Hemp Growing

Adult criminal justice systems are incorporating MI techniques through digital health interventions to reduce substance use and in staff trainings to promote overall harm reduction and associated consequences, but studies are with those already using substances. Our data suggests focusing on youth’s internal distress , and cannabis use expectancies, , for those in first-time legal contact and not yet using, could be an important focus for prevention efforts. Depending on resources and time, interventions could be delivered in-person or through digital health technology.Cannabis is the most widely used substance in the United States after alcohol and tobacco, including during pregnancy . While the federal government still categorizes cannabis as an illicit Schedule 1 substance , states are increasingly legalizing cannabis use, with 18 U.S. states and the District of Columbia legalizing adult recreational cannabis use and 36 states legalizing medical cannabis use as of May 2021 . These states include California, where voters approved medical indoor cannabis grow system use in 1996 and recreational cannabis use in 2016, with retail sales of recreational cannabis beginning on January 1, 2018 . As cannabis legalization spreads, many health professionals are concerned about negative health effects of possible increases in cannabis use , with particular fears focused on potential fetal harms from cannabis use in pregnancy .

Studies investigating potential harms from cannabis use in pregnancy have documented a robust association between cannabis smoking and low birth weight . Some studies find increased risk of pre-term birth or small-for-gestational age associated with cannabis use in pregnancy , but others have not found these associations . Some studies have found associations between prenatal cannabis use and adverse neurocognitive outcomes  and increased psychopathology  in exposed children, especially when maternal cannabis use occurred after pregnancy recognition . However, most studies of harms associated with cannabis use in pregnancy suffer from methodological weaknesses, including an inability to adequately control for potential confounders including poverty  and poly-substance use including tobacco . In light of concerns about cannabis use in pregnancy, in 2019 the U. S. Surgeon General recommended total abstinence from cannabis for pregnant people . The American College of Obstetricians and Gynecologists  recommends that prenatal care providers ask all pregnant people about their substance use, including cannabis, and that “women reporting cannabis use should be counseled about concerns regarding potential adverse health consequences of continued use during pregnancy” . However, adherence to these recommendations appears low.

These studies have documented that pregnant people are uncertain but concerned about potential risks to their fetus from prenatal cannabis use , and that they seek information on risks and benefits of cannabis use in pregnancy from the internet as well as from friends and family . This research has also found that pregnant people would like to discuss cannabis with their healthcare providers but may be dissuaded due to concerns about being reported to child protective services  and potentially being separated from their newborn . Many pregnant people report receiving no counseling and education on health aspects of prenatal cannabis use from their healthcare providers , even after disclosing cannabis use . Instead, providers may emphasize legal consequences of use during pregnancy, rather than health-related aspects . Most of this research, however, was conducted in states and in time periods where recreational cannabis grow set up was illegal .

A recent national study focusing on general  contexts found that people who use cannabis were more likely to disclose use to their healthcare providers in states where such use is legal . We could see similar patterns related to cannabis use during pregnancy . But research in the U.S. to date has not yet examined patient-provider interactions regarding cannabis use during pregnancy in a context of legalized recreational cannabis. To fill these gaps, we conducted a qualitative study of people who used cannabis during pregnancy in California after legalization of recreational cannabis, to explore their experiences of their interactions with providers about cannabis. In May-August 2019, we conducted in-depth interviews for a qualitative study that sought to explore perspectives, decision-making, and experiences of pregnant and postpartum Californians who use cannabis regularly, in the context of legal recreational cannabis. This analysis focuses on participants’ experiences disclosing and discussing cannabis use with providers.

Confirming our hypothesis, frequency of concurrent e-cigarette and cannabis use was associated with increased odds of COVID-19 symptoms and diagnosis, with more pronounced odds observed as frequency of use groups increased, independent of student demographics and current use of combustible cigarettes, cigars, and smokeless tobacco. Thus, there appears to be a dose-related relationship, such that as use increased so too did the risk of experiencing COVID-19 symptoms and receiving a positive diagnosis. Specifically, for COVID-19 symptoms, effect size estimates were 3.5-fold among concurrent e-cigarette and cannabis users at any frequency of use, and these estimates ranged from nearly 5-fold to 7.5-fold among infrequent, intermediate, and frequent concurrent users. Similar findings were indicated for COVID-19 diagnosis, mobile grow systems with odds of nearly two times for concurrent users at any frequency of use, and approximately a 3-fold increase among both intermediate and frequent concurrent users.

There are several potential explanations of why concurrent e-cigarette and cannabis users, especially those with more frequent use patterns, were at higher risk of experiencing COVID-19 symptoms when compared with exclusive e-cigarette users. First, combustible cannabis and tobacco smoke contain similar carcinogenic and other harmful chemical toxins, but cannabis topography results in higher tar and gas per-puff exposures than that of combustible tobacco smoke . This can lead to acute respiratory health symptoms,and potentially airway inflammation and infection especially among heavy or long-term cannabis users . Second, e-liquids of nicotine- and THC-containing vaping products vary in constituents and are a potential source of inhaled toxic metal exposure , and there are over 400 brands that provide diverse products . THC-containing e-liquids may be distinct from nicotine-containing e-liquids and can lead to higher respiratory illness likely due to varying inhaled chemical constituents . For example, it is important to note e-cigarette, or vaping, product use-associated lung injury  was linked to illicit THC-containing vaping products and vitamin E acetate in nearly all  of cases, with median EVALI case patient age of 23 years and the majority being male.

For these and other reasons, the Centers for Disease Control and Prevention recommends individuals not use THC-containing vaping products due to the potential of tampering with e-liquids . While law enforcement seized vaping products containing vitamin E acetate intended for the illicit market , the clinical manifestations and symptoms of EVALI and COVID-19 and other respiratory illness overlap . Further research is needed to assess the associations of e-cigarette and cannabis grow supplies use with COVID-19 outcomes based on use patterns including cannabis inhalation route, and device type and ingredients among vapers. Current smokeless tobacco use increased student e-cigarette users’ odds by nearly 3-fold for reporting COVID-19 symptoms, which aligns with previous research documenting increased risk of respiratory symptoms from smokeless tobacco use.Combustible cigarette smoking and cigar smoking were not significant covariates of COVID-19 symptoms, despite prior research linking dual e-cigarette and combustible cigarette use with increased self-reported respiratory symptoms compared to exclusive e-cigarette use.

Additionally, no differences were found based on current combustible cigarette, cigar, or smokeless tobacco use and COVID-19 diagnosis. Prior research indicates all forms of tobacco use may increase COVID-19 infection susceptibility via the ACE2 receptor  and the furin enzyme found in oral mucosa , and has been recognized as a risk factor for severe COVID-19 manifestations . Future research using objective measures is warranted to better understand the complex associations between tobacco product type and COVID-19-related outcomes. As posited, no differences were detected between current use groups and COVID-19 testing, likely based on similar random testing policies at each university during the data collection period. Concerning our findings on COVID-19 diagnosis, the active ingredients of THC and nicotine and toxic substances vary among cannabis and e-cigarette products, respectively, and cannabis chemicals are metabolized slower in the body, placing cannabis users at increased risk of COVID-19 infection .

In parallel with tobacco regulations, cannabis control policies appear to impact cannabis use. In its Global Drug Report 2020, the United Nations noted that in jurisdictions that have legalized cannabis use, frequency of cannabis use has subsequently increased . Analysis of data for a US representative sample of adults with children living in the home found cannabis use to be more common in states that had legalized recreational cannabis use , possibly leading to increased in-home cannabis smoking and concomitant exposure of non-smokers. An overview of recreational cannabis use regulation by country is presented by Wikipedia on their “Legality of cannabis” webpage . The data demonstrate a substantial diversity across countries regarding whether cannabis has been legalized or decriminalized, the venues restricted, level of enforcement, and consequences for violations. In the US, a growing number of states have legalized cannabis for recreational or medicinal purposes, adding another layer of complexity. As with smoke-free ordinances for tobacco use,marijuana grow system the level of constraint imposed by cannabis control policies is likely to affect home smoking rules and behaviors.

While information about rates of in-home cannabis smoking and in-home exposure to cannabis SHS are not yet available, there is evidence that the perception of health risks associated with cannabis smoke is lower than for tobacco smoke . Furthermore, early evidence from US studies of household rules about in-home smoking suggests that 59% to 71% of people who used cannabis allow cannabis smoking inside their home, while just 26% allowed tobacco smoking in their home . With lower rates of in-home tobacco smoking, lower perceived risk of cannabis smoke, and relatively lax household rules surrounding in-home cannabis smoking, we expect higher rates of in-home cannabis smoking than in-home tobacco smoking. To test this hypothesis, we used data from over 100,000 adults from 17 countries to compare in-home cannabis and tobacco smoking among 2019 Global Drug Survey  respondents who use cannabis only, tobacco only, both tobacco and cannabis, or neither. Data for this cross-sectional analysis were from the 2019 GDS survey.

It was designed by substance use experts to assess existing and nascent patterns of substance use worldwide among annual samples of sentinel, more involved drug-using populations . The GDS promotes their survey via media partners from around the world such as HUFFPOST, VICE, MixMag, Fairfax Media, and The Guardian. They also use targeted social media campaigns on Facebook, Twitter, Reddit and drug discussion forums. The 2019 survey was available in 19 languages and collected data from over 35 countries. The core survey assessed demographics, drug use and consequences and in 2019 took about 15–20 min to complete—additional sections on psychedelic therapies, cannabis vertical farming edibles, and sex and drugs took an additional 25 to 30 min. No financial incentive was provided. Participants confirmed they were ≥ 16 years old, but there were no other eligibility requirements; participation was open to individuals regardless of participation in any prior year administration of the annual GDS. For the current study, eligible participants included 123,814 persons who took the GDS between October 29, 2018 and January 10, 2019 and reported past-year use of at least one of 31 psychoactive drugs, including the most commonly used: tobacco, alcohol or cannabis.

Consistent with previous GDS analyses, only countries that had greater than 1,500 respondents were included so that country-specific analyses could be conducted—therefore data from 17 countries were used, excluding 14,178 participants. Participants were also excluded if they were missing data on cannabis use, tobacco use, or in-home smoking of cannabis or tobacco . The remaining 107,274 comprised our final analytic sample. Ethical approval was obtained from the separate institutions: Joint South London and Maudsley and Institute of Psychiatry NHS , the University of Queensland  and The University of New South Wales . See Barratt et al.  for more information on the methods of the GDS. Participant characteristics were summarized for the total sample and stratified by the four tobacco and cannabis use groups. Group differences were tested using Pearson chi-square or t-tests, as appropriate.

Data were drawn from a larger study of alcohol use during the COVID-19 pandemic among Canadian adults . Four attention check items, as recommended by Prolific’s guidelines, were implemented in this study to ensure data quality  . Participants’ data were automatically excluded from the study if they failed 2 or more attention checks and completed all questions in an unrealistically short time . Of the 400 remaining participants, we selected a sub-sample that endorsed having used any type of cannabis in the past three months  for the present analyses. Participants’ data were further excluded for missing  or non-systematic  data on the Marijuana Purchase Task . The final sample was comprised of 137 participants. Data collection was completed from April 30, 2020 to May 4, 2020, approximately 7–8 weeks after the COVID-19 pandemic was declared. A majority of the measures required participants to respond to items by referencing either a month prior to the COVID-19 state of emergency in their area or in reference to the past month cannabis grow tent. This study was approved by York University’s Office of Research Ethics. All participants were given $13 CAD as compensation.

The present study is among the first to investigate mediational pathways to cannabis use and problems during the COVID-19 pandemic. We aimed to understand the role of indices of cannabis demand on motives for use and patterns of cannabis use and misuse. Previous research has indicated that individual differences in substance demand is a pre-existing factor that may place an individual at vulnerability for increased substance use and problems . In line with previous alcohol demand research, we hypothesized that internal motives for cannabis use, specifically coping and enhancement, may mediate this relationship. Our results indicate that two indices of demand, Persistence and Amplitude, were related to increased cannabis problems via the use motive of coping during the COVID-19 pandemic. This model did not support the role of enhancement motives. This finding indicates that those with increased cannabis demand who tend to use cannabis to cope are at increased risk of experiencing negative cannabis-related consequences. This is largely in line with previous research implicating increased cannabis demand in increased cannabis craving, use quantity and frequency, and dependence symptoms . Of particular note is the finding that the demand facet of Persistence was implicated in this model.

Previous research  has indicated that Amplitude was more associated with increased cannabis use and cannabis-related problems. This difference in finding may be attributable to differences in sample characteristics. The participants in Aston et al.  recruited pre-pandemic from Rhode Island, a U.S. state in which recreational grow lights for cannabis use is illegal. In contrast, participants in the current study were from across Canada during the COVID-19 pandemic, a country in which recreational cannabis use has been legal for over two years. Elevated cannabis demand appears to be a vulnerability factor for experiencing cannabis-related problems, and as such early identification and prevention efforts should be targeted at these individuals. This is especially relevant as the COVID-19 pandemic continues, with its associated unprecedented levels of stress and anxiety, both about the virus itself as well as caused by the associated lock downs and emergency measures.Cannabis use has been well-established as a method to cope with stress for some, and this method may be especially salient to those individuals who perceive cannabis to have a higher reinforcement value .

Other research has shown that COVID-19-related worry is associated with using cannabis to cope . Those that use cannabis to deal with stressors may be more likely to experience heavier cannabis use and more cannabis-related problems . Specifically focusing cannabis interventions on skills for coping with general and traumatic stress might be an important target to improve treatment outcomes . In extreme situations like the COVID-19 pandemic and associated lockdowns in which access to formal interventions might be limited, encouraging stress-reducing activities like exercise and yoga may be beneficial . Broadly, encouraging the use of more adaptive coping strategies rather than cannabis use is a clear implication of the current research. The findings of this study must be considered in light of certain limitations. The most significant limitation is the use of cross-sectional data to test a mediational model, and therefore being unable to determine the temporal precedence of variables.

Such cognitive differentiation is also critical to understanding the developmental neuroscience underlying cannabis use and abuse. The same neural resources supporting top-down regulation of emotion are also used to support non-emotional forms of “top-down cognitive con- trol ”. EA who can engage top-down control systems are able to make more active choices around cannabis use, rather than simply “defaulting to use ”or “following peer norms ”. Yet, emotional and cognitive control are of- ten treated as independent risk factors, ignoring the dynamic interplay between them. In fact, under the widely-accepted assumption of a finite resource pool, when attention is directed to emotional aspects of a stimulus or situation, it is necessarily directed away from other aspects of top- down control . Thus, individual differences in both reactive and regulatory responses to emotional stimuli may directly limit the resources available for top-down cognitive control and impair decision- making in emotion-laden contexts . Understanding how each of these processes is differentially related to cannabis use trajectories is a critical step in clarifying mechanisms of risk.

The bottom-up and top-down systems subserving emotional decision-making do not develop linearly throughout childhood, adolescence, EA,mobile grow system and adulthood. These processes rely on maturation of the prefrontal cortex  and amygdala-striatal emotional and reward processing regions that undergird perception and valuation of emotions . EA reflects a period of natural, but consequential, imbalances between these systems, when limited top-down control resources may be easily disrupted in emotional situations , inherently leading to potentially more hazardous decisions in and around cannabis use contexts . Existing cannabis interventions that focus separately on modifying attention biases  or building top-down control  have thus far, only shown modest efficacy in this age group. Clarifying dynamic relationships among the processes that support emotion regulation and their relationships to development of negative emotion and cannabis use over time will be critical to identifying intervention targets and increasing effectiveness of novel interventions for EA en- gaged in cannabis use.Emotion regulation may be a key risk factor that interacts with social inequality to increase hazardous cannabis use in EA. A growing body of work confirms that reactive attention capture, top-down regulation of emotion, and non-emotional top-down control processes may all be affected by the experience of social inequality .

Much of this work has focused on objective social inequality, and particularly SES, with consistent evidence that individuals from lower-SES backgrounds show increased reactive attention capture by negatively-valenced stimuli, more top-down re- sources directed to regulate emotion , mobile vertical rack as well as differences in the amount of neural resources that are engaged by non-affective top-down control tasks . What emerges is a picture in which EA who experience more objective social inequality tend to direct more neural resources to responding to emotional stimuli than their peers, while at the same time requiring more neural resources to effectively make non-emotional decisions. We note that some of these differences likely reflect adaptive response to environments that consistently stress emotional response systems , but may nonetheless increase risk in other contexts. While very little work has considered subjective social inequality, there is emerging evidence that experiences such as perceived discrimination are related to differences in both central  and peripheral  nervous system measures of emotional regulation as well. Further, the implications of these differences in emotion regulation may vary depending on social inequality context. In lab-based studies, differences in neural response are often found in the absence of performance differences on low-stakes tasks.however, there may be more significant effects on higher-stakes, real-world outcomes.

The same neural resources supporting top-down regulation of emotion are also used to support non-emotional forms of “top-down cognitive control ”. These non-emotional control processes are also implicated in cannabis use . EA who can engage top-down control systems are able to make more active choices around cannabis use, rather than simply “defaulting to use ”or “following peer norms ”. Yet, emotional and cognitive control are of- ten treated as independent risk factors, ignoring the dynamic interplay between them. In fact, under the widely-accepted assumption of a finite resource pool, when attention is directed to emotional aspects of a stimulus or situation, it is necessarily directed away from other aspects of top- down control . Thus, individual differences in both reactive and regulatory responses to emotional stimuli may directly limit the resources available for top-down cognitive control and impair decision- making in emotion-laden contexts . Understanding how each of these processes is differentially related to cannabis use trajectories is a critical step in clarifying mechanisms of risk.

The bottom-up and top-down systems sub-serving emotional decision-making do not develop linearly throughout childhood, adolescence, EA, and adulthood. These processes rely on maturation of the prefrontal cortex and amygdala-striatal emotional and reward processing regions that undergird perception and valuation of emotions . EA reflects a period of natural, but consequential, imbalances between these systems, when limited top-down control resources may be easily disrupted in emotional situations , inherently leading to potentially more hazardous decisions in and around cannabis use contexts . Existing cannabis grow lights interventions that focus separately on modifying attention biases  or building top-down control  have thus far, only shown modest efficacy in this age group. Clarifying dynamic relationships among the processes that support emotion regulation and their relationships to development of negative emotion and cannabis use over time will be critical to identifying intervention targets and increasing effectiveness of novel interventions for EA en- gaged in cannabis use.Emotion regulation may be a key risk factor that interacts with social inequality to increase hazardous cannabis use in EA.

A growing body of work confirms that reactive attention capture, top-down regulation of emotion, and non-emotional top-down control processes may all be affected by the experience of social inequality . Much of this work has focused on objective social inequality, and particularly SES, with consistent evidence that individuals from lower-SES backgrounds show increased reactive attention capture by negatively-valenced stimuli, more top-down re- sources directed to regulate emotion , as well as differences in the amount of neural resources that are engaged by non-affective top-down control tasks . What emerges is a picture in which EA who experience more objective social inequality tend to direct more neural resources to responding to emotional stimuli than their peers, cannabis grow tent while at the same time requiring more neural resources to effectively make non-emotional decisions.

We note that some of these differences likely reflect adaptive response to environments that consistently stress emotional response systems , but may nonetheless increase risk in other contexts. While very little work has considered subjective social inequality, there is emerging evidence that experiences such as perceived discrimination are related to differences in both central  and peripheral  nervous system measures of emotional regulation as well.Further, the implications of these differences in emotion regulation may vary depending on social inequality context. In lab-based studies, differences in neural response are often found in the absence of performance differences on low-stakes tasks.however, there may be more significant effects on higher-stakes, real-world outcomes. For example, disengagement from negative emotion predicts greater negative affect over time, and this association is amplified in youth from low SES back grounds.

Overall, hypothesis-driven approaches to simulation scenario developments should be guided by targeting the sensory, motor, and cognitive processes of interest, incorporating task requirements that require these processes, and that are designed to extract outcome measures that address meaningful application-related implications. Public opinion toward cannabis, particularly for medicinal uses, has shifted in a more positive direction since the 1990’s . The perception of cannabis from the public is informed by a number of factors, and each individual may have a different view based on personal needs or experience.Factors informing opinions of cannabis use may include generational cohort,religious affiliation, media exposure, prior or current prescription and illicit drug use, and political affiliation. However, even as attitudes toward cannabis have improved, there remains a significant stigma attached to cannabis that needs to be addressed .Even though medicinal cannabis was legalized in California over20 years ago, patients have faced difficulties receiving treatment. Patients across the United States have reported that the stigmatization of cannabis is a significant barrier to accessing it for treatment . In a study conducted in Florida, mobile grow system where cannabis is legal for medicinal use, only 9% of medical cannabis consumers reported their primary physician recommend edit as a treatment option .

In another study, patients noted the belief that their employers, family members, and healthcare providers possessed a negative stigma toward medical cannabis; patients noted they were worried about being thought of as a “pothead” or “stoner”. Due to the stigma surrounding medical cannabis, particularly by their own healthcare providers, patients tend to seek out medical cannabis from those with whom they do not have a long-term relationship .The lingering stigma toward cannabis may be due, in part, to the remaining associations from the War on Drugs focus of U.S. health policy.In these lessons, specially trained police officers presented students with general knowledge about illicit drugs. Until 2016, D.A.R.E. lessons taught that cannabis is a “gateway drug,” or a substance that leads to the misuse of more abuse-prone substances . While the D.A.R.E. program has been found to be largely ineffective in reducing illicit drug use among its participants,individuals who completed the lessons retained implicit beliefs on the negative effects of cannabis .

Examining past efforts of de-stigmatization can provide an important pathway to understanding how cannabis can have its stigma removed in the future. A well-documented example of a public health issue that has moved past its stigma is the HIV/AIDS epidemic. The beginning of the HIV epidemic in the 1980s proved to be riddled with misinformation.HIV/AIDS was heavily associated with marginalized groups such as sex workers, gay men, and drug users . However, as medical knowledge advanced in a meaningful way, many of the misconceptions of the HIV/AID Sepidemic began to diminish. The notion that only gay men could get AIDS was eventually dispelled when Magic Johnson publicly announced his HIV status . Medical evidence,mobile vertical rack paired with Magic Johnson’s openness,proved to be a powerful public health education campaign toward removing the dangerous stigma that was associated with HIV/AIDS.To better understand perceptions associated with medical cannabis use,this study sought to analyze the effectiveness of formal education in changing attitudes toward medicinal cannabis.

While there are many factors influencing public perceptions, formal education efforts in the past with the HIV/AIDS epidemic proved to be vital toward removing stigma. Formulating an education plan informing the public, patients, and health carepractitioners may be a driving force for the normalization of medical cannabisuse for patients seeking treatment. Five educational lectures were prepared by the first two authors whohave educational and professional experience in medical cannabis. The presentations were given via PowerPoint, recorded, and uploaded to YouTube for participants to access via the research website. The presentations ranged in length from 7:36 to 19:41, which required a total participant time commitment of approximately 1.5 h.The respective lectures focused on the historical uses of medicinal cannabis;pain; anxiety, mood disorders, and insomnia; cancer; as well as risks and negative effects. Topics for the educational lectures were based on an extensive literature review, which concluded that the most common ailments currently being treated by medicinal cannabis are sleep disorders,pain, and anxiety disorders .

Similarly, in a study among U.S. cannabis consumers, higher rates of home cultivation were found among those living in rural areas of the U.S . It may suggest that Canadians residing in rural areas may have more land and space to grow, further from retail stores, or comfort to grow undetected or without disturbing neighbours. Indeed, respondents living in smaller living spaces in urban settings may be further influenced by restrictions on home cultivation in rented accommodation or shared living spaces . A strength of the current study is its inclusion of both consumers and non-consumers . Previous research focuses on cannabis consumers, where more frequent cannabis grow lights consumers have higher rates of home cultivation than infrequent consumers, as seen in the current study . However, non-consumers also grow cannabis plants either for sharing or sale, and therefore should be included in research. The Canadian Cannabis Survey included non-consumers in their 2020 study; however, the survey did not specify personal cultivation by non-consumers, i.e., non-consumers could report home cultivation in their home by others . Future research should capture non-consumers in studies around home cultivation and examine the reasons for growing. This study is subject to limitations common to survey research.

Respondents were recruited using non-probability-based sampling; therefore, the findings do not necessarily provide nationally representative estimates. The data were weighted by age group, sex, region, education and smoking status in Canada. Cannabis use estimates were generally lower than national estimates for young adults, and higher than national surveys in Canada. This is likely because the ICPS sampled individuals aged 16–65, whereas national surveys included older adults, who are known to have lower rates of cannabis use. The 2018 survey did not ask all respondents about home cultivation, only past 12-month cannabis consumers. We were therefore unable to examine the changes between 2018 and 2019/2020 among all respondents, only past 12-month consumers.A total of 15% of the sample in the regression analysis were removed due to missing values in rural/urban status. To ensure we were not introducing substantial bias into the analyses, we conducted a sensitivity analysis with rural/urban status removed and similar patterns emerged. The survey did not clarify whether the amount spent on plants/seeds or clones corresponded with the number of plants grown, i.e., some seeds may not have been planted or completed gestation. Therefore, the ‘price per plant’ value may change depending on whether only ‘successful’ plants or incomplete plants were counted.  

The use of cannabis has been legalized in varying degrees across the globe, with Canada legalizing it for recreational use in 2018. As a result, there has been an increased urgency to better understand its impact on driving performance and safety. Cannabis affects cognitive, sensory, and motor functions  that are important for safety–critical tasks such as driving, including judgement, working memory, response time, coordination, and concentration . The cannabis grow tent plant is composed of over 400 chemical compounds, including over 60 cannabinoids . The primary psychoactive component is delta-9-tetrahydrocannabinol . This ingredient, along with its psychoactive and non-psychoactive metabolites, is responsible for the majority of the behavioural and pharmacological effects of cannabis use . However, there is limited scientific consensus on identifying THC concentration levels that objectively define levels of impairment , due to a poor concentration–response relationship between THC levels in bodily fluid samples  and driving performance . Thus, it is important to develop methods that will aid in determining whether cannabis use affects driving performance and in what ways.

The two most prevalent methods for cannabis consumption are inhalation  and oral ingestion. Cannabis inhalation results in a fast peak of THC concentration in blood and saliva within the first 5–15 min after smoking , as well as a fast decrease due to the half-life of THC being approximately 1.5–2 h depending on individual usage history and other factors . On the other hand, after oral ingestion absorption of THC into the bloodstream is significantly slower, with peak blood THC levels observed 1 to 5 h after administration . Inhalation results in onset of impairment within a few minutes and recovery within a few hours, while the impairing effects from ingestion begin within 1–2 h and end up to 12 h after use . It is also important to note that blood or saliva THC levels are not necessarily directly associated with the degree of behavioural impairment .

As noted by Lorenzetti et al. , quantification based on a more general metric is recommended in situations where the individual cannot accurately estimate the quantity of cannabis use. Estimating the number of “hits” per day also provides a metric by which to assess changes over time, which is consistent with the goals of the CEA. Other estimates of test–retest reliability were moderate to high, supporting the temporal stability of the CEA over a one-week span. As such, the CEA may be useful in tracking changes in use over time. While interventions for cannabis misuse have typically emphasized abstinence-only outcomes, controlled use is also a popular treatment goal . Evaluation of the utility of interventions for cannabis use among individuals who do not want to achieve complete abstinence required the ability to measure changes in cannabis engagement over time. Other measures, such as the DFAQ-CU, while showing good preliminary psychometric properties, do not provide detailed information of use within a specified timeframe. The CEA, in contrast, is designed to assess cannabis grow tray use in the preceding 30 days. Comparison of the CEA to other measures also provided support for its utility.

When compared to related factors on the DFAQ-CU, indicators of frequency and quantity of cannabis use on the CEA generally showed small to moderate associations. One exception is daily sessions of edible use, which showed only a weak association to the DFAQ-CU daily sessions factor. However, the daily sessions factor is only comprised of items that assess sessions of concentrate and dry product use. Therefore, it is unsurprising that sessions of edible use were unrelated to this factor. Overall, the pattern of results suggests that the CEA assesses related, but not identical, aspects of cannabis engagement as compared to the DFAQ-CU. Estimates of frequency generally showed stronger associations with the CUDIT-R than measures of other less directly related constructs. Moderate correlations were generally observed between the CUDIT-R and indicators of cannabis use frequency and quantity. The AUDIT-C showed smaller associations with these same measures, supporting the CEA’s divergent validity. Overall, the CEA shows good psychometric properties which supports its use as a self-report measure of recreational cannabis use in the preceding 30 days. This study has several limitations. First, the number of community participants who agreed to participate in the follow-up interview was small, despite the higher gift card value for participating in the follow-up interview compared to the online survey.

Therefore, test–retest reliability, and the level of agreement between the CEA and TLFB could not be separately examined for the two samples. Second, the study relied on convenience samples.This is not surprising, given the higher prevalence of cannabis use and misuse among males than females in community samples . In contrast, student samples tend to have an overrepresentation of females . Given the observed imbalance within each sample, as well as between the two, it was not possible to assess gender differences. Third, a few CEA variables showed low test–retest reliability. We have therefore eliminated or changed the questions to improve reliability. Lastly,vertical grow systems for sale the study did not include a biological or other objective measure of cannabis use. Future research should also include other methods for assessing cannabis use such as biological measures to further examine the psychometric properties of the CEA.  The prevalence and frequency of cannabis use among pregnant and non-pregnant individuals of reproductive age has increased in recent years .

Cannabis use during pregnancy is associated with potential adverse health effects, and the American College of Obstetrics and Gynecology recommends that individuals who are pregnant or contemplating pregnancy discontinue cannabis use . Patterns of substance use tend to develop before pregnancy and nearly all individuals who report using cannabis during pregnancy also report using prior to pregnancy . Surveillance of preconception cannabis use is critical given that nearly half of pregnancies in the US are unplanned , and pregnant individuals are particularly at risk for cannabis use during the first trimester. The legalization of cannabis has led to the proliferation of new cannabis products with various modes of administration  and is associated with greater preconception cannabis use . The likelihood of quitting cannabis use before pregnancy and the potential adverse health effects to infants exposed to cannabis in utero might vary depending on maternal mode or combinations of modes of cannabis administration .

Among the taxa that were increased in the saliva of cannabis smokers, five belonged to the Streptococcusgenus, and four belonged to the Actinomyces genus. Among the taxa that were enriched in the saliva of non-smoking controls, six belonged to the Neisseria genus . No differences were observed based on quantity of cannabis use or presence of neurological disease history between the heavy users  and light users , and between smoked cannabis containing THC and cannabis containing no THC .Nonetheless, the enrichment of A. meyeri was inversely correlated with the age of first cannabis use .To study which taxa may represent the cannabis smoking oralmicrobiome, we reanalyzed and compared the saliva microbiome from tobacco smokers and non-smoker controls from our published data . Consistent with the results from previously published studies, we found increased Streptococcus and decreased Neisseriain the oral microbiome of tobacco smokers compared with those in non-smoking controls , which was similar to cannabis smokers. However, Actinomyces genus was only increased in cannabissmokers but not in tobacco smokers . To further analyze Actinomyces genus bacteria, mobile grow system we have shown four Actinomyces species bacteria that were significantly increased in cannabis smokers .

Only Actinomyces turicensis was increased in tobacco smokers when compared with non-smoker controls . We further analyzed the difference after adjusting for age, sex, and/or alcohol use. All differences between cannabis users and controls identified in the univariate analysis shown in Fig. S1 remained significant after adjusting for sex, age, and alcohol consumption, although P values were attenuated slightly . When comparing tobacco users to controls, only Streptococcus  andA. turicensis , but not Neisseria, remained significant after adjusting for sex and age.The smoking and altered microbiome composition may lead to a compromised mucosal epithelial barrier, which results in the translocation of bacteria or microbial products into circulation. Thus, bacterial fragments or whole bacteria can appear in the blood from translocation and thereby influence the immune system . To study oral microbial translocation in cannabis users, we evaluated the plasma levels of IgG antibody against antigens derived from A. meyeri, A. odontolyticus,and N. elongata. Plasma levels of IgGs against A. meyeri antigenstended to increase in the cannabis smokers compared to controls, while similar levels of IgGs against antigens from the other two bacteria were observed .

These results imply that A. meyeri or its antigens may preferentially translocate from the oral mucosa to the circulation in the setting of an altered oral or periodontal environment in cannabis smokers. In a previous study, oral administration of Campylobacter jejuni activated state of neurons in nucleus tractus solitarius and increased c-Fos expression in the hypothalamic paraventricular nucleusas inmice . To determine if cannabis use-associated oral microbiome affects CNS, we inoculated live A. meyeri, A. odontolyticus, and N. elongata into the oral cavity of C57BL/6 mice. A. meyeri and A. odontolyticus are oral commensal bacteria  and were enriched in theoral microbiome of cannabis smokers found in this study. N. elongata,which was enriched in non-smoking controls , mobile vertical rack was used as a control. We examined mouse activity through a uniformly cylindricalarena. The behaviors of mice were quantified and shown by global activity, total distance traveled , average speed , and resting time.

The behavior of N. elongata-treated mice in the arenawas comparable with the PBS-treated mice. However, compared with N. elongata-treated mice, A. meyeri-treated mice exhibited decreases in global activity, distance traveled, and mean speed, as well as increases in resting time .Next, we have evaluated amyloid production in mouse brain tissues as it is a marker of neurodegenerative diseases. Although Ab 40tended to be increased in A. meyeri-treated mice, there was no statistical difference between any two groups . Notably, the Ab 42peptide in the brain from A. meyeri-treated mice was increased significantly compared to the control groups . To validate alterations in oral and gut microbiome, we collected the samples from oralswab and stool one week after the final oral administration of live bacteria. Specific bacteria were quantified using qPCR, and the abundance of each bacterium was normalized by total 16S rDNA. We confirm edoral inoculated bacteria by qPCR . Notably, both A.odontolyticus and N. elongata, but not A. meyeri, presented in the orals wab of some mice from the PBS group, suggesting A. odontolyticus and N. elongata may be oral commensal microbiome in mice .