Cannabis Grow

It is important to note that employers cannot ask about applicants’ criminal backgrounds according to California’s 2018 ”Ban the Box” policy. However, they can run background checks. Furthermore, using self-disclosed criminal history in the experimental design is justified for the following reasons. First, according to correspondence studies, it is not uncommon to self-disclose criminal history . Previous studies show that self-disclosing criminal history is recommended to ex-offenders applying for jobs because they can control disclosure rather than waiting for their history to be disclosed in a background check. Thus, self-disclosure of criminal history is a realistic experimental setting. Treatment 2 is nearly identical to Treatment 1, the only difference being the applicants’ conviction status. The resumes, rather than stating the applicant has been convicted of a misdemeanor, state that they have been arrested but not convicted. Thus, Treatment 2 includes those with misdemeanor arrest records but not convictions. Treatment 3 has the same characteristic feature as Control but includes applicants with a different racial background. Treatment 3 contains resumes for black job applicants with clean records. Race is indicated by using black-sounding names. Names are borrowed from Bertrand and Mullainathan . Treatment 4 is identical to Treatment 1, greenhouse tables except that resumes are for black applicants who have been convicted of misdemeanors. Treatment 5 is identical to Control, except that resumes are for white female applicants.

Treatment 6 includes the same characteristics as Treatment 1 but with white female applicants. Table 2.1 presents the main characteristics of each group. After rating all the resumes, subjects were asked to rank them from the best to worst . Subjects did not have to explain their decisions in this phase. This different approach enforces the idea of there being competition between resumes. In the field experiments studying employment such as Leasure’s study, applicants received callbacks if they met the requirements of the employers, and there is a cut-off point: if applicants are above the points required by the companies’ hiring standard. Ranking does not provide such a clear cut-off point. However, the better the ranking, the more likely it is that applicants will move to the next round of interviews, which means they are closer to the cut-off point. Thus, ranking serves a similar purpose. In the rating task, the competition among applicants is not obvious, and the rating is based on individual resumes. Additionally, I held a treatment session for the same resumes but with the expungement treatment included. In each of the groups of those with records – “convicted white male,” “convicted white female,” “convicted black male” – and the “arrest-only white male” group, one resume is randomly selected to have a clean record. I simply removed the self-disclosure of their criminal background to demonstrate the effect of expungement. In the treatment session, subjects performed the same tasks in relation to these modified resumes as with the other resumes. The goal was to study whether these modified resumes received better ratings after any criminal background was expunged. Thus, the experiment is divided into a control session and a treatment session. One concern in this experiment is whether the quality of data is as good as that collected by field experiments. Thus, to safeguard the quality of the data, I implemented numerous steps to ensure that subjects understood their task to rate and rank these applicants as if it were part of a real hiring process. Another concern regarding the rating task was that, on average, some subjects might consistently award low scores and others consistently award high scores; for example, if subject A’s average rating for all resumes is 5.8 and subjectB’s average rating is 7.6.

After ranking all resumes, the subjects completed a short survey to disclose their own race and gender. Their demographic information made it possible to check whether they might have racial or gender preferences in relation to applicants that could compound or affect the impact of the applicant having a misdemeanor record. There are some drawbacks and limitations to using lab experiments to study hiring decisions. As mentioned above, the quality of lab data and how realistic they are compared to field experiments are still under investigation. The experimental design lacks a connection between subjects’ earnings and their ratings and rankings. However, laboratory experiments require less time to collect data and allow easy modification of the research design to study race, gender, and expungement simultaneously.The following tables present the results of the experiment. Table 2.2 presents the linear regression results when comparing resumes with different conviction statuses. Column 1 shows that, when pooling all the resumes, as long as a resume indicates that the applicant has a record , the rating is negatively affected at a 1% significance level. The result allows Hypothesis H1 to be rejected and demonstrates that having a misdemeanor record has a strong negative impact on employment outcomes. Thus, it is worth studying whether expungement also affects the ratings. The results also suggest that black applicants are discriminated against, and this result is significant at the 1% level. Female applicants receive slightly lower ratings, but this result is not statistically significant. All the resume data for female and black applicants are then dropped to compare the impact of having a misdemeanor conviction on record compared to having only an arrest record. White male applicants with clean, arrest-only, or convicted status were kept in the sample to control for race and gender.

Column 2 suggests that being arrested without conviction lowers an applicant’s ratings by 1.971 points, and being convicted lowers the rating by 1.652 points. Both results are significant at the 1% level. This shows that subjects do not differentiate between a conviction or an arrest when dealing with applicants with records. Although the results suggest that applicants with arrest-only records receive lower points than those with misdemeanors, flood tray the difference is small. Subjects tend to pay some attention to job experience and score accordingly, but the dominant impact still comes from the criminal record. Hypothesis H2 can thus be rejected, contradicting the results in Uggen et al. . Uggen et al. find that being arrested has almost no effect on employment access. However, Uggen et al. use an audit study and increase contact with employers. For example, applicants are always asked to have a conversation with the hiring manager when they fill out the in-person application. Uggen et al. conclude that contact with hiring managers is significantly related to increased callbacks. However, applicants applying for jobs online do not have such close contact. Thus, the present experimental design is closer to an online job application process, which does not facilitate direct contact between employers and applicants. The results demonstrate that although marijuana is legalized in California, subjects still consider marijuana-related misdemeanors as a negative component in the job hiring processes. Thus, both Columns 1 and 2 suggest that marijuana-related misdemeanors have a negative impact on employment access, implying that automatic expungement should improve employment outcomes. Table 2.3 presents the linear regression results with the inclusion of expungement. All resumes with clean records were dropped other than those for which records were expunged. The expungement process involves removing the record from an applicant’s background. I removed the self-disclosure of applicants’ criminal backgrounds to mimic this result. I then divided the control session into three groups consisting of around 30 participants and calculated the average rating for all resumes that included a criminal background. Because of limited funding, I only conducted one treatment session consisting of 30 participants.I calculated the average ratings for all resumes with criminal backgrounds and those with expungement. Column 1 of Table 2.3 shows that the difference in the average scores between the control and treatment sessions are significantly affected by the expungement process. Without expungement, the difference between the two sessions for the resumes with criminal records is almost neglectable. With expungement of records, however, the ratings for the resumes increased by 1.173 points, and this result was statistically significant at the 1% level. Hypothesis H3 can thus be rejected, demonstrating that the same resumes perform much better in the ratings after expungement, which further supports the idea that automatic expungement should improve ex-offenders’ employment outcomes. Table 2.4 presents the linear regression results when comparing the resumes of applicants of different races. Black and white applicants with clean records or a conviction were kept in order to control for gender and conviction status. Both Columns 1 and 2 suggest that black applicants receive lower scores. The results show that the discriminatory attitudes are statistically significant at the 1% level. The interaction term of black applicants and a misdemeanor record in Column 2 suggests that black applicants receive ratings that are 0.246 points lower than those of white applicants with misdemeanor records. Thus, Hypothesis H4 can be rejected, which is in line with many previous research findings. It is important to pay attention to those with marijuana-related misdemeanors who are black because of the racial disparity in ratings . The results here also demonstrate that black applicants are double-penalized for having a marijuana-related record, and automatic expungement will improve their employment outcomes. Table 2.5 presents the linear regression results for the comparison of resumes for applicants of different genders.

Applicants’ racial background was controlled, and only the resumes of white male and white female applicants with either clean or misdemeanor records were kept. Column 1 shows that female applicants received slightly lower ratings, with this result being significant at the 5% level. Thus, Hypothesis H5 can be rejected. Column 2includes the interaction term of female applicants and misdemeanor records. As the results suggest, female applicants receive lower scores than male applicants with similar misdemeanor records, but the effect is not statistically significant at the 5% level. However, the results still suggest that female applicants face a similar double penalty as black applicants in the job market. Both gender and race play important roles when applicants have marijuana related misdemeanor records. Thus, it is safe to conclude that automatic expungement will significantly improve ex-offenders’ employment outcomes, particularly for racial minorities and women. To summarize the results of the resume-rating process, contrary to Uggen et al.’s findings, having a record for a misdemeanor, regardless of conviction status, has a significant negative effect on employment access . The results also suggest that race significantly impacts employment access, and gender has some impact. The results are largely consistent with Leasure . Leasure finds that employers did not distinguish between applicants with records on the basis of the crime’s severity. A misdemeanor record had the same negative impact on employment access as a felony record. These results resonate with my findings here that arrest and conviction have an almost equal negative effect on employment access. Furthermore, black and female applicants receive worse ratings than other applicants with misdemeanor records and are double penalized. The following tables present the regression results for the rankings. Table 2.6 presents the linear regression results comparing the rankings of resumes with different conviction statuses. Column 1 shows that, as predicted, having a record, regardless of conviction status, significantly increases the ranking. Note that the higher the ranking, the worse subjects think the applicants are in terms of employ ability. Race and gender are then controlled to compare only the effects of a conviction and of an arrest only. Column 2 shows results consistent with the rating. Resumes with arrest records are ranked much worse than resumes with no records. The impact of only being arrested is almost the same as having a misdemeanor conviction. Table 2.7 presents the linear regression results when comparing the resumes of applicants of different races. Black and white applicants with clean records or a conviction are kept to control all other variables. All columns show that black applicants receive a slightly worse ranking than white applicants. Including the interaction term of black applicants and a misdemeanor record, the results in Column 2 suggest that among applicants with misdemeanor records, black applicants receive a ranking of 1.12 points worse than that of white applicants. The results correspond with the ratings, but having a criminal background still has a larger impact on a resume’s ranking than race. Table 2.8 presents the linear regression results comparing the resumes of applicants of different genders.

Similar interventions implemented via GSN apps may be protective against substance misuse among GSN appusing MSM. Finally, those interested in promoting health behaviors among GSN app-using MSM must bear in mind that GSN apps are used for much more than substance use and/or casual sex partner seeking; instead, GSN apps represent important social contexts for affiliation between gay, bisexual and other MSM. Recognition of the important social role that GSN apps play in the lives of MSM will assist public health practitioners to develop interventions that promote positive affiliation while reducing high-risk behaviors.Policymakers seeking to present a logically justifiable regulatory system for tobacco may want to consider policy coherence, integration, and proportionality. The concept of ‘policy coherence’ suggests that various policies related to an issue are mutually reinforcing. The coherence can be across jurisdictions ,1 across agencies or arenas , or across the broader spectrum of substances . Maintaining consistency may involve ‘policy integration’, in which all substances are regulated by the same agencies . ‘Policy proportionality’ ensures that substances are regulated in according to the harm or risk they present. One way of approaching tobacco policy coherence, integration, and proportionality would be to regulate tobacco as part of a continuum of addictive or psychoactive substances that cause varying degrees of harm. Currently, plant bench indoor in many countries some substances are criminalized and some are legal but controlled in multiple different ways , often by different agencies.

Regarding coherence and integration, taxation of tobacco, for example, is often not administered by health agencies, and the rate is rarely at levels recommended from a health perspective. Proportionality is also an issue. Tobacco is addictive, kills more than half its users, and impairs the health of others. Alcohol is addictive to some and can lead to abuse and both short term and long term health problems, as well as indirect harms , but may also be used unproblematically. Marijuana may be addictive for some, but can also be used for medical purposes or recreation without harm. In the state of Virginia tobacco sellers are not licensed; spirits are sold only in state operated stores and beer and wine retailers must be licensed; and possession of marijuana is criminalized. This incongruence allows the most dangerous substances to be the most widely available. A more coherent, integrated, and proportional policy approach to tobacco that has been raised – but not yet analyzed – is to limit tobacco sales to government-controlled outlets. This approach could be used by any jurisdiction, but would be most practical for those that already have – or are considering instituting – such outlets for other substances, such as alcohol or marijuana. Internationally, some 15 countries already have government retail monopolies for alcohol, and Hungary recently established such a system for tobacco, though it does not have one for alcohol. Uruguay decriminalized marijuana with the intention of establishing government dispensaries; however, this part of the law remains to be implemented. In the U.S..

Federal law permits state or local governments to regulate or prohibit the sale of tobacco products, and the 2014 U.S. Surgeon General’s Report mentioned sales restrictions as a possible endgame strategy. Several jurisdictions in the United States may be ideally situated to implement such a measure, as they have already established government retail monopolies for alcohol. Some are contemplating adding marijuana to the mandate of their alcohol control systems. Other states, currently without alcohol control systems, are considering such systems for marijuana. Moving tobacco sales to government-operated stores could facilitate better congruence between the potential harm of substances and their regulatory status and movement toward a tobacco endgame. This paper analyzes potential advantages, challenges, and disadvantages of such an approach to tobacco control, focusing primarily on the US although in most respects the analysis could be applied in any jurisdiction.Although currently alcohol, tobacco, and marijuana are all considered psychoactive substances with varying potentials for harm, addiction, and abuse, historically they were regarded as very different from one another. Thus in the US lawmakers placed them in different regulatory systems. Early in the 20th century, concerned primarily about unregulated use of opiates and cocaine, the U.S. Congress and the states established anti-narcotics laws. Marijuana was gradually included in these laws due to a confluence of factors, including its association with poor and working class Mexicans . Regulators and the popular press claimed marijuana was highly addictive, caused users to commit violent crimes, and ultimately resulted in insanity and death. By the late 1930s, nearly all states prohibited marijuana sales and use; this was followed by Federal legislation. However, in the 21st century, numerous states have loosened regulations to allow for medical or recreational use of marijuana.

Tobacco, specifically cigarettes, was a target of social reformers in the U.S.. Numerous states passed laws prohibiting cigarette sales in the years before World War I. The war transformed cigarettes from a symbol of moral weakness and dissipation to one of soldierly manliness. By the end of the 1920s cigarettes were legal for adults in all states. The Food and Drug Administration’s enabling legislation excluded tobacco from oversight and tobacco products remained unregulated at the federal level until enactment of the Family Smoking Prevention and Tobacco Control Act in 2009. Internationally, the situation is similar to that in the U.S., with different jurisdictions having varying restrictions on use , licensing for sale and age of purchase, and packaging, but little regulation of the product which is almost universally legal for adult use. As with marijuana, an unfortunate association arose between immigrants and problematic use of alcohol. After many years of temperance advocacy with some success in the states, the US ratified the Eighteenth Amendment to the Constitution in 1919. It prohibited manufacture, sale, and transportation of alcohol and came to be known as ‘Prohibition’. Its repeal in 1933 returned alcohol policy to the states. Those that chose to regulate it then established state monopolies for alcohol sales at the wholesale or retail level; most other states developed license systems. Twelve states continue to have governmentally-operated retail outlets. Others have abandoned the control-store approach in favor of licensing . The alcohol industry advocates privatization and has used referenda, legislation, and litigation to achieve it.16 In the twelve alcohol control retail states, however, the state stores model limits the number of liquor outlets. As Table 1 shows, where measured, tobacco outlets per 100,000 population far outnumber alcohol outlets in such states. In terms of regulatory policy coherence, integration, and proportionality, there is no public health justification for maintaining the vastly higher density of tobacco outlets. Adoption of a government tobacco monopoly could contribute to a broader ‘endgame’ strategy – one specifically designed to change or eliminate permanently the structural, political, greenhouse rolling racks and social dynamics that sustain the tobacco epidemic– to end it in a specific jurisdiction within a specific time. Achieving an endgame is now a national goal in Finland17 and New Zealand, for example, although they do not have specific, concrete plans for achieving this goal. The 2014 US Surgeon General’s report on tobacco use suggested consideration of bans on tobacco sales at the city or state level as one option for achieving a tobacco endgame. A recent sales ban in Massachusetts was, however, quickly rescinded after public protests. Thus, it may not be feasible to move directly from allowing cigarettes to be sold virtually everywhere to prohibiting sales altogether. Instead, an endgame, like other tobacco control policy innovations, will likely involve a variety of incremental approaches in multiple jurisdictions. A state tobacco monopoly could be one such approach.Policy change is more feasible if it incrementally builds on existing policies, coordinates problem definition with political and policy initiatives, and serves to advance multiple governmental objectives. Personnel at government alcohol stores already enforce age of purchase rules. If jurisdictions established the same age limit for alcohol and tobacco purchases such verification systems would be simple to implement. If marijuana is legalized, the existing system of alcohol stores could sell those products as well.

A transition of tobacco sales to government stores could promote more coherent policy for regulation of legal substances whose use causes social harms. Because the government would retain all profits from sales, moving tobacco sales to government-operated alcohol outlets should be economically feasible. Costs would consist primarily of creating display and storage space, training personnel, and purchasing products. Governments could negotiate wholesale terms and set retail prices high enough to discourage use while covering costs. To mitigate objections from tobacco retailers, governments could create a ‘transition fund’ from tobacco revenue– to provide retailers a one-time or multi-year payment based on their usual tobacco profits. These funds would enable retailers to reduce reliance on tobacco sales. As tobacco consumption continues to drop, they would need to do this anyway. Government stores could facilitate information gathering about profits from tobacco sales. This could assist other governments attempting novel retail policies. Reduction in outlets would allow funds currently used for surveillance and enforcement of age of purchase laws to be redeployed for public education about and enforcement of the ban on sales by private retailers. Compliance checks for a smaller number of government stores would be easier to conduct regularly. Nearly ubiquitous availability of tobacco 22 contributes to misperceptions that tobacco is a normal consumer product and undermines public health messages. Moving sales to existing government-operated alcohol outlets would signal that tobacco products are dangerous and require special measures. It would also give governments maximal control over multiple policy instruments. Governments could limit or eliminate point of sale advertising or display, limit the range of brands or products for sale, refuse to sell flavored or menthol products, sell only one variety per brand family, or set purchase limits to reduce secondary illegal sales to minors. These measures could be undertaken incrementally to allow time for consumer education. Selling tobacco in government stores only would also limit the hours of sale and the density and location of tobacco outlets. Currently, when governments raise tobacco taxes, the industry either temporarily lowers prices to minimize the quit attempts that a sharp price increase can inspire, or increases prices to maximize profits while suggesting to consumers that the price increase is due to the tax. A government tobacco monopoly would neutralize both responses. Any increase in price redounds to the good of the government. Pricing policies might be constrained by tobacco prices in neighboring states or countries, particularly in border areas. Establishing a government tobacco monopoly could reduce relapse and smoking initiation by making products less available and visible. Tobacco outlet density has been positively correlated with smoking status, youth and young adult initiation; exposure to cigarette retail displays undermines quit attempts. By contrast, alcohol monopolies reduce consumption and alcohol-related problems; in the U.S., alcohol control states consistently have lower alcohol consumption per capita than non-control states. Fewer high school students in monopoly states than those in non-monopoly states report drinking alcohol in the past 30 days or binge drinking in the past 30 days. Selling tobacco in government stores would also likely reduce sales to underage youth. As government store employees, clerks would be accustomed to performing age checks for all purchases . Increased compliance checks would make risking illegal sales less appealing. As government store employees, clerks would not be motivated by the potential profits to be made by underage sales, as owners or operators of small stores might be. Challenges and Potential Concerns A major challenge to implementing such a policy change will be the tobacco industry’s political influence and ability to mobilize opponents. The tobacco industry would be likely to mobilize political actors such as convenience store associations and ‘citizen’ front groups to oppose the measure. Tobacco sellers in France have been strong opponents of tobacco control measures they perceive to affect their profits. Some objections from retailers might be assuaged by the transitional payments discussed above, but we must acknowledge that stores will be unable to sell a profitable item that brings in customers who may make other purchases. Developing retailer and public education programs with effective messaging would be essential, and this could require additional expenditures. There might also be opposition to the initial costs .

Cannabis can have serious impacts on health, and patients often use the drug instead of other prescription medications to manage their health . The purpose of this paper is to better understand the relationship between cannabis use, as documented in electronic health records , and other health diagnoses among primary care patients in a time when state law allowed for medical cannabis use, but not non-medical cannabis use. Understanding the associations between cannabis use, medical conditions, and behavioral health can equip practitioners to more effectively identify patients who use cannabis and address the possible impacts the drug may have on their health. Currently, little is known about how often cannabis use is identified among primary care patients in health systems, or the degree to which it is associated with medical and psychiatric diagnoses among primary care populations. EHR data can be used to address these questions. For example, Campbell and colleagues analyzed EHR data from community clinics in Oregon, California, and Washington State between 2012 and 2016, and found that primary care patients were more likely to have a cannabis use disorder , but not cannabis use without a disorder , documented in EHRs if they had psychiatric diagnoses. Lapham and colleagues analyzed data from a large integrated healthcare system in Washington State from 2015 to 2016, and found that mental health disorders, depression symptoms, tobacco use, cannabis grow system unhealthy alcohol use, illicit drug use, and substance use disorders were associated with increased cannabis use.

Matson and colleagues recently analyzed EHR data from a large integrated healthcare system in Washington State from 2017 to 2018 to measure the prevalence of documented medical cannabis use and its association with health conditions for which cannabis use could be potentially beneficial or harmful. They found that patients who had documented medical use of cannabis had higher prevalence of diagnoses for both conditions that could be adversely impacted or helped by cannabis use when compared to non-medical users and non-users. Campbell and colleagues’ data was collected from a mix of states that allowed for both medical and non-medical cannabis use , while Matson and colleagues’ data was collected only from Washington. To our knowledge, no published research has used EHR data to examine the prevalence of cannabis use or the association of cannabis with health diagnoses in places where cannabis is only legal for medical use. It is important to analyze data from samples in locations that have different cannabis policies because cannabis’ legal status can influence who decides to use the drug, how frequently they use it, and the potency of the cannabis they consume. Policy contexts also affect cannabis pricing, access, marketing, and social acceptability, which in turn can lead to differences in cannabis use and its consequences. The legal status of cannabis may influence patients’ willingness to disclose their use to their physician when they seek treatment for a health problem leading to differences in how frequently it is documented in EHRs, and it can also impact the degree to which cannabis use may have negative social or legal consequences.

The goal of this paper is to complement the work of Campbell et al. and Matson et al. by analyzing EHR data from California between 2013 and 2017, when cannabis was only legal for medical use. As of May 2021, 18 states in the United States and countries across the world—including the United Kingdom, Australia , and many nations in continental Europe and South America — allowed for medical cannabis use, but not adult cannabis use. Findings from this study can be used to inform clinical practice in these places, and other jurisdictions that may allow medical cannabis use—but not non-medical cannabis use—in the future. The paper has two aims: to measure the prevalence of documented cannabis use disorder and cannabis use in a large health system’s EHR; and to determine the odds that patients with documented CUD and CU had general co-occurring medical conditions and conditions known to be associated with cannabis use.Under one percent of the sample in this study had documentation of CU or CUD in their EHR, compared to studies of EHR data from Washington State, which found EHR-documented cannabis use rates between 15 and 22%. Some of this difference may be due to higher levels of adult CU, frequent cannabis use, and CUD in states like Washington that allow non-medical marijuana use. Also, the sample in this study was mostly commercially insured and of relatively high income, so these factors may account for the differences from the Washington State samples. However, the rate of CU and CUD documentation in EHRs in this study was still surprisingly low. According to the U.S. National Survey on Drug Use and Health, 16.4% of Californians over age 12 reported past-year CU between 2014 and 2017, and 2.0% of this population had a CUD. Part of the reason for these discrepancies could be in the methods used to identify CU and CUD among the patient populations. In the Washington State studies, all patients completed a cannabis screening at a primary care visit, whereas in this study, patients were not routinely screened. The large gap between rates of CU and CUD in California population surveys and the frequency of CU and CUD documentation in EHRs in this study could be indicators of how cannabis use can go undetected during primary care visits in the absence of systematic screening. California healthcare providers may now begin screening for CU and CUD more since the U.S. Preventive Services Task Force has recommended drug use screening for adults in primary care, and this may lead to better identification of cannabis use in medical settings. This finding also underscores the importance of having healthcare providers in other states and countries—both those with and without legalized marijuana—systematically screen patients for CUD and cannabis use. Study findings also shed light on the association between CUD documentation, CU documentation, and health among primary care patients in medical marijuana jurisdictions, showing that cannabis use is associated with many physical health conditions. CUD documented patients in this study were over seven times as likely as matched controls to have HIV/AIDS diagnoses, three times as likely to have sleep disorder diagnoses, and twice as likely to have nervous system disease, digestive system disease, circulatory system disease, ischemic heart disease, fbromyalgia, and sleep apnea diagnoses. CU-documented patients also had increased odds for most of these conditions, though not as much as CUD-documented patients. Elevated rates of medical problems could result from direct physical effects of regular cannabis use and associated behaviors, and the fact that individuals with substance use disorders are less likely than others to access and receive quality health care. Conversely, it is possible that some of this association is due to people with medical conditions using cannabis to manage or alleviate their symptoms. These findings indicate a stronger association between cannabis use and medical diagnoses than that found by Matson et al. in their study of EHR data from Washington State. These differences may be attributable to the fact that unlike Washington State, California was a medical marijuana state at the time of this study, but had not yet legalized cannabis use generally. California patients may have been less likely to report their cannabis use due to fear of legal or social consequences for disclosing their substance use, leading providers to only identify CU or CUD in cases where it was discernible from patient presentation. Furthermore, unlike in the Matson et al. study, flood table patients in this sample were not identified by universal screening. Consequently, it is possible that patients in this sample only had their cannabis use noted in their EHR if it emerged as a topic in the course of their primary care encounter, meaning that their cannabis use and its consequences may have been particularly severe or salient. By having respectful, nonjudgmental, and balanced discussions about the pros and cons of cannabis use with patients, medical providers may be able to decrease patient reluctance to disclose and discuss their cannabis use. Further research can help determine the degree to which the policy context and/ or different methods for identifying patients who used cannabis may have accounted for the different findings reported here and those reported in other EHR studies. When compared to physical health diagnoses, the odds of CU-documented and CUD-documented patients having behavioral health diagnoses relative to matched controls were particularly high.

CUD-documented patients were nearly six times as likely as matched controls to have diagnoses of schizophrenia/psychotic disorders, over seven times as likely to have a depression diagnoses, over six times has likely to have a bipolar disorder diagnosis, and six times as likely to have anxiety diagnoses. For CU-documented patients, odds of these conditions were also elevated, but not nearly as much as for CUD documented patients. Moreover, CUD-documented patients were over three times as likely as CU patients to have schizophrenia/psychotic disorders, and over twice as likely to have depression or anxiety diagnoses. These findings support the extensive body of research demonstrating a correlation between cannabis use and mental health problems and the association between cannabis use documentation and the presence of psychiatric diagnoses in EHRs. They also underscore the importance of screening and assessment for co-occurring mental health disorders among people who use cannabis or have cannabis use disorders, and ensuring that they receive evidence-based psychosocial and pharmacological interventions as needed. Many of the behavioral interventions that have shown efficacy in addressing problematic cannabis use—such as motivational enhancement therapy, cognitive behavioral therapy, and contingency management—are also effective for treating other behavioral disorders, and could help improve the overall behavioral health of primary care patients with CUD. Odds of other substance use disorders were also higher among the CUD-documented group when compared to matched controls, as they had over 21 times the risk of having other substance use disorder diagnoses. As with mental health diagnoses, the CU-documented group was also at elevated risk for substance use disorder diagnoses, but not nearly as much as the CUD-documented group. Compared to CU-documented patients, CUD-documented patients were over five times as likely to have another substance use disorder diagnosis. These findings align with other research demonstrating associations between cannabis use, increased use of other substances, and increased risk for other substance use disorders . The significantly increased odds of HIV/AIDS diagnoses among CUD-documented patients—but not among CU-documented patients—is also notable. There is limited evidence showing cannabis can be effective for increasing appetite and decreasing weight loss associated with HIV/AIDS, though evidence on its long-term safety and impact on long-term AIDS-related morbidity and mortality is limited. However, some research has found cannabis dependence is associated with lower adherence to anti-retroviral therapy and increased HIV symptoms and medication side effects, so the high prevalence of HIV/AIDS among the CUD-documented group in this study is concerning. This finding aligns with previous research showing relatively high levels of frequent cannabis use among people living with HIV and highlights the need to detect CUD among this population and provide them with effective counseling and support to help them manage their cannabis use.Several key limitations should be noted. First, the study drew data from one university health system, and may not be generalizable to other primary care populations in other regions or countries. Second, measures of CUD and CU documentation were extracted from EHRs that did not have specific questions prompting provider to elicit data concerning cannabis use. This could account for the low rates of CUD and CU documentation in the sample, and it is possible that CUD and CU were only noted either when patients mentioned cannabis, or when providers detected issues that prompted them to ask about substance use. Consequently, there is a good possibility that only patients with outward signs of cannabis use or who self-disclosed cannabis use were detected, and these patients may use cannabis more frequently or heavily than most patients who use the drug. Other studies have documented under-diagnosis of CUD in medical records in the absence of routine screening and assessments. Study findings can be interpreted as supporting the associations between CUD and CU at a threshold level that merits documentation in medical records, and should be interpreted within this context. Third, since the dataset only allowed for identification of CUD and CU documentation, the study does not include information concerning frequency of use, duration of use, quantities used, types of products used, or potencies of cannabis products consumed. This information would be needed in order to come to more precise conclusions concerning the relationship between cannabis and medical conditions.

Changes in tobacco blends and curing of tobacco has caused US cigarettes to have higher levels of tobacco specific nitrosamines , a group of carcinogens found in tobacco and nicotine products. The 2014 Surgeon General Report observed that “[f]or Kentucky reference cigarettes, mutagenicity per mg of total particulate matter was 30–40% lower for unfiltered cigarettes than for the same cigarette with a filter added.” These design changes have not only made cigarettes become more dangerous in terms of rising lung cancer rates, but also contributed to an increase in overall mortality, chronic obstructive pulmonary disease and heart disease. The rising risks correspond to changes in cigarette design – unfiltered to filtered, higher tar to lower tar, introduction of filter vents, among other changes to cigarette design. Deeper inhalation of more dilute smoke increases exposure of the lung parenchyma. These and other design changes in cigarettes mayalso have contributed to the shift, beginning in the 1970s, in the histologic and topographic features of lung cancers in male smokers, with an increase in the incidence of peripheral adenocarcinomas that largely offset the decrease in squamous-cell and small cell cancers of the central airways. Filters are part of modern cigarette design, weed trimming tray including the presence of microscopic “ventilation” holes designed to dilute smoke when it is being tested in a smoking machine to trick tests into rating the cigarettes as having lower tar and nicotine deliveries than they actually do.

Filters represent the kind of technology that a corporatized marijuana industry could develop to mislead the public into thinking that products were less dangerous than they are and to engineer products to increase use. The resulting lower tar and nicotine readings were used to mislead smokers into thinking that the cigarettes were safer to keep health-concerned smokers smoking. Filter technology is also an important element of the design of a modern cigarette to lower particle size and make the smoke go deeper into the lung to increase nicotine absorption, with the effect that it causes more disease. In addition, the filters themselves break down and deposit tiny pieces of the filter material in smokers’ lungs, which may contribute to the diseases smoking causes. Filter material found in smokers’ lungs includes toxin-containing charcoal granules and plant and plastic fibers. Cigarette filter fibers have been observed in lung Thissue from patients with lung cancer and who were known to be habitual smokers. In short, a cigarette filter functions much as the way Volkswagen manipulated the pollution controls on its diesel engines: They create the illusion of being less polluting while making the disease burden worse. Internal industry documents demonstrate that the cigarette companies designed cigarettes with filters knowing from the beginning that filters did not actually reduce risk. Filters were part of an overall public relations strategy and marketing tool to manipulate smokers into continuing to use hazardous tobacco products. The tobacco companies use menthol and other flavour additives including fruit and candy flavouring as marketing tools to attract young smokers. National survey findings from the United States and Japan confirm that menthol cigarette use is disproportionately common among younger and newer adolescent smokers. Tobacco products that disguise the taste of tobacco through flavouring agents and palatability enhancers create products that largely appeal to youth and young adults. 

Menthol is the most popular characterizing flavour of cigarettes in the US, with more than 90% of all cigarettes containing menthol. Such harsh effects, if experienced by the smoker, could encourage quit attempts and cessation among menthol users. Women perceive the minty aroma of menthol cigarettes to be more socially acceptable than nonmenthol cigarettes, which complicates public health efforts to denormalize tobacco use. In the US, the tobacco companies intensely market menthol cigarettes in predominately black communities through price discounts, signage, and through associations of menthol use with hip hop lifestyle and culture. Family and social factors that prevented smoking among African American teens do not seem to carry over into young adulthood likely due to tobacco company targeted marketing. In 2012, teenage smoking prevalence among whites was twice as high as black smoking prevalence . While use rates among young adults remains higher for whites than blacks , compared to white smokers, menthol cigarettes are disproportionately used among black smokers. National data from the United States show that around 80% of African American smokers use menthol cigarettes compared to around 30% of whites. Tobacco-caused morbidity and mortality rates are disproportionately higher among African Americans compared to whites, and menthol cigarette smoking is disproportionately high among African Americans, which may help to partly explain the disproportionate tobacco-related disease burdens. These rapid changes in medical costs are due to the fact that risks of cardiac events, non-cancer lung disease, complications of pregnancy, and effects on children  begin to appear almost immediately when people stop smoking or being exposed to secondhand smoke. Cancer is also affected, albeit more slowly over time. Hospitalizations for heart attacks, other cardiovascular conditions, stroke, and pulmonary conditions drop immediately following implementation of smoke free laws, as do need for treatment of respiratory conditions, and complications of pregnancy and hospitalizations for childhood illnesses. The fact that marijuana smoke exposure has similar – indeed larger – effects on vascular function73 suggests that there may be similar adverse consequences and medical costs if marijuana use increases following legalization and expansion of the market.

Tobacco control policy change in Australia between 2001 and 2011 played a substantial role in reducing smoking prevalence among Australian adults between 2001 and 2011. During that time, the Australian government increased tobacco taxes, adopted more comprehensive smoke free laws, and increased investment in mass media campaigns, which can explain 76% of the decrease in smoking prevalence from 23.6% to 17.3% . Comprehensive tobacco control policies may have an even greater impact on cigarette consumption and demand reduction in low and middle income countries compared to high income countries.306 For example, there has been a 50% reduction in male and female smoking prevalence in Brazil between 1989 and 2010, which represents a 46% relative reduction compared to the 2010 prevalence under the counterfactual scenario of policies held to 1989 levels. Combined these policies had averted 420,000 deaths by 2010, with estimates of an almost 7 million deaths averted projected by 2050. Uruguay, an international leader in tobacco control, became one of the first countries to fully implement the Framework Convention on Tobacco Control. In 2006, Uruguay implemented its national smokefree law, and in 2009 the government implemented the largest graphic warning label, covering 80% of the package. In that same year Uruguay prohibited use of false or misleading statements on tobacco packages . There were three tobacco tax increases in June 2007, June 2009, and February 2010, which made tobacco products in Uruguay the highest in the region. In 2012, the Ministry of Health launched an aggressive mass media campaign308 and in 2014 the government prohibited all forms of tobacco marketing including advertising, promotion and sponsorship, product promotion, and point-of sale displays. Since implementation of its comprehensive tobacco control program, tobacco consumption, risk perceptions, and social acceptability of use and the tobacco industry have shifted dramatically. From 2003 to 2011, adult smoking dropped by 3.3 percent each year while youth smoking dropped by 8 percent, from 39% to 31% for males and from 28% to 20% for females. In 2012, 75% of Uruguayans favored a total ban on all tobacco products within 10 years and 60% of the population believed the tobacco companies were unethical. Support for comprehensive smoke free laws among smokers increased from 54% in 2006 to 90% in 2012. After Uruguay implemented its smoke free law, hospital admissions for heart attacks dropped 20% and non-hospital emergency visits for bronchospasm dropped by 15%. A 2000 study on marketing restrictions in OECD countries found that the effects of marketing bans are cumulative and that partial bans were not associated with reductions in tobacco use. Overall, cannabis grow setup comprehensive bans on advertising and promotions were associated with a significant reduction in tobacco consumption since implementation, with larger effects for more comprehensive bans. Market segmentation is an important aspect of tobacco industry marketing. 

Tobacco companies use market research to understand smoking behaviour among different segments of the population, and, in turn, use such research in future marketing campaign messages. This information can be used to design advertising campaigns that circumvent partial advertising restrictions by shifting expenditures toward other media outlets .For example, after the 1998 Master Settlement Agreement in the United States, in which the tobacco companies agreed to some limitations on their advertising and promotional activities, the tobacco industry shifted marketing expenditures to direct mailings and online marketing. Partial advertising restrictions permit cigarette companies to target young adults through lifestyle magazines created by the industry, event sponsorships, and low income and less educated women through distribution of coupons with food stamps, direct mail, and bundle offers at the point-of-sale. Following implementation of a 2012 law that prohibited point-of-sale tobacco displays in New Zealand the odds dropped significantly for experimentation with smoking , smoking initiation , and smoking prevalence , among adolescents, consistent with similar studies from Ireland, Norway, and Australia. There was a marginal decrease in perceived peer smoking among New Zealand smokers, which may have been greater if all forms of tobacco marketing had been prohibited simultaneously. Because the tobacco industry continuously seeks to evade any advertising restrictions, the World Health Organization recommends that governments license tobacco manufacturers and retailers, with penalties and sanctions for noncompliance, including license suspension and revocation for repeat violations commensurate on the nature and seriousness of the offence, to magazines created by the industry, event sponsorships, and low income and less educated women through distribution of coupons with food stamps, direct mail, and bundle offers at the point-of-sale. Following implementation of a 2012 law that prohibited point-of-sale tobacco displays in New Zealand the odds dropped significantly for experimentation with smoking , smoking initiation , and smoking prevalence , among adolescents, consistent with similar studies from Ireland, Norway, and Australia. There was a marginal decrease in perceived peer smoking among New Zealand smokers, which may have been greater if all forms of tobacco marketing had been prohibited simultaneously. Because the tobacco industry continuously seeks to evade any advertising restrictions, the World Health Organization recommends that governments license tobacco manufacturers and retailers, with penalties and sanctions for noncompliance, including license suspension and revocation for repeat violations commensurate on the nature and seriousness of the offence, to assist with enforcement efforts to control tobacco advertising. It is also recommended by the World Health Organization that governments dedicate funding for comprehensive enforcement programs provides legal protection and an ongoing revenue stream for government efforts to monitor and enforce regulatory compliance with marketing bans.In 2006 the U.S. Surgeon General affirmed that there is no risk-free level of exposure to tobacco smoke. Secondhand smoke causes cardiovascular disease, lung cancer, stroke, respiratory disease, and premature death in adults. Infants and children exposed to secondhand smoke are at risk for sudden infant death , asthma attacks, ear infections, and respiratory infections. Smoke free laws are designed to protect the health and safety of the public from secondhand smoke. They also have the beneficial side effect of denormalizing tobacco use, and supporting smoking cessation. In addition, comprehensive smokefree laws stimulate adoption of voluntary smokefree home policies, which also help to denormalize smoking, discourage initiation , and supports quit attempts and smoking cessation among current smokers. Comprehensive smokefree laws are associated with larger drops in hospitalizations for heart attacks, other cardiovascular conditions, stroke, and pulmonary conditions, as well as complications of pregnancy, hospitalizations for childhood illnesses, and perinatal complications. Exemptions in smokefree laws negatively impact lower socioeconomic groups and contribute to health disparities. Lower socioeconomic status individuals are more likely to work in establishments that do not have 100% smokefree coverage or circumvent the law through exemptions . In addition, women are disproportionately impacted by exemptions in smokefree laws because women are over represented in the hospitality industry. In California, for example, exemptions in the statewide smokefree law had disproportionately exposed low income workers, Latinos, and young adults to secondhand tobacco smoke in the workplace, thereby contributing to health disparities. In 2016 California passed a law that eliminated these exemptions. 

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 14 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 cigars15 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, plant benches 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. A greater presence of marijuana co-marketing in neighborhoods with a higher proportion of school-age youth and lower median household income raises concerns about how industry marketing tactics may contribute to disparities in LCC use. The study results also suggest that $1 buys significantly more cigarillos in California school neighborhoods with lower median household income. Policies to establish minimum pack sizes and prices could reduce the widespread availability of cheap cigar products and address disparities in disadvantaged areas. After Boston’s 2012 cigar regulation, the mean price for a grape-flavored cigar was $1.35 higher than in comparison communities. The industry circumvented sales restrictions in some cities by marketing even larger packs of cigarillos at the same low price, 22 and the industry’s tipping point on supersized cigarillo packs for less than $1 is not yet known.

The retail availability of 5- and 6-packs of LCCs for less than $1 observed near California schools underscores policy recommendations to establish minimum prices for multipacks . A novel measure of marijuana co-marketing and a representative sample of retailers near schools are strengths of the current study. A limitation is that the study assessed the presence of marijuana co-marketing, but not the quantity. The protocol likely underestimates the prevalence of marijuana co-marketing near schools because we lacked a comprehensive list of LCC brands and flavor varieties. Indeed, state and local tobacco control policy research and enforcement would be greatly enhanced by access to a comprehensive list of tobacco products from the US Food and Drug Administration, including product name, category, identification number and flavor. Both a routinely updated list and product repository would be useful for tobacco control research, particularly for further identifying how packaging and product design reference marijuana use. This first assessment of marijuana co-marketing focused on brand and flavor names because of their appeal to youth. However, the narrow focus is a limitation that also likely underestimates the prevalence of marijuana co-marketing. Other elements of packaging and product design should be considered in future assessments. Examples are pack imagery that refers to blunt making, such as the zipper on Splitarillos, as well as re-sealable packaging for cigarillos and blunt wraps, which is convenient for tobacco users who want to store marijuana. Coding for brands that are perforated to facilitate blunt making and marketing that refers to “EZ roll” should also be considered.

Future research could assess marijuana co-marketing across a larger scope of tobacco/nicotine products. The same devices can be used for vaping both nicotine and marijuana. Advertising for vaping products also features compatibility with “herbs” and otherwise associates nicotine with words or images that refer to marijuana . Conducted before California legalized recreational marijuana use, the current study represents a baseline for understanding how retail marketing responds to a policy environment where restrictions on marijuana and tobacco are changing, albeit in opposite directions. The prevalence of marijuana co-marketing near schools makes it imperative to understand how tobacco marketing capitalizes on the appeal of marijuana to youth and other priority populations. How marijuana co-marketing contributes to dual and concurrent use of marijuana and tobacco warrants study, particularly for youth and young adults. In previous research, the prevalence of adult marijuana use in 50 California cities was positively correlated with the retail availability of blunts. Whether this is correlated with blunt use by adolescents is not yet known. Consumer perception studies are necessary to assess whether marijuana co-marketing increases the appeal of cigar smoking or contributes to false beliefs about product ingredients. Research is also needed to understand how the tobacco industry exploits opportunities for marijuana co-marketing in response to policies that restrict sales of flavored tobacco products and to policies that legalize recreational marijuana use. Such assessments are essential to understand young people’s use patterns and to inform current policy concerns about how expanding retail environments for recreational marijuana will impact tobacco marketing and use.Alcohol and other drug use is high among US adolescents and increases with age. In the United States, current use of alcohol, tobacco and marijuana is reported by 32.8%, 16% and 21.7% of high school students, respectively. In the same group, lifetime use of alcohol, tobacco and marijuana is 63.2%, 32.3% and 38.6%, respectively1 . Early initiation of alcohol has also been associated with subsequent misuse of prescription drugs and illicit drugs6 . Furthermore, in recent years, the number of drug overdose deaths has exceeded fatalities from motor vehicle crashes among adults. Given the potential negative consequences of drug use during adolescence, screening for alcohol and other drugs is recommended by numerous medical and federal organizations. A pediatric emergency department visit represents a distinctive opportunity to capture high-risk adolescents missed in other settings. Nearly 1.5 million adolescents use the nation’s emergency departments as their only source of care. These adolescents may be more likely to report drug use, worsening health status, and mental health problems, highlighting a need for PED-based screening . In light of the public health crisis of drug abuse, the PED represents a unique opportunity for identification and intervention of youth at risk for this condition. Drug use screening through interviewing or surveys as part of a comprehensive biopsychosocial screening, rolling bench is recommended when delivering routine or emergency adolescent health care. Studies in busy PEDs have shown that brief screening is feasible and acceptable. The ideal screen should require minimal training and implementation time and should be sensitive enough to detect patients who have alcohol and other drug use and misuse while not over identifying those with non-hazardous use. Many alcohol and drug screening instruments exist; however, one brief instrument that can be incorporated into triage assessments and accurately detect alcohol and drug use issues would be most efficient.

A number of brief screening instruments are appropriate for use in the PED, yet no one instrument is universally utilized. A recent review of pediatric alcohol and other drug screening instruments for the emergency department found evidence supporting the use of a Diagnostic and Statistical Manual of Mental Disorders 2-question instrument to screen for alcohol misuse and a Diagnostic Interview Schedule for Children 1- question instrument to screen for cannabis misuse. Other options for brief drug use screening for adolescents include the Brief Screener for Tobacco, Alcohol and Other Drugs , which asks about past year alcohol, tobacco and cannabis use or the Screening to Brief Intervention tool which identifies frequency of alcohol, tobacco, marijuana and other drug use. The National Institute of Alcohol Abuse and Alcoholism has recommended a brief screen which asks about a teen’s drinking frequency and friends’ drinking, as a potentially effective predictor of current and future alcohol misuse. Recent studies demonstrate the NIAAA two-question screen to be a valid approach for alcohol screening that is briefer than most other comparable screens. If a positive alcohol screen is positively associated with drug use, this may represent a strong screening option for the PED where short implementation time is necessary. The purpose of the present study was to examine whether the NIAAA two-question alcohol screen is also positively associated with an adolescent’s cannabis use disorder , cigarette smoking, or lifetime use of other drugs in a PED setting. A secondary aim was to determine if the association between the NIAAA two-question alcohol screen and other drug use varied by demographic characteristics. The present study is a secondary analysis of baseline data from a prospective cohort design which examined the reliability and validity of the NIAAA two-question screen. Sixteen PED sites from the Pediatric Emergency Care Applied Research Network participated in this study. Youth 12 to 17 years of age who were being treated for a non-life threatening injury, illness or mental health condition were eligible for this study if they were medically, cognitively and behaviorally stable based on the medical team’s recommendation. Exclusion criteria included not being accompanied by an adult qualified to give written permission for the youth’s participation in the study; parents or teens unable to read and speak English or Spanish; or lacking a telephone or an address of residence. A detailed study methodology is described in a previously published paper . After enrollment, an assessment battery that included the NIAAA two-question screen28 and other measures of drug use and risk behavior was self-administered on a tablet computer. The NIAAA two-question alcohol screen28 asks slightly different questions based on whether a teen is in middle or high school. Middle school and high school were determined by age unless participants identified as 14 years which were sorted by grade level . The past year alcohol use question is used to categorize teen risk level based on NIAAA recommendations . Any alcohol use among middle school participants categorizes them at moderate or high risk, while high school users can be categorized as lower, moderate or high risk based on their frequency of use. We have reported on the reliability and validity of this instrument in the PED41; others have reported on its validity in other medical settings. To determine the relationship between the NIAAA two-question screen and CUD, the screen was compared to marijuana diagnoses derived from the substance abuse module of the DISC. For this study, a question about craving marijuana was added so that the CUD diagnosis would be based on DSM-5, rather than the DSM-4, criteria. The tobacco module of the DISC was also administered to assess tobacco use disorders. However, since in the practice setting tobacco use is more commonly examined lifetime tobacco use was coded yes or no. The DISC is the most widely used and studied mental health interview that has been tested in both clinical and community populations. DISC has high sensitivity for psychiatric disorders, including substance use disorders. The Drug Use Questionnaire was used to assess the number of days the teen used cocaine, lysergic acid diethylamide , phencyclidine , inhalants and other drugs in a given time period. Internal consistency of the DUQ is 0.75. The Cochran-Armitage test was used to test the association between the NIAAA two question screen categories and CUD diagnosis, lifetime tobacco use, and lifetime other drug use. A logistic regression was used to test for the association of sex and age group with CUD diagnosis, lifetime tobacco use and lifetime drug use.

A total of 5 items address the student’s own experience with teachers, such as ‘‘they help if I have trouble learning something,’’ and ‘‘they help me catch up if I am behind in class.’’ Each item was scored from 1 to 4 and all 9 items were averaged together to generate on overall score with higher scores reflecting more perceived teacher support. The Cronbach’s alpha for this scale was 0.85 in our sample. For ease of interpretation, this scale was standardized such that a 1-U difference corresponds to a difference of 1 SD. In addition, to capture teens’ personal relationships with adults at school we included the number of athletic coaches and the number of teachers named in each participant’s social network. Family measures. Parenting style was measured via the Index of Parenting Style,30 which assesses the level of acceptance/involvement and strictness/supervision that adolescents perceive their parents to exhibit. On the basis of adolescent responses, parents were categorized as indulgent, neglectful, authoritative, authoritarian, or mixed . We also included 2 measures of perceived parental values related to academic and behavioral competence. Participants were asked what each of their parents thought was the most important thing to do after high school.

Based on their responses we categorized participants as perceiving that all , some or none of their parents thought the most important thing for them to do after high school was to attend college. Participants were also asked how much their parents would approve or disapprove of them using tobacco, alcohol, cannabis grow setup and marijuana at this time in their life . Adolescents who said their parents would strongly disapprove of them using all 3 substances were dichotomized as perceiving high parental value of behavioral competence. A sensitivity analysis using a continuous parental approval for substance use score yielded similar results. To account for the negative family role models with respect to behavior, we included a dichotomous measure of whether 1 or more of each participant’s parents ever used illicit drugs. Peer measures. We included measures of both positive and negative peer modeling regarding academic and health behaviors. These measures included the proportion of peers named in a participant’s social network who engaged in alcohol use, cigarette use, and other drug use in the last month and the proportion of peers named in the social network who had sexual intercourse. Because correlation between these items was moderate to high, values were summed to create an index of risky peer behavior . For ease of interpretation the index was standardized such that a 1-U difference corresponds to a difference of 1 SD.

To measure perceived peer value of academic competence, for each peer named in participant’s social network, participants were asked how much they agreed or disagreed that the peer ‘‘thinks that it is important to do well in school,’’ ‘‘thinks that is it important to attend every class,’’ and ‘‘tries hard in school.’’ We calculated the proportion of peers named in the social network for whom the participant agreed with each statement and then summed these values to create an index of perceived peer value for academic competence . Once again, this index was standardized on the mean and SD of our sample. To measure negative academic peer modeling, we calculated the proportion of peers named in the social network who the respondent reported ‘‘causes or gets into trouble at school.’’ Participants were also asked how many of their close friends had dropped out of school. On the basis of distribution of responses we created an indicator for having 1 or more close friends who had dropped out. A sensitivity analysis using the number of friends who had dropped out of school yielded similar results. Substance use. Participants were asked how many times they drank alcohol, used marijuana, and used any other drug in the last 30 days. A report of any of these behaviors was considered a positive dichotomous measure of alcohol use, marijuana use, and other drug use, respectively. Additional covariates. We selected additional covariates for their potential to impact adolescents’ relationships with teachers or coaches and self-concept. These included sex, grade level, raceethnicity , student-reported household income , and student-reported parental level of education, which was dichotomized as high school graduate or not based on the distribution of responses. In addition, academic performance, both individually and relative to one’s peers, is thought to have a reciprocal relationship with self-concept, and may also determine aspects of a teen’s social network.

As a result, we controlled for the Academic Performance Index growth score of the participants’ school and their self-reported grade point average. The API is based on the California Standards Test . To determine the associations between relationships with teachers and coaches and self-concept domains we used generalized estimating equations to account for non-independence of students clustering within schools, controlling family and peer factors, and additional demographic covariates. We used the Karlson,Holm, and Breen -method to test for mediation along with generalized estimating equations of 30-day alcohol, marijuana, and other drug use, respectively, on relationships with teachers and coaches and self-concept, controlling for demographic covariates, to determine whether self-concept mediated the associations between teacher or coach relationships and adolescent substance use. Because the KHB method does not take into account hierarchical data, we performed the mediation test using logistic regressions. A sensitivity analysis comparing the estimated odds ratios resulting from generalized estimating equations and logistic regression models revealed similar results. Data were analyzed using STATA . Missing data were multiply imputed and represented less than 5% for all variables in the analysis. The demographics are representative of low-income neighborhoods in Los Angeles with the majority of students identifying as Latino . Nearly 40% came from families earning less than $30,000 a year, and for just over half the sample, the highest level of parental education was less than a high school degree. About 45% of the sample was comprised of boys, with equal representation from 9th to 12th graders, and just under 50% attended a charter school. Most parents displayed a mixed parenting style , but over 15% exhibited neglectful parenting. Further, while a large majority of participants reported that their parents highly valued academic competence, nearly 37% perceived low parental value of behavioral competence, and over 11% reported that at least 1 parent used illicit drugs. Just over 10% of the sample named a coach, and 37% named a teacher in their social network, with the number of these adults ranging from 0-5 to 0-8, respectively. Fewer girls and charter school students named a coach in their network. Most students perceived a high level of teacher support, as the teacher support scale ranged from 1.8 to 5 with a mean of 4.3. Approximately one third of respondents reported using alcohol, over 20% reported marijuana use, vertical grow system and 6% reported other illicit drug use in the previous 30 days. Respondents reported relatively risky peer networks. Approximately half of participants reported no peers in their social network who try hard in school or who think it is important to attend every class in school , and 62.9% named no peers who think it is important to do well in school. Over 84% of participants reported that most of the peers named in their network were not disruptive in class, but over 40% reported that a close friend Table 1. On average, respondents reported that 30% of their named peers had ever had sexual intercourse, and that 23% had used alcohol, 5% had smoked cigarettes, and 15% had used other drugs in the last 30 days.

Generalized estimating equations modeling academic and behavioral self-concept were conducted separately. For academic self-concept , higher perceived teacher support was associated with higher academic self-concept . In addition, there was a positive correlation between the number of teachers named in a social network and academic self-concept that did not quite meet statistical significance . Parenting style was also significantly associated with whether teens saw themselves as good students or poor students. Specifically, neglectful, and authoritarian parenting styles were associated with lower academic self-concept scores and authoritative parenting style was associated with higher academic self-concept scores , relative to mixed-style parenting. In addition, perceiving a low parental value of academic competence was associated with lower academic self-concept . Having a peer network that was more engaged in school was associated with higher academic self-concept , but there were no other significant peer factors. Table 3 shows the results of the model for behavioral self-concept. Both higher levels of perceived teacher support and naming more coaches in one’s social network were associated with healthier behavioral self-concept scores. Similar to academic self-concept, authoritative parenting style was associated with higher behavioral self-concept . In addition, more risky peer networks , having at least 1 close friend who had dropped out of school , and the proportion of peers in the network who caused trouble at school were all associated with lower behavioral self-concept scores. We then conducted a mediation analysis to determine whether 1) teacher support and the number of coaches named in a network were significantly associated with 30-day alcohol, marijuana and other drug use; and 2) these associations with substance use were mediated by self-concept. As Table 4 shows, we found that higher levels of perceived teacher support were associated with lower odds of marijuana [odds ratio = 0.76, p = .003] and other drug use in the reduced model. However, after adding self-concept, the full model revealed that these relationships were no longer significant . Using the KHB method to quantify this difference demonstrated that associations between teacher support and substance use were reduced 12.7-28.4% by academic self-concept and 34.2-61.7% by behavioral self-concept, suggesting that self-concept, particularly the behavioral conduct domain, mediated the relationship between teacher support and 30-day substance use. Naming more athletic coaches in one’s social network was significantly associated only with lower odds of marijuana use in the reduced model. Once again, after adding self-concept, this association was no longer significant. KHB analysis demonstrated that academic self-concept mediated 0.7% and behavioral self-concept mediated 19%of the association between coaches and marijuana use . We also tested mediation in the reverse direction— ie, whether teacher support or the number of named coaches mediated the association between self-concept and substance use. Teacher support mediated up to 43.2% of the associations between academic self concept and substance use but only up to 2.1% of the associations between behavioral self-concept and substance use. The number of named coaches mediated only 3.4% of the association between academic self-concept and marijuana use and 2.9% of the association between behavioral self-concept and marijuana use.Adolescence is typically considered a time when peers and parents engage in a contest for influence. We found, however, that positive interactions with adults at school were also significantly associated with healthier academic and behavioral self-concept, even after controlling for family factors, peer influence, and individual academic achievement. Relationships with coaches, which are likely to focus more on general behavior rather than academic competence, was associated with behavioral self-concept, while teacher support was associated with both academic and behavioral self-concept. This suggests that school-related adults in adolescent social networks might significantly influence how teens develop their sense of self. Our findings build on previous work demonstrating that social support is associated with healthier self esteem and predicts improved academic achievement over time by increasing academic self-concept; and that both healthier self-concepts and more social support from adults are associated with lower rates of substance use.5 Our results extend this work by identifying specific school-related adults, namely teachers and coaches, who might meaningfully influence the development of both academic and behavioral self-concept—domains closely tied to adolescent substance use. In particular, the strong association between relationships with school-related adults and behavioral self-concept is a new finding which might, if confirmed, explain 1 mechanism through which school environments shape adolescent health behaviors. Together, these findings point to schools as potential platforms for self-concept interventions, suggesting that the influence of teachers and coaches might be leveraged to help adolescents develop a healthy sense of self and avoid risky health behaviors. By providing teens with opportunities to connect with supportive adults in and out of the classroom, the school environment itself might be harnessed to prevent risky health behaviors.

As shown in Appendix Table 2, the estimates from both models are quite similar to our main Table 2 estimates. In Appendix Table 3, we explore the impact of extending the study window. Specifically, we present results that lengthen the study period to 60 days but include 3 separate indicators for closure days 1-10 , 11-20 , and 21-30 . We break up the extended post-period into three parts because lengthening the post-closure period likely introduces control days to the treatment period since, as documented in McDonald and Pelisek , some dispensaries reopened within a couple of weeks of closure.30 Col shows that increasing the pre-period generates results similar to our main specification with slightly tighter confidence intervals: the estimated effect of the first 10 days of closure on total Part I crime at 1/8 of a mile is almost 30% and is significant at the 1% level. At 1/4 and 1/3 of a mile, the first 10-day estimates are 12 and 9%, respectively, consistent with a decreasing monotonic relationship between the distance around dispensaries and the change in crime. Col shows the effects of dispensary closures 11-20 days after the event. We find effects that are both smaller in magnitude and only significantly different from zero at 1/3 of a mile. Estimates for the 21-30 day closure period in col are much less precise and are inconsistent in sign. This analysis confirms that pre-period trends are not driving our findings and that temporary dispensary closures had an immediate and temporary impact on crime. In Appendix Table 4, we test the sensitivity of the results to confusion over the closure date and potential lags in crime reporting. Specifically, cannabis grow equipment we drop June 6-8, 2010 from the analysis. Because this significantly limits our sample, we show results using 9, 19 and 29 days on either side of the June 7, 2010 but excluding June 6-8.

Those results are quite similar and, in many cases, more precisely estimated than our main Table 2 results. Finally we examine the effect of the multiple counting of crimes due to geographic overlap in dispensary neighborhoods. Because closure status is not geographically clustered, the main effect of this overlap is to mechanically bias our estimates towards zero, leading to an underestimate of the magnitude of the closure effect. To see this, we would ideally analyze dispensaries that have no neighbors within a wide radius, e.g., 1 mile. In practice, less than 5% of dispensaries are so geographically isolated. Consequently, in Appendix Table 5, we show sensitivity checks using the less restrictive requirements that dispensaries have a nearest neighbor more than 1/3 mile or more than 1/2 mile away. Using these restrictions leaves us with 158 dispensaries with a nearest neighbor more than 1/3 mile away and 79 dispensaries with a nearest neighbor more than 1/2 mile away. Across both restricted samples, the magnitude of the change in Part I crime is consistently larger than in the sample as a whole. The results for crime at 1/3 and 1/4 of a mile are statistically significant, despite the greatly reduced sample size. Restricting to dispensaries with a nearest neighbor more than 1/3 mile away, the estimates imply that Part I crime within a radius of 1/4 mile was about 47% higher around dispensaries ordered to close compared to those allowed to remain open, more than triple the main estimate in Table 2. When we restrict to the 79 dispensaries with a nearest neighbor more than 1/2 mile away, the estimates imply that Part I crime within 1/4 mile is 93 percent higher around dispensaries ordered to close compared to those allowed to remain open. While the results in Appendix Table 5 follow the expected pattern of increasing in magnitude as we reduce catchment overlap, the set of geographically isolated dispensaries may differ on other unaccounted for dimensions. As such, we cannot use the difference in these coefficients relative to the full sample to measure the average downward bias. Rather, these results provide suggestive evidence that our main results underestimate the true effect sizes.

We next analyze categories of Part I crimes, which are divided by the FBI into property and violent crimes. We estimate separate models for the following property crimes: burglary, grand theft auto, and larceny theft. Larceny theft is separately broken out as thefts from vehicles and other theft. Arson, a sub-category of Part I property crime is too rare to analyze separately. For violent Part I crime, we analyze aggravated assault and robbery. Murder and rape, which are included in total Part I violent crimes, are also too rare to analyze separately . Table 4 shows the impact of dispensary closures on crime by type using the preferred ITT approach that codes closures according to order status. These results show that the effect of dispensary closures loads on property crimes, specifically larceny, and, breaking that out further, theft from vehicles. As with total crime, the effects are very local and monotonically decrease with catchment area radii. This monotonic decrease in the closure estimates and confidence intervals can be seen clearly in Figures 3 and 4, which plot the implied percent change in Part I crimes and theft from vehicles, respectively, along with 95 percent confidence intervals at distances from 1/8 to 2 miles. At distances of 1/2 mile or greater we find no effect of closures on crime, and the small coefficients with relatively tight confidence intervals means we can explicitly rule out even small increases in crime at these larger distances. At 1/3 of a mile the models imply that property crimes increase by 12%, largely driven by increases in larceny and, specifically, theft from vehicles. Even more locally, the estimated effects imply that thefts from vehicles increase by almost 30% at 1/4 of a mile and by 100% at 1/8 of a mile around dispensaries ordered to close relative to those allowed to remain open. While the percent increase in crime near closed dispensaries is large, proper interpretation of these effects must take into account the low number of crimes around each dispensary on any given day. For example, combining the results of Tables 1 and 2, we see that closing a dispensary leads to just 0.0512 additional crimes per day within a third of a mile of the closed dispensary.

Burglary is the one exception to the general monotonic pattern. Here we find a large, negative and marginally significant coefficient for closures at 1/8th of a mile, positive and statistically insignificant coefficients at 1/4th, 1/3rd and 1/2 of a mile, a small negative and statistically insignificant coefficient at 1 mile, and a small negative statistically significant coefficient at 2 miles. While intriguing, this non-monotonic pattern does not admit to an obvious explanation. In addition, unlike the results for total crime or larceny, the burglary results do not hold up in robustness checks and are based on a very small number of events, vertical grow rack with an average of 0.0245 burglary per day at 1/8 of a mile. As such, this result should be interpreted with caution. As with our main results, we find that results for crime by type are insensitive to the treatment of defiers or the inclusion of the closure date .A crucial question in determining the social costs of crime associated with dispensary closures is whether the changes represent an increase in total crime or a shift of crime across either space or time. If crime is spatially displaced, then the increase in crime near a closed dispensary may be offset by decreases in crime further away. Since our main results show that closures lead to significant crime increases at distances of 1/4 to 1/3 of a mile around a dispensary, spatial displacement would imply corresponding decreases in crime at distances of greater than 1/4 to 1/3 mile. To check for this type of displacement, we examine the impact of closures on crime in concentric rings around each dispensary.32 Specifically, in Table 5 we analyze crime occurring between 1/4 and 1/3 of a mile, 1/3 and 1/2 of a mile, 1/2 to 1, 1/2 to 2 and 1 to 2 miles around dispensaries. At distances of 1/4 to 1/3 of a mile the coefficient on closure is, with the exception of violent crimes, positive. The increase within this band is not statistically distinguishable from zero, however. At 1/3 to 1/2 of a mile, the property crime estimate is negative but close to zero, albeit with a wide confidence interval. Since the overlap issue discussed previously should be exacerbated at larger radii, the magnitude of the estimates within the larger rings could be more downward biased than those at smaller distances. But given that these coefficients are never significant, these results do not provide strong evidence for spatial displacement. Analogous to spatial displacement, temporal displacement of crime would mean that the changes in crime associated with closures are offset by changes in crime either before or after the closure period. While the dispensary closure date was well known in advance, there are no clear “re-opening” dates. As such if criminal activity exhibited a significant ex-ante temporal elasticity, we would expect a decrease in crime around dispensaries scheduled to close but prior to actual closures as criminals waited until June 7 to commit crimes. We find little evidence of pre-closure differences in either the level or trend in daily crime around dispensaries ordered to close relative to those allowed to remain open. Most directly, since extending the pre-period window around June 7, 2010 yields similar results , it is unlikely that a pre-period decline in crime in anticipation of future crime commission can explain our results. In other words, criminals do not appear to postpone crimes in anticipation of the mass closure of dispensaries. Given the variation in pre-closure crime levels, we can generally rule out economically significant temporal displacement in the period just prior to the June 7, 2010 closures.In Los Angeles County, the Department of Public Health is charged, under the California Uniform Retail Food Facilities Law , with enforcing uniform statewide health and sanitation standards for retail food facilities according to the“science-based standards.” DPH inspects all facilities that provide food to the public . Based on the guidelines outlined in the California Retail Food Code , DPH environmental health specialists grade restaurants on various health and sanitation measures including improper holding temperatures, poor personal hygiene of food employees, contaminated equipment and the presence of vermin and, depending on the outcome, may order a temporary shutdown for remediation. Based on a Food Official Inspection Report , restaurants receive a numerical score between 0-100. Restaurants that score 70 and above are given a grade card that must be posted in an easily visible location . Restaurants that score less than 70 receive a numerical score card rather than a grade. Restaurants that score less than 70 twice in any twelve month period are subject to closure and the filing of a court case. Such closures are rare. More commonly, if the inspection turns up a “major violation,” meaning a violation, such as vermin harborage or infestation, sewage disposal problems or food temperature problems, that poses an imminent health hazard, the restaurant is subject to immediate closure without a permit suspension hearing. Restaurants closed for major violations remain closed until a subsequent follow-up inspection confirms that the situation has been satisfactorily resolved. Restaurants are inspected twice a year, although those that handle large quantities of “risky foods” or consistently score low may be inspected three times a year. The DPH may conduct an additional inspection in response to consumer complaints. Individual inspectors work specific geographic areas determined by the local environmental health office. They work with supervisors to set a schedule for restaurant inspections in increments of one or more months. While inspection scheduling is not standardized, inspections are, depending on the specific supervisor, scheduled weeks to months ahead of time. As such, although the timing of inspections are not explicitly randomized, the process makes it highly unlikely that the exact timing of inspections are correlated with trends in crime in the immediate area around each restaurant. In addition, DPH officials have stated that local conditions have no bearing on the timing of inspections.Most closures are caused by “major violations,” with roughly two-thirds of the closures in our sample due to vermin harborage or infestation.

Similar to effects seen in adolescent rats exposed to ethanol, long-lasting effects on learning, memory, and object recognition have been shown in adolescent rats with chronic cannabis exposure , which have been attributed to a reduction in quality or efficiency of synaptic connections in the hippocampus . While most existing studies examine the impact of alcohol or marijuana use separately, understanding the impact of concomitant use is also highly relevant. One study found that use of cannabinoids in a neonatal rat brain enhanced sensitivity to damage from ethanol . The combination of THC and mildly intoxicating doses of ethanol produced widespread and severe neuronal degradation similar to levels observed from much higher doses of ethanol administration. In sum, animal literature has linked both independent and concurrent alcohol and marijuana use to microstructural and macrostructural changes that likely contribute to observed behavioral and cognitive differences, including poorer neuropsychological functioning. The extant human literature also suggests that heavy and recent alcohol exposure in adolescence is associated with poorer neuropsychological outcomes relative to those of non-drinkers . A recent study examining community youth of heavy episodic drinkers relative to their non-drinking peers found that even after one month of monitored abstinence, adolescent drinkers still showed differences in prospective memory, cognitive switching, inhibition task accuracy, verbal memory, and visuospatial construction . More specifically, cannabis trimming tray numerous studies examining neuropsychological impact of drinking among adolescents with alcohol use disorders suggest deficits in verbal memory and recognition discriminability and in recall of nonverbal information such as delayed recall of a complex figure .

Similar to alcohol use, marijuana use during adolescence may also disrupt the normal neuromaturational processes that take place during this time period . After at least three weeks of abstinence, adolescent marijuana users still show decrements in memory, attention, psychomotor speed, and planning and sequencing; increased errors on a speeded visuomotor sequencing task; and more intrusions on word list learning . One study that tested adolescent marijuana users once per week over three weeks of sustained abstinence found initial differences in verbal memory and verbal working memory that improved with three weeks of sustained abstinence, but not to levels of controls . Deficits in accuracy on a visual attention task were seen at the first assessment and across time . Another study found that MJ-using teens continued to show poorer functioning in complex attention, sequencing ability, verbal story memory, and psychomotor speed following one month of monitored abstinence . While multiple studies report neuropsychological deficits in alcohol and marijuana using teens, even after one month of abstinence, one major limitation across these studies is the high rate of comorbid substance use among participants. Many alcohol-using populations have moderate to high levels of marijuana use; similarly, many marijuana-using teens have significant exposure to heavy drinking. Therefore, much of the existing literature cannot report confidently if cognitive decrements are primarily related to alcohol, to marijuana, or to use of both substances. Additionally, few studies have directly compared alcohol-using youth and marijuana-using youth to each other. One study comparing non-using teens, alcohol users, and marijuana users used 12-hour abstinence protocols and 9th grade scores as indications of pre-morbid academic functioning ; another study used marijuana users who had consumed alcohol up to 810 times and other drugs up to 70 times . Therefore, there is a great need to distinguish the impact of alcohol, marijuana, and concomitant use on neuropsychological outcomes using extended abstinence protocols, indicators of premorbid functioning that predate initiation of substance use, and group eligibility criteria to limit exposure to other substances much more stringently.

These limitations are addressed in the current study.We examined the effects of alcohol and marijuana use during adolescence in a sample of substance using teens and demographically similar non-using teens using a neuropsychological battery after four weeks of monitored abstinence. Using strict criteria to differentiate groups, we compared neuropsychological performance among alcohol users, marijuana users, those who use both marijuana and alcohol, and non-using controls. Based on prior adolescent research, we hypothesized that even following one month of sustained abstinence, users of marijuana and alcohol would show poorer performance relative to non-users. Poorer executive functioning and visuospatial ability were expected in the alcohol group, but not in the marijuana group. Poorer task accuracy and psychomotor speed were expected to be most notable among the marijuana users. Given previous animal and human research , we expected youth who use both marijuana and alcohol to show poorest performance in the same domains as heavy users of alcohol or marijuana, while also possibly showing unique changes attributable to concomitant use.In accordance with the University of California, San Diego Institutional Review Board and high school district policies, written informed assent and consent were obtained prior to participation. The current study examined 131 adolescents who were classified into four groups using “episode” to describe the number of days on which a substance was used in a participant’s lifetime: heavy episodic drinking adolescents , protracted marijuana users , heavy alcohol and marijuana using teens , and control teens . The higher group cutoff for alcohol use among MJ youth was used because three MJ participants had 50-75 alcohol episodes; however, they had over 800 marijuana episodes, so 10-20 times more marijuana than alcohol in their lifetimes. Also, in the three months prior to starting the study, MJ youth reported 0 heavy episodic drinking episodes and 0 alcohol withdrawal symptoms. The HED and HED+MJ groups, however, reported 5-20 heavy episodic drinking episodes per month and 3-9 alcohol withdrawal symptoms in the three months prior to study initiation. All participants were drawn from the same schools, and groups were similar on socio-demographic factors including age, gender , ethnicity , grades completed, grade point average , socioeconomic status , family history of substance dependence, and 5th grade California Achievement Test, 6th Edition language arts and mathematics scores . Groups who used similar substances were matched on their common substance in the following areas: lifetime episodes, frequency of recent use , days since use at study initiation, and age of onset of regular use . HED and HED+MJ had a heavy episodic drinking experience 4.18 and 6.75 days per month, respectively; MJ and HED+MJ smoked marijuana 17.78 and 18.38 days per month, respectively .Participants were recruited from San Diego high schools and colleges via mailings and fliers that advertised an “Adolescent Development Project.” No information regarding alcohol or drug use criteria was described in the flier or discussed prior to screening. Participants responding by phone were informed of the study protocol and assessment schedule, potential risks and benefits, and the confidentiality of their participation. All interested teens and their guardians underwent an extensive screening process to determine eligibility, and those potentially eligible were mailed consent packets. After completing the assents/consents, teens and their guardians participated in more detailed, structured clinical interviews. To minimize confounds, exclusionary criteria included history of a DSM-IV Axis I disorder other than substance abuse; extensive other drug use ; head trauma ; a learning disorder; neurological dysfunction; serious medical illness; family history of bipolar I or psychotic disorder; significant prenatal alcohol or drug exposure; sensory problems; use of psychoactive medications; and substance use during the abstinence protocol.After providing their assent/consent, trimming tray for weed adolescent participants and their parents were separately administered confidential structured clinical interviews assessing demographics, social and academic functioning , family history of psychiatric disorders using the structured clinical interview of Family History Assessment Module Screener , and personal history of Axis I psychiatric disorders using the Computerized Diagnostic Interview Schedule for Children [DISC; Shaffer, Fisher, Lucas, Dulcan, & Schwab-Stone, 2000]. Parents completed the Child Behavior Checklist [CBCL; Achenbach & Ruffle, 2000] and teens completed the Youth Self Report [YSR; Achenbach & Ruffle, 2000] to assess levels of internalizing and externalizing psychopathology. Teen substance use history was documented using the Customary Drinking and Drug Use Record [CDDR; Brown et al., 1998], which assessed both lifetime and recent tobacco, alcohol, and drug use , withdrawal symptoms, DSM-IV abuse and dependence criteria, and other negative consequences associated with heavy drinking.

Good inter-rater reliability, internal consistency, and test-retest ability have been demonstrated with the CDDR among adolescent participants . The Timeline Followback [TLFB; Sobell & Sobell, 1992] modified to include other drugs was used to collect frequency and quantity of alcohol, marijuana, and other drug use for the four weeks prior to initiating protocol and for the four week duration in the study.All eligible participants who initiated the study protocol were monitored for abstinence from substance use for four weeks and then assessed using neuropsychological tests at the completion of their abstention period. Prior to the NP testing session, participants provided a urine sample, submitted a Breathalyzer reading , and completed emotional state measures. To minimize the possibility of substance use during the four-week abstention period, supervised urine and breath samples were collected three times weekly to assess for recent use of alcohol with ethyl glucuronide and ethyl sulfate metabolites and use of methamphetamines, cocaine, THC , benzodiazepines, methadone, barbiturates, MDMA , opiates, PCP, and oxycodone. We utilized an observed sample collection procedure to minimize the likelihood of participant tampering. Samples were analyzed by Redwood Toxicology using cloned enzyme donor immunoassay kits. If abstinence maintenance was confirmed via subject self report, Breathalyzer, and quantitative toxicology results, participants continued to be scheduled for appointments. Abstinence was also facilitated using a standardized Motivational Interviewing protocol demonstrated to encourage the maintenance of abstinence for adolescents in prior research . To minimize the impact of study participation on subjects’ daily lives, research staff worked closely with enrolled youth to select a one-month period that did not conflict with birthdays, school events, or breaks. As this was not a treatment-seeking sample , eligibility was not contingent upon a teen’s expressed desire to quit substance use. Instead, participants were motivated by financial compensation and the opportunity to contribute to research. HED, MJ, and HED+MJ youth started the study protocol within three weeks of exposure to the substance of interest . At the time of assessment following one month of monitored abstinence, average days since exposure to the substance of interest ranged from 31-35 days in HED, MJ, and HED+MJ youth .We used chi-square tests and Analysis of Variance to compare demographic characteristics among groups. We used Multivariate Analysis of Covariance to test for group effects on neuropsychological task performance after one month of monitored abstinence. Given that poor externalizing behavior has been linked to academic underachievement, impulsivity, poor decision making, and neurocognitive deficits , CBCL externalizing behavior was used as a covariate in the analyses since the three groups of substance using teens scored higher on this trait. Post-hoc contrasts were examined using Tukey’s HSD tests. Secondary analyses examined the associations between alcohol and marijuana use characteristics and performance on tasks of executive functioning, learning and memory, visuospatial construction, attention and psychomotor speed, and language and achievement. Due to non-normal distribution of substance use characteristics, Spearman’s correlations were calculated to describe these relationships. A False Discovery Rate correction for multiple comparisons was used to recalculate p-values from the outputs . All reported p-values were generated from the FDR correction.We examined neuropsychological differences following one month of monitored abstinence among adolescents with limited substance use history compared to those who predominantly use alcohol, marijuana, or both substances. This study features the design strengths of matching groups on premorbid academic functioning, lifetime and recent substance use characteristics, and recency of use at time of testing. While the performances for each group were predominantly in the average range and no group means suggested clinical impairment, subtle differences were evident between groups, with substance-using groups scoring lower than non-using controls in multiple domains. Importantly, these differences were observed after one month of abstinence, on average, which is sufficient time for acute withdrawal symptoms to abate and for THC to be eliminated from the body. Our results suggest that use of alcohol and/or marijuana produces unique and shared cognitive differences in teens earlier in their use continuum than shown previously. These differences seem to emerge in youth prior to the onset of clinical dependence and in the midst of ongoing brain development. Teens with histories of heavy drinking showed poorer cognitive flexibility, recall and semantic organization of verbal information, and reading achievement relative to non-using controls. Worse performance among HED youth on the D-KEFS Trail Making Number-Letter Switching task suggests poorer cognitive flexibility .

Slower processing speed has also been identified among heavy marijuana using youth , even after one month of monitored abstinence .In sum, adolescents seem to show modest but significant deficits in cognition across multiple domains. In the area of executive functioning, adolescent drinkers show worse decision making and inhibitory control, whereas adolescent marijuana users show worse flexible thinking and more perseverative errors. The area of visuospatial functioning appears especially sensitive to heavy alcohol use as adolescent heavy drinkers show worse spatial operations, block design, complex figure copying, and pattern recognition. Both adolescent alcohol and marijuana users show similar deficits in verbal and nonverbal learning and memory, worse attention, slower psychomotor speed, and lower IQ. Taken in concert, these group findings suggest neuropsychological differences across multiple domains in both heavy alcohol and marijuana using adolescents. Since much of what has been reviewed to this point discusses group findings in the animal and human literature, trim tray it is important to now consider what potential aspects of substance use may contribute most strongly to observed differences. Each substance use characteristic is examined and any association described in the extant literature between that characteristic and a group finding is provided.

As binge drinking and heavy marijuana use are so prevalent among adolescents, it is important to consider studies’ efforts to correlate observed impairments with recent exposure to high quantities of alcohol or of marijuana . Animalresearch indicates that recent exposure to high doses of ethanol results in neurodegeneration of the corticolimbic circuit and more perseverative errors on a spatial learning task . Studies have shown that recent consumption of large amounts of alcohol correlates with reduced white matter integrity in the splenium . Among adolescents, more frequent consumption of alcohol correlates with poorer visuospatial task performance in complex figure delay for females and in block design for all participants . Frequent, heavy use of alcohol was also related to neuropsychological performance over time, with more frequent drinking associated with worse visuospatial memory and verbal short-term memory task performance . Similar to findings for alcohol, studies examining marijuana using youth also found correlations between greater frequency of marijuana use and worse performance on tasks of learning and memory . Smaller right hippocampal volumes were also correlated with greater self-reported cannabis use and with more weekly cannabis use .Age of onset is an important correlate with alcohol-related outcomes as earlier age of drinking onset is associated with greater likelihood of alcohol toxicity induced disruptions in developing brain regions, particularly the frontal lobe , greater lifetime risk for developing alcohol dependence , and elevated risk for myriad social and mental health problems . It is interesting to note that while earlier age of onset relates to long-term alcohol use disorders and worse outcomes, studies have not found consistent correlations between age of onset of drinking and neuroanatomical and neurocognitive measures.

An initial study found a positive correlation between age of onset and hippocampal volume , but a later study failed to replicate that finding . One study found that participants who initiated binge drinking at an earlier age had worse decision making on a gambling task . Age of onset of marijuana use, however, appears strongly related to multiple findings. Age of initiation of marijuana use correlates positively with prefrontal cortex volume, with younger age of first use associating with reduced volume . Alterations of cortical thickness are also related to younger age of initiation of cannabis . Earlier age of onset of marijuana use has also been associated with worse visual scanning performance ; decreases in verbal IQ, verbal recall, and use of semantic categories ; and poorer performance on tasks of sustained attention, impulse control, and executive functioning .When examining the effects of a substance on a developing adolescent brain, it is important to consider the impact of cumulative exposure measured as either total lifetime episodes or years of abuse or dependence. Several studies have identified associations between lifetime drinking episodes and structural, functional, and neurocognitive outcomes. Among adolescents, longer duration of heavy drinking was related to decreased white matter integrity in the corpus callosum , and those with longer lasting AUDs had smaller hippocampi . Lifetime drinking episodes have also been found to correlate with several neurocognitive outcomes. Among adolescents with AUD, greater lifetime consumption correlated with increased perseveration errors on a verbal memory task and worse attention functioning . Among marijuana using adolescents, severity of use has been linked to worse performance on tasks of learning and recall .The correlations between withdrawal and neuroanatomical and neurocognitive outcomes have been examined most extensively in the adolescent alcohol literature. Acute effects of high dose alcohol exposure continue to be experienced in the day or two following alcohol consumption. In adolescents, these effects include headaches, muscle aches or weakness, feeling weak or faint when standing, heart racing, feeling depressed or irritable, nausea, vomiting, sweating, trouble sleeping, or tremor and shaking .

Additionally, youth who develop physical addiction to alcohol can experience alcohol related seizures in the first few days of abstinence . Hangover and withdrawal symptoms are very common following binge drinking and appear to be strongly related to cognitive impairments among teens who frequently binge drink . A body of compelling evidence suggests that it is the repeated withdrawal from alcohol that may be responsible for many of the central nervous system effects of chronic alcohol exposure and that repeated withdrawal from alcohol provokes cognitive impairments . In animals, repeated withdrawal from alcohol resulted in higher rates of seizures during withdrawal than were observed after continuous exposure over the same duration, suggesting a strong association between repeated withdrawals and withdrawal seizure susceptibility .Negative affective states – including hyperirritability, depression, and anxiety that commonly occur among those experiencing post alcohol effects and impact neurocognitive performance – seem to maintain alcohol consumption and promote relapse . The severity of withdrawal-like symptoms is an important indication of neuropsychological impairments in detoxified human adolescents and young adults, which makes the examination of withdrawal’s relation to impairments warranted . Research needs to address whether impairments are likely caused by alcohol itself, by negative affective states provoked by alcohol, or by damage caused by repeated withdrawals. The research is largely consistent in its findings about the relationship between lifetime withdrawal and neuroanatomical and neurocognitive outcomes. Withdrawal experience does not seem to correlate with reduced hippocampal volumes , while it does correlate with reductions in white matter integrity and neuropsychological deficits. Among youth with AUDs, reduced white matter integrity in the corpus callosum was significantly related to the number of alcohol withdrawal symptoms . Among subclinical, binge drinking teens, those with more hangover symptoms showed more compromised white matter in the body and genu of the corpus callosum, frontal lobe projection fibers, and cerebellar tracts . Of note, among adult alcoholics, alcohol-related seizures were associated with smaller white matter volumes in the temporal lobe, suggesting cumulative effects of these withdrawal experiences .Among adolescents with alcohol use disorders, those with more withdrawal symptoms performed worse on tasks of working memory , visuospatial functioning , delayed verbal retention , and attention . Lifetime withdrawal predicted attention and visuospatial functioning at year 8 of a longitudinal study . Withdrawal scores also predicted slower DVT completion times for males, which suggests that withdrawal and hangover symptoms significantly predict deterioration of attention skills in boys who initiate heavy drinking . Recent withdrawal is also important to consider as a potential contributor to brain changes and neuropsychological deficits. Associations between neuroanatomical and neurocognitive measures of interest and recent withdrawal are consistent with findings for lifetime withdrawal. Among youth with AUDs, trim tray with screen those who reported more withdrawal symptoms in the prior three months showed poorer visuospatial abilities, working memory, and attention – even after controlling for gender, history of head injury or learning disability, socioeconomic status , and grades completed .

Similarly, the number of substance withdrawal symptoms in the three months prior to neuropsychological testing significantly predicted verbal learning, recall, and recognition with greater withdrawal negatively affecting immediate, delayed, and recognition memory performance among youth followed over a ten year period . Both lifetime and recent withdrawal showed relationships with poorer visuospatial functioning, memory, and attention. Lifetime withdrawal symptoms may reflect distinct, negative effects on brain functioning, with a particular impact on white matter integrity and on memory and visuospatial functioning.It is important at this time to reflect on some of the methodological limitations of the aforementioned studies. As these studies were done on adolescents after their initiation of alcohol and/or marijuana use, it is not possible to determine if their substance use led to their neuroanatomical and neurocognitive deficits or if those with lower cognitive functioning have a propensity to drink alcohol or smoke marijuana. This issue emphasizes the need for studies to utilize prospective designs to collect data on participants in late childhood or early adolescence and follow them through adolescence. Alternatively, efforts to match groups on aspects of their premorbid functioning would also be warranted. Also of note, in both the adult and adolescent literature of neuroanatomical and neuropsychological outcomes, abstinence periods vary widely , thereby making direct comparisons challenging and leaving unclear the chronicity of cognitive changes among alcohol and marijuana using youth.It is also important to consider differences between clinical and subclinical populations, as much of the original research in the field was conducted on teens in clinical settings. Those in treatment both for alcohol and for marijuana manifest more severe substance use disorders and tend to have poorer cognitive, behavioral, and social functioning . So while more recent efforts to recruit from the community may be more generalizable to the population of adolescent users, these youth may be higher functioning than those in treatment programs. In general, heavy users of alcohol and/or marijuana are also more likely to have other comorbid disorders, making it difficult to disentangle unique effects attributable to the substance distinct from mood, anxiety, or attentional features, unless specific efforts are made by researchers to consider such differences in analyses. While multiple studies reviewed have reported neuroanatomical and neuropsychological differences in alcohol and marijuana using teens, even after one month of abstinence, another limitation across these studies is the high rate of comorbid substance use. Many alcohol-using populations have moderate to high levels of marijuana use; similarly, many marijuana-using teens have significant exposure to heavy drinking. Therefore, much of the existing literature cannot report confidently if cognitive decrements are primarily related to alcohol, marijuana, or to use of both substances. Until this point, studying users of mainly alcohol or mainly marijuana may have limited sample size in a population that is already difficult to recruit and study; so many users studied also have use of other substances. Additionally, the existing literature predominately compares alcohol users to nonusers or marijuana users to nonusers. Existing investigations have not compared alcohol users and marijuana users directly to each other.This review inspired three investigations to address specific areas previously unexplored in the extant literature and/or limitations in the existing research. The first study aimed to make a contribution to the literature on the affective vulnerability processes governing alcohol misuse among adolescents by investigating the rate and pattern of changes in emotional reactivity and distress tolerance during the initial days to weeks of abstinence from alcohol in heavy drinking youth. Adult research has demonstrated improvements in mood with sustained abstinence that contribute to decreased emotional reactivity and improved distress tolerance, but this possibility had not yet been explored in adolescent populations. Many researchers have examined relapse phenomena via self-report outside of a relapse risk context, either using retrospective report of previous relapse events or in the context of longitudinal studies that utilize prospective reports , yet without proximity to the additive impact of stress. This study introduced an objective stressor to examine affective response, cognitive performance, and distress tolerance in heavy episodic drinking and non-drinking adolescents and to assess potential group differences and determine whether affective reactivity, performance, and distress tolerance improve over a four-week period following cessation of substance use in the heavy drinking youth. The utilization of the PASAT-C task created an opportunity to test a negative reinforcement model by employing a behavioral measure that provides measurable responses in close proximity to a stressor. The second study hoped to fill a void in the existing literature by examining neuropsychological functioning during early abstinence in adolescents with histories of heavy episodic drinking as compared to well-matched controls.