely to report weekly drug use. Syndemics [clusters of mutually reinforcing epidemics that interact with one another to make overall burden of disease within a population worse ] has been used in research with GBM to explain how various psychosocial variables such as poly drug use, mental health conditions, and intimate partner violence increase the likelihood of acquiring HIV . However, nearly all of these studies have relied on convenience samples through online and venue-based recruitment; thus, they may not be representative of the larger underlying population of GBM. In order to address issues of representativeness and limitations of non-probability sampling in past research with GBM, we used respondent-driven sampling to estimate population parameters that are more representative than convenience samples . RDS is a type of chain-referral research technique in which participants are asked to recruit individuals from within their social networks in successive waves, and estimates population parameters using measures of network size and recruitment homophily. By utilizing RDS we sought to produce a more representative sample of the GBM population in Metro Vancouver in order to determine the prevalence of mental health issues and substance use as well as the association between these factors.We analyzed cross-sectional data from participants enrolled in the Momentum Health Study, a longitudinal bio-behavioral prospective cohort study of HIV-positive and HIV-negative GBM in Metro Vancouver, Canada.

The overall aim of this study was to examine the impact of a biomedical intervention—increased access to highly active antiretroviral therapy for HIV— on HIV risk behaviors among GBM. The present analysis utilized data collected from participants’ first study visit that occurred between February 2012 and February 2014. We used RDS to recruit GBM in the Greater Vancouver area . Initial seeds were selected in person through partnerships with community agencies or online through advertisements on GBM socio-sexual networking mobile apps or websites . These seeds were then provided with up to six vouchers to recruit other GBM they knew. All participants were screened for eligibility and provided written informed consent at the in-person study office in downtown Vancouver. A computer-assisted, self-administrated questionnaire was used to collect socio-demographic, psychosocial, and behavioral variables. Subsequently, a nurse-administered structured interview collected information on history of mental health and substance dependence diagnosis and treatment, and participants provided blood samples to test for HIV and other sexually transmitted infections . Participants received a $50 honorarium for completing the study protocol and an additional $10 for each eligible GBM they recruited into the study. All project investigators’ institutional Research Ethics Boards granted ethical approval. Moore and colleagues have published additional detail on the Momentum Health Study protocol.We sought to determine the prevalence of doctor diagnosed mental health conditions and self-reported substance use among GBM, as well as the association between these two domains, using cross-sectional data from the Momentum Health Study of GBM living in the Metro Vancouver, British Columbia, Canada. Substance use and mental health conditions were highly prevalent among GBM. As expected, there were strong associations found between a substance use disorder diagnosis and various substances in our study, which corroborate previous research regarding smoking and alcohol-related problems among GBM. Further, cigarette smoking and erectile dysfunction drugs were the only substances associated with any other mental health disorder diagnosis at the univariable level, and did not remain in the multi-variable model. Our findings suggest that GBM have higher rates of mental health disorders than the overall population. According to the 2012 Canadian Community Health Survey , a third of Canadians reported a mental health or substance use disorder diagnosed in their lifetime , while more than half of the participants in our sample reported any lifetime doctor-diagnosed mental health disorder.

Examining depression, anxiety, and drug abuse/dependence more specifically, our study reported population prevalence estimates approximately three times larger than the overall population: 8.7% of Canadians versus 25.9% of GBM report being diagnosed with anxiety in their lifetime, 11.3% of Canadians versus 42.4% of GBM report being diagnosed with depression in their lifetime, and 4.0% of Canadians versus 14.8% of GBM reported lifetime drug abuse or dependence. This discrepancy is greater than what was reported by Meyer and King et al. ,mobile grow rack which found the prevalence of mental health conditions in GBM to be approximately two times greater than in heterosexual men across multiple studies. However, neither Meyer nor King et al. included Canadian data in their analyses, nor did previous studies utilize RDS, making our findings more representative, at least for urban GBM in Metro Vancouver, Canada. Our use of respondent-driven sampling to generate population parameter estimates indicated that we had over-sampled White GBM and under-sampled low-income GBM, GBM with less formal education and bisexual-identified men. Our findings also indicate that GBM have higher rates of substance use than the overall population. According to the Canadian Tobacco Use Monitoring Survey , 18.4% of Canadian men are current smokers,which includes those who do not smoke daily , while in our study, 47.1% of GBM smoked cigarettes in the past 6 months. These percentages fall at the upper end of the 25–50% range in the review conducted by Ryan and colleagues , which looked at the prevalence of smoking across multiple studies of GBM and found that GBM were much more likely to smoke than their heterosexual counterparts. Our study found that recent cannabis use among GBM was higher than lifetime use in the Canadian population: 63.6% recently used in our study versus 41.5% lifetime use in the Canadian Alcohol and Drug Use Monitoring Survey . Other substances, such as cocaine and ecstasy, also had recent prevalence estimates at much greater magnitudes in our study at 29.5% and 18.9%, respectively, versus the 1.1% and 0.6% lifetime estimates found in CADUMS. These findings are consistent with the review by Hughes and Eliason , whom found that GBM are more likely to use substances than heterosexual men.AUDIT and AUDIT Consumption have been used previously in research with GBM to assess alcohol use. A larger proportion of GBM were categorized to be hazardous drinkers or possibly dependent on alcohol in our study versus other studies: 9% among older LGB adults and 15.4% among HIV-positive men who have sex with men . D’Augelli, Grossman, Hershberger, and O’Connell studied older lesbian, gay, and bisexual people and found a mean AUDIT score of 3.06, which is nearly half the median value of 6.0 in our study. For studies using the AUDIT-C that focused only on consumption patterns, hazardous drinking categorization was more prevalent: 71.4% among gay and bisexual youth aged 13–24 , 65.4% among gay men and 58.8% among bisexual men aged 18–25 , and 58% of adult GBM . These disparities in prevalence may be due to the age group or HIV-status specificity of the samples in other studies, differences in measurement approaches, benefits of using RDS to access hard-to-reach GBM subgroups, or may reflect a local phenomenon among GBM in Metro Vancouver. Few studies have used the Hospital Anxiety and Depression Scale to measure anxiety and depression in GBM, allowing our study to provide some of the first estimates using this scale in a nonclinical population and with RDS-weighted population parameters. However, this also makes it difficult to compare the results of our study with others.

Gray and Hedge found that only 40% of gay men were in the normal range for the HADSAnxiety measure and 77% of gay men were in the normal range for the HADS-Depression measure, which are similar to the percentages found in our study where 42.9% of GBM scored within normal range for the HADS-Anxiety measure and 80.9% scored in the normal range for the HADS-Depression measure. Many studies assessing anxiety and depression in GBM have used the Composite International Diagnostic Interview ; a nonclinical, structured interview often used in epidemiological surveys and is based on the diagnostic criteria outlined in the Diagnostic and Statistical Manual of Mental Disorders as well as the International Classification of Diseases . Cochran et al. found that 69% of GBM were not depressed and 97.1% were not anxious according to the CIDI, which differs from the 80.9% and 42.9% in our study for HADS-Depression and HADS-Anxiety respectively. The percentage of participants who scored within the normal range for the HADS-Depression measure in our study is similar to the percentage by Wang et al. , which was 80.8% versus 80.9% in our study, while the anxiety measure differed greatly which was 78.1% in their study versus the 42.9% in our study. While the HADS is easier to use because it is a self-administered questionnaire, the CIDI has been shown to demonstrate high validity as a diagnostic instrument , which could be useful in future studies of GBM mental health. A number of salient social factors were identified as important determinants of mental health. Our study found that GBM with lower annual incomes were more likely to have been diagnosed with a substance use disorder. Income is considered to be one of the most important social determinants of health because it effects whether one may access nutritious food, housing, transportation, and other basic health prerequisites . This upstream determinant impacts one’s general and physical well being, which in turn may explain this greater burden of mental health disorders. Lastly, we found that participants who were currently students were less likely to have a substance use disorder than participants who were not. This may be due to students generally being younger in age, and as such are biased towards a shorter lifetime reporting period within which to have been diagnosed with any mental health conditions.

Cultivating Green Gold: The Art and Science of Cannabis Growth

Future work must also continue focusing on improving functioning and symptom reduction via more comprehensive and multi-modal wrap-around services, and including empirically supported treatments for schizophrenia such as psychosocial therapy and mindfulness interventions. Given observed progressive declines in global cognitive function in patient with schizophrenia over time, increased participation in cognitive remediation training programs and/or cognitive control programs may be additionally useful. Lastly, researchers and clinicians alike should aim to reduce the gap between their respective fields in order to facilitate widespread utility of CHR classification and intervention. This likely begins with addressing classification discrepancies and refining clinical/research tools as needed; specifically, whether it is more efficacious to define psychosis from a dichotomous or continuous perspective. The adoption of low-cost screening methods may also prove fruitful here. In conclusion, many important findings in CHR research have emerged over the past year, particularly in the domain of clinical functioning. This field continues to progress in its attempts to clarify both clinical and biological markers of psychosis risk, and has begun to offer important insight into interventions for reducing the likelihood of psychosis emergence. Although more work is necessary to elucidate and expand the current literature, we have started gaining traction on utilizing research findings to reach a point of meaningful intervention and prevention of psychosis. Cigarette smoking causes and exacerbates chronic obstructive pulmonary disease and asthma,and is associated with wheezing and cough in populations without a respiratory diagnosis.Quitting cigarettes improves respiratory symptoms and limits lung function deterioration.While the relationship between cigarette smoking and respiratory symptoms is well-established, the relationship between use of other tobacco products besides cigarettes and respiratory symptoms in adults is less clear. Changes in the tobacco market, in part,mobile vertical growing racks reflect efforts to market products that may cause less harm than cigarettes. Electronic nicotine delivery devices may represent such a product. With respect to respiratory symptoms, findings have been mixed, however.

Numerous animal and in vitro studies raise theoretical concerns about e-cigarette use and lung disease.Short term human experimental studies have linked adult e-cigarette use with wheezing and acute alterations in lung function,and lower forced expiratory flow.One longer term 12-week prospective study of cigarette smokers switching to e-cigarettes found no effects on lung function,and two 1-year randomized controlled clinical trials found reduced cough and improved lung function in persons who used e-cigarettes to reduce or quit cigarettes.Cross-sectional observational studies using Waves 2 and 3 data from the Population Assessment of Tobacco and Health Study have found an association between e-cigarette use and respiratory symptoms. One longitudinal W3-W4 PATH Study analysis found no relation between exclusive e-cigarette use and incident respiratory symptoms but suggested that dual users of cigarettes and e-cigarettes had significantly higher risk for symptom onset compared to exclusive cigarette users.Finally, one prospective study of young adults found an association between cannabis vaping and respiratory symptoms.There are many design issues that make these studies hard to compare. The clinical importance of the respiratory outcome is not clear in most cases because the multiple wheezing questions are analyzed in isolation from each other, or an endorsement of only one item is considered symptomatic. Many of the studies included adults with COPD, which is a diagnosis strongly linked to a history of cigarette smoking, and many people with COPD have chronic severe wheezing and dyspnea. Another concern is residual confounding: Most of the studies showing an association between e-cigarette use and respiratory symptoms failed to adjust for cigarette smoking history and concurrent marijuana use, both associated with respiratory problems and concurrent e-cigarette use. Finally, few studies addressed alternative tobacco product categories besides e-cigarettes. To better understand these divergent findings on how tobacco product use relates to respiratory health, we analyzed W2 and W3 data from the PATH Study.We developed a dependent variable that incorporated all available questions on wheezing and nighttime cough and determined cut-off values associated with functional outcomes. We focused on both cross sectional and longitudinal associations between functionally-important respiratory symptoms and ten mutually exclusive tobacco product use categories, adjusting for past cigarette smoking history and concurrent marijuana use. We also examined results for two different cut-off values for a respiratory symptom index to test for sensitivity to symptom severity. Covariates were derived from W1 and W2, and included variables associated with both tobacco exposure and functionally-important respiratory symptoms.

Low socioeconomic status is associated with tobacco use and poorer lung function.Sociodemographic variables included age, sex, race/ethnicity, education, income, and urbanicity. Medical conditions that could result from tobacco use and also cause respiratory symptoms included asthma, congestive heart failure, heart attack, diabetes, cancer, being overweight, and use of anti-hypertensives known to cause coughing or wheezing . Smoke-related exposures included pack-years of cigarette smoking, second-hand smoke exposure, and marijuana use. Calculating pack years of smoking We were particularly concerned with adjusting results carefully for each individual’s cigarette smoking history, an important predictor of respiratory outcomes. We derived lifetime pack years to account for cigarette smoking history in this analysis. Lifetime pack years is a clinical metric calculated by multiplying the number of packs of cigarettes per day someone smokes by the number of years they have smoked cigarettes. The following text annotates the algorithm to calculate Wave 1 lifetime pack years. Data from Wave 1 lifetime pack years was used in conjunction with variables describing subsequent cigarette use to determine lifetime pack years at W2 and beyond. Never smokers were assigned a pack years value of zero. All questions used in the algorithm and response categories are listed in Supplemental Table 3. Because of routing instructions in the PATH Study interview, only those respondents who said that they have smoked cigarettes “fairly regularly” were asked about how long they have smoked or did smoke . For any respondent at Wave 1 who currently smokes regularly or formerly smoked fairly regularly, lifetime pack years was calculated by multiplying the number of cigarette packs smoked per day by the number of years they have smoked fairly regularly. Two different formulas were used for this calculation, depending onanswers to the questions for variable R01_AC9004 and R01_AC9009 . At W2, the prevalence of functionally-important respiratory symptoms was 7.2% . Table 1 shows that respiratory symptoms were more common in the four categories of tobacco use that included cigarettes , compared to never tobacco use, and among those who used marijuana. Functionally-important respiratory symptoms were much more common among those with asthma, and also more common among those with comorbid conditions, obesity, and those using medications known to cause coughing or wheezing . Figure 1 illustrates the unadjusted linear relationship between frequency of cigarette use and proportion of persons with functionally-important respiratory symptoms for the four use categories featuring cigarettes.

The shape of the dose-response lowess lines were almost identical and the 95th percentile for cigarette use intensity was essentially the same for all four groups, regardless of what other tobacco products were added to cigarettes, emphasizing the importance of cigarettes in these four most prevalent categories of tobacco use. In the full, adjusted, multi-variable cross-sectional model , all four tobacco use categories that featured cigarette smoking were associated with a doubling of the risk of functionally-important respiratory symptoms vs. never tobacco users ,mobile vertical system grow and risk for the multiple use categories were not significantly different from exclusive cigarette use . As illustrated in Figure 2, we observed a significant positive dose-response relationship for current use of cigarettes . Compared to never users, the risk of functionally-important respiratory symptoms were not significantly different for exclusive users of e-cigarette, cigar, hookah and smokeless tobacco; moreover post hoc testing indicated that risk ratios for each of these categories were significantly lower compared to exclusive cigarette use . None of these cross-sectional results changed when the analysis was repeated at a respiratory index cut-off level of ≥2. Testing sensitivity to key confounders of the e-cigarette—respiratory symptom association Cigarette smoking pack-years, second-hand smoke exposure, and marijuana use were also associated with functionally-important respiratory symptoms . Table 2 highlights the importance of cigarette smoking pack-years and past-month marijuana use as confounders of the association between tobacco product use and respiratory symptoms. Cigarette pack-years was a particularly strong confounder; adding this variable alone to the cross-sectional multi-variable model attenuated association estimates for cigarettes and cigarettes+e-cigarettes by 30% and for exclusive e-cigarettes by 25%. That was partly because all three groups had a similarly long cigarette smoking history—weighted mean 13.4 cigarette pack-years for exclusive cigarette smokers, 12.9 for the dual users, and 10.8 for exclusive e-cigarette users. Similarly, 19.2% of exclusive e-cigarette users also currently used marijuana; adding P30D marijuana use to the multi-variable model attenuated association for e-cigarettes by 9%. Adding all three confounders together attenuated the e-cigarette-respiratory symptom association RR from 1.53 to 1.05. The categorical analysis did not address whether functionally-important respiratory symptoms increased with increasing frequency of use. Figure 2 explored this for cigarettes and e-cigarettes, adjusting for cigarette smoking history. For cigarettes, there was a significant linear increase in the percent with functionally-important respiratory symptoms with higher intensity of use; prevalence of respiratory symptoms was less than 5% for never users and over 30% for those smoking a pack a day or more. There was also an increase in respiratory symptoms with higher intensity of e-cigarette use, but the trend did not reach statistical significance .There were no statistically significant associations between exclusive use of cigars, smokeless tobacco or hookah and worsening of respiratory symptoms compared to never users.

Post hoc testing indicated that risk ratios were significantly smaller than for exclusive use of cigarettes, regardless of cutoff level for the respiratory symptom outcome . In contrast, findings for exclusive e-cigarette use were sensitive to symptom severity, showing a significant association with worsening symptoms at a threshold of ≥2 , but not at a symptom threshold of ≥3 . This study underscores the adverse consequences of continued cigarette smoking among people without COPD or other non-asthma respiratory disease on functionally-important respiratory symptoms. Consistent with other studies,a longer history of cigarette smoking predicted worsening respiratory symptoms and decreased chances of improvement, independent of P30D cigarette smoking, underlining the importance of cigarette smoke exposure in the development or worsening of respiratory symptoms. The consequences of cigarette use were the same regardless of which additional tobacco products were used. As shown previously, dual users of cigarettes and e-cigarettes smoked cigarettes as frequently as exclusive cigarette smokers,their respiratory response to cigarette smoking intensity was essentially the same as exclusive cigarette users, and they had indistinguishable risk for symptom worsening.We found no evidence to support the idea that dual use of cigarettes and e-cigarettes carries higher risk for respiratory symptom worsening compared to exclusive cigarettes for the symptom outcomes we examined. This contrasts with increased risk of dual use in the analyses of PATH Study data reported by Reddy et al,an analysis that involved a different period , and adjusted only for demographics; we doubt the finding reported by Reddy would have remained statistically significant after adjustment for the multiple confounders included in the present analysis. In contrast, respiratory symptom risk for exclusive users of other tobacco products was significantly lower than for cigarettes, and was largely not significantly different from never or former tobacco users. The finding for e-cigarettes contradicts two cross-sectional studies of tobacco use and respiratory symptoms, one using PATH Study W2 data18 and one using W3 data,both concluding that there was an association between e-cigarette use and wheezing. These studies examined the association with each item on the respiratory index and neither adjusted for cigarette smoking history or marijuana use.34 Based on the present study findings— lack of a crude dose-response for e-cigarette frequency illustrated in Figure 2 and the confounding analysis in Table 2—we conclude that the reported associations in these papers were likely spurious, primarily because of the failure to adjust for cigarette smoking history. Our supplemental materials include a method for determining cigarette pack-years from PATH Study data to support the inclusion of this important confounder by other users of these data. The longitudinal results seem contradictory if the reference of focus is never users—ecigarette users are significantly more likely to have symptoms worsen at one cut-off level and significantly more likely to have symptoms improve at another—an example of how results for ecigarette users may be sensitive to how health outcomes are determined. But another viewpoint is that potentially reduced harm tobacco products are judged also by how health risks of the product compare to the health risks for cigarette smokers.

A response button that could register a mouse click was underneath each of the two boxes

The task consisted of 20 discrete choices between a smaller immediate reward presented in a box on the left side of the screen and an 80¢ delay reward presented in a box on the right side of the screen . At the top center of the screen was a box displaying total earnings on the task. On any trial, if the smaller sooner reward was selected with a single mouse click, the response options disappeared and a button appeared that stated “Click here to bank your amount.” Upon a single mouse click on this button, that amount was dispensed from the coin dispenser, and the total earnings box was updated. If the delayed 80¢ was selected, the response options disappeared and a number in the middle of screen counted down the number of seconds to wait . When the delay elapsed, a button appeared that required the participant to click to “bank” the 80 cents, at which point the coins were delivered and the total earnings were updated. When money was delivered, participants removed the coins from the dispensing tray and dropped them into a glass jar. There were 5 blocks of 4 trials each, with each block associated with a different delay for the 80 cent reward. The delays were 5, 10, 20, 40, and 80 s, and followed an increasing order across blocks. On the first trial of each block, the immediate reward size was 40¢ . The smaller reward was then adjusted within the block using a “decreasing adjustment” algorithm, which has been used in previous human studies involving hypothetical rewards . Specifically, the smaller sooner reward was adjusted by 20, 10, and 5¢ on Trials 2, 3, and 4 of the block, respectively, in the direction that would move choice toward indifference . The indifference point was defined as the value that would have been presented on a 5th trial had the algorithm continued . Indifference points therefore varied by increments of 2.5¢,vertical grow rack and were divided by 80¢ to be expressed as the proportion of the larger reinforcer. Indifference points were expressed as a proportion of the larger later reward .

A waiting period was imposed after the final trial to prevent participants from choosing the smaller immediate reward to end the task or session sooner . Participants were told before beginning the task that the total duration of the task would be independent of the choices made during the task, although participants were not explicitly told about the waiting period at the end of the task that was responsible for ensuring approximately equal task duration. The waiting period was defined as 660 s minus the sum of all larger reward delays that the participant experienced throughout the task. Although this manipulation ensured that total programmed waiting time did not substantially differ across participants, differences in participant response latency nonetheless allowed for some variability in total task time. At the end of the task, participants exchanged whole dollar amounts of coins for paper currency.The schizophrenia and control groups had qualitatively similar DD functions, but quantitatively, the schizophrenia group showed a significantly greater DD than controls on the experiential task, and normal DD on the hypothetical task. The schizophrenia group’s performance on the DD tasks was generally not associated with a range of potential confounds. In addition, test-retest reliability was examined for the schizophrenia group and was good on both tasks. These findings provide the first evidence of impaired DD in schizophrenia using an experiential paradigm that parallels tasks used in animal research much more closely than conventional human paradigms. While not all aspects of reward processing are impaired in schizophrenia , these findings suggest alterations do extend to a delay discounting context that involves real rewards and real delay periods. As described below, the schizophrenia group’s pattern of altered experiential and normal hypothetical DD likely reflects the fact the these tasks differed on several key dimensions, including reward type , reward magnitude , and delay time frame . Regarding qualitative analyses, the shape and orderliness of the DD data were generally similar across groups. In line with a prior report , the schizophrenia group showed typical hyperbolic discounting functions across tasks. Further, a large majority demonstrated orderly data for both DD tasks. The proportion with less-orderly data on the hypothetical, though not the experiential, task was significantly larger than controls.

However, the main study findings were unchanged after removing the subset of participants from both groups with less-orderly data. In this first study of experiential DD in schizophrenia, the schizophrenia group showed quantitatively greater discounting than controls for actual monetary rewards delivered in real time. Diminished discounting on this and similar experiential tasks has been reported in other clinical populations, including cocaine dependence, ADHD, and smokers . Experiential tasks appear to tap into a rather different aspect of DD than hypothetical tasks. For example, the correlation between hypothetical and experiential DD tasks was relatively small in both groups. Several studies have also reported relatively low convergence between these tasks and one found altered experiential but not hypothetical discounting in ADHD . There were no quantitative group differences for the hypothetical DD task and this study included the largest schizophrenia and control samples examined to date. Our finding on this task is consistent with two prior studies , but inconsistent with four others that found greater hypothetical DD in schizophrenia . The rather substantial methodological differences across the few DD studies make it difficult to pinpoint why three studies found normal DD but four did not. Since all prior studies included chronically ill samples, and all except one examined outpatients, the discrepancies across studies are not attributable to these participant characteristics. However, the tasks and data analytic approaches varied widely. For example, across the seven studies, the maximum delayed reward magnitude ranged from $86 to $1000, and the maximum delayed reward duration ranged from a few months up to 50 years. Further research will want to systematically assess the impact of these parameters on hypothetical DD in schizophrenia. For example, it could be informative to examine how individuals with schizophrenia perform on a hypothetical task with reward magnitudes and delay intervals that correspond to those in the experiential task. The current study considered a wide range of potentially confounding factors on DD and found that their impact was small. The only relevant factor was smoking status.

Smokers showed greater hypothetical DD than non-smokers, which converges with prior findings from the general population and schizophrenia . However, we still found the pattern of altered experiential and normal hypothetical DD in schizophrenia when we limited our analyses to non-smokers. There were no significant associations between DD and other substances, symptoms, or anti-psychotic medication dosages. Given the conceptual link between reward processing and negative symptoms , it is somewhat puzzling that alterations in DD, particularly on the experiential task, did not significantly correlate with higher clinically rated negative symptoms. Although some studies have found that neuroscience-based reward and decision making tasks are associated with negative symptoms a number of studies by our group and others failed to detect such relationships . The reason for these discrepancies is not year clear. We have suggested that there are complex intervening steps on the causal pathway between the relatively discrete processes measured by decision-making tasks and the broad aspects of experience and behavior that are captured by clinical rating scales,cannabis grow racks which may substantially diminish direct correlations . DD also showed no significant associations with global or particular domains of neurocognition. This does not support prior suggestions that DD disturbances in schizophrenia reflect problems in the representation and maintenance of reward value . The schizophrenia group’s pattern of altered experiential but normal hypothetical DD was also not attributable to differences in the test-retest reliabilities of the tasks. The test-retest correlations of approximately .70 for both tasks are similar to prior reports in healthy samples and the group means showed good stability across occasions. These findings, in conjunction with the lack of associations with symptoms, suggest the DD tasks are measuring relatively stable traits among individuals with schizophrenia. These properties support the use of the experiential DD task as a performance measure of decision-making impairment in clinical trials for schizophrenia . Its potential usefulness for clinical trials is bolstered by evidence that it is sensitive to state-related changes, such as sleep deprivation, dopamine agonist administration in Parkinson’s disease, alcohol administration, and methylphenidate administration in ADHD . One might have expected the schizophrenia group to show greater difficulties for hypothetical, distant rewards in light impaired abstract thinking and longer-term prospection associated with this disorder . However, the pattern found in the current study may relate to participant and task characteristics. Regarding participant characteristics, since schizophrenia is associated with decreased SES and many in the schizophrenia group were receiving limited fixed incomes, the schizophrenia group may have valued immediately available, real rewards more than controls. This possibility is bolstered by our finding that the schizophrenia group assigned higher value ratings than controls for the lowest value but similar ratings for the highest value on the subjective valuation of money index, and with previous research showing greater discounting in lower income adults . Although individual differences in subjective valuation ratings did not significantly correlate with performance on the DD tasks, this factor remains a possible contributor . Regarding task characteristics, Paglieri postulated key differences between hypothetical tasks and experiential tasks, beyond reward magnitude and delay length.

Whereas hypothetical tasks merely involve postponing receipt of a reward with no constraints on how subjects spend their time during the intervening delay, the waiting period in experiential tasks comes with associated costs. These include direct costs, such as boredom or discomfort, and opportunity costs, such as valuable activities that the participant could be engaged in if not forced to wait. The relevance of such costs was demonstrated in a recent study that found DD rates increased as an orderly function of the constraints on what people could do during the delay interval on a hypothetical task . Perhaps the individuals with schizophrenia in our study were hyper-responsive to the associated costs of doing nothing in the delay period and experienced alterations in their cost/benefit calculations. For example, schizophrenia is associated with an elevated tendency to experience negative affect/arousal and boredom , as well as altered decision-making on tasks that involve weighing the relative effort expenditure costs against monetary rewards . Studies that manipulate the constraints, or obtain subjective ratings/ psychophysiological measures, during delay intervals could shed light on the possible impact of these costs in DD in schizophrenia. Strengths of the current study include the large clinical sample, use of two different types of DD tasks, rigorous evaluation of data integrity, examination of many potential confounds, and evaluation of test-retest reliability. However, the study has some limitations and highlights areas in need of further study. First, participants with schizophrenia were taking medications at clinical dosages. Although dosage equivalents were not related to DD, the impact of medications remains unclear. Second, the schizophrenia sample was chronically ill and it is unknown whether similar DD patterns would be evident in younger or high-risk samples. Third, the order of delay discounting task administration was not counterbalanced, so we are unable to examine potential order effects. Fourth, although performance on the tasks was not related to subjective valuation of money, we did not obtain objective measures to evaluate whether income or socio-economic status was associated with DD task performance. Fifth, this study only assessed monetary rewards and it is unknown whether similar patterns would be found for other primary or secondary reinforcers. Sixth, although the schizophrenia group showed normal performance on the hypothetical DD task, we cannot tell if the normal choice patterns were achieved through abnormal neural processes. For example, a small fMRI study reported that individuals with schizophrenia showed an abnormal hypo-activation in some regions and hyper-activation in others while making DD decisions . Further attention to these issues can help clarify the nature of impaired reward processing and decision-making in schizophrenia. General Scientific Summary: Delay discounting refers to whether one is willing to forego a smaller, sooner reward for the sake of a larger, later reward. This study found that people with schizophrenia showed a greater preference for smaller, sooner rewards than healthy comparison participants on a DD task that involved making choices about actual monetary rewards provided in real time.

What are the considerations for efficient water and nutrient use in large-scale cannabis cultivation to minimize environmental impact?

Efficient water and nutrient use in large-scale cannabis cultivation are essential for minimizing the environmental impact and promoting sustainability. Here are key considerations and strategies to achieve this:

Water Management:a. Irrigation Efficiency:
- Use drip or precision irrigation systems to deliver water directly to the root zone, vertical grow rack reducing wastage and minimizing runoff.Implement irrigation scheduling based on plant needs, climate conditions, and soil moisture monitoring.
b. Water Recycling:
- Invest in water capture and recycling systems to reuse irrigation runoff and rainwater.Implement closed-loop systems to minimize water loss.
c. Water Quality:
- Regularly test and monitor water quality to ensure it meets the needs of cannabis plants and does not introduce contaminants.
d. Mulching:
- Apply mulch around plants to reduce evaporation and maintain soil moisture levels.
e. Drought-Resistant Cultivars:
- Consider selecting cannabis strains that are more drought-tolerant to reduce water requirements.
Nutrient Management:a. Soil Testing:
- Conduct regular soil tests to assess nutrient levels and adjust fertilizer applications accordingly.
b. Balanced Fertilization:
- Apply fertilizers in the right ratios to match plant nutrient requirements, preventing excess runoff and leaching.
c. Organic and Slow-Release Fertilizers:
- Use organic and slow-release fertilizers that release nutrients gradually, reducing the risk of nutrient imbalances and environmental pollution.
d. Microbial Inoculants:
- Incorporate beneficial microbes into the soil to improve nutrient availability and uptake by plants.
e. Precision Nutrient Delivery:
- Implement precision nutrient delivery systems to target the root zone and minimize wastage.
f. Fertigation:
- Combine irrigation and fertilization through a fertigation system to improve nutrient uptake efficiency.
Compost and Organic Matter:
- Add compost and organic matter to the soil to enhance water retention and nutrient-holding capacity.
Cover Crops:
- Plant cover crops during non-cannabis growing seasons to prevent soil erosion, improve soil health, and reduce nutrient runoff.
Regulatory Compliance:
- Stay informed about local regulations and restrictions related to water use, nutrient management, and runoff control.
Education and Training:
- Train staff in efficient water and nutrient management practices to ensure compliance with best practices.
Monitoring and Data Analysis:
- Implement monitoring systems to track water and nutrient usage,cannabis grow racks allowing for data-driven decisions and optimization.
Integrated Pest Management (IPM):
- Implement a robust IPM program to prevent pest and disease outbreaks, reducing the need for excessive water and nutrient application due to plant stress.
Energy Efficiency:
- Use energy-efficient equipment for water management, such as pumps and irrigation systems.
Environmental Impact Assessment:
- Conduct regular environmental impact assessments to identify areas for improvement and track progress in reducing resource use and environmental impact.

By integrating these considerations and implementing sustainable practices, large-scale cannabis cultivation can reduce its environmental footprint, conserve water, and optimize nutrient use while still producing high-quality cannabis products.

There are several limitations to the study presented here that should be noted

An isomer of 2,3,5-trimethyl-1,4-benzenediol has also recently been identified as a substantial VEA degradation product at temperatures 220˚C. Authentic standards were purchased for 2-methyl-1-heptene, phytol, and 2,3,5-trimethyl-1,4-benzenediol to confirm identities of observed products . Other compounds, such as vitamin E, DQ, DHQ, 1-pristene, and 3,7,11-trimethyl-1-dodecanol, have been consistently identified as VEA decomposition products. Several products, such as DHQMA or ketene, that have been previously reported in VEA vaping emissions could not be found in our spectra, likely due to the limitations of the emission collection and analysis method described in section 3.4. A heat map of the mass fractions of degradation products generated at each temperature is shown in Fig 4. Products that contribute to the majority of the observed VEA degradation were separated from the total heat map to better visualize the change in each concentration as a function of temperature. VEA, 1-pristene, and 3,7,11-trimethyl- 1-dodecanol were found to be the most dominant vaping emission products at all of temperature settings, while other compounds, such as duroquinone, durohydroquinone, and 2-methyl-1-heptene steadily increase in concentration as temperature increases. Furthermore, certain compounds including 2,3,5-trimethyl-1,4-benzenediol, 2,6-dimethyl-1,6-heptadiene, 3,7-dimethyl-1-octene, and 3-methyl-1-octene are not produced in concentrations above the detection limit of our instrument until 322˚C,cannabis grow system which suggests a potential risk that users who operated vaping devices at lower temperatures would not be exposed to. However, while most identified compounds appear to increase in concentration as temperature increases, phytol and 2,6,10-trimethyl-dodecane are produced at detectable levels at 176 and 237˚C but cannot be found at higher temperatures.

Another recent study has also detected production of phytol when vitamin E were heated in a micro-chamber/thermal extractor at 250˚C. It is possible that at these compounds are stable at lower temperatures but begin to break down into degradation products themselves as the temperature increases. Another important pattern to note is the increase in compounds that may pose a risk of oxidative damage to lungs, such as DQ and 2,3,5-trimethyl-1,4-benzenediol, at higher concentrations. While not investigated in this study, prior research has shown that increased temperature may result in the enhanced emission of carbonyl-containing compounds when vaping e-liquids containing propylene glycol and glycerin. Thus, vaping VEA at greater temperature settings may also carry the risk of exposure to highly electrophilic molecules and subsequent oxidative lung injury. In order to better understand the interactions between temperature and the generated emission products, a Pearson correlation analysis was performed . Overall, all but fourof the identified compounds were strongly correlated with temperature . Compounds such as DQ, 1-pristene, 2-methyl-1-heptene, 2-hydroxy-4-methoxy-3,6-dimethyl benzaldehyde, and 2,6-dimethyl-1,6-heptadiene, were very well correlated with temperature , indicating a strong increase in concentration as temperature increases. VEA and phytol, in contrast, were strongly anti-correlated with temperature , while VE and 2,6,10-trimethyl-dodecane were moderately anti-correlated with temperature . In addition, VEA was found to be weakly to strongly anti-correlated with all degradation products excepting phytol and VE, which demonstrate a strong positive correlation . These results support our analysis of the mass fractions, indicating that as temperature increases, thermal decomposition of VEA is heightened. Further analysis of the correlations between degradation products shows that phytol is strongly anti-correlated with all VEA degradation products with the exception of 2,6,10-trimethyl-dodecane, which was found to have a strong positive correlation with phytol .

Phytol was also found to be strongly correlated with VEA , likely because as more VEA was evaporated during the vaping process, the greater the chance of degradation into phytol. These relationships further suggest that while some degradation products may be stable at high temperatures, phytol may further decompose into shorter-chain alcohols, alkanes, and alkenes and enhance the production of VEA vaping emission products. Phytol is known both as a precursor for the synthesis of VE and vitamin K12, as well as a byproduct of chlorophyll degradation. Inhalation of aerosolized phytol has previously been shown to induce lung injury in exposed rats. In addition, phytol is a long chain alkyl alcohol compound, meaning that it has the potential to induce damage to the membrane of cells in a biological system. Overall, the toxicity of phytol raises questions about the safety of vaping not only VEA but cannabis-containing vape products that may result in phytol production. These results clearly indicate that the product distributions of VEA vaping emissions are highly dependent on the operating temperature of the vape pen. As a result, the exposure for vape users operating the same e-cigarette products at different temperatures may differ significantly.Previous reports of VEA pyrolysis indicate that VEA begins to degrade starting at ~200–240˚C. However, our results clearly demonstrate degradation of VEA and formation of products such as DQ at 176˚C, indicating that the device itself may play a larger role in the decomposition of VEA than initially anticipated. Previous study in our lab has also found substantial formation of DQ at 218˚C–several hundred degrees lower than what has been predicted. To further understand if the device itself may impact the thermal degradation of VEA, pure pyrolysis of VEA oil was carried out using a tube furnace reactor.At 176 and 237˚C, VEA was fairly stable; substantial consumption of VEA oil was not observed until the two higher temperatures, despite clear consumption at all temperatures during the vaping collection.

Fig 6 demonstrates the product distribution of VEA degradation products collected and analyzed using GC/MS. Here, we did not observe substantial thermal decomposition of VEA when heated at 176˚C for 75 minutes, which greatly contrasts with the degradation of VEA at 176˚C for only 4 s during the vaping collection. At 237˚C, the parent VEA molecule was the only detectable emission product, indicating that VEA again did not degrade at this lower temperature, though 237˚C was enough to evaporate VEA so that it could be collected in the cold trap. Degradation products were only detectable from samples collected at 322 and 356˚C, though the number of products and abundance of observed peaks are drastically reduced when compared to the vaping emissions. It should be noted that the tube furnace is capable of heating VEA at more accurate and consistent temperatures than the vape pen itself, which often saw temperature fluctuations that may influence results. The stark difference in product distribution provides evidence that VEA vaping emissions may not be the result of pure pyrolysis alone. Instead, external factors such as the device elements themselves or environmental interactions may play a role in the catalysis of VEA degradation. The cartridge used in this study is a newer THC cartridge that contains a ceramic heating element, a nichrome filament wire, a fibrous wick/insulation wrap through which oil was delivered to the heating element, and a stainless steel air flow tube and heating element housing that the oil remained in direct contact with. The emission of metals during the vaping process has been documented in several prior studies, but the interaction between VEA and the metal components of the vape device are still being investigated. Saliba et al. recently found that interaction between a metal heating element and PG greatly decreased the temperature required to observe PG thermal decomposition. Certain metals such as stainless steel, which is present in the cartridge used in this study,cannabis grow lights resulted in a nearly 300˚C reduction in required temperature compared to pure pyrolysis, highlighting a clear interaction between the PG decomposition and the device itself. Furthermore, a study by Jaegers et al. found that pyrolysis alone in an anaerobic environment was not able to induce thermal degradation of PG and VG at low temperatures , despite previous studies observing degradation at temperatures as low as 149˚C during vaping. However, when heated in an aerobic environment, thermal decomposition was observed at 133 and 175˚C, both without and with the addition of metal oxides Cr2O3 and ZrO2, suggesting that oxidation is a key process during vaping. In combination with the results shown here, evidence highly suggests that pure pyrolysis alone may not be the only pathway for VEA degradation. During the vaping process, not only may VEA come into direct contact with metals that are present in the filament wire or stainless-steel body, but VEA must also come into contact with molecular oxygen in ambient air. These interactions may promote VEA degradation at temperatures lower than predicted under pure pyrolysis conditions. Ultimately, it is then possible that compounds such as DQ or ketene may be able to form at lower temperatures than what is theoretically calculated if these interactions are considered.However, further study is required to fully understand the effects of the e-cigarette device and vaping environment on the degradation of e-liquids.First, this study presents a range of decomposition products that were identified using a -40˚C cold trap and GC/MS analysis.

Approximately 40% of the mass of VEA consumed by the vape pen could be attributed to the compounds identified here. However, compounds with high vapor pressure, such as ketene, that have been previously reported from VEA pyrolysis may not have been efficiently captured using the cold trap method described in this study. This method is expected to better traps particle-phase compounds that are able to condense at -40˚C and are stable enough to transfer from the cold trap to collection vials at room temperature and is unable to capture highly volatile or reactive VEA vaping emission products. For example, ketene, which is expected to form during VEA pyrolysis, has an estimated boiling point of -56˚C and, as a result, was not expected to be observed in our collection. Furthermore, highly volatile and/or reactive compounds such as ketene and various low molecular weight carbonyl-containing species, etc., often require additional derivatization methods that were not used in this study to be observed using GC/MS. This study was also only able to identify compounds with mass spectra that could be found in the NIST mass spectral library. While PubChem currently reports over 111 million unique chemical structures, the NIST library used in this study contains MS fragmentation patterns for only 242,466 compounds. As such, a large portion of the TIC for each collection could not be matched to a known compound . Furthermore, several peaks were observed that were believed to be co-elution of two or more products, which prevented clear analysis of the fragmentation patterns. Several identified products, such as VEA, may also have multiple isomeric forms that have only slight differences in their retention times and mass spectra that the NIST library matching program is unable to account for. In the case of VEA, all peaks were assumed to be and quantified as the same α form, but it is possible for VEA to exist in α, β, γ, or δ forms. This may be true for other structures identified in this study. The use of QCEIMS to identify products that cannot be found in the NIST database, such as 1-pristene, is a potential avenue for further identification of vaping product emissions, though its use for non-target analysis is limited if the researcher does not have a proposed structure in mind to simulate fragmentation. While this study was able to account for ~40% of the mass consumed by the pen during the vaping process, the remaining mass is likely attributable to these uncaptured volatile or reactive products, as well as degradation products that were captured, but unable to be identified at this time. Finally, the vaping topography used in this study was adapted from previous literature on nicotine vaping and optimized for capture of particles in the cold trap system. Real-word nicotine vape users have been reported to inhale between 50–80 mL/puff at greater flow rates than used in this study, whereas parameters for THC-vaping have not been well-characterized at this time. The production yields of VEA degradation products reported in this study could consequently differ for those who vaped at higher flow rates. The temperature dependence of product distribution, however, remains true.This is the first large scale randomized trial that provides the opportunity to compare the treatment retention of participants on buprenorphine and methadone in community treatment programs in the U.S. The results demonstrate that those treated with BUP were more than 50% less likely to remain in treatment for 24 weeks than those receiving MET. This finding is consistent with other controlled trials or observational studies, even including studies that focused on special populations such as pregnant patients.19

The only exception is that GMs assigned male evidenced elevated odds for alcohol dependence

This study was embedded within a larger longitudinal birth-cohort study and therefore limited by attrition. It is possible that mothers who chose to participate in the study and to continue for multiple assessments may have differed from those who did not, although retention since age 9 was around 95%. Given limitations, results should be replicated among diverse populations, as well as other samples of Mexican-origin youth. Lastly, the study was limited to youth who had no gang involvement because of risk for violent responses to the TSST. This criterion may have attenuated associations, as gang members often show greater substance use . Substance use disorders affect more than 20 million individuals in the United States annually, increasing risk for psychiatric disorders, chronic diseases, and disruptions to social, family, and work lives . SUD prevalence peaks during young adulthood , with co-occurrence of multiple SUDs also common during this time period, which increases clinical severity and complicates treatment . Previous research has established that, compared to completely heterosexual and cisgender individuals , sexual and gender minorities engage in greater substance use beginning in adolescence and extending throughout life .Even fewer have examined more serious SUD outcomes by sexual orientation or gender identity or have focused on SUDs during young adulthood . The present study addresses these gaps by examining associations between SGM statuses and past 12-month prevalence of SUDs in a community cohort of U.S. young adults. SGM disparities in SUDs persist because SGMs use substance to cope with SGM-related minority stressors,cannabis grow system including self-stigma and interpersonal and structural-level discrimination . Disparities may also be driven by differences in substance use norms within SGM communities . For example, research indicates that sexual minorities perceive greater availability of substances and have more tolerant use norms than do heterosexuals .

Additionally, gender minority youth may perceive less risk associated with substance use than cisgender youth .Research has found persistent variation in SUD risk by sex. In the general population, men experience single and co-occurring SUDs at higher levels than women . Among SMs, however, sex differences are typically reduced or even reversed, with greater sexual orientation disparities among adult women compared to men, and especially elevated rates among bisexual women . Nonetheless, studies have rarely tested whether sex modifies relationships between sexual orientation and SUDs by including interaction terms in statistical models. Prevalence of SUDs tends to peak around age 25 and declines with age . Research examining SUDs among SMs, however, suggests a slower agenormative decline . Rarely have researchers compared sexual orientation or gender identity disparities in SUDs among individuals older than 25 years with those in younger age groups. Knowledge of how the magnitude of sexual orientation and gender identity differences in SUDs vary by birth sex and age can help identify subgroups in need of interventions. Research on how gender identity is associated with SUD risk is severely lacking, with available studies using small, subgroup samples . Studies also frequently lack cisgender comparison groups, preventing quantification of gender identity differences. This study analyzed data from the longitudinal Growing Up Today Study when participants were aged 20-35 to estimate sexual orientation and gender identity differences in probable SUDs. Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria were used to assess past 12-month nicotine dependence, alcohol abuse/dependence, drug abuse/dependence, any SUD, and co-occurring multiple SUDs . Because research demonstrates sex differences in associations between sexual orientation and substance outcomes , we estimated statistical interactions between 1) sexual orientation and birth sex, and 2) gender identity and birth sex, and present birth-sex-stratified estimates.

We hypothesized that SGMs would be more likely than non-SGMs of their same birth sex to meet criteria for SUDs, and that sexual orientation differences would be larger among participants assigned female at birth compared to those assigned male. Additionally, we estimated statistical interactions between 1) sexual orientation and age, and 2) gender identity and age. We hypothesized that sexual orientation and gender identity differences in SUD risk would be larger in older versus younger periods. Among participants meeting criteria for a past 12-month drug use disorder, we examined associations of sexual orientation and gender identity with past 12-month specific drug use.Our study quantified sexual orientation and gender identity differences in SUD risk during young adulthood, when SUD prevalence in the general U.S. population is high . We examined SUDs based on DSM-IV criteria including nicotine dependence, alcohol abuse and dependence, drug abuse and dependence, and multiple co-occurring SUDs. Aligning with previous literature , we found that SM status was associated with greater odds of past 12-month SUDs among young adults assigned female, and to a lesser extent among those assigned male. Co-occurrence of 2 or more SUDs in the past 12-months was also more common among SMs compared CHs, aligning with previous studies of lifetime SUD co-occurrence . Contrary to our hypothesis, age-related declines in SUD prevalence were largely similar across sexual orientation and gender identity groups. This finding may be due, in part, to our sample age range and age periods compared in analysis . Previous studies have shown differential age-related declines in alcohol problems between SMs and heterosexuals and noted the largest sexual orientation differences in ages 40 or older . An analysis of representative U.S. data showed declines in the prevalence of tobacco and alcohol disorders among SMs between ages 26-35 but increases in prevalence between the mid-30s to mid-40s . We uniquely examined how GM status is related to risk for SUDs. This is an important contribution as studies assessing SUDs by gender identity are limited and typically focused on substance use instead of abuse . In contrast to findings related to sexual orientation, we did not find consistent evidence of greater prevalence of SUDs among GMs after accounting for sexual orientation in statistical models.This lack of evidence, however, should be interpreted with caution considering small numbers of GM participants in GUTS and previous evidence indicating their disproportionate substance use .

Additional studies quantifying associations between gender identity and SUDs are needed.Among the general population, more people assigned male at birth report probable SUDs than do people assigned female at birth . In contrast, we found SMs assigned female generally had similar or higher levels of SUDs compared to SMs assigned male, and sexual-orientation differences were larger in assigned females than assigned males. One reason is that comparisons between SM and CH women will yield relatively large effect sizes because CH women have the lowest levels of SUDs of all groups defined by sexual orientation and birth sex. Beyond this explanation, there is little insight into why SM women are at especially elevated risk, though some have proposed that SM women are at greater risk for minority-specific stressors and mood disorders, resulting in greater risk for SUDs .Among participants with a drug use disorder,marijuana grow system we found that some subgroups of SGMs had elevated odds of reporting use of certain drugs compared with CHs and cisgender participants. Studies examining sexual orientation or gender identity differences in drug use among individuals with drug use disorders are rare; however, cross-sectional studies with participants of the NSDUH found that SM adults were significantly more likely than heterosexuals to report past-year marijuana and other drug use . This indicates that SGMs may be more likely to use different substances than non-SGMs, which has implications for screening, intervention, and treatment . The DSM-IV defined separate criteria for substance abuse and dependence, whereas in the updated DSM-5, abuse and dependence are combined into a single SUD diagnosis . Studies comparing DSM-IV and DSM-5 SUD diagnostic criteria have shown increases , no differences , and decreases in prevalence. Increases in SUD prevalences under DSM-5 may relate to the inclusion of ³GLDJQRVWLF RUSKDQV´ in diagnoses² those who meet one or two DSM-IV criteria for dependence, but none for abuse . Nonetheless, concordance of DSM-IV and DSM-5 diagnoses are acceptable, with concordance increasing with severity , suggesting that our findings are likely similar to those resulting had we used DSM-5 criteria. Further research is needed to clarify this issue. GUTS participants are not representative of the U.S. population as they are children of registered nurses and predominantly non-Hispanic White. The prevalence of SUDs in GUTS, however, is comparable to same-aged participants of the NSDUH , as is the distribution of SGMs enrolled in GUTS compared to population-based studies . Additionally, GUTS participants were not enrolled based on their sexual orientation or gender identity. GUTS assessed sexual orientation with a single item tapping both identity and attraction. This limits direct comparisons between our findings and other studies assessing dimensions of sexual orientation separately because research indicates these dimensions have different associations with substance involvement . Further, despite the large sample size, we were limited in our ability to detect within group differences among SGMs. Despite these limitations, our study is strengthened by including multiple SGM subgroups, enabling examination of heterogeneous outcomes that may otherwise be obscured when combining SGM categories. Future research should include more diverse, nationally representative samples to enable examination of interactions between sexual orientation, gender identity, and other sociodemographic factors to further identify higher-risk SGM subgroups.

Among the general population, young adults with SUDs experience disproportionate economic and public health burdens and have low utilization of SUD treatment . For SGM young adults, these issues may be even more persistent, with one study finding that less than 4% of the 14-20% of SMs needing treatment actually accessing treatment . Specific barriers to treatment among SGMs include a lack of targeted interventions, differences in coping strategies and psychiatric comorbidities, discrimination within healthcare settings, lack of provider knowledge about SGM health needs, and lack of insurance . Consequently, increasing access to treatment alone may be insufficient to address SGM SUD disparities. Efforts should also focus on bolstering the provision of culturally tailored, SGM affirming treatment which promotes resilience, coping, and wellness. Further, given high co-morbidity with other mental disorders, interventions are needed which integrate psychological and SUD treatment .Methamphetamine dependence commonly accompanies HIV infection, typically because of behaviors during drug use that increase the risk of viral transmission . While each of these conditions by themselves often have negative effects on the individual’s cognition and functional behaviors, there is also evidence that the combined effect of HIV infection and heavy METH use may have additive effects, e.g., resulting in worse neuronal injury , compounded damage to frontostriatal circuits , and more profound neuropsychological impairment than either condition alone. Neuropsychological deficits, particularly those that are frontally-mediated, are thought to substantially impact everyday functional ability, i.e., the ability to engage in vital tasks of daily living . For people living with HIV, an added demand is adherence to an antiretroviral therapy regimen. Although HIV and METH dependence have each been associated with worse performance on tasks of everyday functioning , the combined effects of HIV infection and heavy drug use on the ability to carry out tasks of daily living have not been widely studied [but see ] but are important to understand given the high co-occurrence of these two conditions and the potential adverse implications for medication adherence and other important functional behaviors. Parsing the relationships among HIV illness, METH use characteristics, and everyday functioning may help inform treatment decisions. For example ART seems to reduce the severity of HIV-associated neurocognitive disorders , however some antiretroviral medications do appear to have neurotoxic effects . Furthermore, there are limitations in the operationalization of everyday functioning in previous investigations. Many studies of everyday functional ability, including those conducted in HIV and substance dependence have used self-report measures that ask the individual to rate how well they perform activities of daily living. We and others have proposed that reliance on self-report is problematic especially during the study of conditions with known cognitive impairment. Performance based functional measures, such as the UCSD Performance Based Skills Assessment , are useful in that they divide everyday function into specific components and have high reliability and validity , e.g., comprehension and planning abilities, financial skills, knowledge in use of transportation and managing the household, and the extent to which individuals can internalize and plan to take a complex daily regimen of medications.

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