These two models were able to isolate the impacts of recreational marijuana legalization from the impacts of medical marijuana legalization on opioid prescriptions. Comparing eight states and DC to all the remaining 42 states violated the difference-in-difference assumption, because states without medical marijuana legalization had different trends in opioid prescriptions compared to states with medical marijuana legalization . To test the assumption of parallel trends in treatment and comparison states in the absence of policy change, we used repeated ANOVA to compare time trends in opioid outcomes between treatment and comparison states in years 2010, 2011, and 2012 when none of these states adopted recreational marijuana legalization. Linear regressions were used, controlling for time-varying state covariates, state indicators, year and quarter indicators, and state-specific linear time trends. State indicators accounted for time-invariant state-level unobserved heterogeneities such as social norms about opioid use. Year and quarter indicators accounted for time-specific heterogeneities common to all the states at the same time, such as CDC Guideline for Prescribing Opioids for Chronic Pain published in 2016 . State-specific linear time trends accounted for statelevel time-variant trends in outcomes. Standard errors in the regression were clustered at the state level. To test the robustness of results, we conducted a series of sensitivity tests. 1) Because California, Maine, Massachusetts, and Nevada had limited number of post-legalization observations, the policy impacts in these states may not be statistically discernable. In addition, the most recent quarters of Medicaid State Drug Utilization data may contain errors and are often subject to future revision. We excluded the observations after 3rd quarter of 2016 when these states implemented recreational marijuana legalization to focus the analyses on states legalizing recreational marijuana before 2016. 2) We moved Hydrocodone-combination drugs to Schedule III opioids to test results sensitivity to recent drug reclassifications. 3) It is suggested that adding state-specific time trends may attenuate estimates of policy impact if the policy impact acts upon the trend itself . We removed state-specific time trends in regressions and expected that the associations would be more discernable. 4) Following previous research ,ebb and flow tray we also performed falsification tests on 4 drug classes, including blood-thinning agents, phosphorous-stimulating agents, antivirals, and antibiotics, as there is no scientific evidence suggesting the associations between marijuana and the underlying conditions that these drugs treat.

These drugs were assumed to be not associated with recreational marijuana legalization but associated with common unmeasured confounding factors such as those affecting general prescribing, healthcare utilization, and healthcare resources at the state level. Table 2 reports the descriptive statistics of pooled data by recreational marijuana legalization status. Compared to six states with medical marijuana legalization but without recreational marijuana legalization, eight states and DC that legalized recreational marijuana in the study period had slightly and insignificantly higher rates of Schedule II and III opioid prescriptions. Supplemental Table S22 reports ANOVA tests for time trend comparisons, suggesting that the time trends prior to legalization did not significantly differ between the states legalizing recreational marijuana in 2012 and the six comparison states, between the states legalizing recreational marijuana in 2015 and the six comparison states, or between the states legalizing recreational marijuana in 2016/7 and the six comparison states. Figure 1 shows the unadjusted time trends in number of Schedule III opioid prescriptions by legalization status. States that legalized recreational marijuana in 2015 and 2016/7 saw a reduction in number of Schedule III opioid prescriptions after the legalization took effect, whereas states that legalized recreational marijuana in 2012 saw a slight increase. Trends in number of Schedule II opioid prescriptions did not appear to differ by legalization status . Based on difference-in-difference regressions, Figure 2 reports predicted percentage changes in number of opioid prescriptions associated with recreational marijuana legalization . In Model A that compared among eight states and DC with recreational marijuana legalization, recreational marijuana legalization was not associated with number of prescriptions, total doses, or spending of Schedule II opioids.In Model B that compared eight states and DC to six states with medical marijuana legalization, recreational marijuana legalization was not associated with any Schedule II or Schedule III opioid outcome. Using eight-year quarterly data on prescription opioids received by Medicaid enrollees in the US, the study added to the still limited literature about the impacts of recreational marijuana legalization on opioid use. It enhanced internal validity by adding comparison states and controlling for multiple confounders that were absent in previous research , such as presence of prescription drug monitoring program, Medicaid expansion.

It also enhanced generalizability by investigating all states legalizing recreational marijuana in the US. We found no evidence to support the concern that recreational marijuana legalization increased opioid prescriptions received by Medicaid enrollees. Instead, there was some evidence in some model specifications that the legalization might be associated with reduction in Schedule III opioids in states that implemented legalization in 2015 . It appeared that, if the hypotheses about marijuana’s substitution effect and gateway effect on opioid use are both valid, the gateway effect of marijuana did not outweigh its substitution effect. Another possibility is that the hypothesis about marijuana’s gateway effect lacks support. Unfortunately, we were not able to directly assess these mechanisms in this study. It is not clear why two comparisons yielded slightly different results. Both models have advantages and limitations. The treatment and comparison states in the first model comparing among eight states and DC were more comparable, as they all had adopted recreational marijuana legalization at some time points. On the other hand, the second model comparing eight states and DC to six states with medical marijuana legalization had a larger sample size to detect statistical significance. We therefore chose to report findings in both comparisons. Irrespective of their slight differences, the core findings from the two comparisons were consistent that recreational marijuana legalization did not increase prescription opioids received and most coefficients for the outcome variables were non-significant. In accordance with our previous study on medical marijuana legalization and prescription opioids received by Medicaid enrollees , the association between recreational marijuana legalization and reduction in prescription opioids seemed to be only evident in some models for Schedule III opioids but not for Schedule II opioids. Because this line of research only emerged recently, the explanation for the differential associations remains unknown. As discussed in our previous study , we hypothesized that such differences may be partly attributable to the differences in clinical practice and drug efficacy between the two drug classes. According to Controlled Schedule Schedules classified by US Drug Enforcement Administration, Schedule II opioids have greater potential for opioid misuse and overdose than Schedule III opioids . In clinical practice, Schedule II opioids must be refilled with monthly prescriptions whereas Schedule III opioids are fillable within six months without new prescriptions . Receiving regular monitoring and evaluations from physicians, patients prescribed with Schedule II may be less likely to switch to other drugs. Regarding drug efficacy, Schedule III opioids are often used to treat mild to moderate pain symptoms,rolling greenhouse benches for which marijuana is suggested to be also effective . But the evidence for marijuana’s efficacy to treat severe pain symptoms is still limited. Patients prescribed with Schedule II opioids might be less likely to receive recommendation from physicians to switch to marijuana. These hypotheses need future research on individual observations to provide empirical support. It is also worth noting that despite large effect size detected for Schedule III opioids in terms of percentage point reduction , the absolute level of opioid prescribing rates was low for this drug class . The impact of the legalization converted to absolute levels was modest. This study has limitations primarily related to data availability. First, we evaluated the implementation of legalization instead of commercialization . Because several states did not open retail markets during our study period, our results may be biased toward the null. Second, despite the size of state-level observations is larger in this study than previous research, our study sample is still small and some statistically non-significant associations may simply reflect the lack of statistical power. Particularly, observations in post legalization period were limited for states implementing legalization in 2016/7. Third, we were not able to explore why states implementing legalization at different time points may demonstrate differential changes in opioid prescriptions. Fourth, we grouped states based on their law implementation dates. However, the states implementing the legalization on the same dates may have opened their retail markets on different dates . We were not able to identify the degree of marijuana commercialization in each state or evaluate the independent impacts of commercialization because of limited sample size. Further, similar to other state-level investigations of aggregate data, we were not able to explore causal mechanisms of the findings at individual level.

Particularly, the hypotheses about substitution and gateway effects of marijuana cannot be directly tested. Additionally, the outcomes analyzed in this study represented opioid prescribing but not patients’ legitimate use or misuse of prescription opioids. Finally, the findings may not be generalizable to opioids dispensed in non-outpatient settings or to the general population. The findings represented a limited number of states in the US but may not be generalizable to other states in the US or to population in other countries. Alcohol and marijuana use are common in adolescence. In 2003, 31% of 12th graders reported getting drunk in the past month, 21% of 12th graders revealed using marijuana in the past month, and 6% of 12th graders disclosed daily marijuana use . Further, 40% of high school students who used marijuana in the past year met criteria for marijuana abuse or dependence . Moreover, 58% of adolescent drinkers also report marijuana use , and alcohol and marijuana use disorders are highly comorbid . Despite the prevalence of heavy alcohol and marijuana use in teenagers, it is unclear how such protracted use may affect brain functioning during youth, particularly as adolescent neuromaturation continues. Neuropsychological studies of teens with alcohol use disorders have reported decrements in language skills, problem solving, verbal and non-verbal retention, working memory, and visuospatial performance . In addition, we previously examined functional magnetic resonance imaging brain response during a spatial working memory task among teens with AUD and demographically similar non-abusing controls . Groups performed comparably on the task, but AUD teens demonstrated less brain response than controls in the midline precuneus/posterior cingulate, and more activation in bilateral posterior parietal cortex, suggesting subtle alcohol-related neural reorganization and compensation. These neuropsychological and imaging findings suggest that heavy alcohol use during youth adversely affects frontal and parietal circuitry, but the additional impact of marijuana use is less well understood. Neuropsychological assessments of substance use disordered teens have described marijuana use related deficits in learning and memory and attention . A longitudinal study of marijuana dependent adolescents demonstrated further short term memory decrements that persisted after 6 weeks of monitored abstinence . In addition, compared to individuals with adult-onset cannabis use disorder and non-abusing controls, adolescent-onset cannabis use disordered adults showed attenuated electrophysiological response during selective attention , as well as smaller frontal and parietal volumes and increased cerebral blood flow . These studies indicate that heavy marijuana use during youth may adversely affect cognition and brain functioning, particularly short-term memory and attention, and raise questions about the integrity of frontal and parietal brain regions in adolescents with marijuana use disorders. In order to understand the neural correlates of concomitant heavy marijuana and alcohol use during youth, we assessed blood oxygen level dependent fMRI response among short term abstinent teens with comorbid marijuana and alcohol use disorders compared to AUD-only and non-abusing control teens reported in a previous study . We measured BOLD response during an SWM task that typically activates bilateral prefrontal and posterior parietal networks among adults and youths . Based on our earlier findings among AUD and control adolescents, we predicted that MAUD teens would show greater fMRI response than controls in regions sub-serving SWM, including prefrontal and bilateral posterior parietal cortices. We hypothesized further that MAUD teens would show more prefrontal and parietal activation than AUD youths, since we predicted that concurrent heavy marijuana and alcohol use would influence functioning more than protracted alcohol use alone.Flyers were distributed at local high schools to recruit adolescents, as described previously .

Column gives results from a reduced form specification regressing market prices and controls on worker productivity directly, and column provides the results of my preferred two-stage least squares specification instrumenting for wages with market prices. When I instrument for wages, their effect on worker productivity remains statistically insignificant, but the relevant point estimate becomes barely positive. The temperature response function is quite stable across columns and lending support to the conclusion that I accurately recover a true relationship. While the richness of my data allows me to exploit intra-day variation in temperature, I can also collapse my data to the day-level and investigate how daily temperature affects daily worker productivity. Figure 1.15 reports the results of three different day-level temperature specifications. The first uses time-weighted average daily temperature experienced by each picker, the second uses daily maximum temperature, and the third uses daily minimum temperature. Overall, the results from these specifications support the qualitative results of my primary specification: extreme temperatures lower picker productivity, and cool temperatures are more damaging than very hot temperatures. One threat to the credibility of my findings in tables 1.2 and 1.3 is that temperature and wages may affect workers’ labor supply, both on the intensive and extensive margins. That is, workers may decide to work fewer hours on a particularly hot day, or choose not to come to work at all if the piece rate wage is particularly low.Such behavior would bias my estimates of how temperature and wages affect productivity by introducing unobserved systematic selection into or out of my sample. I investigate this possibility in table 1.5 by regressing temperature, wages, and controls on both hours worked and the probability of working.

In column ,cannabis grower supplies the dependent variable is the number of hours worked by a picker in a single day, and temperature is measured as a time-weighted average experienced by the picker during that day. Here, I control for a picker’s start-time rather than their picking “midpoint.” In column , the dependent variable is an indicator for whether a picker worked at all in a given day, and temperature is measured as a daily midpoint temperature: /2. I use daily midpoint temperature in column in order to provide a consistent comparison between employees who show up to work and employees who do not, since I do not know when or for how long these absent employees would have worked had they come to work. Figure 1.16 displays the relevant temperature results from columns and of table 1.5. Overall, table 1.5 reports that neither wages nor temperatures affect labor supply in a statistically significant way. Similar to Graff Zivin and Neidell , I find the labor supply of agricultural workers to be highly inelastic in the short run. This also matches the findings of Sudarshan et al. for weaving workers in India. This evidence gives me confidence in the validity of my baseline results.I now turn to how temperature affects berry pickers’ wage responsiveness. Table 1.6 reports the results of estimating a variant of equation separately across eight temperature bins.I find that wages have no meaningful effect on productivity at most temperatures, but have a statistically significant and positive effect on productivity at cool temperatures: those between 50 and 60 degrees. In particular, my estimate suggests an increase in the piece rate wage of one cent per pound at temperatures below 60 degrees increases average productivity by 0.28 pounds per hour. This reflects an elasticity of productivity with respect to the wage of roughly 1.6 at cool temperatures,and an elasticity statistically indistinguishable from zero at other temperatures. This “productivity elasticity” is considerably smaller than the 2.14 number estimated by Paarsch and Shearer . Table 1.7, which repeats the analysis from table 1.6 using ordinary least squares , highlights the importance of instrumenting for piece rate wages. This table highlights two important things. First, the effects of wages on productivity at low temperatures do not show up in a statistically significant way without correctly instrumenting for wages with market prices. Second, I am able to rule out any dramatically large effect of wages on productivity at most temperatures.

Another threat to my findings is that workers who do not out-earn the hourly minimum wage in a given day may shirk when they know that additional productivity will not increase their take-home pay. Figure 1.13 reports the frequency with which workers fall below this minimum wage threshold. I face an econometric problem if the effects of temperature reduce workers’ productivity, increase the probability that workers earn the minimum wage, and hence encourage shirking. To ensure my findings are not meaningfully altered by this phenomenon, I re-estimate my main results using only picker observations where the picker out-earns the minimum wage for the day. This procedure drops my number of picking period observations from 305,980 to 257,689: a decrease of 15.8%. Figure 1.17 and table 1.8 present the results of my main temperature and piece rate wage specifications using this subsample. My findings remain qualitatively stable and statistically significant.Finally, even if temperature and wages do not affect labor supply directly in a statistically significant manner, and even though worker-specific fixed effects capture individual workers’ average productivity levels, I still face a potential adverse selection problem. Specifically, if variation in temperature and wages affects which sorts of workers choose to show up for work, my results may capture workforce compositional effects rather than individual productivity effects. To address this concern, I re-estimate my results only using observations from those workers who work more than thirty days in the relevant season. The intention here is to focus on workers who are likely to have the least elastic extensive labor supply. The results of this robustness exercise are presented in figure 1.18 and table 1.9. Taken together with the other available evidence, these results largely support my baseline findings. My primary finding is that labor productivity, on average, is very inelastic with respect to piece rate wages: I can reject with 95% confidence even modest positive elasticities of up to 0.7. This upper bound is considerably lower than the estimates derived by Paarsch and Shearer and Haley . I show that, without controlling for seasonality, a regression of productivity on piece rate wages results in a negative and significant point estimate . However, even once I control for seasonality, a naïve OLS regression of productivity on piece rate wage may be biased toward zero of table 1.4.

By instrumenting for piece rate wages with the market price for blueberries, I can identify a precisely-estimated inelastic effect of table 1.2. However, my primary specification makes the restrictive assumption that wages affect productivity linearly and in the same manner at all temperatures. Table 1.6 confirms that piece rates’ effect on productivity is very much non-linear across different temperatures. Specifically, wages seem to spur productivity at cool temperatures . At other temperatures, wages do not affect productivity in a statistically significant way. This empirical finding directly challenges one of the core assumptions of the model presented in section 1.2.1: that productivity always rises with the wage . What is going on? One possible explanation for my findings is that, at moderate to hot temperatures, workers’ face some binding physiological constraint on effort that prevents them from responding to changes in their wage. Put bluntly, blueberry pickers in general may already be “giving all they’ve got” at the temperatures and wages I observe.Figure 1.19 summarizes this possibility using the theoretical framework developed in section 1.2.1. While the model in section 1.2.1 is straightforward and tractable, it is not the only way to conceptualize worker effort and productivity. In particular, rather than modeling effort as an unrestricted choice variable,dry racks for weed one could assume each worker has a finite daily budget of effort that must be allocated across different activities throughout a day and Becker. Such a model would allow Xr to be zero or even negative under certain conditions, implying a backwards-bending effort supply curve, somewhat analogous to the canonical backward-bending labor supply curve . The downside of such models is that they fail to provide comparative statics that can be tested with the data I observe in this setting. A growing literature has rigorously documented the non-linear impact of temperature on everything from corn yields to cognitive performance , but has not focused specifically on how temperature affects agricultural workers.Nevertheless, several recent papers in this literature seem particularly relevant to my findings. Adhvaryu et al. show that factory workers in India produce more output when heat-emitting conventional light bulbs are replaced LED lighting, especially on hot days. Sudarshan et al. find similar evidence that temperature reduces worker productivity in a variety of Indian manufacturing firms. Finally, Seppänen et al. show that temperature even has large effects on the productivity of office workers.Other researchers have asked broader questions about how temperature affects aggregate production or labor decisions at the county- or country-level. The growing consensus is that weather shocks – particularly exposures to extreme heat – reduce aggregate production in a wide variety of settings. For instance, Hsiang exploits natural variation in cyclones to find negative impacts of high temperatures in both agricultural and non-agricultural sectors at the country-level. Deryugina and Hsiang and Park find similar county level effects of daily temperature in the United States, despite widespread adoption of air conditioning. Heal and Park document relevant findings throughout the economics literature and provide a useful theoretical link between heat’s physiological effects and aggregate economic activity.Extreme heat may reduce aggregate production through several channels. The first possibility, discussed at length in the previous paragraph, is that employees are less productive while working at high temperatures.

Another possibility is that employees may choose to work fewer hours when temperatures are particularly high. In other words, there may be a labor supply response to temperature on the extensive margin. Graff Zivin and Neidell provide support for this hypothesis by analyzing data from the American Time Use Survey. They find that at high temperatures, individuals reduce the time they spend working and increase the time they spend on indoor leisure. Finally, temperature can affect even broader aspects of the labor market like aggregate demand for agricultural labor in India , or the composition of labor in urban vs. rural regions of Eastern Africa . While this paper examines how a particularly salient environmental condition, temperature, affects labor productivity, previous research has shown that other environmental factors matter as well. Chang et al. , for instance, find that outdoor air pollution negatively affects the indoor productivity of pear packers. The same authors conduct a similar exercise using data from Chinese call-centers and find comparable results. Adhvaryu et al. find a steep pollution-productivity gradient in the context of an Indian garment factory, and Graff Zivin and Neidell find large damages from ozone in an agricultural context somewhat similar to my own. In an older case study, Crocker and Horst, Jr. study seventeen citrus pickers in southern California and find negative effects of both high temperatures and air pollution. It is useful to think of temperature not as a single sufficient statistic to describe environmental quality, but rather as one condition among many that is relevant for understanding labor productivity. This paper makes several important contributions to the literature discussed above. First, because I observe berry-pickers’ productivity multiple times during a single day, the variation I observe in both productivity and temperature is much more temporally precise than in many previous studies. Additionally, since I use temperature observations that are taken hourly, and sometimes more frequently, I do not need to interpolate temperature over time. Second, I study a setting where both very hot and cool temperatures have negative effects on productivity, highlighting the particularities of different production processes when it comes to temperature impacts. Third, and most importantly, I look at how how environmental conditions and incentive schemes interact.Table 1.2 and figure 1.14 provide my estimates of the direct effects of temperature on labor productivity in the California blueberry industry. Whereas most previous studies have focused on the negative effects of extreme heat , I find that cool temperatures have just as large negative effects as very hot temperatures, if not larger.

Motives of celebration, coping, and social anxiety are significantly associated with symptoms of anxiety at p ≤ 0.05. Only coping remains significantly associated with symptoms of anxiety using the Bonferroni corrected p ≤ 0.003. Coping is positively and significantly associated with symptoms of anxiety whereas the more often marijuana use is motivated by coping, the higher the score for symptoms of anxiety. The magnitude of the association of motives of coping with symptoms of anxiety is of almost 1 indicating that for any one unit change in the strength of coping motive there is almost a one point change in scores of symptoms of anxiety. Post hoc power analyses indicate that the statistical power greater than 0.99. Results from the mediation analysis with past 90 days marijuana use as a mediator are presented in Tables 4.45a-d. There is no evidence of any indirect effects of motives of marijuana use on symptoms of anxiety through past ninety days marijuana use. All 95% bootstrap confidence interval for the indirect effect, based on 10,000 bootstraps, include zero. There is however evidence of a positive direct effect with symptoms of anxiety for motives of coping and social anxiety, independent of past 90 days use. Results from the mediation analysis with daily number of hits as a mediator are presented in Tables 4.46a-d. All 95% bootstrap confidence interval for the indirect effect, based on 10,000 bootstraps, include zero. There is, however, evidence of a negative direct effect with symptoms of anxiety for motive of celebration and a positive direct effect for motives of coping and social anxiety. After controlling for age, gender, user group, and race/ethnicity, there is a negative direct effect between motives of marijuana use and symptoms of anxiety for motives of celebration and sleep,vertical grow systems and a positive direct effect for motives of coping and social anxiety. Table 4.47 presents the regression estimates without and with control variables.

Motives of marijuana use account for approximately 24% of the variance of overall psychological distress. Motives of celebration, coping, conformity and social anxiety are significantly associated with overall psychological distress at p ≤ 0.05. Only coping remains significantly associated with overall psychological distress using the Bonferroni corrected p ≤ 0.003. Coping is positively, significantly associated with overall psychological distress whereas the more often marijuana use is motivated by coping the higher the score for psychological distress. The magnitude of the association of motives of coping with psychological distress is of approximately 3 indicating that for any one unit change in the strength of coping motive there is almost a three-point change in scores of symptoms of anxiety. Post hoc power analyses indicate that the statistical power greater than 0.99.Results from the mediation analysis with past 90 days marijuana use as a mediator are presented in Tables 4.48a-d. There is no evidence of any indirect effects of motives of marijuana use on overall psychological distress through past 90 days marijuana use. All 95% bootstrap confidence interval for the indirect effect, based on 10,000 bootstraps, include zero. There is however evidence of a positive direct effect with overall psychological distress for motives of coping and social anxiety, and evidence of a negative direct effect for motives of celebration and conformity. The negative direct effect with celebration is no longer significant after controlling for gender, age, user group, and race/ethnicity. Results from the mediation analysis with daily number of hits as a mediator are presented in Tables 4.49a-d. There is no evidence of any indirect effects of motives of marijuana use on overall psychological distress through daily number of hits. All 95% bootstrap confidence interval for the indirect effect, based on 10,000 bootstraps, include zero. There is however evidence of a negative direct effect with psychological distress for motives of celebration and conformity, and a positive direct effect for motives of coping and social anxiety.

When controlling for age, gender, user group, and race/ethnicity, the negative direct effect between motives of marijuana use and psychological distress for motives of celebration and conformity remains as well as the positive direct effect for motives of coping and social anxiety. Gender was found to moderate the association between social anxiety motives of use and symptoms of depression when tested with and without control variables. The addition of the interaction term between the motive of social anxiety and gender explained a significant increase in variance for symptoms of depression ∆R2 = 0.012, p < 0.05 for the model without control variables, and ∆R2 = 0.014, p < 0.05 for the model with control variables. The interaction was probed by testing the conditional effect of the social anxiety motive of use on symptoms of depression for both men and women. For women, but not men, the motive of social anxiety was significantly associated with more symptoms of depression . Furthermore, the slope of the interaction term indicates that women scored higher on symptoms of depression than men at the average level of the social anxiety motive. When analyzed with and without control variables, gender was found to moderate the associations for the motives of experimentation and availability with symptoms of anxiety. The addition of the interaction term between the motive of experimentation and gender explained a significant increase in variance for symptoms of anxiety: ∆R 2 = 0.012, p < 0.05. The addition of the interaction term between the motive of availability and gender explained a significant increase in variance for symptoms of anxiety: ∆R2 = 0.01, p < 0.05. Probing of the interactions, for both motives of experimentation and availability, however yielded no significant conditional effect for neither men or women. Conditional effects for motives of experimentation are as follows: This could therefore indicate a crossover interaction where there is no overall effect of either motives of use or gender on symptoms of anxiety. In both cases, the effect of gender on symptoms of anxiety is opposite, depending on the value of motives of use.

Although gender was initially found to moderate the association between motives of boredom and symptoms of anxiety, the interaction was no longer significant following the addition of control variables. When analyzed with and without control variables, gender was found to moderate the association for the motive of social anxiety with overall psychological distress. The addition of the interaction term explained a significant increase in variance for psychological distress ∆R2 = 0.010, p < 0.05. The interaction was probed by testing the conditional effect of social anxiety for both men and women. For women, but not men, the motive of social anxiety was significantly associated to overall psychological distress . Furthermore, the slope of the interaction term indicates that women score higher on psychological distress than men at the average level of social anxiety motive. Although gender was initially found to moderate the association between motives of boredom and psychological distress, and motives of availability with psychological distress, these interactions were no longer significant following the addition of control variables. The purpose of this dissertation was to determine the associations between motives of marijuana use and symptoms of depression, symptoms of anxiety, and overall psychological distress in a sample of young adults who use marijuana for medical and/or recreational reasons. Furthermore, I sought to establish whether these associations differ by gender. As marijuana use is common and on the rise amongst young adults , and as young adulthood is a period of increased mental health vulnerabilities , it is urgent to disentangle the potential effects of marijuana use on the mental health of young adults, particularly because mental health in young adulthood is the strongest predictor of mental health in adulthood .The work presented in this dissertation advances our understanding of motives of marijuana use as well as the associations between motives of marijuana use and symptoms of depression, symptoms of anxiety, vertical grow rack and overall psychological distress in young adults who use marijuana for medical and/or recreational reasons. The purpose of the first aim was to confirm the factor structure of the motives of marijuana use questionnaire used to study motives of marijuana use in young adults of Los Angeles who use marijuana for medical and/or recreational reasons. It was hypothesized that from the fifty-one-item questionnaire, seventeen motives of marijuana use would emerge. Twelve of these motives would replicate those found by Lee et al. in their study to develop and validate a comprehensive marijuana motive questionnaire. The other five motives to be confirmed would be the medical use motives drafted by the CHAYA team. Furthermore, it was hypothesized that there would be no gender differences in the factor structure of motives of marijuana use. The best fitting and most psychometrically sound factor structure for motives of marijuana use for this sample was the originally hypothesized seventeen factor structure composed of Lee et al.’s twelve motives and the five medical motives drafted by the CHAYA team.

The final twelve non-medical items are: boredom, availability, coping, conformity, experimentation, alcohol, celebration, altered perceptions, social anxiety, relative low risk, and sleep. The final five medical motives are: pain, nausea, substitution, natural remedy, and attention. Following and extending Cooper’s Motivational Model of Use , these motives can be conceptualized as motives promoting positive experiences, motives to avoid negative experiences, and medical use motives. Motives that promote positive experiences are motives of celebration, altered perceptions, experimentation, enjoyment, alcohol, relative low risk, and, availability. Motives for avoidance of negative experiences are motives of coping, conformity, sleep, boredom, and social anxiety. Medical motives are motives of attention, substitution, natural remedy, pain, and nausea. These seventeen motives proved to be consistently well fitting, stable over time, and gender invariant when tested using both wave 1 and 2 data. Although these findings need to be replicated using a random sample, the Amended Comprehensive Marijuana Motive Questionnaire, is the first to integrate both recreational and medical motives of use. Given the high rates of overlap between recreational and medical use , the validation of such an instrument, and its stability over time and across gender, will allow for a more accurate assessment of motives of marijuana use. To date, neither gender invariance for the motives from the Comprehensive Marijuana Motive Questionnaire nor endorsement of motives by gender had been examined. Interestingly, in this sample, except for the motives of experimentation and boredom, the reporting trend was higher for women compared to men. There were also significant differences in mean scores of reported motives of use between men and women for motives of attention, celebration, enjoyment, natural remedy, nausea, pain, sleep and social anxiety. This indicates that women endorse any given motive more strongly than men do. As discussed in Chapter 2, the gap in marijuana use prevalence between men and women is closing . Additionally, in line with gender socialization and changing gender norms, whereas marijuana use was considered acceptable for men but less so for women, it is now increasingly considered acceptable behavior for women . These changes in norms and behaviors may be starting to reflect in data collected. With that said, it is important to note that these preexisting differences between genders may be a confounding factor for causal inferences and reflect the unbalanced nature of our sample due to it being nonrandom rather than a true reflection of patterns within the population. The work presented in this dissertation also advances our understanding of the associations between motives of marijuana use and mental health outcomes in a sample of young adults who use marijuana heavily for medical and/or recreational reasons. It does so by: 1) replicating previous findings for the coping motive of use whereas the more an individual endorses coping motives of use, the poorer the associated outcomes are; 2) extending knowledge with regards to indirect effects of motives on mental health outcomes through frequency of use; and 3) establishing that some of the associations between motives of use and mental health outcomes vary by gender. The second and third aims of this dissertation were to investigate the associations between motives of marijuana use and symptoms of depression, symptoms of anxiety, and overall psychological distress, and to determine whether these associations varied by gender in a sample of young adults who use marijuana for medical and/or recreational reasons in a context of legalized medical marijuana.

As a central tenet of this model is the conceptualization that use behavior motivated by different needs constitutes phenomenologically distinct behaviors, and that these distinct use behaviors may be differently associated with mental health outcomes. Data will come from the Cannabis, Health and Young Adult Study , with a sample size of 366 comprised of young adults, in Los Angeles, who use marijuana for recreational and/or medical reasons. The first aim focuses on confirming and validating the instrument used to operationalize motives of marijuana use in young adults who use marijuana for recreational and/or medical reasons and to evaluate whether this factor structure varies by gender. The second aim investigates the associations between motives of marijuana use and symptoms of depression, symptoms of anxiety, and overall psychological distress for young adults in the CHAYA study. The third aim examines whether the associations between motives of marijuana use and symptoms of depression, symptoms of anxiety, and overall psychological distress differ by gender in this sample. The Literature Review is presented in chapter 2, followed by Methods in chapter 3. Chapters 4 and 5 cover the Results and Discussion, respectively. Finally, a Conclusion and Future Directions are presented in chapter 6. Young adulthood. Emerging or young adulthood, the period between 18 and 25 years of age, is a distinct developmental phase with unique tasks and expectations. It is characterized by pervasive changes in autonomy, residence, identity, social roles, and career pursuits . Successfully negotiating the transitions of young adulthood is associated with positive trajectories of mental health well being and allows for optimal development during adulthood . Emerging adulthood is a period that involves extensive and often concurrent contextual and social role changes, increased self-direction and opportunities for exploration flexibility . In young adulthood,planting drying rack symptoms of depression and symptoms of anxiety are the most common mental health concerns . Mental health. Poor mental health in early adulthood has been shown to be a strong individual predictor of persistent and recurrent mental health problems into adulthood . Mental health processes during these critical transitional years can however be positively influenced, given opportunities to do so .

Differently said, there are as many opportunities to disrupt and negatively influence mental health and the transition from young adulthood to adulthood as there are opportunities to positively impact mental health and promote a successful transition from young adulthood to adulthood. Depression1 . As one of the most common health disorders in the United States , depression is a leading cause of disability, diminished quality of life and heightened risk for physical health problems . Depression is a serious psychopathological disorder that can have a consequential economic drain on individuals, families, society, lead to long-term suffering, risk of suicide, occupational impairment, and interpersonal impairment in peer and family relationships . Depressive disorders are characterized “by pervasive mood disturbances that involve feelings of sadness and loss of interest or pleasure in most activities in conjunction with disturbances in sleep, appetite, concentration, libido and energy” . The chronicity of the disorder can remain burdensome for a significant period . Individuals between the ages of 15 and 24 experience the highest rates of depressive disorders in the United States . The incidence of depression increases in adolescence and peaks in young adulthood . Prevalence estimates place the rate for Major Depressive Disorders in young adults at 15.4% . Between 2013 and 2015, the 12-month prevalence of a Major Depressive Episode, a period characterized by low mood and depression symptoms, among young adults ages 18 to 25 rose from 8.7% to 10.3% . Furthermore, rates of Major Depressive Episodes are almost double for females compared to males ages 18 and over .Depressed mood, one of our outcomes of interest, is defined as a single symptom or group of symptoms that involve a dysphoric effect . Between 2013 and 2015, approximately 5% of the 18-24 age group reported experiencing two or more symptoms of depression in the past 30 days . Anxiety. Anxiety disorders are often comorbid with depression and substance use disorders, and are associated with fear, nervousness, apprehension, and panic, but may also involve the cardiovascular, respiratory, gastro or nervous system, individually or in combination . Anxiety disorders are subdivided into panic disorder, social phobia, posttraumatic stress disorders, obsessive compulsive disorders, and generalized anxiety disorders .

They tend to start early in life, and affect school and work performance as well as psychological functioning, and social relationships, and are persistent and chronic . Anxiety disorders are a leading cause of disability among all psychiatric disorders . Anxiety can be as disabling as chronic somatic disorders, and is associated with reduced productivity, absenteeism from school or work, suicide, increased likelihood of school dropout, marital instability, and poor career choices , all of which are crucial to successfully transition from young adulthood to adulthood. Young adulthood is a period of heightened risk for the onset of anxiety disorders . Past year rates of anxiety amongst 18 to 29-year-old were elevated at 30.2% in 2005 . Rates of anxiety amongst young adults are as worrisome with the lifetime prevalence of any anxiety disorder in the 18 to 29 age bracket being 30.2% in 2005 , compared to a lifetime prevalence of 28.8% in the total United States population . Furthermore, past year prevalence of any anxiety disorder was higher for females than for males . In addition to being a period marked by mental health vulnerabilities , young adulthood is also a period marked by increased drug use. Mental health vulnerabilities, such as those present in young adulthood, can be exacerbated by drug use, thus potentially hindering or delaying a successful transition to adulthood. Traditional risk factors associated with onset of marijuana use in adolescence and maintenance of use in young adulthood are being male, prior or concurrent alcohol and tobacco use, poor parental relationships, and peers who use marijuana . Marijuana use is associated with poor academic achievement, lower expectations for success, family problems, and other drug use . Marijuana use is also common among young adults and is on the rise. Rates of marijuana use by adults ages 18 to 29 have steadily risen from 10.5 percent to 21.1 percent since 2005 and 19.8 percent of 18 to 25-year-old report using marijuana in the past month . Furthermore, between 1990 and 2002, rates of marijuana disorders increased from 25% to 32% amongst 18 to 29 year olds . There are gender differences in rates of marijuana use by young adults with 23.4% of males ages 18-25 reporting past month use of marijuana, and 16.2% of females of the same age group reporting past month use. Past year use was 36.0% for males and 28.4% for females ages 18-25 in 2015 .

These prevalence rates suggest that marijuana use varies across gender and that there may be inherent differences in patterns of use and associated outcomes across groups. Thus far, research that has sought to disentangle the association between marijuana use and associated outcomes has largely been conducted in a context where marijuana use is illegal. As more states move forward with either the legalization of recreational or medical marijuana use, it is important to understand what the associations between motives of marijuana use and associated outcomes might be in such a context. Prior work has demonstrated key differences between states that have moved toward legalization compared to those who have not. For instance,hydroponic rack populations in states that have moved forward with legalization had higher rates of marijuana use to begin with and perceived marijuana use as not risky . Marijuana use has also been found to be higher in states that allow medical use . In these states, past month marijuana use as well as heavy marijuana use were higher than in states without legalized medical marijuana . Legalization of medical marijuana has also been associated with increases in reported marijuana use. Using Los Angeles County as an example, past year rates of marijuana use have increased for both men and women and across all racial and ethnic groups between 2005 and 2015 . Among those who reported marijuana use in Los Angeles County, adults between the ages of 18 and 29 are those that reported the highest rates of use compared to other age groups . Other work by Pacula et al. has demonstrated a significant overlap between medical and recreational use, even in states where recreational use was not legal. In a different study, with regards to reasons of use, 89.5% of adults who report marijuana use report doing so mainly for recreational purposes, 10.5% uniquely for medical purposes, and 36.1% reported a mixed use . In sum, it appears as though legalizing marijuana, whether only medical or both medical and recreational, has brought forth changes not only in the prevalence of use but also contributes to validating the perception of marijuana as a safe drug to use. Furthermore, for some individuals who use marijuana, there does not seem to be a clear divide between medical use and recreational use. There are three hypothesized ways in which marijuana and mental health are thought to be associated, and these may not be mutually exclusive. First, through a common risk factor such as family or individual characteristics .This suggests that the relationship between marijuana use and mental health is non-causal, and explained by overlapping psychosocial risk factors . Second, via early self-medication and subsequent association with a subculture that uses drugs . Here, early use to alleviate symptoms encourages later use which can have an impact on anticonventional behaviors, increase of delinquency, and personal difficulties . Third, marijuana use can bring about its own consequences by worsening mental health through direct effects on psychological and physiological functioning or related effects on interpersonal and role functioning .

This third point is reinforced by work that demonstrates clear and consistent associations and dose-response relations between the frequency of adolescent marijuana use and all adverse young adult outcomes, which included decreased odds of high school completion, and degree attainment, increased odds of marijuana use disorder or alcohol and other use disorders, and suicide attempts . Although there is increasing recognition that marijuana use could be associated to affect based psychological susceptibility , the evidence is inconclusive. Use of marijuana among young people has been inconsistently associated with co-morbid or concurrent mental health problems in cross sectional and longitudinal studies . Some studies have demonstrated that frequent marijuana use is associated with higher levels of anxiety . Other studies, have demonstrated that marijuana may not play a causal role in the development of anxiety , or that the associations between marijuana use and mental health outcomes disappear after adjusting for confounders . The directionality of the association between marijuana use and mental health outcomes also remains unclear. Although the anxiolytic effects of marijuana have been supported in cross sectional studies , longitudinal studies have demonstrated that frequent marijuana use preceded anxiety disorders , while in others anxiety disorders preceded use . Other longitudinal studies have also demonstrated no associations between marijuana and anxiety disorders . This illustrates the importance of choice and inclusion of confounders and intervening variables in the study of marijuana use and mental health. Depressive and anxious disorders are more common in women compare to men whereas substance use disorders are more common in men than women . Two possible explanations for these trends are gender socialization and the operationalization of mental health symptoms. Gender socialization is the process whereby both men and women learn of and conform to gender specific traits . Illustrative of that are previously demonstrated gender differences in responses to stressors whereas men are more likely to externalize distress and turn to substance use and women are more likely to internalize stress and exhibit more symptoms of depression and anxiety . Instruments used to operationalize mental health and symptoms of mental health rely heavily on women gendered symptoms. As a result, men may under report or misreport their mental health distress or status because the indicators or symptoms assessed are not reflective of their experiences. Work by Martin et al. has demonstrated that men who are depressed are more likely to endorse symptoms such as anger, self-destructive behavior, risk taking, and substance use over the more, traditionally women endorsed, symptoms of sadness, loss of interest, and hopelessness. In fact, in the same study by Martin et al. , there were no differences in prevalence rates between men and women when symptoms of depression were assessed using a scale that combined both men and women specific symptoms.

Regardless of the product, the supply of recombinant proteins is challenging during emergency situations due to the simultaneous requirements for rapid manufacturing and extremely high numbers of doses. The realities we must address include: the projected demand exceeds the entire manufacturing capacity of today’s pharmaceutical industry ; there is a shortage of delivery devices and the means to fill them; there is insufficient lyophilization capacity to produce dry powder for distribution; and distribution, including transportation and vaccination itself, will be problematic on such a large scale without radical changes in the public health systems of most countries. Vaccines developed by a given country will almost certainly be distributed within that country and to its allies/neighbors first and, thereafter, to countries willing to pay for priority. One solution to the product access challenge is to decentralize the production of countermeasures, and in fact one of the advantages of plant-based manufacturing is that it decouples developing countries from their reliance on the pharmaceutical infrastructure. Hence, local production facilities could be set up based on greenhouses linked to portable clean rooms housing disposable DSP equipment. In this scenario, the availability of multiple technology platforms, including plant-based production, can only be beneficial.Several approaches can be used to manage potential IP conflicts in public health emergencies that require the rapid production of urgently needed products. Licensing of key IP to ensure freedom to operate is preferred because such agreements are cooperative rather than competitive. Likewise, cooperative agreements to jointly develop products with mutually beneficial exit points offer another avenue for productive exploitation. These arrangements allow collaborating institutions to work toward a greater good. Licensing has been practiced in past emergencies when PMP products were developed and produced using technologies owned by multiple parties. In the authors’ experience,indoor growing trays the ZMapp cocktail was subject to IP ownership by multiple parties covering the compositions, the gene expression system, manufacturing process technology/knowhow, and product end-use.

Stakeholders included the Public Health Agency of Canada’s National Microbiology Laboratory, the United States Army Medical Research Institute of Infectious Diseases , Mapp Biopharmaceutical, Icon Genetics, and Kentucky Bio-processing, among others. Kentucky Bio-processing is also involved in a more recent collaboration to develop a SARS-CoV-2 vaccine candidate, aiming to produce 1–3 million doses of the antigen, with other stakeholders invited to take on the tasks of large scale antigen conjugation to the viral delivery vector, product fill, and clinical development.25 Collaboration and pooling of resources and know how among big pharma/biopharma companies raises concerns over antitrust violations, which could lead to price fixing and other unfair business practices. With assistance from the United States Department of Justice , this hurdle has been temporarily overcome by permitting several biopharma companies to share know how around manufacturing facilities and other information that could accelerate the manufacturing of COVID-19 mAb products.26 Genentech , Amgen, AstraZeneca, Eli Lilly, GlaxoSmithKline, and AbCellera Biologics will share information about manufacturing facilities, capacity, raw materials, and supplies in order to accelerate the production of mAbs even before the products gain regulatory approval. This is driven by the realization that none of these companies can satisfy more than a small fraction of projected demands by acting alone. Under the terms imposed by the DOJ, the companies are not allowed to exchange information about manufacturing cost of goods or sales prices of their drugs, and the duration of the collaboration is limited to the current pandemic. Yet another approach is a government-led strategy in which government bodies define a time-critical national security need that can only be addressed by sequestering critical technology controlled by the private sector. In the United States, for example, the Defense Production Act was first implemented in 1950 but has been reauthorized more than 50 times since then . Similar national security directives exist in Canada and the EU. In the United States, the Defense Production Act gives the executive branch substantial powers, allowing the president, largely through executive order, to direct private companies to prioritize orders from the federal government.

The president is also empowered to “allocate materials, services, and facilities” for national defense purposes. The Defense Production Act has been implemented during the COVID-19 crisis to accelerate manufacturing and the provision of medical devices and personal protective equipment, as well as drug intermediates. Therefore, a two-tiered mechanism exists to create FTO and secure critical supplies: the first and more preferable involving cooperative licensing/cross-licensing agreements and manufacturing alliances, and alternatively , a second mechanism involving legislative directives.Many companies have modified their production processes to manufacture urgently-required products in response to COVID- 19, including distillers and perfume makers switching to sanitizing gels, textiles companies making medical gowns and face masks, and electronics companies making respirators.27 Although this involves some challenges, such as production safety and quality requirements, it is far easier than the production of APIs, where the strict regulations discussed earlier in this article must be followed. The development of a mammalian cell line achieving titers in the 5 g L−1 range often takes 10–12 months or at least 5–6 months during a pandemic . These titers can often be achieved for mAbs due to the similar properties of different mAb products and the standardized DSP unit operations , but the titers of other biologics are often lower due to product toxicity or the need for bespoke purification strategies. Even if developmental obstacles are overcome, pharmaceutical companies may not be able to switch rapidly to new products because existing capacity is devoted to the manufacture of other important bio-pharmaceuticals. The capacity of mammalian cell culture facilities currently exceeds market demand by ~30% . Furthermore, contract manufacturing organizations , which can respond most quickly to a demand for new products due to their flexible business model, control only ~19% of that capacity. From our experience, this CMO capacity is often booked in advance for several months if not years, and little is available for short-term campaigns. Furthermore, even if capacity is available, the staff and consumables must be available too. Finally, there is a substantial imbalance in the global distribution of mammalian cell culture capacity, favoring North America and Europe. This concentration is risky from a global response perspective because these regions were the most severely affected during the early and middle stages of the COVID-19 pandemic, and it is, therefore, possible that this capacity would become unusable following the outbreak of a more destructive virus.

Patents covering several technologies related to transient expression in plants will end during or shortly after 2020, facilitating the broader commercial adoption of the technology. This could accelerate the development of new PMP products in a pandemic situation . However, PMP production capacity is currently limited. There are less than five large scale PMP facilities in operation, and we estimate that these facilities could manufacture ~2,200 kg of product per year, assuming a combined annual biomass output of ~1,100 tons as well as similar recombinant protein production and DSP losses as for mammalian cells. Therefore, plant-based production certainly does currently not meet the anticipated demand for pandemic countermeasures. We have estimated a global demand of 500–5,200 tons per year for mAbs, depending on the dose, but only ~259 tons per year can be produced by using the current global capacity provided by mammalian cell bioreactors and plant-based systems currently represent less than 1% of the global production capacity of mammalian cell bioreactors. Furthermore, the number of plant molecular farming companies decreased from 37 to 23 between 2005 and 2020, including many large industry players that would be most able to fund further technology development . Nevertheless, the current plant molecular farming landscape has three advantages in terms of a global first-line response compared to mammalian cells. First, almost two thirds of global production capacity is held by CMOs or hybrid companies ,mobile vertical grow racks which can make their facilities available for production campaigns on short notice, as shown by their rapid response to COVID-19 allowing most to produce initial product batches by March 2020. In contrast, only ~20% of fermentation facilities are operated by CMOs . Second, despite the small number of plant molecular farming facilities, they are distributed around the globe with sites in the United States, Canada, United Kingdom, Germany, Japan, Korea, and South Africa, with more planned or under construction in Brazil and China . Finally, transient expression in plants is much faster than any other eukaryotic system with a comparable production scale, moving from gene to product within 20 days and allowing the production of up to 7,000 kg biomass per batch with product accumulation of up to 2 g kg−1 . Even if the time required for protein production in mammalian cells can be reduced to 6 months as recently proposed , Medicago has shown that transient expression in plants can achieve the same goals in less than 3 months . Therefore, the production of vaccines, therapeutics, and diagnostics in plants has the potential to function as a first line of defense against pandemics. Given the limited number and size of plant molecular farming facilities, we believe that the substantial investments currently being allocated to the building of bio-pharmaceutical production capacity should be shared with PMP production sites, allowing this technology to be developed as another strategy to improve our response to future pandemics.In the past decade, the massive scale-up of insecticide treated bed nets and indoor residual spraying , together with the use of artemisinin-based combination treatments, have led to major changes in malaria epidemiology and vector biology. Overall malaria prevalence and incidence have been greatly reduced worldwide. But the reductions in malaria have not been achieved uniformly; some sites have experienced continued reductions in both clinical malaria and overall parasite prevalence, while other sites showed stability or resurgence in malaria despite high coverage of ITNs and IRS.

More importantly, extensive use of ITNs and IRS has created intensive selection pressures for malaria vector insecticide resistance as well as for potential outdoor transmission, which appears to be limiting the success of ITNs and IRS. For example, in Africa, where malaria is most prevalent and pyrethroid-impregnated ITNs have been used for more than a decade, there is ample evidence of the emergence and spread of pyrethroid resistance in Anopheles gambiae s.s., the major African malaria vector, as well as in An. arabiensis and An. funestus s.l.. Both the prevalence of An. gambiae s.s. resistance to pyrethroids and DDT and the frequency of knock-down resistance have reached alarming levels throughout Africa from 2010–2012. Unfortunately, pyrethroids are the only class of insecticides that the World Health Organization recommends for the treatment of ITNs . Furthermore, a number of recent studies have documented a shift in the biting behavior of An. gambiae s.s. and An. funestus, from biting exclusively indoors at night to biting both indoors and outdoors during early evening and morning hours when people are active but not protected by IRS or ITNs, or to biting indoors but resting outdoors. Apart from these intraspecific changes in biting behavior, shifts in vector species composition, i.e., from the previously predominant indoor-biting An. gambiae s.s. to the concurrently predominant species An. arabiensis, which prefers to bite and rest outdoors in some parts of Africa, can also increase outdoor transmission. Because IRS and ITNs have little impact on outdoor-resting and outdoor and early-biting vectors, outdoor transmission represents one of the most important challenges in malaria control. New interventions are urgently needed to augment current public health measures and reduce outdoor transmission. Larval control has historically been very successful and is widely used for mosquito control in many parts of the developed world, but is not commonly used in Africa. Field evaluation of anopheline mosquitoes in Africa found that larviciding was effective in killing anopheline larvae and reducing adult malaria vector abundance in various sites. Microbial larvicides are effective in controlling malaria vectors, and they can be used on a large scale in combination with ongoing ITN and IRS programs. However, conventional larvicide formulations are associated with high material and operational costs due to the need for frequent habitat re-treatment, i.e., weekly re-treatment, as well as logistical issues in the field. Recently, an improved slow-release larvicide formulation was field-tested for controlling Anopheles mosquitoes, yielding an effective duration of approximately 4 weeks.

Some tags may be approved in certain circumstances , but their immunogenicity may depend on the context of the fusion protein. The substantial toolkit available for rapid plant biomass processing and the adaptation of even large-scale plant-based production processes to new protein products ensure that plants can be used to respond to pandemic diseases with at least an equivalent development time and, in most cases, a much shorter one than conventional cell-based platforms. Although genetic vaccines for SARS-CoV-2 have been produced quickly , they have never been manufactured at the scale needed to address a pandemic and their stability during transport and deployment to developing world regions remains to be shown.Regulatory oversight is a major and time-consuming component of any drug development program, and regulatory agencies have needed to revise internal and external procedures in order to adapt normal schedules for the rapid decision-making necessary during emergency situations. Just as important as rapid methods to express, prototype, optimize, produce, and scale new products are the streamlining of regulatory procedures to maximize the technical advantages offered by the speed and flexibility of plants and other high-performance manufacturing systems. Guidelines issued by regulatory agencies for the development of new products, or the repurposing of existing products for new indications, include criteria for product manufacturing and characterization, containment and mitigation of environmental risks, stage-wise safety determination, clinical demonstration of safety and efficacy, and various mechanisms for product licensure or approval to deploy the products and achieve the desired public health benefit. Regardless of which manufacturing platform is employed, the complexity of product development requires that continuous scrutiny is applied from preclinical research to drug approval and post-market surveillance,cannabis vertical farming thus ensuring that the public does not incur an undue safety risk and that products ultimately reaching the market consistently conform to their label claims.

These goals are common to regulatory agencies worldwide, and higher convergence exists in regions that have adopted the harmonization of standards as defined by the International Council for Harmonization ,2 in key product areas including quality, safety, and efficacy.Both the United States and the EU have stringent pharmaceutical product quality and clinical development requirements, as well as regulatory mechanisms to ensure product quality and public safety. Differences and similarities between regional systems have been discussed elsewhere and are only summarized here. Stated simply, the United States, EU, and other jurisdictions follow generally a two-stage regulatory process, comprising clinical research authorization and monitoring and result’s review and marketing approval. The first stage involves the initiation of clinical research via submission of an Investigational New Drug application in the United States or its analogous Clinical Trial Application in Europe. At the preclinicalclinical translational interphase of product development, a sponsor must formally inform a regulatory agency of its intention to develop a new product and the methods and endpoints it will use to assess clinical safety and preliminary pharmacologic activity . Because the EU is a collective of independent Member States, the CTA can be submitted to a country-specific regulatory agency that will oversee development of the new product. The regulatory systems of the EU and the United States both allow pre-submission consultation on the proposed development programs via discussions with regulatory agencies or expert national bodies. These are known as pre-IND meetings in the United States and Investigational Medicinal Product Dossier 3 discussions in the EU. These meetings serve to guide the structure of the clinical programs and can substantially reduce the risk of regulatory delays as the programs begin. PIND meetings are common albeit not required, whereas IMPD discussions are often necessary prior to CTA submission.

At intermediate stages of clinical development , pauses for regulatory review must be added between clinical study phases. Such End of Phase review times may range from one to several months depending on the technology and disease indication. In advanced stages of product development after pivotal, placebo-controlled randomized Phase III studies are complete, drug approval requests that typically require extensive time for review and decision-making on the part of the regulatory agencies. In the United States, the Food and Drug Administration controls the centralized marketing approval/authorization/ licensing of a new product, a process that requires in-depth review and acceptance of a New Drug Application for chemical entities, or a Biologics License Application for biologics, the latter including PMP proteins. The Committee for Medicinal Products for Human Use , part of the European Medicines Agency , has responsibilities similar to those of the FDA and plays a key role in the provision of scientific advice, evaluation of medicines at the national level for conformance with harmonized positions across the EU, and the centralized approval of new products for market entry in all Member States.The statute-conformance review procedures practiced by the regulatory agencies require considerable time because the laws were established to focus on patient safety, product quality, verification of efficacy, and truth in labeling. The median times required by the FDA, EMA, and Health Canada for full review of NDA applications were reported to be 322, 366, and 352 days, respectively . Collectively, typical interactions with regulatory agencies will add more than 1 year to a drug development program. Although these regulatory timelines are the status quo during normal times, they are clearly incongruous with the needs for rapid review, approval, and deployment of new products in emergency use scenarios, such as emerging pandemics.

Plant-made intermediates, including reagents for diagnostics, antigens for vaccines, and bio-active proteins for prophylactic and therapeutic medical interventions, as well as the final products containing them, are subject to the same regulatory oversight and marketing approval pathways as other pharmaceutical products. However, the manufacturing environment as well as the peculiarities of the plant-made active pharmaceutical ingredient can affect the nature and extent of requirements for compliance with various statutes, which in turn will influence the speed of development and approval. In general, the more contained the manufacturing process and the higher the quality and safety of the API, the easier it has been to move products along the development pipeline. Guidance documents on quality requirements for plant-made biomedical products exist and have provided a framework for development and marketing approval . Upstream processes that use whole plants grown indoors under controlled conditions, including plant cell culture methods, followed by controlled and contained downstream purification, have fared best under regulatory scrutiny. This is especially true for processes that use non-food plants such as Nicotiana species as expression hosts. The backlash over the Prodigene incident of 2002 in the United States has refocused subsequent development efforts on contained environments . In the United States, field-based production is possible and even practiced, but such processes require additional permits and scrutiny by the United States Department of Agriculture . In May 2020, to encourage innovation and reduce the regulatory burden on the industry, the USDA’s Agricultural Plant Health Inspection Service revised legislation covering the interstate movement or release of genetically modified organisms into the environment in an effort to regulate such practices with higher precision [SECURE Rule revision of 7 Code of Federal Regulations 340].In contrast, the production of PMPs using GMOs or transient expression in the field comes under heavy regulatory scrutiny in the EU, and several statutes have been developed to minimize environmental, food, and public risk. Many of these regulations focus on the use of food species as hosts. The major perceived risks of open-field cultivation are the contamination of the food/feed chain,cannabis drying rack and gene transfer between GM and non-GM plants. This is true today even though containment and mitigation technologies have evolved substantially since those statutes were first conceived, with the advent and implementation of transient and selective expression methods; new plant breeding technologies; use of non-food species; and physical, spatial, and temporal confinement . The United States and the EU differ in their philosophy and practice for the regulation of PMP products. In the United States, regulatory scrutiny is at the product level, with less focus on how the product is manufactured. In the EU, much more focus is placed on assessing how well a manufacturing process conforms to existing statutes. Therefore, in the United States, PMP products and reagents are regulated under pre-existing sections of the United States CFR, principally under various parts of Title 21 , which also apply to conventionally sourced products. These include current good manufacturing practice covered by 21 CFR Parts 210 and 211, good laboratory practice toxicology , and a collection of good clinical practice requirements specified by the ICH and accepted by the FDA . In the United States, upstream plant cultivation in containment can be practiced using qualified methods to ensure consistency of vector, raw materials, and cultivation procedures and/or, depending on the product, under good agricultural and collection practices . For PMP products, cGMP requirements do not come into play until the biomass is disrupted in a fluid vehicle to create a process stream. All process operations from that point forward, from crude hydrolysate to bulk drug substance and final drug product, are guided by 21 CFR 210/211 .

In Europe, bio-pharmaceuticals regardless of manufacturing platform are regulated by the EMA, and the Medicines and Healthcare products Regulatory Agency in the United Kingdom. Pharmaceuticals from GM plants must adhere to the same regulations as all other biotechnology-derived drugs. These guidelines are largely specified by the European Commission in Directive 2001/83/EC and Regulation No 726/2004. However, upstream production in plants must also comply with additional statutes. Cultivation of GM plants in the field constitutes an environmental release and has been regulated by the EC under Directive 2001/18/EC and 1829/2003/EC if the crop can be used as food/feed . The production of PMPs using whole plants in greenhouses or cell cultures in bioreactors is regulated by the “Contained Use” Directive 2009/41/EC, which are far less stringent than an environmental release and do not necessitate a fully-fledged environmental risk assessment. Essentially, the manufacturing site is licensed for contained use and production proceeds in a similar manner as a conventional facility using microbial or mammalian cells as the production platform. With respect to GMP compliance, the major differentiator between the regulation of PMP products and the same or similar products manufactured using other platforms is the upstream production process. This is because many of the DSP techniques are product-dependent and, therefore, similar regardless of the platform, including most of the DSP equipment, with which regulatory agencies are already familiar. Of course, the APIs themselves must be fully characterized and shown to meet designated criteria in their specification, but this applies to all products regardless of source.During a health emergency, such as the COVID-19 pandemic, regulatory agencies worldwide have re-assessed guidelines and restructured their requirements to enable the accelerated review of clinical study proposals, to facilitate clinical studies of safety and efficacy, and to expedite the manufacturing and deployment of re-purposed approved drugs as well as novel products . These revised regulatory procedures could be implemented again in future emergency situations. It is also possible that some of the streamlined procedures that can expedite product development and regulatory review and approval will remain in place even in the absence of a health emergency, permanently eliminating certain redundancies and bureaucratic requirements. Changes in the United States and European regulatory processes are highlighted, with a cautionary note that these modified procedures are subject to constant review and revision to reflect an evolving public health situation.In the spring of 2020, the FDA established a special emergency program for candidate diagnostics, vaccines, and therapies for SARS-CoV-2 and COVID-19. The Coronavirus Treatment Acceleration Program 5 aims to utilize every available method to move new treatments to patients in need as quickly as possible, while simultaneously assessing the safety and efficacy of new modes of intervention. As of September 2020, CTAP was overseeing more than 300 active clinical trials for new treatments and was reviewing nearly 600 preclinical-stage programs for new medical interventions. Responding to pressure for procedural streamlining and rapid response, the FDA refocused staff priorities, modified its guidelines to fit emergency situations, and achieved a remarkable set of benchmarks . In comparison to the review and response timelines described in the previous section, the FDA’s emergency response structure within CTAP is exemplary and, as noted, these changes have successfully enabled the rapid evaluation of hundreds of new diagnostics and candidate vaccine and therapeutic products.

The rise in substance use related ED visits was driven by sedatives, stimulants, and hallucinogens, with alcohol and other substance use-related visits being relatively stable .There was a parallel increase in mental health-related visits, with these visits making up 2.34% of total ED visits in 2013 and 3.88% in 2018, representing a 66% relative increase. Among substance-use related visits, the 25-44 age group made up 44.58% of visits, as compared to 35.49% of the non-substance related group . There was also a male predominance among substance use-related visits: males accounted for 63.38% of visits in the substance group vs 41.74% in the reference group . While the West geographic area accounted for only 21.34% of all ED visits, it made up 29.67% of substance use-related visits. In addition, substance use-related visits were much more likely to happen during the night shift , with 27.07% of all substance use-related visits taking place then compared to 14.81% in the reference group . Mental health issues were more prevalent in the substance use group compared to the reference group, present in 14.48% vs 2.99%, respectively. With regard to the primary outcomes, patients associated with substance use-related visits were more likely to undergo any diagnostic study and toxicology screening ; however, they were less likely to have imaging studies . There were no significant differences in the use of medications or procedures between the substance use and reference groups, with the differences in means being 0.08 and 0.04 , respectively . Substance use-related visits were associated with higher odds of admission or transfer to another facility and higher odds of receiving a mental health consult [aOR 5.70; 95% CI: 4.47-7.28; P <0.0001. With regard to stratified analyses those patients with mental health disorders were more likely to have imaging studies,vertical farming system and this reached statistical significance for interaction .

For substance use-related visits without the concurrent presence of a mental health disorder, the aOR of undergoing any imaging study was 0.65 , and for substance use-related visits with concurrent mental health disorder, the aOR of undergoing any imaging study was 1.44 . All substance use-related ED visits were more likely to undergo toxicology screening, but those without concurrent mental health disorders were even more likely to receive screening, with aOR of 11.47 . The presence of a mental health disorder did not have an impact on the relationship between undergoing any diagnostic study in ED and substance use .Consistent with previously published work, our study shows that sedative-, stimulant-, and hallucinogen- related ED visits continue to increase rapidly compared to alcohol and other substances of abuse.Substance use-related ED visits are more likely to result in diagnostic investigations overall, admission or transfer to another facility, and mental health consultations. Conversely, they are less likely to result in imaging studies. While the higher rate of admission/transfer and mental health consultations for substance use- related ED visits has been reported previously,to our knowledge the use of diagnostic services has not yet been assessed at the national level. Among the common substances of abuse, the rapid increase in stimulant-related ED visits in recent years is remarkable; in 2018, the percentage of stimulant-related visits matched that of sedative-related visits , representing approximately 0.7% of total ED visits. This is consistent with other study findings that have reported a rise in prevalence of stimulant use across all age groups from 2010–2014, with adults between 20-64 years the most affected.Our study also showed that the rise in stimulant-related visits was more pronounced in the 18-44 age group , compared to the > 45 years age group . The most frequently cited motivation for stimulant use among adults was performance enhancement,which supports the need to improve public education for young adults on the addictive potential of stimulants and restricting prescriptions to appropriate clinical indications only. Regarding the use of diagnostic services in the ED for substance use-related visits, research has been relatively sparse. Our study showed that substance use-related visits are more likely to receive diagnostic services overall and toxicology screening.

Some studies have called into question the routine practice of ordering urine drug screens for substance-related visits and laboratory studies in general for mental health-related visits, as they have rarely led to changes in management.The American Psychiatric Association and the American College of Emergency Physicians both support targeted diagnostic investigations for patients presenting with acute psychiatric symptoms, instead of routine testing.However, drug testing is often required as part of initial assessment to enter treatment facilities, regardless of medical indication or emergency healthcare team preferences.Although most of the studies on this topic focused on mental health-related ED visits, the often-overlapping presentations of substance- and mental health-related visits argue for standardization of practices to diagnostic services. In terms of the use of imaging studies specifically, both ACEP and the APA support individual assessment of risk factors to guide brain imaging in the ED for mental health-related visits, due to low yield of routine imaging.In contrast to our finding of substance use-related visits being associated with less use of imaging studies, previous work has shown a rising trend in the use of CTalong with the rise of opioid-related visits.However, that study did not assess the use of CT in relation to a non-substance use reference group and did not include other imaging modalities. The lower rate of utilization of imaging studies could be explained by the possibility that imaging was not needed for management or disposition after completion of laboratory screening in substance use-related visits. In addition, since substance use-related visits occurred disproportionately after hours, imaging might not be readily available after hours in smaller centers. Visiting hours were adjusted for as a potential confounder; so the latter explanation is considered less likely. Notably, the presence of a mental health disorder made it more likely for patients with a substance use diagnosis to undergo imaging studies. It is well documented that patients with serious mental health disorders have higher mortality rates than those without, attributable to both injuries and chronic diseases.It is, therefore, possible that additional imaging studies were needed because of increased medical complexity.

Furthermore, the presence of SUDs was associated with significantly increased rates of mental health consultations in the ED, which in turn have been shown to be associated with increased ED length of stay.These findings support the fact that healthcare is more costly for patients with mental health or SUDs, highlighting the need to address physical and mental health in an integrated fashion.In fact, multiple studies have shown the effectiveness of case coordination and combined medical and behavioral health clinics to help decrease substance use- or mental health-related ED visits.Our study results should be interpreted in the context of several limitations. First, only associations and no causal relationships could be made due to the cross-sectional nature of the study. Second, it is possible that some substance use related ED visits represented repeated visits over time, meaning the statistical methods used in the analysis could yield biased results away from the null. As the NHAMCS is an event-level database, it is not possible to ascertain this as data linkage could not be performed. Third, the study results relied heavily on ED reporting and ICD codes, which could be subject to inaccuracies and bias the results toward the null, although steps were taken to mitigate this through staff training. Fourth, due to limitations in sample size, detailed analysis on the specific types of diagnostic services or imaging modalities, with the exception of toxicology screening, were not done. Further studies incorporating data from previous years would be needed to obtain more granular data. Fifth, due to concerns about multiplicity, resource utilization pattern with respect to the subgroups of substances analyzed can only be used for hypothesis-generating purposes. Furthermore, improved screening strategies for substance use in the ED could have contributed to the increase in visits,indoor grow facility following the emergence of evidence demonstrating improved outcomes associated with ED initiated interventions, biasing the results away from the null.Finally, this study did not include information on ED-initiated substance use treatment or outpatient referral pattern over time, making it difficult to comment on specific strategies to help improve care for patients with SUD in the ED. In summary, many of the limitations arose from the design of the survey itself and were difficult to mitigate at the data analysis stage. Marijuana and tobacco co-use is common among young adults . On average, young adults perceive marijuana as less harmful to health, less addictive, and more socially acceptable than tobacco , and are less ready to quit marijuana than cigarettes . While a few studies have found that marijuana users were less likely to quit smoking than non-users , others have found no significant differences in smoking outcomes between marijuana co-users and non-marijuana users . Previous research focused on general adult populations, collected data in-person, and was conducted before the advent of widespread changes in marijuana legalization and social norms . It is unclear whether and to what extent marijuana use interferes with smoking cessation and related outcomes among young adults in an era of rapidly shifting laws and attitudes regarding marijuana. It is particularly important to study young adults in this context, because they are less likely to seek smoking cessation treatment and are more likely to use marijuana than are older adults. Moreover, due to the stigma around marijuana use and its illegal status in many states, collecting data online may be a useful strategy to improve accuracy of self-reported marijuana use and to further examine its relationship with smoking cessation. Lastly, marijuana use has become increasingly accepted in society and increasingly common among cigarette smokers .

Given the widespread availability and acceptability of marijuana among young adults, current tobacco smokers may experience more difficulty quitting than those surveyed in previous decades. As such, this study uses data from a randomized controlled trial of the Tobacco Status Project , a smoking cessation intervention for young adults delivered on Facebook, to examine differences in smoking outcomes between marijuana users and non-marijuana users. Participants were young adult smokers who reported smoking 100+ cigarettes in their lifetime, currently smoking 1+ cigarettes per day 3+ days per week and using Facebook 4+ days per week, and who were English literate. Recruitment consisted of a paid Facebook ad campaign from October 2014 to July 2015 . Clicking on an ad redirected participants to a confidential eligibility survey. Eligible, consented participants were randomly assigned to one of two conditions: 1) the Tobacco Status Project intervention, or 2) referral to the National Cancer Institute’s Smoke free.gov website . Participants in both conditions were included in all analyses except treatment engagement and perceptions . TSP included assignment to a private Facebook group tailored to participants’ readiness to quit smoking, daily Facebook contact with study staff, weekly live counseling sessions, and six additional Cognitive Behavioral Therapy counseling sessions for those ready to quit. Study staff posted once a day for 90 days and participants were asked to comment on the posts. Post content varied by readiness to quit smoking and included strategies informed by the Transtheoretical Model and the U.S. Clinical Practice Guidelines for smoking cessation . Participants were emailed follow-up surveys at 3, 6, and 12 months after the study began. This research was approved by the University of California, San Francisco Institutional Review Board. Nicotine dependence was assessed using the 6-item Fagerström Test of Cigarette Dependence , scored on a scale of 0 to 10, from low to heavy dependence. Daily smoking at baseline was measured with the item, “On average, how many days in a week do you smoke cigarettes ?”. Responses were recoded into daily smoking or non-daily smoking . The Smoking History Questionnaire assessed early smoking as well as usual number of cigarettes smoked per day. The Stages of Change Questionnaire was used to categorize participants into one of three stages of change based on their readiness to quit smoking at baseline. Alcohol is another substance commonly used by young adults, and use of alcohol can co-occur with tobacco and/or marijuana . Hence, we measured alcohol use for possible inclusion as a covariate in the models, using the item, “Have you consumed alcohol in the past 30 days?” .Current marijuana use was measured at each time point using the Staging Health Risk Assessment , based on the Transtheoretical Model stages of change and the Healthy People 2020 goals for the United States .

That trial is a measure of executive function requiring inhibition of a prepotent interfering behavioral response. This effect could not be attributed to differences in HIV-related clinical factors. There were no differences between HIV+ women and men with and without depression in tests of psychomotor speed/attention and motor skills. The domain that was most vulnerable among HIV+ depressed women was a measure of executive function that relies on select areas of the cognitive control network , in particular the rostral anterior cingulate cortex and the dorsolateral PFC which are invoked during inhibitory tasks such as Stroop interference42,43. Neurobiological features of depression contributing to cognition include glucose metabolism in the PFC44 and functional alterations of the ACC, during cognitive task performance. An eventrelated functional magnetic resonance imaging study involving an in-scanner version of the Stroop revealed hyperactivity in the rostral ACC and left dorsolateral PFC in patients with unipolar depression versus healthy participants, and those alterations in brain function correlated with Stroop infererence. This pattern of regional hyperactivity can be induced by lowering serotonin levels with tryptophan depletion, and can be reversed with the antidepressant escitalopram. Although causality cannot be determined in the present study, other work suggests that decreased levels of serotonin alter ACC and PFC function to influence performance on inhibitory tasks. These functional brain alterations partially overlap with the HIV-associated alterations in brain circuitry. Multiple neurobiological features of HIV infection,drain trays for plants including chronic neuroinflammation, reduction of trophic factors, and alterations in dopamine and other neurotransmitters can contribute to depression in HIV.

Mechanistically, neuroinflammation and impaired neurogenesis are key features of depression and HIV and are contributors to NCI. Similarly, hypothalamic-pituitaryadrenal axis function alterations can contribute to NCI in depression and HIV. In our previous publication using this same sample, we demonstrated that although HIV+ women show cognitive vulnerabilities in several domains versus HIV+ men , they show no vulnerability in Stroop. The current data show that it is only in the context of depression where they show greater vulnerability on Stroop colorword [interference], a task reliant on the CCN compared to depressed HIV+ men as well as depressed HIV- men and women. Biological explanations for this selective vulnerability may include females greater sensitivity to the negative effects of inflammation-induced depressed mood. Inducing inflammation via endotoxin exposure leads to increased depressed mood and neural activity in the ACC in healthy females but not males. Converging evidence from preclinical models also demonstrate that the adult female brain has more microglia with an activated phenotype versus the male brain. Microglia play a critical role in maintaining homeostasis in the presence of a number of factors including infection or injury. Sexual dimorphisms in genetic variations in the dopaminergic system may also contribute to a female-specific vulnerability in cognitive control. The catechol-O-methyltransferase gene and the dopamine receptor D2 gene interact with sex on cognitive control behavioral measures. Transcriptional signatures in brain regions in the CCN in MDD also differ by sex. Lastly, sex differences in the HPA, and/or immune alterations may contribute to these findings. For example, cortisol levels negatively relate to executive function in HIV- women but not men. The tighter coupling of depression and HIV in women compared to men suggests a tighter coupling of these neural manifestations of HIV and depression in women than men, and consequently might explain the greater cognitive effect of these comorbidities in women than men. There are also non-biological explanations for the decreased executive function among HIV + depressed women versus all other groups. Depressed HIV+ men could have had greater access and availability to mental health services versus depressed HIV+ women, and this treatment may have minimized the cognitive sequelae of depression in men.

That explanation does not, however, account for the specificity of findings to Stroop color-word [interference] but not other tests. Second, depression among female HIV positive individuals may have the greatest adverse effects on cognitively demanding tasks regardless of domain. Of the tasks administered, Stroop color-word [interference] was the most difficult. Third, we used the same CES-D cutoff for men and women though some argue in favor of a lower cut-off for men than women. Whether a different pattern of findings would emerge with sex-specific cutoffs is unknown. Lastly, performance on Stroop color-word [interference] and possibly other outcomes may have been influenced by unusual patterns within the HIV- depressed men who showed lower performance than HIV+ depressed men in several tests . Even if these patterns did not lead to emergence of any other three-way HIV-serostatus X Sex X Depression interactions, they may have led to the lack of two-way HIV-serostatus X Depression interactions. HIV- depressed men were more likely than HIV+ depressed men to be heavy alcohol users, smoke, and use cannabis and cocaine/crack, but those factors did not account for the three-way interaction on Stroop color-word [interference]. HIV+ depressed men may also have had better engagement in care due to their HIV status versus HIV- depressed men. We also found that elevated depression regardless of HIV status or biological sex was negatively associated with psychomotor speed/attention, executive function, and motor skills. Findings are consistent with studies in HIV- individuals demonstrating that primary NCI among depressed individuals are in psychomotor speed/attention and executive function; sex differences were not examined. In HIV, similar patterns are seen among mixed samples of HIV+ and HIVindividuals . Overall, MACS men compared to WIHS women were more likely to report ever being depressed. Furthermore, HIV serostatus was associated with higher depression rates in women while in men depression rates did not differ by HIV-serostatus. This finding seems unexpected because the depression rate is twice as high in women than men. Similarly in the few studies of sex differences in depression among PWH, HIV+ women have higher depression rates and more severe depressive symptoms versus HIV+ men.

In most studies, the sample sizes were smaller than in the present study so this study might provide more reliable estimates. However, men in the present study, had more opportunities to develop depression because they were followed for a longer period of time versus women . When restricting our analysis to crack/ cocaine non-users, men still had higher levels of depression versus women despite having fewer visits than women. A likely explanation for the higher frequency of depression in MACS men includes primarily sexual minority men whereas WIHS includes primarily heterosexual women. In both sexes, the prevalence of depression is higher among sexual minorities versus heterosexuals. The high prevalence of depression in sexual minorities is associated with stress exposure resulting from stigma and lack of social support. In the MACS, men are predominately Black and all are gay or bisexual. Notably, even though depression was more frequent among HIV+ men, the increased frequency among HIV+ men did not increase NCI on any domain versus either depressed HIV+ women or HIV- men. Moreover, accounting for HIV RNA which was higher in depressed HIV+ men than non-depressed HIV+ men did not not account for the pattern of NCI correlates. This study has a number of limitations including the limited cognitive battery , unmeasured confounders ,4 x 8 grow tray and use of a self-report measure of depression. The preferred diagnostic interview to assess depression was unavailable in both cohorts. Additionally, we did not assess other diagnostic comorbidities commonly cooccuring with depression including anxiety and substance use disorders . Finally, while there were differences in the data collection time frame in the two cohorts, it is unlikely that these differences led to a bias towards or against visits completed while a participant was depressed as depressive symptom trajectories are relatively stable in individuals. Despite limitations, few studies have sufficient statistical power to examine whether the depression-NCI associations differ by HIV-serostatus and sex. To our knowledge, this is the largest study in PWH examining sex and depressive symptoms as contributors to NCI in PWH. The importance of this topic is evident in the high frequency of depression and in the finding that overall depression is associated with impairment in psychomotor speed, executive function, and motor function. Focusing on sex differences is important because for women, the association between depression and executive function was particularly strong, increasing the odds of impairment 5-fold. This pattern was the case even though depression rates were higher in men regardless of HIV-serostatus. Findings indicate that depression is an important prevention and treatment target and that improved access to psychiatric and psychological services may help minimize the influence of this comorbidity on NCI. More high school students smoked little cigars and cigarillos than cigarettes in 33 US states in 2015. Concern is growing about co-use of tobacco and marijuana among youth, particularly among African-American youth.In a 2015 survey, for example, one in four Florida high school students reported ever using cigars or cigar wraps to smoke marijuana. One colloquial term for this is a “blunt.” Adolescent cigar smokers were almost ten times more likely than adults to report that their usual brand offers a flavored variety. Since the US ban on flavored cigarettes , the number of unique LCC flavors more than doubled. Anticipating further regulation, the industry increasingly markets flavored LCCs with sensory and other descriptors that are not recognizable tastes.For example, after New York City prohibited the sale of flavored cigars, blueberry and strawberry cigarillos were marketed as blue and pink, but contained the same flavor ingredients as prohibited products. Among the proliferation of such “concept” flavors , anecdotal evidence suggests that references to marijuana are evident. Cigar marketing includes the colloquial term, “blunt”, in brand names and product labels . Other marketing techniques imply that some brands of cigarillos make it easier for users to replace the contents with marijuana.For example, the image of a zipper on the packaging for Splitarillos and claims about “EZ roll” suggest that products are easily manipulated for making blunts.

We use the term “marijuana co-marketing” to refer to such tobacco industry marketing that may promote dual use of tobacco and marijuana and concurrent use . In addition to flavoring, low prices for LCCs also likely increase their appeal to youth. In California, 74% of licensed tobacco retailers sold cigarillos for less than $1 in 2013. Before Boston regulated cigar pack size and price in 2012, the median price for a popular brand of grape-flavored cigars was $1.19. In 2012, 78% of US tobacco retailers sold single cigarillos, which suggests that the problem of cheap, combustible tobacco is widespread. Additionally, the magnitude of the problem is worse in some neighborhoods than others. Popular brands of flavored cigarillos cost significantly less in Washington DC block groups with a higher proportion of African Americans and in California census tracts with lower median household income.For the first time, this study examines neighborhood variation in the maximum pack size of cigarillos priced at $1 or less and assesses the prevalence of marijuana co-marketing in the retail environment for tobacco. School neighborhoods are the focus of this research because 78% of USA teens attend school within walking distance of a tobacco retailer. In addition, emerging research suggests that adolescents’ exposure to retail marketing is associated with greater curiosity about smoking cigars and higher odds of ever smoking blunts. The Table summarizes descriptive statistics for store type and for schools as well as mixed models with these covariates. Nearly half of the LCC retailers near schools were convenience stores with or without gasoline/petrol. Overall, 61.5% of LCC retailers near schools contained at least one type of marijuana co-marketing: 53.2% sold blunt wraps, 27.2% sold cigarillos marketed as blunts and 26.0% sold blunt wraps, blunts or other LCC with a marijuana related “concept” flavor. After adjusting for store type, marijuana co-marketing was more prevalent in school neighborhoods with lower median household income and with a higher proportion of school-age youth. Nearly all LCC retailers sold cigarillos for $1 or less. The largest pack size at that price contained 2 cigarillos on average . The largest packs priced at $1 or less were singles in 10.9% of stores, 2-packs in 46.8%, 3-packs in 19.2%, 4-packs in 5.5%, and 5 or 6 cigarillos in 5.5%. After adjusting for store type, a significantly larger pack size of cigarillos was priced at $1 or less in school neighborhoods with lower median household income and near schools with a lower proportion of Hispanic students .In California, 79% of licensed tobacco retailers near public schools sold LCCs and approximately 6 in 10 of these LCC retailers sold cigar products labeled as blunts or blunt wraps or sold cigar products with a marijuana-related flavor descriptor.

PWID who experience homelessness are subject to additional structural and environmental barriers—such as poverty and exposure to violence—that amplify the IDU-related harms they face . Further, among PWID, experiencing homelessness is associated with an additional elevated risk of acquiring HIV and hepatitis C . While preventing injection-naïve individuals from transitioning into IDU has long been a public health goal , better characterizing the role of homelessness in transitions into IDU could directly inform strategies to respond to some of the upstream drivers of IDU-related morbidity and mortality. Recent research has highlighted the key role of experienced PWID in assisting injection naïve individuals initiating IDU . Across study samples, between 75%–95% of PWID reported that their IDU initiation was assisted by established PWID . While research has demonstrated that experiencing an episode of homelessness in the past six months increases the risk that injection-naïve individuals initiate IDU , there is a lack of research concerning the relationship between recent homelessness and the provision of IDU initiation assistance among PWID. In fact, prior studies of IDU initiation assistance have operationalized recent homelessness or housing status as a covariate to be controlled for in subsequent analyses, rather than as a critical factor in and of itself . In the present study, we therefore assessed the association between recent homelessness and providing IDU initiation assistance among PWID from two cities in North America .Preventing Injecting by Modifying Existing Responses is a multi-cohort, multicountry, plant benches mixed-methods study with a primary aim of identifying socio-structural factors that influence the likelihood that PWID help injection-naïve individuals inject for the first time . For this study, data were drawn from four PRIMER-affiliated longitudinal cohort studies in Tijuana, Mexico and Vancouver, Canada. In Tijuana, PRIMER was conducted within the Proyecto El Cuete cohort study .

For ECIV, at baseline, all participants were at least 18 years old, had reported IDU in the prior month, spoke at least Spanish or English, were residing in Tijuana with no plans to relocate, and were not participating in any other intervention studies . In Vancouver, data were collected within three ongoing cohort studies: the At-Risk Youth Study ; the AIDS Care Cohort to Evaluate exposure to Survival Services study; and the Vancouver Injection Drug Users Study . For ARYS, recruited participants were between the ages of 14 and 26, reported illicit drug use in the past month, and reported recently being homeless or accessing services intended for homeless youth at baseline . For ACCESS, recruited participants were at least 18 years old, HIV seropositive, and reported illicit drug use at baseline . For VIDUS, recruited participants were at least 18 years old, HIV seronegative, and reported IDU on at least one occasion in the past month at enrolment. At recruitment and semiannually thereafter, all participants of these PRIMER-affiliated cohort studies completed interviewer-administered questionnaires that capture participant-reported information on socio-demographic characteristics and drug use behaviors. Starting in late 2014, corresponding cohort questionnaires were amended under PRIMER to add survey items concerning participants’ experiences with providing injection initiation assistance to others. The first interview completed by a participant involving the PRIMER items on injection initiation assistance is referred to as that participant’s PRIMER baseline interview . The present study includes data collected on ECIV and ARYS/ ACCESS/VIDUS participants from 2014 to 2017. The PRIMER study was approved by the Institutional Review Board of the University of California San Diego . It is also important to highlight that the dynamics of homelessness and IDU are different across these two sites. While there are challenges in estimating the number of people who experience homelessness, estimates indicate that, at minimum, several thousand individuals experience homelessness each year in both Tijuana and Vancouver .

In Vancouver, homelessness and IDU are concentrated and highly visible in the Downtown Eastside neighborhood . This centralization reduces barriers to recruiting and providing resources to PWID. Whereas, in Tijuana, homelessness is more dispersed and encampments that do arise are frequently subject to law enforcement interaction . As such, our study reflects on the relationship between homelessness and IDU initiation assistance provision across two heterogenous settings, expanding the potential generalizability of our findings. Our study was restricted to members of the ECIV and ARYS/ACCESS/VIDUS cohorts who: 1) completed a PRIMER baseline interview within the study window; 2) reported a history of IDU at baseline; and 3) completed at least one follow-up visit six months after baseline. Eligible participants contributed a minimum of 1 and a maximum of 5 follow-up visits. If a participant had missing baseline data for any time-varying measure , then baseline was redefined to be that participant’s first subsequent visit with complete data. All subsequent PRIMER follow-up visits within the study period with complete data for a participant were included. If a participant had missing data for a follow-up visit, then that follow-up visit and all subsequent follow-up visits for that participant were excluded from the analysis. The outcome of interest was recent provision of IDU initiation assistance . To operationalize this measure, participants were asked if they had helped an injection-naïve individual inject for the first time in the past six months. This question is intended to capture participants’ recent experiences with direct assistance and/or indirect assistance . The exposure of interest was recent homelessness , defined via self-report as experiencing an episode of homelessness in the past six months. Due to differences in the cohort questionnaires by setting, the self-reported exposure was measured differently for participants from Tijuana and Vancouver. In Tijuana, participants were given a set of locations and asked to mark all the places they have lived or slept in the past six months.

Participants that reported having lived or slept in their workplace, in a vehicle, in an abandoned building, in a shelter, on the streets, or in a shooting gallery in the past six months were deemed to have recently experienced homelessness. In Vancouver, participants were asked a single yes/no question: “Have you been homeless in the last six months?” with those responding “yes” deemed to have recently experienced homelessness. Both the exposure and outcome were repeatedly assessed at each visit over follow-up. We identified a set of covariates a priori that might confound the relationship between our exposure and outcome of interest based on prior literature. The set consists of both baseline-fixed and time-varying covariates. Baseline-fixed covariates included: age , gender , and cohort . Time-varying covariates included: whether participants reported being stopped by law enforcement in the past six months ; whether participants reported being incarcerated in the past six months ; whether participants reported IDU in the past six months ; and for Vancouver participants only, neighborhood of residence . Excluding the baseline-fixed covariates, values of all other variables were allowed to vary over time to reduce misclassification bias. Prior to any analyses, time-varying covariate values at a given followup visit t were recoded to their corresponding value at visit t-1 occurring six months earlier. This lagging was done to ensure that covariate measurement always preceded both exposure and outcome measurement at the same visit. Due both to differences in underlying study design and how the exposure was defined between the Tijuana and Vancouver cohorts ,gardening rack all analyses described herein were undertaken separately by setting. Given our interest in estimating the effect of recent homelessness on recent provision of injection initiation assistance , it is important to note that traditional regression-based approaches to control for measured confounding may yield a biased effect estimate when the set of covariates includes time-varying variables that are caused by prior exposure and also influence subsequent exposure and outcome values . This consideration is relevant to our study, as we have measured several time-varying covariates that may satisfy these criteria; for example, recent IDU may be both a consequence of prior homelessness and a confounder of subsequent homelessness and providing injection initiation assistance). Alternatively, an unbiased estimate of the effect of interest can be obtained from an inverse-probability-of-treatment-weighted marginal structural model, which accounts for baseline-fixed and time-varying confounding via weights . Estimation of this marginal structural model requires two steps: first, we calculate stabilized inverse probability-of-treatment weights for each person-visit occurring after baseline to account for confounding; and, second, we fit a generalized estimating equations logistic regression model to the weighted sample to estimate the parameters of a marginal structural model. IPTWs are calculated in order to evenly distribute potential confounders across the different treatment groups – the application of the weights to the study sample generates an artificially balanced pseudo-sample in which recent homelessness status is independent of all measured confounders . The IPTW approach is particularly appropriate given that it can effectively account for confounding caused by time-varying measures in longitudinal analyses . See the Supplemental Materials for full details on the calculation of IPTWs. Next, we fit a GEE logistic model to the inverse-probability-of-treatment-weighted sample with our repeated measures outcome regressed on terms for exposure , time , and all baseline-fixed covariates . A first-order autoregressive working correlation matrix was specified to account for repeated measures within participants – meaning that the model assumed that a participant’s outcome response at follow-up visit t was correlated with their outcome response at visit t-1 .

Assuming the absence of model misspecification, unmeasured confounding, and informative censoring, the inverse-probability-of-treatment-weighted GEE coefficient estimates estimate the corresponding causal parameters of a marginal structural model . In other words, under these assumptions, the exponentiated exposure coefficient estimate from our weighted model – which is an adjusted odds ratio – may be interpreted as the relative effect of recent homelessness on a participant’s odds of providing injection initiation assistance over the same six-month period . Corresponding 95% confidence intervals were calculated for effect estimates using robust sandwich-type standard errors with clustering by participant. We performed two sensitivity analyses to assess the influence of measured confounding on our estimates of the association between recently experiencing homelessness and recently providing IDU initiation assistance: first, to assess the influence of measured time-varying confounding, we ran the GEE logistic model as described above without the IPTWs; second, to assess the influence of measured time varying and baseline-fixed confounding, we ran the GEE logistic model as described above without the IPTWs and without adjusting for baseline-fixed covariates. We identified 703 eligible participants in Tijuana and 1551 eligible participants in Vancouver . At baseline, 12.5% of participants in Tijuana and 23.3% of participants in Vancouver reported experiencing homelessness in the past six months. Individuals in Vancouver who reported recent homelessness at baseline were younger on average than those who had not . In both Tijuana and Vancouver, individuals who reported recent homelessness at baseline reported higher prevalence of being stopped by police in the past six months. In Vancouver, 21.0% of those who recently experienced homelessness at baseline reported recent incarceration versus just 3.0% of those who did not report recent homelessness. In Tijuana, past six-month IDU was more prevalent among those reporting recent homelessness at baseline than those who did not . The same was true in Vancouver, where 80.9% of recently homelessness participants reported IDU in the past six months compared to 58.9% of participants who did not report recent homelessness. A higher proportion of those reporting recent homelessness at baseline also reported recently providing IDU initiation assistance in both Tijuana and Vancouver . The median number of follow-up visits was 5 in Tijuana and 4 in Vancouver . At a given follow-up visit, between 11.6% and 16.5% of participants in Tijuana and between 9.4% and 18.9% of participants in Vancouver reported experiencing homelessness in the past six months. Between 3.3% and 5.4% of participants in Tijuana and 2.5% and 4.1% of participants in Vancouver reported recently assisting an IDU initiation at each follow-up visit. In Tijuana and Vancouver, respectively, 79 and 150 participants reported assisting at least one IDU initiation across the study period, with 19 and 28 of these participants reporting recent injection initiation assistance provision at multiple follow-up visits. In Tijuana, at a given follow-up visit, between 12.5% and 30.4% of participants who reported recently assisting a first-time injection also reported recent homelessness during the same six-month period. In Vancouver, through the first 4 follow-up visits between 18.4% and 36.5% of participants reporting recently assisting IDU initiation also reported recent homelessness, though this fell to 5.6% at the 5th follow-up.

There is also concern that using both marijuana and tobacco at the same time can reinforce the rewarding effects of both substances . Using a sample of 9th and 12th grade students recruited from California schools, this study addresses important gaps in the literature by first reporting adolescents’ rates and patterns of use of and access to marijuana, blunts, and cigarettes. Second, this study examines and compares adolescents’ perceived prevalence, social acceptability, and risks and benefits of marijuana, blunts, and cigarettes. Lastly, this paper assesses to what extent these factors are associated with actual use of marijuana. Such information is important in order to inform the creation of better education and warning messages, especially as marijuana and blunt use increases in popularity and moves from an illicit drug to a legal drug for recreational use .This study utilized a convenience sample, in which we recruited participants from 10 large high schools throughout California. These schools were diverse with respect to geographic location , race/ethnicity, and socioeconomic status ; and were schools that were willing to participate in the study. Researchers introduced the study and invited all ninth and 12th graders to participate, during which time they provided students with consent forms for parents and students 18 and over, assent forms for students under age 18, and project information to take home and discuss with their parents/guardians. Approximately 4,000 students learned about the study, of whom 1,299 returned signed consent/assent forms; 405 of the consented students were disqualified from the study because of incorrect contact information, being in the wrong grade,vertical growing systems or non-response to subsequent contact. Overall, 786 of eligible consented students completed the survey. There were some small but non-meaningful racial/ethnic differences between those who did and did not complete the survey; however, there were no differences by mother’s education.

The sample size was designed to allow sufficient power to detect the contrasts of interest. The sample included 484 females and 281 males; mean age = 16.1 . Participants were ethnically diverse, with 207 White, 171 Asian/Pacific Islander, 232 Hispanic, and 168 other. Demographics of the students who participated in the study reflected the demographic make-up of their respective schools. The survey included 125 questions addressing a number of research questions; and took participants between 30 and 60 minutes to complete. Participants were allowed as much time as they wanted to complete the survey, although they were encouraged to complete the survey at one time to increase confidentiality of their responses. Only those measures related to the current study are reported here. Comprehensive results regarding the cigarette use data can be found in Roditis et al. . Many measures were derived from past surveys on adolescents’ attitudes towards substances, including those that have tested the validity of the assessments . Participants indicated items that were not clear, and then we revised the survey and pilot tested it again until all measures were clear. Most items were continuously scored; the few that were dichotomized are noted below. Differences in perceptions of risks and benefits and social norms across products were assessed using a generalized linear model with the generalized estimating equation method and an exchangeable correlation matrix to adjust the variance estimates for non-independence within school as implemented in Proc Genmod of SAS, v94. Post hoc testing utilized Tukey-Kramer tests. The relationship among marijuana use, perceptions of social norms, risks and benefits, and viewing of ads on social media was assessed using logistic regression. The outcome variable, marijuana use, was coded into 2 categories of never used and ever used. Predictor variables included: perceived prevalence variables, perceived risk and benefit variables factor analyzed into the following categories: health and social risks, benefits, and risk of addiction, and awareness of social media attitudes and beliefs related to marijuana. Age, sex, and race/ethnicity were also included in the model; however, interactions with sex and race/ethnicity were not significant and therefore were removed in the final model.

Missing data, which was negligible and varied item to item, were left missing. SPSS version 23 was used for the descriptive analyses.There were significant differences in participants’ reports of mother, father, sibling, and friend use of these products. Participants reported lower rates of marijuana and blunt use and higher rates of cigarettes use among adult figures in their lives. Conversely, participants reported much higher rates of marijuana than cigarette use among friends . They perceived significant differences in rates of use among peers, reporting that 50.92% of their peers had ever used marijuana, 42.63% had ever used blunts and 34.43% had ever used cigarettes. Participants viewed marijuana and blunts as more socially acceptable than cigarettes .Participants rated cigarettes as being overall more harmful to their health, more harmful to their friends’ health, more harmful to the environment, and more addictive than marijuana or blunts . Post-hoc analyses showed that participants perceived marijuana as more harmful to the environment than blunts, and perceived blunts as more likely to lead to addiction than marijuana. Participants viewed marijuana and blunts as similarly risky when it comes to their and their friends’ health . Generally, participants rated marijuana and blunt use as less likely to result in short-term health risks than cigarettes, with post-hoc analyses showing that they viewed marijuana and blunts as similarly risky. Participants also rated marijuana and blunt use as less likely than cigarettes to result in the short-term social risks of friends getting upset and bad breath. Participants reported no difference in the likelihood of getting in trouble from using marijuana, blunts, or cigarettes. Adolescents rated marijuana and blunts as more likely to confer social benefits of looking cool and fitting in than cigarettes, though they rated all products as equally likely to make them look mature. Participants rated marijuana and blunts as less likely to make them feel jittery or nervous, more likely to reduce stress, and more likely to make them feel high or buzzed than cigarettes. They rated all three products as equally likely to help with concentration. Marijuana and blunts were rated as less addictive, and easier to quit than cigarettes .

A similar number of participants reported seeing messages on social media about the risks and benefits related to marijuana use . Additionally, 34.4% reported seeing messages about risks related to blunt use and 28.6% reported seeing messages on benefits related to blunt use. A smaller number of participants reported actively posting online about these products, with 13% posting about the risks related to marijuana use, 10.9% posting about the benefits, 10.1% posting about the risks of blunt use, and 4.6% posting about the benefits of blunts . Use rates in this study were highest for marijuana, followed by blunts and cigarettes. Most adolescents who use these products get them from friends, use them in friends’ houses, and when they feel stressed. Adolescents perceived lower marijuana and blunt use but higher cigarette use among parents. Conversely, adolescents perceived higher use of marijuana and blunts and lower use of cigarettes among their siblings and peers. These differences in perceived use may reflect current trends in adolescent marijuana and cigarette use nationwide, in which rates of cigarette use is much lower than marijuana use, with cigarette use continuing to decline, marijuana use remaining higher , and rates of marijuana use being higher among adolescents and young adults compared to adults . While approximately a quarter of participants report having used marijuana, they thought that more than half of their friends have used marijuana. Importantly,grow trays participants who reported that their friends used marijuana had a 27% greater odds of using marijuana themselves. Previous studies also show relationships between friend drug use and adolescent drug use, and friend use is a powerful influence on adolescents’ social norms and acceptability of particular behaviors . The fact that participants report friend use rates of marijuana as double that of self-reported use may be reflective of changing social norms in which marijuana use is seen as an acceptable and common behavior, which, in turn, may be influencing decisions to use . Marijuana and blunts were generally perceived as more socially acceptable, less risky, and more beneficial than cigarettes. Despite the fact that blunts contain nicotine yet marijuana doesn’t, adolescents didn’t perceive differences in the likelihood of becoming addicted or being able to quit marijuana or blunts, although adolescents rated marijuana as more addictive than blunts. This is of particular importance, as it is possible that using both tobacco and marijuana together may actually increase the addictive potential of these products . While perceptions of benefits and addiction were not related to use in this study, perceptions of greater health and social risks were associated with lesser odds of using marijuana. Other studies have also found risk perceptions related to use . The fact that perceptions of benefits were not related to use is surprising as other studies have found perceptions of benefits to predict use .

It is possible that perceived social norms are more important drivers of adolescents’ decisions to use marijuana than perceived risks and benefits despite the fact that these constructs are linked . While perceptions of benefits of marijuana were not related to use, seeing messages about the good things or benefits of marijuana use was associated with a 6% greater odds of use. In contrast, despite adolescents seeing ads for both risks and benefits of marijuana, messages regarding risks were not related to use. It is possible that individuals who use marijuana are actively seeking and more aware of messages related to benefits of marijuana use. There are limitations to this study. The data are self-reported. Further, given the cross sectional nature of our data, we cannot suggest a causal relationship between factors associated with marijuana use and marijuana use itself. Additionally, some of the factors associated with marijuana use have a confidence interval approaching 1.0. Finally, these data were collected throughout Northern and Southern California and thus are not nationally representative. Despite these limitations, this is one of the few studies to assess perceptions of social norms, risks and benefits for marijuana, blunts, and cigarettes. Additionally, this study assessed how these factors as well as awareness of social media are related to marijuana use. Results from this study offer a number of important public health implications, particularly as states move towards legalization of marijuana for recreational use. As this occurs, states need to take adolescents’ perceptions of risks, benefits, social norms, and peer influences into account. Though there is mixed evidence on how legalization impacts adolescent marijuana use, advocates for marijuana legalization argue that legalization itself does not increase use among youth . However, there is no evidence that legalization alone does anything to decrease use or access among adolescents. The results from this study have a number of implications for prevention strategies. Perceived rates of marijuana use among friends is higher than participant self-reported use rates and reported national averages of adolescent use. This finding is similar to findings in the alcohol use literature, which finds that youth and young adults tend to overestimate rates of binge drinking. Importantly, dispelling this misperception has been used effectively in a number of social norms campaigns focused on reducing binge drinking in college campuses . This suggests that using a similar social norms marketing approach, in which youth learn that rates of marijuana use among peers are much lower than they think, may be a useful strategy to prevent use. In this study, both perceived friend use and having seen positive messages about marijuana was associated with greater odds that an adolescent used marijuana. These findings also suggest the need for marketing, education and intervention strategies that specifically tackle social acceptability and peer use. This study also shows that adolescents perceive marijuana and blunts to be significantly less harmful than cigarettes, despite the fact that all of these products are combustible smoking products. Additionally, despite the fact that blunts have nicotine, adolescents did not perceive these to be more addictive than marijuana. These findings suggest that there is also a need for educational and marketing campaigns that realistically address what the risks of marijuana and blunt use are for both youth and adults, including risks of addiction. National, state, and local public health agencies should consider lessons learned from regulatory and informational strategies that have been used in tobacco control, and should implement such strategies before legalization occurs .