Hemp Growing

Among the 3.6 million students with past-month e-cigarette use, more than 80% used flavored products . Although banning sales of e-cigarettes and/or flavored tobacco may reduce adult smokers’ options, such policies may also help combat the epidemic of youth e-cigarette use . Non-tobacco flavored e-liquids are a primary driver of young people’s experimentation with e-cigarettes. In the 2019 National Youth Tobacco Survey, middle and high school students reported flavors as one of their primary reasons for use . The majority of youth e-cigarette ever-users initiated e-cigarette use with a non-tobacco flavored product . Further, initiation of e-cigarette use with non-tobacco flavored e-liquids is associated with more rapid progression in e-cigarette use frequency . Flavors appear to increase the reinforcing potential of e-cigarettes, both in conjunction with and independent of nicotine exposure . Hence, restrictions on non-tobacco flavored e-cigarette sales have gained attention in an effort to dissuade young people’s ecigarette use and the development of nicotine-containing e-cigarette dependence. In the U.S., it is against the law for retailers to sell tobacco products, including ecigarettes, to people under 21 years of age. Nonetheless, underage consumers in the U.S. frequently purchase vaping products at both brick-and-mortar stores and online stores. In a qualitative study, underage young adults in southern California reported buying vaping products from stores by using fake IDs and by frequenting retailers they knew did not have strict age verification. Age restrictions on online sales were evaded by using websites without strict verification, by using online delivery services , and by shipping products to an overage friend’s home . Online age verification is often easy to circumvent. Of the warning letters FDA sent to online retailers selling vaping products in 2018, 29% pertained to selling vaping products to minors . States must enforce the minimum sales age in order to receive full funding from the Substance Abuse and Mental Health Services Administration . However, many jurisdictions implemented the minimum sales age prior to the federal law. Policy enforcement is likely stronger in jurisdictions that had enforcement measures in place prior to implementation of the federal law. In addition, the odds of sales violations vary by neighborhood demographics . Youth who frequently visit convenience stores and other retailers that sell tobacco are at increased risk of subsequent e-cigarette use. Stricter retail restrictions, especially restrictions on the non-tobacco flavored products that young people prefer, may therefore decrease young people’s tobacco use.

Restrictions on flavored products may also discourage young people’s e-cigarette use via their potential impact on risk perceptions. Research indicates adolescents view non-tobacco flavored e-cigarettes as less harmful than tobacco e-cigarettes ,marijuana grow system and current use of non-tobacco flavored e-cigarettes is associated with lower risk perceptions . In sum, flavors increase the appeal of e-cigarettes to young people and may alter their judgment of the risks of e-cigarette use. If flavored e-cigarette sales were further restricted, youth may perceive e-cigarettes as more harmful and may be less likely to initiate use. Prior to the widespread popularity of e-cigarettes, flavored tobacco restrictions in New York City were followed by a decrease in reported flavored tobacco product use among youth . Moreover, research conducted in Massachusetts and Minnesota found that restricting the sale of flavored tobacco products to adult-only stores successfully decreased flavored tobacco product availability . Similarly, California youth and young adults who lived in a jurisdiction that restricted flavored tobacco sales were significantly less likely than their peers in other jurisdictions to obtain vaping products from brick-and-mortar retail sources.A national study estimated that tenth graders’ odds of current daily smoking declined 2% for each 1% increase in average retailer compliance with age restrictions . Recent evidence from Massachusetts also suggests that restricting the sale of flavored tobacco products reduces youth flavored tobacco product use, including e-cigarette use. Among young adults in Southern California, those living in jurisdictions with weaker tobacco retail licensing policies were more likely to endorse flavors as a reason for e-cigarette use compared to those in jurisdictions with stronger policies . Lastly, a few studies have evaluated the effects of San Francisco’s e-cigarette sales ban on young people’s tobacco use. Following the ban, young adults obtained a greater proportion of their e-cigarettes online or through the mail, or from retailers outside the city, yet flavored ecigarette use still decreased overall. Combustible cigarette smoking significantly increased, raising concerns that many young adults may have switched to cigarettes when e-cigarettes were less available . Moreover, a difference-in-difference analysis suggested increased odds of cigarette smoking among San Francisco high school students compared to other districts . Nonetheless, most prior research suggests positive effects of flavored e-cigarette sales restrictions on youth tobacco use. While informative, these studies did not assess the impact of flavored tobacco retail policy on youth e-cigarette risk perceptions. The present study assessed e-cigarette risk perceptions, attitudes toward flavored tobacco policy, and past-month nicotine vaping in a sample of young people in 30 major U.S. cities. Ten of the 30 cities prohibit flavored e-cigarette sales. We hypothesized that young people surveyed in the 10 cities with flavored e-cigarette sale restrictions versus the 20 cities without such restrictions would perceive e-cigarettes as riskier, have stronger beliefs in the effectiveness of flavored tobacco policy, and, among ever e-cigarette users, be less likely to report past-month nicotine vaping.

We also examined demographic differences to characterize young people in the sample reporting past-month nicotine vaping and past-month retail purchasing of nicotine vaping products. Young people were recruited between August 21, 2020 and November 9, 2020 from 30 U.S. cities that are part of the Advancing Science & Practice in the Retail Environment consortium. The cities1 are located in 23 states. At the origin of the ASPiRE project, 27 cities were members of the Big Cities Health Coalition , two cities were added for representation in the southeast , and Providence was added for early adoption of novel retail policies. Using Qualtrics Research Services, recruitment efforts targeted approximately 30 participants per city, roughly balanced on age group and ever e-cigarette use . Recruitment quotas were adjusted as needed to ensure enrollment of approximately 30 participants per city. After a brief online screener, eligible participants completed an online survey of their e-cigarette perceptions and use behavior. Participants were compensated in the form of e-rewards money or points that can be exchanged for gift cards or bank transfers. E-cigarette policies in each city at the time of data collection were derived from the Campaign for Tobacco-Free Kids and supplemented with media sources to determine policy effective dates. Cities were categorized as having a sales restriction on flavored e-cigarettes or no sales restriction on flavored e-cigarettes, based on state and local policies. Dates of state and local Tobacco 21 laws were obtained from the Campaign for Tobacco-Free Kids and from the Preventing Tobacco Addiction Foundation . State e-cigarette tax was obtained from the Centers for Disease Control and Prevention State Tobacco Activities Tracking and Evaluation System . Chicago has a city-level e-cigarette tax and was therefore coded as having an ecigarette tax. A variable was created to reflect cities’ state or local laws raising the minimum legal sales age for tobacco to 21 before the federal law, because such cities likely have stronger infrastructure for enforcing the federal Tobacco 21 law. Cities were coded as 0 , 1 , or 2 . For each of the three outcome variables , null models were estimated to determine whether there was significant between-city variance in each outcome. For outcomes with significant variation between cities, generalized estimating equations tested differences in the outcome as a function of citylevel e-cigarette flavor policy, with individuals clustered by city. Bivariate analyses tested associations between those outcome measures and potential covariates at both the city level and individual level . Location in California and Texas were tested as potential city-level covariates because we sampled from multiple cities in California and Texas,cannabis vertical farming where state-level tobacco policy and enforcement may be a confounder. City-level and individual-level covariates that were significantly related to an outcome in bivariate analyses were included in the adjusted GEE model examining that outcome. Among ever-vapers, GEE models, with participants clustered by city, also examined associations of participant characteristics with past-month nicotine vaping and, among past-month nicotine vapers, purchase of vaping products at a brick-and-mortar retail location . Each characteristic was tested in relation to past-month nicotine vaping and in-store purchasing in separate GEE models. Because these analyses were exploratory, we did not adjust for multiple comparisons. Risk perceptions and policy attitudes had intraclass correlation coefficients < 0.001, indicating that participants’ city of residence did not account for a meaningful portion of the variance in risk perceptions or policy attitudes. Hence, tests of city-level e-cigarette policy on risk perceptions and policy attitudes were not run. Among ever-vapers, a null model of past month nicotine vaping estimated a between-city variance of 0.27. Therefore, analyses of past month nicotine vaping accounted for clustering by city.

Adjusting for participants’ age and race/ethnicity, which were significantly associated with past-month nicotine vaping among evervapers in bivariate analyses, e-cigarette flavor policy was not associated with the likelihood of past-month nicotine vaping among ever-vapers . Full GEE model results are presented in Supplemental Table 1.Participant characteristics are presented by past-month vaping nicotine vaping among those who had ever vaped , in Table 2. Full results from all GEE models are presented in Supplemental Table 2. On average, young people who vaped nicotine in the past month were significantly older than those who had not . Likelihood of past-month nicotine vaping also differed by race/ethnicity . Specifically, compared to non-Hispanic white participants, Black participants were less likely to have vaped nicotine. Gender , sexual identity , and family finances were not associated with past-month nicotine vaping among ever-vapers. Past-month nicotine vaping was more likely among participants who had ever vaped marijuana , but not flavor-only e-liquid or CBD . Past-month nicotine vaping was also more likely among those with lower harm perceptions . Participants who vaped nicotine were significantly more likely to see vaping ads in convenience stores, supermarkets, or gas stations , but did not reach statistical significance for ad exposure in smoke/vape/head shops or online . Having more friends with past-month nicotine vaping and cannabis vaping , living with someone who vapes , and positive vaping attitudes of important others each was associated with a greater likelihood of vaping nicotine in the past month. Likelihood of past-month vaping was not associated with perceived ease of accessing flavored vaping products or flavored e-liquid . Among participants with past-month nicotine vaping, a null model of in-store purchasing estimated a between-city variance of 0.25; therefore, GEE models accounted for clustering by city. Full results from all GEE models are presented in Supplemental Table 3. A majority of young people with past-month nicotine vaping purchased vaping products in retail stores . Young people who did versus did not purchase vaping products in-store did not significantly differ in age, race/ethnicity, gender identity, sexual identity, family finances, lifetime cannabis vaping, lifetime flavor-only e-liquid vaping, e-cigarette risk perceptions, exposure to vaping ads in any venue, friends’ past-month nicotine or cannabis vaping, living with someone who vapes, positive vaping attitudes of important others, perceived ease of accessing vaping products, self-perceived addiction to e-cigarettes, or policy attitudes . Young people who purchased in-store were more likely to use fruit-flavored and menthol-flavored vaping products than those who did not purchase in-store. Likelihood of using mint/ice/frost , candy/dessert/sweets , and tobacco flavored products did not differ between those who did versus did not purchase vaping products in-store. In addition to purchasing vaping products in stores, participants reported using friends’ vaping products , giving someone money to purchase vaping products , buying vaping products online , or receiving vaping products from family . Tobacco retail policies prohibiting flavored e-cigarette sales may benefit young people by decreasing access to kid-friendly products; however, the influence of such policy on young people’s e-cigarette risk perceptions is unknown. Contrary to hypotheses, local e-cigarette flavor policy was not associated with e-cigarette risk perceptions, policy attitudes, or past-month nicotine vaping among young people in 30 U.S. cities. Young people who reported past-month nicotine vaping had lower harm perceptions and viewed flavored tobacco policy as less effective, compared to those without past-month nicotine vaping.

The analysis team met to review and finalize the coding scheme. An iterative process of coding, assessing intercoder agreement, and resolving differences in coding was repeated until a Krippendorff’s α = 0.862 was reached. Research assistants then coded all focus group data. The principal investigator created a subcode for each coded data fragment, which was reviewed by research assistants for appropriateness. The analysis team met and resolved conflicts to achieve a consensus subcoding of data fragments. Research assistants then recoded the data with subcodes within Atlas.ti. A phenomenological approach was utilized to analyze the focus group data . Data relating to EVALI were extracted for participants who reported past 30 days use of e-cigarettes and analyzed for major thematic elements which provided an initial framework to conduct the phenomenological analysis. Following the process described by Moustakas , a textural and structural description of e-cigarette users’ understanding of and behavioral response to EVALI was created for each participant from the focus group transcripts. Textural and structural commonalities among individual experiences were organized into themes to construct a composite description of how e-cigarette users understand and respond to EVALI. The composite description identifies both essential structures of experience as well as thematic variations in meaning. The experience of e-cigarette use within the context of EVALI was composed of four essential structures: awareness, information filtering, risk rationalization, and behavior. Awareness is the initial stage of becoming alerted to and learning about any element of EVALI. Information filtering is the process of comprehending, accepting, and prioritizing the information encountered about EVALI. Risk rationalization refers to the development of rationalizing a course of action in light of information accepted about EVALI, perceptions of harm associated with EVALI, and past and existing e-cigarette behaviors and experiences. Behavior is the action taken in response to risk rationalization. Each domain is composed of interrelated themes which constitute patterns of experience . The highly visible reporting of EVALI cases resulted in a considerable amount of – and sometimes conflicting – information and opinions that had to be comprehended, accepted, and prioritized as salient. The first level of filtering pertained to the very legitimacy of reported EVALI cases. While EVALI cases and reported symptoms were generally accepted as conveyed through information channels, five participants questioned whether EVALI was “fake news,” a “government conspiracy” funded by the tobacco industry, or part of a government effort to ban ecigarettes. A second level of filtering by some participants focused on causes of EVALI.

Three causes of EVALI were the most salient: “fake” cannabis vape products, any “fake” vaping product, and excessive vaping. The most accepted cause of EVALI, reported by nearly a quarter of respondents, was “more of the THC,cannabis grow equipment like fake THC carts” or identification of a particular brand: “Most [EVALI cases] were using something called a Stizzy… a weed type of vape and most of them get fake cartridges.” EVALI was also thought to be caused by any “fake” product , including nicotine and cannabis vaping together. Irreputable products and sources were described as “bad carts… you buy off the street” or “fake cartridges… [that] weren’t like Juul, they weren’t like Suorin, weren’t these name brand trusted sources.” A third accepted cause of EVALI noted by five participants was excessive vaping of nicotine products. Participants were told that “you can actually be harmed by smoking too much” or viewed cases as people who “were smoking three pods a day or something” or “were really addicted to [Juuls].” Accepted information from the filtering process was one variable in developing a risk rationalization which also incorporated previous or existing experiences and beliefs. Among those who accepted the legitimacy of EVALI as a potential source of harm without engaging a second level of filtering on the causes of EVALI, increased risk was rationalized as either a basis for modifying behavior or disregarded altogether .I’m going to do it anyway.” Dual users of cigarettes and e-cigarettes said that “if I wanted to be healthy, I wouldn’t smoke [cigarettes]” or that “I’m already dead right? Because cigarettes are worse.” Among those who engaged in a second level of information filtering, two dominant risk rationalizations were developed which minimized the perceived risk of continued use. The first risk rationalization constructs harm as tied to perceived causes of EVALI, and avoidance of those specific causes as the basis of protection from harm . Participants who concluded that EVALI was related to “fake” cannabis products, any “fake” products, or excessive vaping suggested that because they either did not use “fake” cannabis or nicotine products or vaped infrequently or “in moderation,” they were not at risk for EVALI because they did not use specific product types or vape excessively.

The second risk rationalization references not having experienced EVALI-like symptoms in the past as the basis of protection from harm . For example, one participant suggested that “at this point, I feel that if it [e-cigarette] was going to do that I feel that it would have done it already or something like that, so… I don’t think it’s going to be me that that happens to” encapsulates this point well. Participants who acknowledged but disregarded increased risk of harm from EVALI reported no change in or intention to reduce or stop ecigarette use. On the other hand, participants who perceived increased susceptibility to harm from EVALI considered changing their e-cigarette use with varying degrees of follow up . Some made no change because of chemical dependence/addiction . Though people knew they should not vape, quitting “was easier said than done.” Inability to carry through on desires to quit or cut back were also due to vaping as “like a lifestyle.” Reported behavior change due to EVALI included transitioning to exclusive cigarette use or increased hookah use to reduce vaping. Others were able to reduce use without substituting for other products. Participants “cut back a lot,” were “trying to Juul a lot less,” and not “buying my own” e-cigarettes and only using when offered by another person . Participants who developed a risk rationality which minimized perceived harm based on their understanding of the causes of EVALI or because of past experiences used those rationalities to justify continued e-cigarette use. EVALI “didn’t do anything to dissuade” people from vaping because they felt that “I don’t fall into the category of vaping” that puts them at risk for EVALI, such as cannabis vaping or frequent ecigarette use. Similarly, some participants continued vaping because they only “hit it every once in a while” or thought EVALI was “not going to happen to me because I’ve been doing this for a couple years now. I’ll be fine, you know?” In this study, three essential structures were found to mediate the relationship between exposure to EVALI information and behavior: awareness, information filtering, and risk rationalization. Awareness of EVALI was universally reported, and the legitimacy of EVALI as a health concern was generally accepted. There was suspicion, however, about whether EVALI was “fake news” or part of a government conspiracy. Accepted information about the causes of EVALI included fake cannabis vaping products, any fake vaping products, and excessive e-cigarette use. Behavior was linked to information filtering and EVALI risk rationalization. Those who acknowledged but disregarded the harms associated with EVALI reported no change in behavior. Those who accepted the harms associated with EVALI either reduced their e-cigarette use or intended to but did not follow through due to challenges of addiction.

Continued use was rationalized by not using implicated products, moderate use, or lack of previous EVALI-associated experiences. At the time data were collected, numerous reports on the harms associated with EVALI had been released and reported and the CDC recommended that people should refrain from using all e-cigarette products . Health communications research has found that harm messaging may be effective in discouraging vaping ,vertical grow system which would support the presumption that government reports of harm from e-cigarettes and warnings to refrain from e-cigarette use during the EVALI outbreak would be salient and heeded. However, the results of this study provide possible insights into why harm messages may not discourage vaping in young adult e-cigarette users. The essential structures in e-cigarette users’ experiences described above suggest a central role for cognitive processes in mediating the effect of EVALI information on behavior. Eveland’s emphasis on attention and elaboration as essential cognitive elements of learning from the news are reflected in the awareness and information filtering constructs . Participants were universally aware of EVALI-related harms and connected EVALI information to past experiences and existing knowledge. However, learning from news is also tied to motivation, and Kunda suggests that individuals motivated to reach a particular conclusion may attempt to be rational but selectively search for beliefs and rules or combine knowledge to create new beliefs to support a desired conclusion . This “motivated reasoning” would suggest that participants in this study filtered for information and developed risk rationalizations based on the underlining motivation to continue vaping. Thus, non-compliance with recommendations to refrain from e-cigarette use based on harm messaging may have less to do with the information needs of target audiences and more with their motivation to continue vaping. Importantly, this study identified EVALI specific situational rationalizations that could inform future public health efforts to address EVALI and e-cigarette-related harms that may have an impact on future quitting or cessation behavior . For participants who expressed a desire to cut back use or had begun to successfully do so, the EVALI outbreak acted as a focusing event on the dangers of e-cigarettes. The opportunity to support e-cigarette cessation was missed for some whose difficulty in cutting back or quitting led to continued use or transition to another product. Though both universities from which study participants were recruited have student health centers that offer cessation services, none of the participants who attempted or considered cutting back or quitting mentioned knowing about or seeking services from the student health center or other resources.

This underscores a potential need to make available cessation services tailored to young adult e-cigarette users and communicating the benefits of these programs from a harm reduction perspective; the results of this study provide some potential dimensions on which to tailor such programs. Outreach for cessation services for young adults through colleges and universities may be particularly important during focusing events to take advantage of heightened interest in cessation due to concerns related e-cigarette harm prompted by EVALI. The study was limited to college-going young adults, and thus additional research is needed among a community sample of young adults. Limiting participants to students at two universities may bias results to reflect the pool of knowledge or experiences available at those two universities. In addition, the sample of students in the analysis was drawn from those who have used tobacco products in violation of university policy and may have been particularly amenable to information justifying e-cigarette use, dismissive toward information discouraging ecigarette use, or doubtful of their ability to change behavior. Because this study focused on current users, we were unable to explore the ways in which adverse events may lead to quitting e-cigarettes. The results of this study are not generalizable to all college going young adults but provide descriptions of risk rationalities to be explored in future inquiry. While the risk rationalities described may not be exhaustive of e-cigarette user experiences and textural and structural descriptions could not be created for 9 focus group participants, the study findings provide a basis for guiding future research for public health actions against EVALI. Finally, this study highlights the need for greater understanding of how urgent public health events with large information gaps, such as EVALI and COVID-19, are understood by at-risk groups, and the most effective communication and intervention strategies to bring about desired change. Emotional health is an important component of overall well-being. Negative emotional functioning is closely associated with poorer physical health and everyday functioning, greater disabilities, and shorter lifespans . Poor emotional outcomes are common among persons living with HIV . Compared to HIV- individuals, PLWH are at greater risk for major depressive disorder and experience worse health-related quality-of-life, depression, and anxiety .

We used a likelihood ratio test to compare the fit of this model using an exchangeable covariance structure, which restricts the variance in pre and post intercepts to be equal, to one with an unstructured covariance structure, which allows the variance to differ pre- and post-Prop 47 implementation, as a test of the change in county variance. The latter model is the most flexible and was used to generate the policy effects on the marginal probabilities of felony conviction. For county-specific estimates of outcomes pre vs. post-Prop 47, we generated empirical Bayes estimates of county random pre- and post-Prop 47 implementation intercepts from the models with unstructured covariance and calculated the linear combinations of fixed and random effects corresponding to pre- and post-Prop 47 periods. We also used fixed effects models with county dummy variables, interacted with the pre-post Prop 47 variable to generate marginal probability estimates of within-county pre-post change. A large proportion of arrests had no disposition . We assumed these cases were either never presented to the district attorney or the district attorney did not file charges, and therefore assigned an outcome of no conviction. We compared case characteristics for those with and without dispositions and found support for this assumption. Those without dispositions were less severe cases, and therefore less likely to result in conviction. For example, a larger proportion had no concurrent arrests . They were also less likely to have concurrent felony arrests . It is possible, however, that some of these cases resulted in convictions and the disposition was never reported by the court. We therefore conducted a sensitivity analysis that assumed the most severe extreme: that all sale/transport cases with missing dispositions received a felony conviction, and that all Prop 47 cases with missing dispositions received felony convictions if they occurred in the pre-Prop 47 period or if they included a concurrent felony arrest in the post period. Prop 47 arrests without concurrent felony arrests in the post period are unlikely to have received a felony conviction,cannabis growing facility since the Prop 47 offense was at that point classified as a misdemeanor. Changes in the outcomes of Prop 47 arrest events must be considered in the context of potential changes in the composition of arrestees .

When comparing the full sample prior to propensity score matching, a greater fraction of post-Prop 47 arrest events had concurrent arrests of other types , suggesting a decline in arrests when drug possession was the sole offense. Post-Prop 47 arrestees also appeared to differ in terms of criminal histories, with more prior arrests . The propensity score matched sample had better covariate balance. For sale/transport arrests, pre and post groups were much more similar . Though they were not compared statistically, we find the population arrested for these offenses appears quite different from those arrested for Prop 47 drug offenses. Prop 47 offenders had more numerous but lower level prior arrests and convictions. Racial differences were notable as well, with larger racial disparities among sale/transport arrests .After Prop 47 was adopted, Prop 47 drug convictions declined in both those arrested for Prop 47 drug offenses and those arrested for sale/transport. For those arrested for sale/transport, the decline in convictions overall was approximately equal to the decline in Prop 47 convictions. Although for the Prop 47 group, the percentage point decline in Prop 47 convictions was slightly larger than the decline in overall convictions, suggesting that it may have become more common to convict these arrestees of other crime categories. The question then becomes, which type of convictions replaced the Prop 47 convictions, if any, and did these replacements counteract potential reductions in felony convictions for Prop 47 offenses? Looking first at the Prop 47 group, there was a 14 percentage point decline in felony convictions , from 21.2% to 6.9%. This approximates the percentage point decline in felony Prop 47 convictions , suggesting felony convictions for other concurrent offenses did not increase. This is corroborated by the break-down of convictions for other offenses, which shows increases in convictions for misdemeanor drug and misdemeanor “other” categories, but not felony offenses . For example, the most common concurrent felony offense was felony property, present for 9.9% and 9.8% of Prop 47 drug arrests in pre and post periods, respectively. Yet the proportion of arrestees who received convictions for felony property offenses did not rise: 2.5% pre and 2.1% post.Declines appear to be driven by declines in the fraction of these arrestees who were ultimately convicted of felony Prop 47 offenses.

The likelihood of any felony conviction in this group declined 7.1 percentage points, approximately the drop seen in the proportion convicted of a Prop 47 felony with no other felony drug conviction . In contrast, no significant change occurred in felony convictions for sale/transport, suggesting prosecutors did not pursue more convictions for these offenses as a means to maintain prior levels of felony drug convictions post-Prop 47.With regard to Prop 47 arrests, pre and post estimates for each county suggest counties where felony convictions were more likely pre-Prop 47 were reduced towards zero to a greater degree, such that post-Prop 47 outcomes were more similar across counties. Mixed models with random pre-Prop 47 intercepts, random coefficients for the policy effect, and an unstructured covariance structure allowing for a correlation between intercept and slope random effects, showed a significant, negative covariance between random effects . Aligning with the pattern depicted in Figure 3.2, this suggests counties where felony convictions were more likely in the pre-period also declined more towards the less punitive counties, reducing the variance across counties. The reduction in county differences is corroborated by variance estimates from models with county specific random intercepts for the pre and post periods . We find a larger variance in county random intercepts in the pre-Prop 47 period . The likelihood ratio test comparing an exchangeable covariance structure as a nested model indicated that the unstructured covariance structures which allowed pre- and post-Prop intercept variances to differ, was a better fit to the data . To put this in concrete terms, of the 56 California counties, prior to the policy the most punitive county had a conviction probability of .38 , whereas the least punitive county had a conviction probability of .04 . After Prop 47 was adopted,cannabis grow system the most punitive county had a conviction probability of .19 whereas the least punitive county had a conviction probability of .02 . Another way to conceptualize these results is in terms of how discrepant the statewide probability of felony conviction was from the least punitive county pre-Prop 47, and the extent to which that discrepancy changed post-Prop 47. Prior to Prop 47, the statewide probability of felony conviction was 17 percentage points higher than the least punitive county , meaning 81% of statewide felony convictions following Prop 47 drug arrests would not have occurred if prosecuted in the least punitive county.

Whereas after Prop 47, the statewide probability was just 3 percentage points higher than the least punitive county prior to passage.There was also significant variation across counties in the likelihood of felony conviction following a sale/transport arrest , ranging from 0.05 in Merced County to 0.51 in Calaveras County in the pre-Prop 47 period. However, mixed model results indicated the significant variance in the pre-Prop 47 period , did not decline post-Prop 47 . This suggests that, while people arrested for sale/transport were less likely to ultimately get a felony conviction after Prop 47 was adopted, this effect did not vary substantially across counties, and no county showed an increase in felony conviction probability for sale/transport arrests. In other words, it does not appear that more punitive counties altered plea bargaining practices for sale/transport arrests to retain pre-Prop 47 levels of felony convictions, as this would have resulted in an increase in variance in felony conviction probabilities for this category of arrest. Findings aligned with sensitivity analyses that assumed all cases with missing dispositions received felony convictions .In this study of the change in felony convictions in California counties after Proposition 47 reduced criminal penalties for drug possession, we found significant declines in the likelihood of a felony conviction following arrests for Prop 47 drug offenses and non-Prop 47 felony drug offenses . Prior to Prop 47, dramatic geographic inequalities in probability of felony convictions after drug possession arrests prevailed between counties, and these geographic inequalities were substantially reduced after adoption of Prop 47. The reduction in felony convictions aligns with reports from the Judicial Council of California on reductions in felony filings following Prop 47 passage , while providing new evidence that reductions led to declines in geographic disparities in felony convictions for drug arrests. By holding county-specific case characteristics constant across time, this study identified a reduction in the excess variation that was attributable to county practices. This impact likely reflects that Prop 47 eliminated prosecutorial discretion for how drug possession can be charged. While previous research has found that the county-specific interpretation and implementation of reforms tends to reinforce the preexisting prosecution and sentencing practices within the county , results from the current study do not indicate counties attempted to mitigate the effects of Prop 47 with felony filings for concurrent offenses, or reducing plea bargaining for sale offenses.

Several factors could explain why Prop 47 led to reductions in geographic disparities in case outcomes, when other reforms have not. Prop 47 was a voter initiative, and considering the influence of community priorities for law enforcement on charging policies and decisions, prosecution practices may be more responsive to these types of reforms. Secondly, Prop 47 called for reduced criminal penalties, whereas prior studies have evaluated reforms like three strikes laws which maximize punishment. Maximizing punishment is costly, whereas reducing it can assuage overburdened courts. Therefore, we may be more likely to see change resulting from reforms that call for lesser criminal penalties, and especially when that call comes from the public. Reducing variation in the likelihood of a felony conviction for two equivalent cases mitigates inequalities in criminal justice exposure due to unequal applications of the law. However, requiring that all drug possession offenses be prosecuted as misdemeanors also suggests that cases with different characteristics are now being treated more similarly. A defendant can still be convicted of a felony for concurrent felony offenses, so it is the effect of criminal history on case outcomes which we would expect to be minimized post-Prop 47. Criminal history is strongly associated with race/ethnicity, which may reflect biases and practices in drug law enforcement , while increasing the severity of punishment for subsequent drug offenses . There is evidence Prop 47 in fact reduced the effect of criminal histories in San Francisco, where prior to Prop 47, racial disparities in case dispositions and sentencing were attributable to more extensive pretrial detention and criminal histories among black defendants . When Prop 47 reclassified drug possession offenses to misdemeanors, these characteristics had lesser effects on case outcomes, and racial disparities declined. Further research could assess whether findings from San Francisco apply statewide. There are also implications for substance use disorder treatment. Prop 47 generated $103 million in savings in the first year, awarded through grants to counties to increase access to substance use disorder and mental health treatment, and education . Counties with few felony convictions pre-Prop 47 may have had greater support for and availability of drug diversion options which allow dismissal of charges for successful drug treatment completion. However,Prop 47 generated concerns that without the possibility of a felony conviction, the incentive to engage in treatment would be removed . Prior research has suggested that, as compared to volitional substance users, individuals with more severe substance use disorders tend to fail to meet the court’s conditions for diversion and ultimately receive harsher termination sentences . If this were the case, it would be logical that this group would opt out of diversion options now that the sentence for drug possession is less severe. Whether this is the case, and if so, understanding successful strategies counties have developed to increase access to needed treatment through other routes, would be valuable. CA DOJ’s Statewide Automated Criminal History System data is the most comprehensive data source available for studying criminal justice policy changes in the state, and has been used in significant studies of Prop 47, as well as other reforms such as Prop-36, which increased drug diversion following arrest .

A discussion of agricultural policy can be organized in a variety of ways. In this chapter we examine both major policy tools and major commodity-specific programs to summarize the influence of government. In order to provide a summary measure and a framework for the discussion, we have developed Producer Support Estimates by policy and by commodity for California agriculture.The Producer Support Estimate can be used as an approximate indicator of the magnitude of the net subsidy from a policy. The PSE is a widely applied summary measure of agricultural policy that attempts to measure the money value of explicit or implicit income transfers to agriculture. When calculated as a ratio of total transfer to total industry revenue, the percentage PSE is a rough guide that may be compared across commodities, time, and national or other geographic boundaries. When these comparisons are interpreted with care, they provide useful summary indicators. The PSE may also be decomposed by policy type to indicate the relative importance of different policies , 2002. The Producer Support Estimate is not a measure of production subsidy. It measures all transfers to an industry, including those that may do little to stimulate output. The PSE is not a substitute for a measure of import protection or export stimulant. Nor is the PSE a measure of producer benefit from government programs.The PSE does not offer a substitute for a full analysis of the market and non-market effects of government programs. It is simply a convenient summary measure of a variety of agricultural programs that does not require a full analysis of each industry. Changes in the PSE do not necessarily reflect changes in government programs. In particular, for a PSE that contains aspects of trade barriers, price support,mobile vertical rack or deficiency payments, the movement of market prices may dominate movements in the PSE over time. This means also that a PSE for a single year may not reflect accurately the degree of government support for a commodity in other years. Even with these limitations, we believe that it is useful to summarize government policies affecting California agriculture by using a variety of decompositions of the PSE for recent years.

The following sections discuss the PSE by program or policy category and by commodity, using recent data. The dollar value of the PSE is designed to reflect the government support provided to a commodity industry from a variety of policies and programs. We have used a large number of sources for information on budget outlays, internal and external prices, quantities, and other data that enter the calculation of the PSE. For many of the programs there is relatively little change from year to year. For these we have mainly use the most recent year available, often federal fiscal year 2000 , fiscal year 2001 or 2002. In some cases we use calendar year 2001 or calendar year 2002 data. In many cases we measure a portion of the government support as an average of recent years. For example, for commodity payments under the Farm Bill we use the average for crop years 2000 through 2002 for loan base program benefits and federal fiscal years 2001 through 2003 for payment programs under the Production Flexibility Contracts, Market Loss Assistance, Counter Cyclical Payments and Direct Payments. For discussion of the FSRI Act of 2002 see USDA publications by Westcott, Young and Price, and Sumner, 2003. For broad-based input subsidies, we use national data and allocate a share of the national total to California based on California’s share of national receipts. We then allocate the California total to commodities within California by their share of California agricultural receipts. In other categories of support, we use the California budget data for California fiscal year 2000 or 2001 as available. The California fiscal year runs from July 1 to June 30 so, that fiscal year 2001 runs from July 1 2000 to June 30 2001. Other specific measurements or data issues are dealt with below when we discuss individual programs and policies. The appendix contains a detailed description of our data and calculations. The PSE calculations and the percentage PSE results would differ somewhat if we chose different years or calculation methods, but, under any reasonable procedure, the pattern across commodities and policy instruments would differ little from the results presented here. The state average PSE would also change slightly if we used different base years. However, we do not believe that the current estimate represents any systematic bias. The crop PSE has likely been declining gradually over time as the share of relatively less subsidized crops has expanded. However, dairy, which is a high subsidy commodity, has an expanding share of California farm value. As noted in Table 1, the state PSE is about $3 billion or 10.7 percent of the total value of output and payments . The OECD calculates and reports PSEs for member countries for six major crop categories and seven livestock products. Fruits, vegetables, and other horticultural crops are not included in OECD figures.

For 2001, the OECD reports an aggregate PSE range from about 1 percent for New Zealand to over 69 percent for Switzerland . Norway, Iceland, Japan and Korea all have PSEs over 59 percent. The average PSE for all OECD member countries in 2001 was 31 percent . The OECD reports an aggregate PSE of 21 percent for the United States. For the thirteen commodities classified by the OECD, the average PSE in California is roughly equal to that of the United States as a whole. Support levels tend to be lower for fruits, vegetables and other horticultural commodities in the United States and some other countries. The crops that are less subsidized are particularly important inCalifornia and therefore the average PSE we report is well below the PSE for the United States as a whole as reported by OECD. Figure 1 illustrates substantial variation across commodities in the percent PSE. At that high end, sugar has a PSE of 63.9 percent. Rice is next at about 60.5 percent followed by cotton at about 40.5 percent. Wheat has a PSE of about 29.5 percent. Dairy, the state’s most important commodity in terms of value of production has a PSE of 33.4 percent. Feed grains, which include corn, oats and barley, have a PSE of about 24.3 percent. The PSEs for all other California commodities are in the single-figure percentage range, which is below the state average of 10.7 percent. Alfalfa and hay, for example, has a PSE of about 3.4 percent. Among the horticultural crops, PSEs range from 3 percent to 5 percent. Other livestock and poultry and the remaining crop categories have PSEs between 2 percent and 5 percent. These low PSE groups include such important California crops as nursery and flowers, grapes, lettuce, tomatoes, almonds, and strawberries. As background to further discussion, Figure 2 shows the distribution of total agricultural receipts in California by commodity category. The two broad categories of horticultural crops comprise well over half of all agricultural receipts in California. Dairy is the most important single commodity with about 17 percent of all receipts. Of the field crops, alfalfa hay is most important, followed by cotton and rice. Figure 2 is presented to provide a basis for comparison with Figure 3,vertical grow rack which shows the distribution of total support by commodity. Now the dairy industry is dominant in terms of its share of total support. Dairy is an important industry in California and also has a relatively high degree of government support. About 54 percent of all support in California agriculture is provided to the dairy industry. Notice that, because of their importance in total receipts, even the less subsidized categories of horticultural crops receive a combined total of over 19 percent of all the PSE for the state. Also, the heavily subsidized but relatively minor crops, cotton and rice, show up significantly in Figure 3. Table 2 provides an alternative categorization of the aggregate PSE. Rather than providing a distribution across commodities, Table 2 distributes the PSE by policy area and more specific policy tools. Import barriers account for the largest share of support, followed by government payments. Input assistance is ranked third. By far the most important policy tool in terms of the aggregate PSE is the dairy import barrier, valued at more than $1.15 billion per year.

Government payments are an important policy, accounting for an annual average of $210 million in Market Loss Assistance payments and $194 million in Production Flexibility Contract payments . Support from marketing loan benefits and Loan Deficiency Payments is valued at nearly $277 million. Direct payments account for about 25 percent of the total support in California agriculture.Dairy policy in California is important and unique. Policy governing the industry is highly developed and associated with a substantial share of industry revenue. It is unique in the sense that some policy instruments are unlike those used in other agricultural industries and, whereas much of California dairy policy is the same as in other parts of the United States, some is the instruments are unlike those used elsewhere. The California dairy industry participates in the U.S. federal price support program, the direct payment program and the industry benefits from U.S. import barriers and export subsidies. But California operates its own regulated milk marketing system, which has some features that differ from the federally regulated system governing most milk markets outside California and some federal programs have different effects in California . The federal price support program for milk in the United States is implemented with a government purchase program for manufactured dairy products. The USDA purchases butter, non-fat dry milk , and American cheese from processors at prices calculated to ensure that the farm price of milk used for the manufacture of those programs will generally remain above the legislated support price. From 1990 to 1995, the price support program included a small assessment on milk production to help offset the budget cost of the price support. The assessment varied from year to year and was implemented in a complex way, but was essentially a tax on milk output of approximately $0.11 per hundredweight . The FAIR Act of 1996 was to have eliminated price support program, but that was first delayed and then reversed. The dairy price support program was phased down 15 cents per hundredweight per year, from $10.35 per hundredweight, and was supposed to be completely eliminated by the year 2000 . The assessment on dairy production was eliminated immediately and this affected producers immediately . The FSRI Act continued the price support until 2007 at a rate of $9.90 per hundredweight of milk. Trade barriers are the most significant feature of U.S. dairy policy, and no serious trade policy reform was even contemplated in the discussions leading to the 1996 FAIR Act or the FSRI Act of 2002. In general, imports of dairy products in the United States have been limited to about 2 to 3 percent of U.S. consumption. The United States maintains binding tariff-rate quotas with high in-quota tariffs for imports of most major dairy products. These trade barriers have insulated U.S. dairy product markets from world market forces, with domestic prices for major agricultural products typically significantly higher than world prices. California’s dairy industry, which produces nearly half of the nation’s non-fat dry milk and approximately 20 percent of its cheese, benefits from these border measures. As part of the Uruguay Round Agreement on Agriculture that took effect in 1995, the system of absolute quotas gave way to a system of tariff-rate quotas . However, the second-tier tariffs that limit over-quota imports are prohibitively high; therefore, the effects of the TRQs remain the same as the absolute quotas that were replaced. The Uruguay Round GATT agreement also provided for a gradual increase in the quantity of dairy product imports into the United States under the TRQs. This provision allowed for a gradual increase in import access into the U.S. dairy market until 2000. The North American Free Trade Agreement , which became effective in 1994, eliminated dairy trade barriers with Mexico, but Mexico is a high-cost milk producer and so no new imports have arrived.

In addition, most cities cited incomplete sidewalks and missing or unmarked crosswalks within their industrial areas that need repair. However, while biking and walking to work may sound attractive, cities must thoroughly examine whether or not active commutes are suited for their industrial districts and employees. Bicyclists and pedestrians may face a series of challenges in doing so, and the supporting infrastructure may also pose challenges for the industry’s goods movement system. For instance, many industrial shifts occur during off-hours; biking to or from the night shift may not be an attractive or safe option. Also, bicyclists and pedestrians may simply feel unsafe traveling in an aesthetically unpleasant environment and in close proximity with trucks. From the goods movement perspective, bicyclists and pedestrian infrastructure may stifle their operations. For instance, the West Oakland specific plan includes bulb outs and bicycle boulevards on truck routes. Going forward, decisions about bicycle infrastructure placement must be intentional and clear about who they are intended to benefit. The PPA program provides an opportunity to address last-mile access for workers traveling to industrial businesses that operate within the regional economy. The following recommendations, which were developed based on conversations with city staff, could inform a transportation component of the PPA program. Require comprehensive, multi-modal planning that would acknowledge the trade offs between different types of last-mile options. In some places,cannabis growing supplies shuttle services may be a better option than active transportation, and vice versa. A comprehensive plan would require cities to prioritize between modes. Set guidelines based on lessons learned from case studies. These guidelines could encourage institutional arrangements for last-mile shuttles that would provide targeted services that meet the needs of industrial businesses and employees. The regional framework of the PPA program would allow for a more holistic set of guidelines that cities on their own would not necessarily recognize. Provide funding for at least some aspect of last-mile access improvements.

Although the specific opportunities available for funding are not yet clear, funding opportunities such as planning and technical assistance grants, similar to those provided through Plan Bay Area’s Priority Development Area , could be linked to the PPA program. In addition, given ABAGMTC’s role as a transportation planning and financing agency, some of the agency’s federally allocated transportation funds could be directed towards transportation connections that facilitate improved access for workers commuting to industrial employment centers. Going forward, the PPA program should consider last-mile solutions in the context of a comprehensive transportation plan that examines the needs for both people and goods, as well in the context of the PPA’s broader goals. Shuttle services and bicycle and pedestrian improvements are just a few approaches to last-mile connectivity; other solutions should be considered. Furthermore, a focus on last-mile connections alone will not address the needs of those who do not live near transit. Also, the last-mile approach also may not be suitable for more suburban areas that lack robust regional transit options. In addition, all jurisdictions reported that workers travel to jobs in their jurisdiction from faraway places since they cannot afford to live nearby. This challenge brings up the inter connectedness of the high cost of living and workforce challenges across the Bay Area. Given the broader economic development goals of the PPA program, the policy could attempt to address this challenge by aligning with a jobs to housing goal for communities with a large share of affordable suburban housing, but whose workforce commutes long distances to find middle-wage jobs. Overall, the PPA program could support the planning for and provision of improved last-mile access as one element of a transportation component that should acknowledge broader accessibility and policy goals.People living with HIV experience high rates of mental illness, including elevated rates of depression and anxiety . In the United States , poverty and social deprivation are concentrated among PLHIV , and may contribute to poor mental health. An important challenge that low-income PLHIV in the USA frequently face is food insecurity , which includes food insufficiency and hunger, poor quality diets, persistent uncertainty around access to food and having to engage in personally or socially unacceptable food procurement .

Food insecurity has been associated with a range of poor mental health outcomes including depression , anxiety , symptoms of post-traumatic stress disorder , substance use and suicidality. While people who experience mental illness likely face more barriers to accessing healthy food, evidence from longitudinal and qualitative studies indicates that food insecurity contributes to symptoms of common mental illness . Provision of food support to food-insecure individuals in a manner consistent with the preservation of dignity has been shown to reduce symptoms of depression . These findings raise questions about how symptoms of common mental illness occurring in the setting of adverse social and structural factors should be addressed. Mental illness and its treatment are often formulated according to a ‘bio-psychosocial’ model in which multidimensional influences on mental health are addressed concurrently through psychotropic medications, psychological interventions and services aimed at improving social circumstances. Yet, in practice, psychotropic medications often predominate. In the USA, data have shown significant upward trends over the past two decades for the use of psychotropic medications alone, compared to significant downward trends for the use of psychotherapy and psychotropic medications together or psychotherapy alone . One in six US adults is now prescribed a psychotropic medication, rising to one in five among non-Hispanic White adults and one in four among adults aged 60–85 years . Pharmaceutical drugs are prominent for several reasons. Psychotropic medications have the most extensive evidence base among mental health interventions, as their effects can be measured through randomised controlled trials more easily than other forms of intervention. In meta-analyses of trials, common classes of psychotropic medications including antidepressants and antipsychotics show modest but significant therapeutic effects for their respective indications . Prescribing drugs is also less labour-intensive than psychological or social interventions, and often more accessible and time-efficient for service users. In the USA specifically, the market-based structure of the healthcare system may contribute to higher rates of psychotropic medications, which have the financial and promotional backing of for-profit pharmaceutical companies . Conversely, reimbursement rates for non-pharmacological treatments by Medicare have been falling steadily for many years, driving psychologists and other allied professionals away from low-income service users .

Furthermore, psychotropic medications adhere to a medical model of intervention that accords with the clinical education of prescribers. The paucity of social science training in clinical curricula leaves clinicians lacking the intellectual tools and frameworks to fully understand how social-structural issues may drive distress . Consequently,cannabis indoor growing social interventions may be placed at lower priority than pharmaceutical drugs by default, principally through unfamiliarity and misunderstanding on the part of clinicians. The vulnerability of public funding for social support to changes in fiscal policies and political ideologies may also contribute to the primacy of pharmacologic interventions. In the USA, public spending on social safety net institutions has undergone a sustained reduction since the 1980s . The welfare reforms of 1996 had a particularly detrimental effect on the provision of social support, significantly curtailing access to government income for non-disabled adults, with the most severe restrictions targeting those without dependent children . Notably, this development has left federal disability income as one of the last forms of substantial government assistance available to many indigent adults in the USA . Recent studies have suggested that this shift may be fuelling a ‘medicalisation of poverty’, as diagnoses of chronic illness – and particularly mental illness – play an increasingly important economic role for struggling adults to obtain income security through disability status . In this respect, diagnoses of mental illness, accompanied by treatment with psychotropic medications, can act as an important gateway to a level of income stability otherwise unobtainable for many in the current US context of widespread working poverty under welfare reform . Identifying these social and economic realities does not imply that disabled individuals are malingering, or that clinicians are prescribing for non-clinical reasons, but suggests instead that we consider the impact, at a population level, of structural factors that incentivise the prescription of psychotropic drugs for socially deprived individuals. These arguments raise the question of whether social adversity might drive higher rates of psychotropic prescriptions, independent of psychiatric symptoms. Few empirical studies have attempted to investigate this possibility. We used data from the Women’s Interagency HIV Study , an ongoing prospective cohort study at nine sites across the USA, to investigate the associations between food insecurity and psychotropic medication use among a broadly representative population of women living with HIV in the USA. Our previous studies in the WIHS cohort have demonstrated dose–response relationships between food insecurity and poor mental health outcomes, including depression , anxiety, stress, symptoms of post-traumatic stress disorder , substance use and mental health-related quality of life . Here we used a cross sectional sub-sample of the WIHS cohort for which data on psychotropic medication use were available to test two successive hypotheses: food insecurity would be associated with psychotropic medication use in a dose–response relationship among women living with HIV, mirroring the dose–response relationships between food insecurity and symptoms of common mental illness found in previous studies; and if we additionally adjusted for symptoms of common mental illness, any positive associations between food insecurity and psychotropic medication use would remain significant.Our study was a cross-sectional analysis of data from the WIHS, a prospective cohort study of HIV-seropositive women and demographically similar HIV-seronegative women in the USA. Cohort recruitment, demographics and retention are described elsewhere .

WIHS participants undergo structured interviews and physical examinations every 6 months at nine sites across the USA and have blood and other biological samples taken. The WIHS began with baseline recruitment in 1994 and has undergone three recruitment waves since. Beginning in 2009, a standardised and detailed neurocognitive assessment was added to the WIHS Core exams and administered every 2 years. From April 2013 through March 2016, the Food Insecurity Sub-study collected data every 6 months on food security, nutrition and other key socio-economic variables from all WIHS participants. For the current analysis, women living with HIV who participated in the Food Insecurity Sub-study from April 2013 through March 2015 and also had neurocognitive and psychiatric variables during the same time period were included . Data collection for psychotropic medication use was staggered across four WIHS visits during this period, at five study sites: San Francisco, CA; Chicago, IL; Washington, DC; Bronx, NY and Brooklyn, NY.Food security was the primary explanatory variable, measured using the Household Food Security Survey Module . The HFSSM is an 18-item survey designed to capture the experience of anxiety around household food supplies, inadequate quality of food and/or reduced food intake. Originally developed from in-depth qualitative and survey data among women in the USA , it has since been validated in multiple diverse contexts . Respondents are classified as having high, marginal, low or very low FS. Very low FS corresponds to reduced food intake and hunger, while marginal FS implies persistent anxiety and uncertainty around food. The internal consistency of the HFSSM in this sample was high .The primary outcomes were four categories of prescribed psychotropic medication use . WIHS participants are asked to bring a list of medications to each visit and are also asked specifically whether they are using any medications ‘for psychological conditions or depression’ and for the name of the medication. Self-reported psychotropic medications were coded as antidepressants , sedatives/hypnotics/tranquilisers/anxiolytics or antipsychotics as appropriate. Using these data, we constructed a pooled outcome for any psychotropic medication use and made three separate binary outcomes corresponding to each individual drug class. Other outcomes included symptoms of depression, generalised anxiety disorder and mental health-related quality of life. Symptoms of depression were measured using the Center for Epidemiologic Studies Depression score, a widely used self-report instrument that asks participants how often they experience symptoms of depression including low mood, low self esteem, poor concentration, sleeping difficulties, poor appetite and others . Scores range from 0 to 60, with higher scores indicating greater depressive symptoms.The internal consistency of the CESD in our sample was high.We measured symptoms of generalised anxiety disorder using the Generalised Anxiety Disorder-7 scale, a 7-item self-report instrument used to screen for and categorise the severity of GAD in primary care .

The low pathology cluster one may call resilient in the domain of mental health outcomes. It appears that when trauma and personality interact,they produce differences in behavioral and affective outcomes in trauma survivors. Also, generic diagnostic labels like PTSD may prove to be inadequate to assess for the presence of trauma because reactions to trauma are in line with personality styles and therefore differ fundamentally across individuals. Resilience is impacted by external factors such as family and peer relationships. In terms of family attributes, research suggests that the quality of attachment and the type of parental monitoring predict adaptation . Literature on emotion regulation shows how important parenting is for the development of adequate emotion expression that controls behavioral outcomes of internal states . Trauma. A critical variable when studying youths who commit delinquent acts is trauma. While trauma is classified as an external factor since it is done to the child by someone else, it has long-lasting if not permanent internal effects. Trauma is defined as the intrapsychic outcome of the meaning of a stressful event that directly impact one’s sense of self. The American Psychiatric Association defines a traumatic event as one in which “the person experienced, witnessed, or was confronted with an event or events that involved actual or threatened death or serious injury, or a threat to the integrity of self or others” . It stresses that the reaction of the affected individual is critical whereby a traumatized person shows “intense fear, helplessness, or horror” . Victimization and abuse have a gross impact on the child’s psychological and social functioning. Children who were victimized through neglect, physical, emotional, or sexual abuse are likely to experience difficulty with regulating their own emotions, pots for cannabis plants and are thus vulnerable to develop negative behaviors and mental disorders. A classic study by Stouthammer-Loeber, Loeber, Homish, and Wei found that victims of abuse were more likely to engage in overt problem behavior such as minor aggression and physical fighting.

Additionally maltreated children were four times more likely to display high-risk authority avoidance behaviors like truancy, running away, and status offenses . They also found that maltreated boys follow certain pathways to antisocial behavior, which the authors called the authority conflict, the overt and the covert pathways. Maltreated boys were more likely to progress along the overt pathway, which entails varying degrees of deviance such as bullying, fighting, and rape . Also, maltreated children were more likely than the control group to reach the most severe level of the authority conflict pathway, i.e., truancy. However, maltreated children did not differ from the control group on the covert pathway that is associated with vandalism and theft. There is a solid research basis for the link between delinquency and trauma. Harmony, cohesiveness, and strong emotional bonds between family members have been found to relate to less delinquency . Children, whose parents are warm, responsive, and accepting, are more likely to regulate their emotions , which points to the critical role of parenting for fostering resilience. The ability to regulate emotions is a protective factor because it enables the individual to pursue goals in a persistent manner . Parental arguing, financial stress, and abuse are risk factors for committing crimes . The high prevalence rate of trauma among the population of youths with a criminal history is alarming. As the U.S. Department of Justice reported 93% of detained youths had experienced at least one traumatic experience and 84% had experienced more than one trauma. Those trauma rates dramatically surpass those of adolescents from the general population. Traumatic experiences pose a significant risk factor for the development of psychiatric disorders such as depression, substance use, or conduct disorder, which places youths on probation into a high vulnerability group . Trauma negatively impacts the psychic organization of an individual and causes emotional dysfunction that affects intrapsychic and extrapsychic domains like self-esteem and social support . Martens stresses that trauma increases the victim’s suspiciousness of the outside world because the victim’s trust was violated evoking a strong sense of vulnerability. It can therefore trigger schizoid states and feelings of hostility and separateness from the outside world. A study by Widom, Marmorstein, and White found that victims of childhood abuse and neglect reported using a significantly higher number of different drugs than their matched controls. This trend continued across life phases whereby abused and neglected children reported more illicit drug use in middle adulthood than their nonabused counterparts .

The authors concluded that while drug use and drug experimentation is normative in adolescence and emerging adulthood, victimized children were more likely to continue using drugs beyond those developmental phases . Rosenberg et al.’s study on 350 incarcerated youths found that at least 94% reported at least one traumatic experience and that trauma exposure was significantly correlated with PTSD, depression, and substance abuse. Another study employing the typologies of internalizing versus externalizing personalities examined 568 Spanish participants addicted to drugs and found that, those who clustered in the more severe group, i.e., lower socioeconomic status and less education and income, displayed schizoid traits and were addicted to heroin and multiple drugs . Clearly, there is empirical evidence and theory about the pathways of trauma and personality types, and the risks for substance problems associated with internalizing tendencies of withdrawal, suspiciousness, and emotional detachment. A study conducted by Bernstein et al. looked at inner-city substance dependent veterans to find out whether the types of trauma they experienced in childhood could predict different personality clusters. They found that when using restrictive cut-off scores physical abuse was reported by the majority , followed by sexual abuse , and emotional abuse . Moreover, emotional abuse predicted borderline, histrionic, narcissistic, avoidant, paranoid, and dependent personality disorders.In sum, emotional abuse predisposed the individual to anxiety-prone, mistrusting character traits, and impulsive personality types, i.e., borderline, histrionic, and narcissistic. Importantly, emotional neglect was related to schizoid personality traits confirming the conceptual link between emotional neglect and schizoid personality . Similarly, a study investigating the link between childhood trauma and personality disorders among an outpatient sample confirmed previously reported findings on the effect of emotional neglect on cluster A personality types, i.e., paranoid, schizoid, and schizotypal . The impact of emotional neglect may play a far greater role in the development of serious personality disturbances than previously thought. Support for the trauma-personality pathway came from research conducted by Daud et al. . They compared traumatized Swedish children to a control group on a number of intrapsychic and extrapsychic domains. They found that the traumatized group showed significantly higher levels of internalizing symptoms , higher externalizing symptoms , and more detachment than the nonmaltreated group . Daud et al. argued that early maltreatment leads to impaired personality traits. Related research found that emotional abuse was correlated with dissociative symptoms . Dissociative symptoms have been studied frequently in individuals who suffer from borderline personality disorder, but they are present in schizophrenia and depersonalization disorders as well .

Dissociative symptoms, such as splitting, are part of a defense mechanism that works to create an altered state of consciousness resulting in a loss of a coherent perception of the environment . Psychoanalytic theory understands dissociation as a defense mechanism against intolerable affective experiences that are part of traumatic events . Hence, traumatic experiences have deleterious consequences on the individual’s functioning by altering the way he relates to himself and the world. In other words,cannabis flood table trauma creates a personality pathway. Social support. Social support appears to be a palpable concept by which resources are provided by others; yet it is in fact multifaceted and complex . Ways of measuring social support range from assessing types, frequency, and kinds of support to asking participants whether they felt supported . This is also referred to as structural and functional measures, whereby the former addresses the size of the support network and the latter appraises perception and function of support received . In order to capture the concept of social support in its entirety, it is important to expand the types of social support provided to include a variety of sources. Peer relationships have been described as a protective factor, especially during the developmental period of adolescence where peer groups assume functions for identity development . Sports, friends, and creative outlets are important factors in the process of individuation in which adolescents seek more time spent with peers than parents. In other words, there is a developmental transition from a primary parental support system into a primary peer support system in adolescence . Group membership bestows a sense of belonging and control, which can help overcome feelings of marginalization or isolation. Peer groups provide emotional support, offer the opportunity to experiment with different roles, and to engage in self-disclosure. This is especially important for adolescents who are in the process of forming their identity and establishing their autonomy. Importantly, research shows that it is the satisfaction with social support that is associated with resilience and not the frequency or importance attributed to the support . Research has linked social support in adolescence to a range of outcomes. For example, adolescents with poor social skills showed higher internalizing problems, such as depression . Moreover, there is evidence for gender differences whereby a lack of friends was positively associated with depressive symptoms for girls but not for boys. DuBois et al. reported that social support predicted emotional and behavioral adjustment in adolescence by acting as a mediator. This implies that social support positively affects internal strengths, for example self-esteem, which in turn fosters well being and adjustment. Notably, social support can produce negative effects. For example, it appears that potentially negative effects are domain-specific whereby peer support has been linked to higher externalizing problems compared to adult support . Yet, in their study DuBois et al. found that adolescents preferred support from the peer domain, which may put them at risk for a negative trajectory. This leads to a discussion of the complexity of social support in the case of delinquent youths, in particular. Many youths who engage in illegal activities are affiliated with gangs. For many, their gang is a form of social support. Gang affiliation as a form of peer membership has been linked to alcohol and illicit drug abuse as well as criminal activities . Gangs may therefore be a double-edged sword in that they function as social support and simultaneously pose risk factors in other domains, i.e. substance abuse and criminal activity.

Mouttapa et al. argue that the process underlying the association of gang membership with drug abuse is through identification with gang member characteristics, such as aggressive behaviors and drug use. It is the identification with the negative characteristics that leads to negative outcomes in the context of gang affiliation. Moreover, Mouttapa et al. state that focusing on the identification process enables researchers to understand how even those youths who are not in a gang, but identify with it and its culture, are more likely to engage in negative behaviors . Sharkey, Shekhtmeyster, Chavez-Lopez, Norris, and Sass explored how basic needs of belonging and identity that cannot be found elsewhere are met by gangs. Indeed, gang members often come from low socioeconomic neighborhoods that offer few opportunities for prosocial activities and little hope for a better future. Moreover, families residing in such neighborhoods tend to suffer systemically from disrupted relationships, absent fathers, and domestic violence. Hence, youths from these environments are looking for an alternative to provide them with their needs for esteem, respect, and dignity . Studies distinguished resilient from nonresilient individuals based on their association with deviant versus nondeviant peers . Deviant peer behavior such as drug use and criminality puts individuals at higher risk for engaging in those acts themselves via modeling and social learning. Previous research has depicted gangs to be antisocial and predictive of substance use and criminal activity. The resilience research describes gang membership as a risk factor because of its association with alcohol use and crime in general . Yet, there is the potential that gangs are helpful in developing competencies based on self-esteem and self-respect. Some findings suggest a more nuanced role for gangs as they can provide sources of social support, acceptance, and socialization along group cultural norms for members. This study is less concerned with the source of social support than with its function as something positive in the youth’s life that is conducive to self-development.

If we didn’t have a housing problem, it’d be so much simpler. Before, if we wanted to get a city to think about preserving space for industrial, it was more about aesthetics. But now it’s really about whether there is enough housing […] I think that’s really going to be tough to address.” Yet, it also is important to recognize that market pressures vary across the region. While inner Bay Area cities are experiencing pressure to convert industrial to housing; suburban cities are not necessarily undergoing a similar process. The recent legalization of cannabis is directly impacting industrial land values across much of the Bay Area. Cannabis offers a much higher-value use compared to more traditional industrial uses; thus, speculation for cannabis uses is driving up land values and out pricing traditional users. An industrial land expert highlighted that in more suburban areas, such as Santa Rosa, the market pressure from cannabis is even higher than that of housing. The City of Santa Rosa has been a leader in regulating cannabis, as the city proactively adopted a comprehensive cannabis ordinance in December 2017, which went into effect in January 2018. Since 2014, Santa Rosa has experienced a drop from 12 percent vacancy to 5 percent vacancy in industrial zoning largely due to cannabis the inability to retain and/or grow businesses. Retaining and growing businesses was mentioned in the context of startups. While startups often are attracted to the Bay Area, economic development staff in the East Bay stated that they have experienced the loss of industrial startups who need just a little space in the beginning,cannabis grow indoor but who eventually leave the region once they grow and require bigger scale production. On the contrary, staff at the City of San Francisco cited the lack of space as a positive influence on the preservation of industrial land. A city official stated that due to its smaller amount of industrial land relative to other cities, “we recognize that we need to preserve it because otherwise it’ll be cannibalized by something else.” The same city official suggested that higher demand and pressure on these spaces eased the implementation of their industrial land program .

City staff reported varying levels of success in their mixed-use industrial areas. Likely, this varies greatly according to the type of industrial use and the use it is mixed with. San Francisco has what they call “trade shop” zoning that allows for light industrial in neighborhood corridors. Economic development staff reported that retail on site and increased foot traffic has been an asset for these manufacturing businesses. Staff at many cities have seen community uses, such as churches or schools, locate in industrial spaces because the land is less expensive than in other areas lack of flexibility. Staff at the City of Hayward described how the blanket application of regulations for all industrial uses has posed issues for both the city and businesses. From the city perspective, the uniform regulations have limited the city’s ability to facilitate which uses they would like to see in their industrial area. From the business perspective, the blanket zoning has created uncertainty about whether or not they are allowed in the industrial area, which poses a challenge for business attraction to the area. The City of Hayward is currently addressing this challenge through an update to their industrial zoning code that will clarify these ambiguities. Furthermore, as the nature of industrial uses changes, some city officials expressed the desire for more flexible regulations. For instance, staff at the City of Fremont emphasized that uses, which were once separated, now occur under the same roof. They cited Tesla as a great example of this: “You’ve got PhD engineers at computers who are interacting with the line staff who are in the production areas, and they need to be collocated. And then they’re also shipping the product, that is under the same roof. And R&D used to be [collocated] until they outgrew the space.” The city officials stressed that they need to update their zoning codes to adapt to this trend. This would help to reduce the bifurcation of uses and accommodate developers who don’t want the city to be too prescriptive. In addition to zoning, the City of Fremont has been working on loosening up other requirements, such as parking, to ease the collocation of uses. Staff at the City of San Jose highlighted that the evolving nature of R&D from one-third office, production space, and warehousing to almost entirely office has not been incorporated into land use definitions.

Failure to keep pace with the evolving nature of these businesses has created a number of problems, including the way their taxes are structured. Much of the infrastructure supporting industrial spaces suffers from a lack of maintenance: buildings, roads, as well as fiber optics. All city officials stressed the disrepair of roads and the supporting goods movement infrastructure. A number of city staff highlighted the outdated building functionality of rigid, large-scale warehouses. At a certain point, market values and land values will likely increase so much that the existing business will want to relocate. Staff at the City of Hayward stated that, “We’re already starting to see that. The base users are being priced out […] We’re starting a lot of speculation projects. Developers have no idea who their tenants are going to be, so let’s make the buildings as flexible as possible.” Staff at the City of Pittsburg mentioned a 375,000 square foot building that was once attractive for heavier industry users, namely a spiral pipe company, for its high ceilings, roll-up doors, and rail spurs, but is now “one of those spaces that we’ve had people come in they want to take a portion of it, but not the full space.” City of Hayward staff actively acknowledge this challenge, suggesting that “if you break down that million square feet into multiple buildings on a site, [the developer] is achieving what they want and we’re getting longevity for reuse on these sites.” Other cities, such as Newark, are shutting out large-scale warehousing altogether and encouraging advanced manufacturing. Furthermore, San Leandro city officials argued that infrastructure also should include internet connectivity. Access to high-speed internet is essential to many driving manufacturing industries, including biotech, food R&D, advanced manufacturing, and future uses. However, it is also important to consider that fiber optics also may open up real estate to other new uses that may compete with traditional industrial uses. Perhaps unsurprisingly, environmental issues associated with industrial uses were brought up primarily by cities with a larger existing, or historical, heavy manufacturing base. Staff at the City of Pittsburg highlighted that “in general, the community is supportive of industry, but they want to see clean and safe industry, which is totally reasonable.” Additionally, underutilized land that was formerly occupied by heavy industry often poses many environmental remediation challenges.

Thus, cities with available land are not able to easily adapt to other uses. A prior study found that the City of Richmond, a city with a high share of heavy industry, is concerned that “[PPAs] have the potential to ‘cement into place’ environmental hazards and burdens on a few select places – and that these places risk being those already most disadvantaged within the region” . The PPA program must recognize such concerns and consider how cities who bear a disproportionate burden from industrial uses could also benefit this policy.One of the major challenges for the PDR sector in the Bay Area is a shortage of workers. Most city staff attribute this issue to the high cost of living and the associated displacement of residents who are willing to work lower wage jobs, which are likely direct impacts of a housing supply deficit. A shortage of local workers was cited as a major issue for cities across the Bay Area, including both core and suburban cities. City officials in Petaluma emphasized that the land costs are not as much of an issue for industrial businesses,vertical farming supplies it is more the shortage of workers who can support industrial processing. Staff at many cities emphasized the two-hour plus “super commutes” that industrial workers are making from Central Valley cities, such as Stockton and Tracy, because they cannot afford to live nearby. The East Bay EDA cautioned that designating an area as industrial, when businesses cannot employ a local workforce, will not help the economy of the Bay Area. Thus, they suggested the larger question is, “how do you make the Bay Area a place that can sustain workers?” While the driving forces behind this issue can be an argument for converting industrial land to housing, maintaining and creating space for both workers and jobs is critical to supporting the regional economy. This issue is likely outside of the scope of the PPA program itself; however, recognizing these broader interrelated issues and determining how the PPA will interact with other related policies or programs will be essential to its success. Many cities around the Bay Area lack the resources required to conduct a needs assessment and regulatory updates for industrial land. San Francisco staff stated that their planning department conducted a significant amount of research prior to implementing their citywide industrial zones, and that being able to dedicate those kinds of resources to a similar effort would be challenging for some cities. In addition, city initiatives often suffer due to competing priorities. In the case of Santa Rosa, staff is primarily focused on rebuilding their housing stock post the fires that occurred in Fall 2017. Furthermore, an economic development expert suggested that a city’s management structure can greatly influence a city’s understanding of and strategy for addressing issues. For instance, they theorized that some cities have housing under the same management structure as economic development, and they tend to have a better understanding of the trade offs between these two issues; whereas other cities’ economic development staff is in the city manager’s office or another department that may be isolated from other inherently connected issues.

Politics play a strong role in shaping the conversation and action, or lack thereof, around industrial land. The rotating political cycles and the current focus on the housing crisis pose challenges for the preservation of industrial lands. San Jose city officials stated that they constantly have to educate new council members on San Jose’s predicament and challenges related to industrial land and why they have policies in support of these spaces. They stated, “it takes constant maintenance. We always have to be talking about this. We always have to be reminding and informing council. There’s no guarantee. It’s, I don’t want to say a battle, but we’re always having to tout the line and educate folks on why this is important. It’s a career.” The current makeup of a city council will directly influence if a city chooses to embrace a policy. In the South Bay, an economic development expert said that “cities come in the flavor of we want jobs or we want housing; very few want both.” More often than not, politicians believe that these two interests are at odds, creating competition between the two interests rather than enabling them to work together. Given the pressures of gentrification and the lack of opportunity for a diverse population, elected officials are focused on the housing crisis. Experts suggest that elected officials may actively avoid endorsing the need for industrial land in fear of jeopardizing their political career. Consequently, industrial spaces often suffer from a lack of a constituency or consistent voice. Other advocates and users of industrial spaces are rarely involved in political issues and thus do not provide a voice for industrial land either. As a result, development often occurs in these areas of least resistance. One of the primary goals of the conversations with city officials was to understand why a local jurisdiction would or would not be interested in a PPA program. Cities overwhelmingly expressed interest in the potential for funding to be channeled through the PPA program and directed into investments related to industrial uses in their cities. The majority of cities were also interested in the PPA program emphasis on employment, the idea that the PPA program could provide a platform for shared experiences or best practices, as well as its potential for elevating the profile, importance, and functionality of industrial lands across the region.

Importantly, the study of personality traits can include individuals diagnosed with a personality disorder but is not constrained to diagnostics. Also, personality is not confined to intrapsychic processes but is characterized by interpersonal patterns of behaviors, commonly used defense mechanisms, and cognitive schemas for thinking about self and others. Therefore, when taking this perspective personality can be influenced by external factors like trauma and social support, for example. What is referred to as schizoid personality style appertains to a selection of personality presentations characteristic of cluster A personality organizations . They are based on descriptions and characterizations of schizoid personality as found in the Diagnostic and Statistical Manual of Mental Disorders and relevant psychiatric case formulations . Schizoid personality describes individuals who tend to be introverted, solitary, and who engage in tangential thinking. Individuals high on schizoid traits tend to use intellectualization as a defense mechanism and display an indifference to external affairs preferring a solitary world of imagination . In other words, individuals with such personality tend to revert to reasoning in order to avoid discomfort elicited by emotional distress. And, they prefer solitude over their social environment much like an introvert would. They tend to manage emotions by avoidance, withdrawal, distrust, or escaping.Antisocial personality dimensions have been more frequently studied in relation to youths who have an offending history. There is a dearth of research on schizoid personality types and substance problems. And that despite the fact that research suggests that internalizing disorders are associated with marijuana abuse whereas externalizing disorders relate to alcohol abuse . Marijuana abuse or dependence is a commonly reported,mobile grow system co-morbid issue of juveniles and it has been considered to be associated with more severe illicit drug use . Hence, it is important to study personality types that are typically not on the radar of treatment providers’ screening procedures because of their more introverted characteristics that are less disruptive compared to aggressive and extroverted types.

From a psychoanalytic standpoint, child abuse leads to the fragmentation of the child’s sense of self. Parents have a critical role for the development of the self because they act as mirror of the child’s inner sensations and experiences, and they contribute to the child’s sense of inner coherence . The child withdraws from others as a defense from unsatisfying relationships with caregivers who were overbearing or who communicated an emotional ingenuity that significantly disrupted the integration of the I and the It, i.e., the experience of the self in its subjectivity and as an object in the outside world. Those early disruptions and deficient early child-caregiver relationships can lead to traumatic experiences that will be referred to as trauma throughout the study. Children who were abused often develop emotional dysregulation, lack of ego functioning, and primitive defense structures . The high prevalence of mental health symptoms such as anxiety, hostility, dissociation, narcissism, and depression among juvenile delinquents is considered symptomatic of high trauma levels. Similarly, personality characteristics such as impulsiveness, manipulative behavior, withdrawal and aloofness can be considered symptoms of underlying traumatic experiences. Interest in the link between personality and delinquency is not novel. For example, Glueck and Glueck found several personality traits such as narcissism, impulsiveness, hostility as well as feelings of not being recognized, to be linked to delinquency. The trauma literature has provided research on the pervasiveness of the co-occurrence of trauma and substance abuse. Drugs by altering the state of consciousness deliver a temporary relief from the fragmenting and painful experiences of trauma . Substance abuse has been frequently cited as a precursor to criminal activity, so that by targeting substance problems one is likely to impact criminal behavior as well . Substance problems unlike substance use disorders delineate problems in relationships, difficulties at school, and legal problems in relation to drug use . Yet, substance problems do not necessarily imply an excessive use of substances; rather, they denote associated psychological problems of using, which is why substance problems rather than substance use disorders were included in the analysis.

Some researchers report that the prevalence of mood and substance use disorders among incarcerated youths is two to three times higher compared to the general public . Although adolescents in general are at risk for substance problems due to the developmental phase of testing boundaries, seeking greater autonomy, and risk-taking, there is strong evidence to suggest that youths who were abused report more substance abuse than those who were not . Traumatic experiences lead to unpleasant and interfering psychological and physical sensations such as intrusions, arousal, and hyper vigilance that often are “treated” by the victim through the use of substances . In other words, substance problems are merely symptoms of deeper-rooted issues. This study conceptualizes the effects of trauma on the child as profound disturbance of the inner structure of the developing self whereby trauma is a “breaking of the continuity of the line of the individual’s existence” . Trauma, personality development, and substance problems appear to share certain pathways, in that early traumatic experiences are associated with personality types that are more prone to abuse illicit drugs due to the trauma’s impact on affect regulation and self-cohesion . When applying a psychoanalytic lens, corrective emotional experiences can occur through adequate reflection of internal sensations by others than the parents, for example, by social peers or romantic partners. Social support has been found to foster self-esteem and coping contributing to an individual’s resilience against adversity . Undoubtedly, the peer group is central in adolescents’ lives since it is a platform for identity formation and for instilling a sense of belonging . Low-risk behaviors have been linked to perceived social support by peers, family, and others among Latino/a fifth and sixth graders . A longitudinal study by Kathib, Bhui, and Stansfeld found that low social support predicted emotional symptoms related to psychological distress forBritish students who were assessed between the ages of 11 and 16 years. However, social support not only has an important role for the adolescent’s development but also for mental health treatment as it is positively related to the therapeutic alliance . A study by Garner et al. found that higher social support was associated with better problem recognition, more identified reasons for quitting drugs, and higher ratings of the therapeutic alliance . Also, research on social support recognizes that supportive networks fulfill different needs; for example, emotional, instrumental, and informational needs.

Emotional support is defined as love and compassion, instrumental support as concrete help with needs, and informational support refers to guidance and advice . In conjunction with the different needs,mobile vertical rack there are distinct sources of social support to consider. It appears that a majority of research on social support focuses on one or two sources; in the case of adolescents and children those tend to be familial systems and friends. Therefore, considering the role of a variety of distinct sources for social support including teachers, counselors, family, and friends, is indicated in order to be able to address the different needs they may fulfill. Juvenile delinquency has been studied by a variety of approaches, a recent one being through a positive, developmental lens of resilience. Resilience is a concept that is often misunderstood to represent invulnerability or resistance to negative influences. Instead resilience describes a process of strengths or protective factors interrupting a negative trajectory . It has become a prevalent conceptual and methodological approach in the medical sciences and humanities alike because it helps ascertain what factors are protective against risks of genetic predispositions for physiological illnesses and psychological disorders. Even though this study will not take a classic resilience approach, it shares some core concepts with it. First, it takes a variety of risk factors into consideration, such as trauma, maladaptive personality traits, and previous illegal activity. Second, it inserts social support as a potential protective factor against substance problems for youths released from juvenile detention. From a clinical point of view a reduction in substance abuse problems represents a positive outcome because it indicates rehabilitation and lower risk levels for on-going antisocial behaviors. Finally, this study borrows from resilience theory some important tenets, such as the idea of developmentally shaped pathways. There is an interdisciplinary consensus that, when studying youths with an offending history, researchers should adopt a developmental perspective that addresses newly emerging risk and protective factors along cognitive, affective, and behavioral changes. For example, trauma is regarded a risk factor for emerging maladaptive personality traits . Incarceration has proven to be an ineffective treatment method for youths who offended because it insufficiently, if at all, addresses mental health issues, and because it suppresses protective factors’ influence . While in detention, social support and self-esteem, for example, are not fostered in ways that would help youths build ego strength and modify their trajectories. Moreover, many drug treatment programs rely heavily on group therapy formats and emphasize the role of social support in recovery.

However, group-based modalities may not be effective for individuals with introverted personality traits who experience large group settings as uncomfortable or threatening. Resilience addresses the phenomenon that not all of the children who were traumatized develop maladaptive personality traits or other negative psychological outcomes such as internalizing problems or deviant behaviors . This leads to the assumption that there must be other factors involved, apart from the traumatic experience, that account for maladjustment. Previous resilience studies have predominantly investigated risk factors for juveniles who commit crimes and identified genetic predispositions, dysfunctional family background, mental illness, psychological distress, emotional dysregulation, and gang involvement to heighten the risk for recidivism . Generally, resilience studies are conducted within an ecological theoretical framework that stresses the influence of interpersonal environment, institutions, and societal structures on development. However, certain psychoanalytic concepts directly apply to a person’s resilience as well. For example, ego strength, ego control, and ego resiliency correspond to psychoanalytic tenets of the ego’s role in adaptation . Resilience research on developmental trauma found that children who suffered maltreatment displayed lower ego control and lower ego resiliency . Ego control and ego resiliency are concepts developed by Block and Block whereby the ability to control emotional impulses , and the ability to adjust emotionality to the context are strengths related to personality. Just like the dimensional understanding of personality, ego control and ego resiliency function on a continuum. Ego strength is a personality construct that pertains to a resilience framework. The ability to control emotions and impulses is referred to as ego strengths. Ego strength refers to psychoanalytic theory of the structure of the self and it has been related to self-awareness, psychological maturity, and adaptive personality characteristics . It is part of the self that is fundamental for organizing experiences and maintaining a cohesive sense of self. The psychoanalytic construct of the ego can be considered a resilience factor because it has an adaptive function in that it enables a person to relate his self to an outer reality . The ego integrates desires and ideals of the self, and it helps direct behavior by being grounded in reality . Therefore, ego strength is an internal protective factor against risks of fragmentation of self, dissociation, and regression. Resilience is assessed by protective factors in an adverse environment to see how they relate to adaptation in a specific domain of functioning . For example, emotional abuse and dysfunctional attachment styles put children at risk for later substance problems . As a result, a child who developed substance problems may struggle academically , but still report good social support, for example. Strengths or protective factors counter risks, and enhance the possibility for adaptation despite adversity. The challenge is to find out what protective factors work for what specific domain in an adverse context. Importantly, an asset can only be called a protective factor when a risk is present . Assets occur in the absence of significant adversity and are called promotive factors because they directly strengthen positive developmental outcomes . While vulnerability factors tend to worsen the risk effects on the individual’s functioning, protective factors act as buffers that “modify the effects of risk in a positive direction” . The community, family, and the individual’s competencies can influence vulnerability and protective factors, and thus act as active agents in the promotion of resilience.

Additionally, patients who may be traumatically injured and who are not admitted to a participating trauma center will not be included in the NTDB, nor will trauma patients who died on scene before being transported. Another consideration to note is that participating hospitals may differ in their criteria of which patients to include in the database, specifically patients who are dead on arrival or those who die in the Emergency Department . This discrepancy in inclusion and exclusion criteria between hospitals regarding specific injuries makes representative comparisons potentially difficult. Lastly, it is important to mention that large databases such as the NTDB are subject to missing data or disparate data. This is often due a multitude of factors, a few of which various demographic data points, test results and other key information, such as procedures, that may not be documented in the health record and therefore omitted in the database . Missing data often contributes to information bias; however, it can also contribute to selection bias because one of the methods in dealing with missing data is excluding participants for which data is missing thereby creating potential selection bias. Missing data may undermine the ability to make valid inferences, therefore, steps will be taken throughout the design and operational stages and methods within this study to avoid or minimize missing data. Methods to reduce information bias that can lead to selection bias will be discussed in the analysis section of this paper.Due to the methods by which data are collected and inputted into the NTDB,ebb and flow flood table potential problems are encountered in terms of data accuracy. Under reporting of variables obtained from the NTDB has often been noted as a problem due to the reliability of data extraction by participating hospitals .A major variance between participating hospitals is that hospitals with more resources are more likely to have dedicated staff to data collection.

This can lead to informational bias in those hospitals that are more compliant in reporting data metrics when compared to others that are not. For example, hospital data registries that have incomplete data on complications may appear to deliver better care than hospitals that consistently record all complications. A recent study by Arabian et al. revealed the presence of inaccuracy and variability between hospitals, specifically in the areas of data coding and injury severity scoring. Additionally, the type of registry software a hospital utilizes can report injury severity scores differently . This too, renders data subject to informational bias. Information bias is due to inaccurate or incorrect recording of individual data points. When continuous variables are involved, it is called measurement error; when categorical variables are involved, it is called mis-classification . In this study, the potential for information bias is mostly due to 1) incomplete data documented in the medical record, or 2) inaccurate entry into the hospital trauma database by hospital staff. Missing data will be analyzed in terms of potential effect for both the independent and dependent variable . While the database captures marijuana exposure through the first recorded positive drug screen within the first 24 hours after first hospital encounter, it is recognized that at times patients will not be screened, even if they have been exposed to marijuana. Marijuana exposure is identified through the presence of Cannabinoid in a urine toxicology screen. Marijuana presence can be detected in the urine up to 3-5 days from exposure in infrequent users; marijuana can be detected up to 30 days for chronic users . Therefore, patients could potentially have a positive marijuana toxicology screen even though they may not have ingested marijuana the day of the event. A positive marijuana urine toxicology screen indicates the probability of prior use, not immediate use. This is an important limitation to note. In clinical practice, the determination for a toxicology screen is often symptomology, so it is reasonable to assume that patients who have ingested marijuana a week prior to the event date may not exhibit the expected symptomology. Unlike other observational cohort studies, the potential of recall bias is minimal due to the availability of an objective marker to measure the independent variable, namely, the presence of marijuana.

The presence of marijuana is captured from the hospital lab urinalysis results and is recorded as present within 24 hours after the first hospital encounter. Similarly, the data entered to measure the GCS score is also captured objectively through a numeric recorded score found in the medical record. See analysis section for how this type of bias will be addressed. The Trauma Quality Programs research database housed in the NTDB for the year 2107 is the time frame for this study. Though initially the researcher intended to include data from 2013-2017, data from years other than 2017 had to be excluded. In effort to standardize the type of data collected by local, regional, and state trauma registries, the NTDB designs a National Trauma Data Standard Data Dictionary that is designed to establish a national standard for the collection of trauma registry data while also providing the operational definitions for the NTDB. In summary, the NTDS provides the exact standards for trauma registry data submitted to the NTDB. Prior to the 2017 data dictionary, trauma registry programs had limited selections regarding data related to drug use. The options provided by the NTDB registry only included whether drug use was present and whether it was confirmed by a test or by prescription. It did not allow the trauma data abstractor to specifically identify the type of drug found. In 2017, the data dictionary was revised to include a drug screening category that aimed at recording the first positive drug screen result within 24 hours after the first hospital encounter. Typically, in trauma hospitals reporting to NTDB and within the context of trauma, acquisition of a urine and blood drug and alcohol screen is standard expectation of practice. It then provided a list of 15 options for the abstractor to choose from. Because it was impossible to isolate cannabinoid use in earlier data sets, the researcher was only able to use the 2017 NTDB data set, which at the beginning of the study was the latest available data set by the NTDB. As of February 13th, 2021 the 2018 NTDB data set was not available. All the trauma data used in this study are organized by an element INC_KEY, which is a designated unique identifier for each record. The designated unique identifier INC_KEY expresses a unique clinical visit/episode by an individual at a participating trauma center. It is important to consider that an individual could have been included/counted more than once in the registry because of more than one traumatic event within the year.

The Participant Use File Trauma data set contained all the demographic, environmental, and clinical data information. However, it did not identify or delineate TBI cases as such. Therefore, a separate data set that contained ICD 10 Diagnosis Codes had to be utilized to identify TBI cases which then could be used to create a merged data set that is complete. The 2017 PUF Trauma data set was uploaded to SPSS version 25 on September 10th, 2020. The PUF Trauma data set included a total of 997,970 unique identifier cases. A frequency analysis was performed to ensure no duplicate cases were found . The PUF Trauma data set included 328 unique variables. Next, the PUF ICD-10 Diagnosis data set was uploaded and examined. The PUF ICD Diagnosis data set is organized via the same INC_KEY identifiers. The PUF ICD Diagnosis data set included 3 variables: ICD CM diagnosis code, ICD CM diagnoses code Blank Inappropriate Values and ICD Clinical Modification version. This data set was used to distinguish TBI cases from cases related to other traumas such as pneumothorax, liver laceration or femur fractures. The way this was done was first the researcher identified TBI related ICD 10 CM diagnosis codes by visiting the ICD 10 Data website at www.icd10data.com and searching for all head injury related codes. Additionally,hydroponic drain table the selection of TBI related ICD 10 codes was corroborated by examining a list of codes found in existing studies on TBI which validated the inclusion of the specifically identified TBI codes in this study. Though these other studies included ICD 10 Diagnosis codes related to concussion injuries , these codes were excluded from this study as the researcher was only interested in identifying cases with either a moderate or severe TBI and concussions are designated as mild TBI. The following codes were ultimately selected: S02.0xx ; S02.1 ; S06.1 ; S02.19XD ;S06.2 ; S06.30 ; S06.31 ; S06.32 ; S06.33 ; S09.X . Next, PUF ICD 10 Diagnosis codes were regrouped into the following categories via numerical representation. ICD 10 Diagnosis code S02.0xx was grouped into group 3683-3687; S02.1 into group 3688; S02.19XD into group 3738; S06.1 into group 4008-4025; S06.2 into groups 4026-4045; S06.3, S06.31, S06.32, and S06.33 into groups 4046-4095; S09.X into groups 4310-4311. When missing values in each variable account for less than 5%, those values can be missing at random and list wise deletion can be performed relatively safely is appropriate to do. This holds true for all the variables except for THC Combo, positive for drugs, alcohol screen result, age in years, ethnicity and total GCS. These variables, three quantitative and three categorical, were found to have greater than 5% missing values. On observation of the missing value analysis, it was observed that most cases had these two variables as missing, perhaps suggesting a relationship, or an effect. Furthermore, the Little’s MCAR test revealed that missing data may not be missing completely at random. Deleting cases with missing values can reduce the statistical power of the analysis and result in biased outcomes and estimates.

Therefore, the use of multiple imputation is appropriate for this dataset and this study. Another method in SPSS that can be utilized is the Replacing Missing Values method. The Linear Interpolation method will be utilized. The Linear Interpolation method is a simple statistical method used by SPSS which estimates the value of one variable from the value of another and using regression methods to find the line of best fit. Using the Replacing Missing Values method in this study will help solve the problem of bias and ensure that power is not decreased because a large majority of the sample size will be preserved. It is important to consider the implications associated with imputing or replacing missing data. Multiple imputation or missing value replacement analyses will avoid bias only if enough variables predictive of missing values are included in the replacement method. If variables that may be predictive of the estimates are not included in the model, for example the effect of age on alcohol result, replacement computation will underestimate these associations and bias the final analysis. Therefore, it is preferrable to include as many predictive variables as possible in the model when either imputation or replacing missing value methods are utilized.Replacing missing values was utilized to minimize the many problems associated with missing data. The absence of data reduces statistical power and can also lead to bias in the estimation of parameters and analyses. Finally, missing data can diminish the representatives of the sample size and cases . It is important to consider that though replacing or imputing data is a common approach to the problem of missing data, it still does not allow analyses of actual data that is provided by actual participants, or in this case, data entered by abstractors and hospital registry systems. In gaining a larger sample size, and perhaps a more representative sample, confidence is lost that actual responses provided are those analyzed. It is important to note that methods used to account for missing data only provide researchers with the best estimated guess of what actual data may have been had it been documented in the first place. It is this ideology that influenced the decision to include some of the variables with missing data to be multiply imputed. Replacing missing values is another form of multiple imputation that was selected for this study. Though multiple imputation process was utilized, it presented a complication in terms of the number of iterations and the subsequent analysis.

The six trained workers in teams of two audited verified RMDs.ii On average, each RMD visit took 10-15 minutes. The 103 RMDs had unique RMD-school pairs and the 60 RMDs were the closest ones to two or more schools out of the remaining 230 schools. In the main analysis, we reported observations in the unique RMDs . In the secondary analysis, we reported observations on RMDs using school as the unit of analysis . The 60 RMDs shared by two or more schools were counted multiple times or over-weighted in the secondary analysis, reflecting their potential to influence children in multiple schools. The Human Research Protections Program at the University of California San Diego deemed this research non-human-subject and required no review. This study demonstrated that, in the early stage of marijuana commercialization in California, point-of-sale marketing practices that are appealing to children were minimal on the exterior of the RMDs around schools. However, such practices were abundant on the interior. Marketing practices not specifically appealing to children were common on both the interior and exterior of the RMDs. Given the age limit, RMDs’ exterior marketing might be the most concerning source of exposure for children. It is reassuring that child-appealing marketing was rarely observed on the exterior of the RMDs around schools. Yet, three quarters of the RMDs had some form of child appealing marketing on the interior, which violated the California laws. Although children should have little direct access to the interior, child-appealing items may be available to children through indirect pathways and should not be overlooked. For instance, children’s social networks such as older relatives, peers, or caregivers are their important sources of drugs. A study reported that almost three quarters of underage users obtained marijuana from friends, relatives, or family members. Child-appealing products, paraphernalia,flood tray or promotional materials could then be made available to children through these adults who are eligible for marijuana purchase. Particularly, about 30% RMDs violated the California law to offer free samples, which could be taken out of the dispensaries and given away to children.

These child-appealing items in RMDs could be also resold to children in illicit markets by street dealers. Research on tobacco and alcohol have suggested that children are exposed to and influenced by tobacco and alcohol products and point-of-sale marketing despite the age limit for purchase . Whether and how the marketing activities inside of RMDs impact children’s perceptions and behaviors should be examined in future research. Meanwhile, exterior retail environments not specifically relevant to children still warrant further attention. For instance, 63% RMDs had image or wording indicative of marijuana on the exterior. One third of the RMDs had generic advertisements, and some advertisements were of a relatively big size. Marijuana could be smelled outside of 25% RMDs. All of these might potentially increase perceived presence of RMDs in the neighborhoods and shape children’s social norms. Approximately half of schools had RMDs located within a 3-mile distance that is reachable to children by walking, cycling, or driving. Some RMDs were located further away, especially in suburban or rural areas. Nonetheless, children are not free from exposure to RMDs even if RMDs are located more than 3 miles away from schools. In 2009, the average travel distance from home to school among all school children was 4.4 miles; among high school students, the average distance was even longer . The travel distance was also increasing over time. An interesting exploratory observation indicated that, compared to RMDs located further away from schools, a larger proportion of RMDs in reachable distance to schools had interior child-appealing marketing. It is possible that RMDs intentionally targeted children if they were in closer proximity of schools. Unfortunately, our study was not able to test this hypothesis directly. Almost all the audited RMDs followed California rules on age verification. If continuous monitoring and enforcements are not in place, however, children might get access to abundant child-appealing marketing practices inside of the dispensaries, the consequences of which could be grave. Furthermore, exterior signs of age limit were absent in over 80% RMDs and security personnel were only observed in 40% RMDs. These might increase the risks of accidental or even intentional attempts of children to enter RMD premises, who would be then exposed to interior marketing in waiting area. Compared to laws in other states, California regulations on child-appealing marketing seem to be vague and less comprehensive during the study period.

Because content restrictions are inherently subjective, it might be challenging for California RMDs to comply and for regulators to enforce without objective, operationalizable measures of “child-appealing”. Fortunately, after this study was completed, California released new regulations in January 2019 on child-relevant products and marketing. Specifically, marijuana products and packages “shall not use any depictions or images of minors” and “shall not contain the use of objects, such as toys, inflatables, movie characters, cartoon characters, or include any other display, depiction, or image designed in any manner likely to be appealing to minors”. These texts are expected to provide clearer guidance to law compliance and enforcements. In addition to prohibitions in laws, California could also consider screening content materials such as packages before they are available in RMDs. For instance, Massachusetts allows manufacturers to submit artwork to a regulatory board for review to ensure non-child-appealing packaging. Standardized packaging might be another alternative, which has shown effectiveness in tobacco control outside of the US. This study has limitations. First, this study used a cross-sectional design to capture a snapshot in summer 2018, approximately half a year after California’s commercialization of marijuana. This unique transition period was characterized with a lack of law enforcement, delay of dispensary licensing, and inadequate understanding of laws. As the legal market matures and government makes endeavors on law interpretation and enforcement, we might expect a stronger compliance with laws and possibly a reduction in marketing practices. The findings may not be generalizable to other time points in California. Second, our observations were largely constrained within the regulatory regime in California and may not be generalizable to other states where different regulatory measures are in place. Third, frequency or quantity measures in each marketing category would be more informative than simple binary indicators for availability. Unfortunately, a dispensary often displays hundreds or even thousands of products, packages, paraphernalia,grow table and advertisements. Obtaining frequency or quantity information requires the field workers to spend a considerably longer time evaluating the RMD environment, which is infeasible in practice. Fourth, California laws lacked specific details related to children during the study period.

The classification of child-appealing was informed by laws in other states and constructed with authors’ own understanding, which may not reflect California lawmakers’ intention or completely align with recently released new regulations. Further, there might be inevitable measurement errors even after two field workers discussed and resolved discrepancies between them. Lastly, this study only gathered data on RMDs in closest proximity to public schools. Results may not be generalizable to RMDs around private schools or children’s homes. To improve representativeness, future research is encouraged to audit a random sample of RMDs. Traumatic brain injury is a significant public health concern as it is a leading cause of mortality, morbidity and disability in the United States. According to the World Health Organization, TBI is expected to become the third leading cause of death and disability in the world by 2020. In the United States TBI contributes to a third of all injury-related deaths. The leading causes of injuries resulting in TBI prevalence are traffic related, such as motor vehicle crashes, or non-traffic related, such as falls. Notably, up to 51% of all TBI patients have substance use exposure at the time of injury.Current existing research suggest that in general, substance-exposed patients may have worse TBI outcomes, including greater rates of mortality and severity of injury. Research has also shown that substance use exposed TBI patients suffer worse functional outcomes, which can result in socioeconomic burden to patients and the nation at large. This healthcare burden has been calculated to be approximately $76.5 billion in 2010 alone. There is a substantial body of research elucidating the role alcohol plays in injuries that lead to TBI prevalence and outcomes. Specifically, alcohol use results in impairments such as diminished motor control, blurred vision, and poor decision making, which has been shown to increase the risk of traffic related injury. This research has been used to create public health policies and prevention programs that have made a significant health impact, such as reducing the number of alcohol-impaired drivers. Other substances have not been as well studied. For example, marijuana is a drug that despite being federally and legally regulated, remains the most widely used drug in the U.S. Marijuana use has been shown to result in similar cognitive impairments as alcohol use, such as lack of coordination, inability to pay attention, and decision-making abilities, suggesting marijuana users are similarly at increased risk for TBI. There is some indirect evidence of this, in that it has been shown that marijuana users in general are about 25% more likely to be involved in a motor vehicle crash and that the older adult marijuana users have a greater risk for falls. However, concrete data linking marijuana exposure at time of injury and TBI prevalence and severity is scarce. Adding to the concern, national surveys on drug use and health have documented an increase in individual daily marijuana use over the last 5 years. As the number of states legalizing marijuana for both medical and recreational use increases, it is imperative to resolve the ambiguity within the research available regarding the relationships between marijuana exposure at time of injury, mechanism of injury, and TBI prevalence and severity.

This study found that the presence of THC was significantly associated with lower GCS scores and a potentially more severe TBI, but this relationship was significant without controlling for other predicting variables. Furthermore, a significant relationship was found between GCS scores, age, and blood alcohol levels at the time of presentation in the ED. Older participants were found to have higher GCS scores, indicating a less serious brain injury. Study participants who had higher blood alcohol levels were found to have lower GCS scores, indicating a more serious brain injury. Age and higher blood alcohol levels were found to be associated, with higher blood alcohol levels noted in younger patients. A linear regression showed different results when examining the relationship between the presence of THC and GCS scores, hence TBI severity. When controlling for all other variables, the presence of THC was not found to be an independent predictor of TBI severity. Alternatively, being male, having elevated blood alcohol levels and having other drugs present on admission were all found to have a significant influence on GCS scores and TBI severity, with GCS scores being lower for all three variables, implying a more serious TBI. Similarly, having a diagnosis of cancer, mental or personality disorder and alcohol use disorder were found to have an influence on GCS scores. Participants with a diagnosis of cancer or mental/personality disorder were found to have lower GCS scores, again, implying a more serious TBI. Conversely, participants with a diagnosis or history of alcohol use disorder had higher GCS scores, indicating a less serious TBI. While the presence of THC initially did show a hypothesized relationship to GCS score , the relationship became insignificant when adjusted for all the other covariates variables. Because of the large percentage of missing data, the validity of findings, such as THC prevalence rate in this TBI population, should be cautiously interpreted for all the included hypothesized explanatory variables. Further research with datasets that are larger and more complete are needed to fully understand and examine the relationship between marijuana and TBI severity. This study importantly underscores the need for better data to enable better research regarding the relationship between marijuana and TBI severity. Traumatic brain injury is a significant public health concern as it is a leading cause of mortality, morbidity and disability in the United States . According to the World Health Organization, TBI is expected to become the third leading cause of death and disability in the world by 2020. In the United States TBI contributes to a third of all injury related deaths .