Hemp Growing

Similar to direct tobacco advertising, viewing tobacco products on TV/movies is also positively associated with youth tobacco use . Several U.S. states, including California, legalized the sale, possession, and use of cannabis recreationally among adults, beginning in 2012. Commercialization and marketing of cannabis products began shortly afterwards . However, unlike with tobacco, there are relatively few restrictions on cannabis marketing, in part because cannabis is classified federally as a schedule I drug despite legal sales of recreational cannabis in 11 states and the District of Columbia . Consistent with studies that show viewing tobacco marketing increases risk for tobacco use, a small body of cross-sectional work has also shown that viewing cannabis advertisements is associated with higher odds of cannabis use , as is seeing cannabis use in TV/movies . The tobacco and emerging cannabis marketplaces have changed considerably over the past decade, resulting in a proliferation of new tobacco and cannabis products , which have become increasingly popular among YA . There is also evidence that tobacco and cannabis companies are marketing these products in new ways – through online platforms such as social media ,which may disproportionately impact YA who rely on the Internet more heavily than older adults . For example, a recent study examining JUUL’s marketing campaign revealed that thousands of Instagram posts, emails, and other advertisements were targeted to youth, and non-smoking populations . Similarly, Medmen recently initiated a well-funded national advertising campaign, including advertisements on the Howard Stern and Adam Carolla shows, YouTube videos, billboards, and social media advertisements .

Given the increasing array of tobacco and cannabis products and methods for marketing them , it is important to identify the extent to which YA recall seeing marketing, for which products, and through which channels . Marginalized populations, including sexual and gender minorities, racial/ethnic minorities, and populations of lower socioeconomic status, use tobacco and sub irrigation cannabis products at higher rates, relative to the national average . Historically, these groups have also been disproportionately exposed to cigarette advertisements targeted specifically to minority populations . However, little is known about whether, or how viewing of marketing for new and emerging tobacco and cannabis products differs across sociodemographic characteristics, such as race/ ethnicity, gender identity, sexual identity, and socioeconomic status in YA. This study had two aims. First, we assessed prevalence of recalling online advertisements, as well as seeing product use in TV/movies, for a wide range of tobacco and cannabis products among a diverse sample of YA cannabis products in California from Southern California. Second, we assessed sociodemographic differences in recalling online advertisements and seeing product use in TV/movies for any tobacco products and any cannabis products. All analyses were limited to never-users of tobacco and cannabis products, respectively. Sociodemographic characteristics were first calculated, separately among never users of tobacco and cannabis products . Then, prevalence estimates were calculated for recalling seeing tobacco and cannabis marketing. Unadjusted estimates are reported for both Internet- and TV/movie-based marketing, and F-tests assessed whether prevalence differed significantly by marketing source for each product. Finally, sociodemographic differences were assessed for recall of marketing for any tobacco or cannabis products, separately for Internet- and TV/moviebased marketing channels. Pairwise comparisons assessed whether response categories of each sociodemographic characteristic differed significantly from one another. Multivariable logistic regressions also assessed associations between all sociodemographic characteristics, in combination, on recalling any tobacco and any cannabis marketing. All analyses were limited to never-users of tobacco and cannabis and were conducted in 2020 using Stata SE version 15. Sample characteristics of users vs. never-users of tobacco and cannabis were compared in Supplemental Table 1. This study assessed prevalence of, and sociodemographic differences in recalling tobacco and cannabis product marketing among a sample of Southern California YA reporting no history of tobacco and cannabis use, respectively.

For the majority of products – all combustible tobacco products, combustible cannabis, and edible cannabis – respondents had higher odds of seeing use of those products on TV/movies than they did seeing online advertisements. Portraying tobacco use in TV/movies has been an effective – and profitable – way to advertise tobacco products , increasing risk for tobacco use initiation among youth . While considerably less research has assessed the role of seeing cannabis products in TV/movies on initiation of cannabis use among young people, cannabis brands have been successful in negotiating product placements with entertainment studios, and with almost no regulation . While it is impossible to discern the degree to which respondents saw tobacco and cannabis products in TV/movies through intentional product placements and/or through the artistic discretion of the TV/filmmakers, our results highlight that shows and movies reaching young people include a considerable amount of tobacco and cannabis product use. Effective measures to reduce exposure to this form of marketing may include giving programs that display tobacco or cannabis use R and TVMA ratings and prohibiting the display of recognizable brand names, among other actions. Consult the Truth Initiative for a full list of measures endorsed by the organization . While there is ample evidence that JUUL and other e-cigarette brands are indeed promoted on TV/movies , respondents in this sample had higher odds of recalling seeing online advertisements for these products. Given that youth and YA remain the largest demographic group of Internet users , and that the proportion of young people using e-cigarettes has risen , online advertisements for e-cigarettes may disproportionately influence underaged youth and YA to experiment with, and become regular users of e-cigarettes. A future direction for effective tobacco regulation might include limiting online marketing for e-cigarette products. While logistically challenging, online marketing should ideally be regulated in such a way that ensures first amendment protections to e-cigarette companies, while also limiting exposure among YA never users. A number of sociodemographic differences were also found with regard to viewing tobacco and cannabis marketing. For example, women reported seeing online cannabis advertisements at higher rates than men. Compared to men, greater percentages of women also reported seeing tobacco and cannabis products on TV/movies. It is possible these findings stem from documented gender differences in processing and recall of advertising details, with women recalling details of advertisements more clearly than men .

However, it is also plausible that young women who recall seeing tobacco and cannabis products in TV/movies may be at especially high risk for using those products themselves. In prior longitudinal work among nonsmokers, young women who watched a favorite actor smoke on screen had a nearly twofold increase in risk for smoking themselves. This association was not significant among young men . In multivariable analysis, LGB-identified YA also recalled seeing online cannabis advertisements at a higher rate than straight respondents, and prior research has shown that LGB youth have a greater willingness to use cannabis products than their straight peers . Together, these findings highlight that young women and LGB people may be priority populations for public health efforts to prevent tobacco and cannabis use. Several racial/ethnic differences were found. Interestingly, racial/ ethnic minority respondents had lower odds of recalling marketing, across a number of comparisons. For example, Asian YA had about half the odds of recalling seeing online cannabis advertisements and seeing use of cannabis products in TV/movies, compared to White respondents. Further, compared to White respondents, Black respondents had about 40% odds of recalling both tobacco and cannabis use in TV/movies, and respondents reporting an “other” race/ethnicity had about 50% odds of recalling cannabis use in TV/movies. While cigarette companies have a long history of targeting advertisements to Black populations , our results suggest that among never-users, White YA are more likely to see online advertisements for tobacco and cannabis, or to see those products used in TV/movies. However, it should be noted that while this analysis was focused on identifying sociodemographic disparities in seeing marketing, all groups did recall seeing some degree of marketing .However, while many U.S. states have legalized the sale of cannabis products, they remain illegal federally. This limits the ability to effectively regulate accessibility to cannabis products for adults and those who may benefit from them , while also limiting exposure to those most vulnerable to misuse . Respondents in this sample were below the legal purchasing age for cannabis products in California, yet a large proportion of them – all of whom reported never using cannabis in the past – reported seeing online advertisements and use of these products in TV/movies. These results highlight a need for more research related to cannabis marketing exposure and subsequent use among YA, and the role of regulations to limit exposure.

While individual states may be unable regulate online advertisements, they would be able to regulate local advertisement , should they be shown to deliberately and effectively target underage youth. More work is still needed to understand how to effectively regulate pro-use messages online and in TV/movies. First, our main outcome measure was self-reported recall of tobacco and cannabis marketing, which may not reflect actual marketing efforts to place ads where YA will see them. Instead, our measure signifies where YA were most likely to notice tobacco and cannabis advertisements. Second, these analyses were cross-sectional; we were unable to assess whether recalling marketing was associated with tobacco and cannabis use initiation. Third, this study assessed whether respondents recalled seeing marketing both online and in TV/movies, though there exist a host of other ways in which tobacco and cannabis products are marketed . Additional research is needed to understand YA exposure to pro-tobacco and cannabis marketing across a wider range of marketing platforms. Further, tobacco products are marketed online largely via organic social media posts not labeled as advertising . Since respondents were asked generally about seeing ads “when using the internet,” we were unable to disentangle the various types of online marketing YA saw. Fifth, patterns of media consumption vary among YA , and heavy media users may recall more tobacco and cannabis marketing than light media users. While respondents were able indicate if they did not use the Internet or if they did not watch TV/movies at all, we were otherwise unable to account for the frequency or timing of their Internet or TV/ movie consumption. Sixth, these data are from a cohort of YA from Southern California, and so may not reflect national or regional trends in perceived marketing exposure. However, the sample was similar to population characteristics of Los Angeles, CA in terms of race/ethnicity and educational attainment . To reduce survey burden, respondents were not asked to report on all characteristics that may potentially be related to substance use . Finally, small sample sizes in some of the sociodemographic subgroups and in some of the specific products marketed resulted in wide confidence intervals on some of our estimates, vertical grow and also precluded us from testing sociodemographic differences in viewing marketing across the various products. The legalization of recreational cannabis use is associated with an increase in both consumption as well as risk of cannabis-use disorder in adolescents and adults . Early research found cannabis use to be an independent risk factor for the development of schizophrenia, allowing for psychiatric and substance use comorbidity . A variety of studies have subsequently supported an association between cannabis use and the development of schizophrenia, with cannabis use in adolescents having a particular impact on cortical development in males with genotypical susceptibility to schizophrenia . Schizotypy is a continuum of personality characteristics and experiences, ranging from normal dissociative states to extreme mental states related to psychosis that can extend to a clinical diagnosis of schizophrenia. Schizotypy is useful in the study of schizophrenia spectrum disorders as it can provide a framework upon which the etiological and developmental pathways to schizophrenia spectrum disorders can be tracked and dissected . Both schizotypy and schizophrenia comprise a similar multi-dimensional structure, with much evidence converging on the presence of three dimensions: positive, negative, and disorganised . The cognitive deficits associated with schizotypy are also well-recognised, and include difficulties in selective and sustained attention, incidental learning, and memory .

The present LRCUG review and recommendations are principally science-based and geared towards related audiences. differentiated and specifically tailored communication approaches will be required for different target audiences . These efforts may need to vary for different age, cultural or other specific groups and involve different communication styles and media formats. These ‘knowledge translation’ challenges are similar to those for other health interventions and need to be better understood and their effects evaluated .According to Small , the consequences of artificial selection make it impossible to determine if unaltered primeval or ancestral populations still exist. This author recommends that C. sativa be recognized as a single species with a narcotic subspecies  and a non-narcotic subspecies , each with domesticated and ruderal varieties. A similar approach is the definition of four major biotypes of cultivated Cannabis  with morphological and chemical differences submitted to different uses, either fiber/oil or drug production . There is also a hybrid between NLD and BLD, known as sinsemilla, which is highly psychoactive  and, hence, is used mainly as a drug. The sinsemilla cultivars were developed in the New World and diffused worldwide. In contrast to the former biotypes, this hybrid is only cultivated, with no feral escapes or ruderal populations. The current distribution of these biotypes is shown in Fig. 1. Cannabis sativa is a sun-loving  species that requires well-drained and nitrogen-rich soils, warmth and moisture. Therefore, most natural populations are found seasonally across accommodating northern temperate latitudes.

This plant grows well along exposed riverbanks, lakesides, margins of agricultural lands and other areas disturbed by humans. Cannabis plants are annual and usually diecious, as determined by X and Y chromosomes, and anemophylous . The annual cycle extends from spring  to summer  and autumn . Male plants, which are slightly taller than female plants, die shortly before pollination. Female plants ripen viable seeds just before the arrival of winter killing frosts. Seed dissemination is carried out mostly by wind or feeding birds. During germination, plant benches seeds are surrounded by bracts with hairs that produce a resinous blend of cannabinoids and aromatic compounds as secondary metabolites, which are believed to protect seeds against pests and pathogens.Almost all parts of the Cannabis plants are utilized for a variety of uses . For example, stem bark and fiber are used for cordage, woven textiles, building materials, paper, animal bedding and fuel. Seeds and seed oils are used for human food, animal feed, industrial feedstock and fuel. Female flowers and seeds are used for medicine or recreational drugs. All parts of the plant, primarily bark, seeds and female flowers, are used in ritual and social activities . Cannabis populations may also be used for environmentally related activities, such as the control of soil erosion and to increase CO2 sequestration. Esthetic and educational applications include botanical gardens and the iconic character of the plant as a symbol of a very ancient crop deeply rooted in human culture . Early attempts to identify the place of origin of wild Cannabis prior to human contact were based on the geographic distribution of its wild, cultivated and ruderal populations, combined with the known ecological requirements and reproductive strategies.

However, the distribution of this plant and its biotypes/varieties is closely associated with human settlements and trade routes, and therefore, the original native range is obscured . In spite of this, a broad area referred to as central Asia  was proposed as the center of origin of Cannabis . Another, less generally accepted, possibility mentioned was south Asia . Regarding timing, accepting that the central Asian steppes were colonized by humans by 35,000 years ago , it has been assumed that wild Cannabis could have originated earlier. These hypotheses, however, were based on circumstantial evidence, and robust empirical evidence was lacking. This empirical evidence was provided by the fossil record and the use of time-calibrated molecular DNA phylogenies.The macrofossil record of Cannabis is relatively scarce and consists of only a few leaf and fruit/seed impressions with ages ranging between the Oligocene and the late Miocene . However, microfossils, specifically pollen, are abundant and widespread and have commonly been utilized to reliably reconstruct the history of Cannabis. Nevertheless, the identification of Cannabis pollen deserves special attention because of its similarity with other members of the family Cannabaceae, especially Humulus , a sister genus that bears contrasting ecological requirements and cultural connotations. Therefore, inaccurate identification might lead to erroneous conclusions . This is why different authors have used broader taxonomic categories for this pollen type, such as Cannabis-type, Cannabis/Humulus or Cannabaceae. In addition, it is unclear whether pollen from wild and cultivated Cannabis may be distinguished morphologically. Several morphological details have been suggested to be useful to differentiate Cannabis and Humulus pollen. Godwin  emphasized several differential characteristics of the pore complex. Further statistical studies revealed that Cannabis pollen is generally larger than Humulus, but this character alone was not sufficient to allow reliable separation .

Pollen size also seems to be an unreliable parameter to separate wild from cultivated Cannabis . The combination of pore complexes and size seems to provide a more reliable, yet not universally accepted, identification criterion to differentiate between Cannabis and Humulus pollen . However, even in the case of conclusive Cannabis pollen identifications, comparisons with studies referring to this pollen type as Cannabistype, Cannabis/Humulus or Cannabaceae remain problematic, which may be a handicap for the development of meta-analyses aimed at reconstructing past biogeographic and cultural patterns. Recently, some meta-analyses have been conducted using different criteria, such as considering the entire Cannabis/Humulus complex or taking into accountonly those studies that explicitly identified Cannabis pollen . These approaches tend to overestimate or underestimate the actual pollen record of Cannabis. A different approach, called here the assemblage approach, has recently been proposed by McPartland et al. . These authors noted that wild C. sativa is typical of open temperate steppe habitats dominated by grasses, chenopods and Artemisia, whereas Humulus is a vine plant that requires trees to climb and is common in temperate deciduous forests dominated by alder , willow  and poplar . A third assemblage corresponds to cultivated Cannabis, which is usually found together with cultivated cereals such as Avena , Hordeum , Secale  and Triticum , as well weeds such as Centaurea  or Scleranthus  species. Using these phytosociological affinities, McPartland et al.  attributed the Cannabis-like pollen types recorded in the literature to wild Cannabis if this pollen occurred together with steppe assemblages; to cultivated Cannabis when it was part of crop assemblages; or to Humulus if the dominant pollen assemblage corresponded to temperate deciduous forests. Based on these premises, these authors developed a more complicated identification algorithm that also considers the relationship between arboreal  and non-arboreal  pollen . Using these criteria, the oldest known pollen compatible with Cannabis was found in 19.6 Ma-old  rocks from the NE Tibetan Plateau , which was proposed as the center of origin of Cannabis . Interestingly, this proposal roughly coincides with the former hypothesis based on indirect biogeographic evidence.

The use of DNA molecular phylogenies calibrated with fossils of related genera such as Humulus, Celtis, Morus and Ficus  allowed to estimate the age of divergence of Cannabis and Humulus to 27.8 Ma . Using the same DNA phylogeny and the associated molecular clock, the divergence between C. indica  and C. sativa  would have occurred in the Middle Pleistocene approximately 1 Ma . These authors noted that there is a gap of ca. 8 million years between the age of origin estimated by the molecular clock and the first fossil pollen encountered. In spite of this, they favored the mid-Oligocene age for the origin of Cannabis on the NE Tibetan Plateau , assuming that, as demonstrated by the presence of Artemisia and other steppe elements, the region was covered by this type of vegetation, which would have been particularly well suited for the development of Cannabis. A previous study using Bayesian calibration estimated the divergence between Cannabis and Humulus to have occurred 21 Ma , which is closer to the age  of the first fossil pollen evidence mentioned above . According to pollen and seed fossil records, Cannabis would have experienced some expansion from its center of origin to Europe and East Asia well before the evolutionary appearance of the genus Homo . The suggested dispersal agents are water  and animals  . The first expansions occurred to the west  and the east  during the Miocene-Pliocene. Most parts of the Asian continent were colonized by Cannabis during the Pleistocene , rolling bench before the onset of the Neolithic, when humans domesticated the first plants. During the Pleistocene, glacial-interglacial recurrence could have contributed to Cannabis diversification without human intervention. It has been suggested that Cannabis underwent recurrent range contractions  and expansions  that facilitated allopatric processes, possibly leading to the differentiation between the European  and Asian  subspecies, which would have diverged nearly 1 Ma .

The first is considered the putative hemp ancestor , and the second is the putative drug ancestor  . In addition to fossils and DNA phylogenies, archeological evidence is of paramount importance to reconstruct domestication and anthropogenic diffusion trends within Cannabis. The main types of evidence of Cannabis from archeological sites are pollen, seeds, fibers, fiber/seed impressions, carbonized remains, phytoliths and chemical remains. During the historical period, written and graphic documents are also of fundamental help . Pollen identification has some additional clues related to its abundance in sediments, as Cannabis produces much more pollen than Humulus, which is usually underrepresented . This is especially useful in cases of very high percentages of this pollen type, which are difficult to explain unless the sediments come from a former hemp-retting site. Indeed, when flowering male hemp plants are soaked in a retting pond to separate the fibers from the stalk, large quantities of pollen settle into pond sediments. In these situations, the percentages of Cannabis pollen in sediments may reach 80–90% of the total, but percentages over 15% or 25% have been considered sufficient to infer hemp retting . The anemophylous pollen of Cannabis may be transported long distances; therefore, the finding of a few grains or their scattered occurrence throughout a stratigraphic section is not necessarily evidence for the local presence of the parent plant. Recent developments in molecular DNA analytical methods have increased the probability of identifying Cannabis sativa in lake sediments and comparing these results with the abundance of Cannabis/Humulus pollen. For example, in lake sediments from the French Alps, Giguet-Covex et al.  found a good agreement between DNA and pollen records for the period 1500–1000 yr BP but significant inconsistencies for the periods 2000–1500 yr BP and 500 yr BP-present.

During these periods, the Cannabis/Humulus pollen attained values of 10–15% and DNA was undetectable, which could be attributed to the dominance of Humulus pollen in the pollen record. The debate regarding the Cannabis center of domestication has paralleled the taxonomic controversy on Cannabis species that, as seen before, was already active by the time of Linnaeus and Lamarck. See, for example, Clarke and Merlin  and Small  for more details on this long-standing discussion. Whether single or multiple centers of Cannabis domestication occurred has profound implications for the tempo and mode of Cannabis diffusion in Eurasia, where the plant evolved and was domesticated. Some authors have proposed that Cannabis was domesticated in Central Asia  by 12,000 BCE , which would place Cannabis among the oldest human domesticates . A recent genome-wide phylogeographic study supports a unique center of domestication in east Asia , from which all biotypes would have emerged and dispersed throughout the world . According to this analysis, early domesticated ancestors of hemp and drug types diverged from wild Cannabis ca. 12,000 yr BP, which indicates that the species had already been domesticated by early Neolithic times. Among the defenders of the single center hypothesis, Small  suggested that Cannabis was domesticated in the northern Caspian Sea and that the four different domesticated groups were transported to other parts of the world during the last millennium. These four groups coincide with the above mentioned biotypes NLH , BLH , NLD  and BLD .

In addition, about 15-30% of PWUC drive under the influence of cannabis, with roughly 20% of cannabis related traffic injuries being fatal Furthermore, it is estimated that only about 2% or less of PWUC experience a severe cannabis induced mental health problem. The population-based probabilities of PWUC experiencing many of the other identified cannabis-associated adverse health outcomes are even smaller. In addition, except for cannabis-related motor-vehicle-crash fatalities, cannabis use makes virtually no direct contribution to mortality. Recent national and global estimates have identified cannabis-impaired driving and related injuries/death – which may include non-using others – and CUD as leading contributors to the cannabis-related disease burden . While the estimated contribution of cannabis to disease burden is not insubstantial, it is far smaller than that for alcohol or tobacco. In many jurisdictions, longstanding laws prohibiting non-medical cannabis use under penalties have been liberalized in recent years. This has, partly, been because cannabis has limited adverse health consequences and partly because of the excess of personal and societal costs of criminal penalties for cannabis use . The most liberal policies have included the legalization and regulation of non-medical cannabis use and supply to adults in Uruguay , Canada , Mexico , and in a growing number of state jurisdictions in the United States , initially including Colorado and Washington .

These legalization regimes, however, feature rather heterogeneous regulatory frameworks . In addition, other jurisdictions have been contemplating legalization reforms. Commonly, the case for cannabis legalization is made to improve public health and safety outcomes . specifically, it is assumed that under legalization, the distribution of cannabis products will shift from criminal to legal markets allowing better regulation of cannabis products and targeted interventions to minimize adverse cannabis-related health and social outcomes from – now legal – use . While mostly US-dominated, evidence suggests that legalization has reduced some social harms.The evidence on public health impacts is mixed. Specifically, data have suggested select increases in the prevalence and intensity of use among adults , hospitalizations, and cannabis-related MVCs,drying racks mostly by comparison to non-legalized settings . The effects of legalization on CUD or treatment seeking has been mixed, while attitudes towards risks of cannabis use have softened in several sub-groups.The success of cannabis legalization as a policy experiment that benefits public health and safety outcomes therefore remains uncertain. However, these desired beneficial outcomes will require PWUC, especially the disproportionately large number of young users, to have guidance on how to reduce key risk-behaviours that contribute to adverse health outcomes and related disease burden . To that general end, international expert teams had previously tabled evidence-based ‘Lower-Risk Cannabis Use Guidelines’ including targeted recommendations for PWUC, with the principal aim of identifying use behaviour-related risk factors modifiable by the user-individual that will aid to reduce risks of adverse health outcomes from non-medical cannabis use . The LRCUG are based on concepts of health behavior change and similar guidance-oriented interventions implemented in other areas of population health.

They represent a targeted prevention tool to complement universal prevention and treatment measures on the intervention continuum . The LRCUG’ previous iterations were endorsed by leading government agencies and health/addiction stakeholder organizations in Canada and internationally to encourage their widespread utilization to reduce cannabis-related health harms among PWUC. They were communicated and distributed widely in different formats customised to different target audiences.The body of scientific evidence on cannabis use and its health outcomes has evolved substantially since the most recent version of the LRCUG. Given these developments, and the building momentum towards cannabis policy liberalization, we undertook a comprehensive review of new scientific evidence to inform an update and refinement of the LRCUG and their recommendations.Literature searches were conducted using the Embase, Medline, CINAHL, PsycInfo, the Cochrane Library, and Web of Science databases. Initial search strategies were developed for use in Embase and modified for other databases. Medical Subject Headings were used where applicable and combined with appropriate keywords for each risk factor topic. An example of the Embase search strategy used can be found in [Supplement 1]. Searches principally focussed on recent systematic or other comprehensive reviews, or other topically pertinent, high-quality studies. Subject areas where systematic review evidence was limited or absent were supplemented by reviewing individual studies identified through targeted or secondary searches, Google Scholar, and manual searches of reference lists. Given that this review was not conceptualized as a systematic review, in addition to the multiple risk factor topics involved, this paper does not present a routinised system for reporting systematic reviews specific inclusion and exclusion criteria were developed for each topical area, but general selection criteria applied to all topics.

In general, we included English language, peer-reviewed journal reviews and individual studies that contained data on behavior-based and -modifiable risk factors for adverse health outcomes associated with cannabis use. As this effort was principally approached as a review and update focusing on new evidence and insights following previously published LRCUG content, we only included literature published in 2016 or later that had not been included in the most recent iteration of the LRCUG. Given our primary focus on modifiable risks of adverse health outcomes among PWUC non-medically, we did not include in our scope studies whose main focus was on the medical benefits of cannabis, use of synthetic cannabinoids, social/legal harms, or risks-to-others.Its main psychotropic effects – as documented per seminal reviews – occur through the central nervous system’s endocannabinoid system , which undergoes major neurodevelopment during this transition period. This renders young, and especially adolescents’ neurological systems, vulnerable to adverse effects from exogenous cannabinoid exposure . Some evidence suggest that the neurobiological effects of cannabis use are similar in adult and adolescent PWUC. Extensive data, however, suggest that those initiating use by their mid-teens are at higher risk of transitioning to regular use and experiencing more persistent adverse outcomes than older PWUC, such as possible alterations in brain structure and functioning, although confounding conditions may contribute and causality is not consistently clear . Systematic and other reviews of human neuroimaging studies suggest that adolescent cannabis use is associated with structural brain alterations expressed in reduced volumes in the hippocampus and orbitofrontal cortex, thicker cerebral cortices, and decreased integrity of prefrontal and medial temporal brain regions .

Functional brain imaging studies among adolescent PWUC show alterations in frontal and parietal brain regions related to inhibition, reward, and memory.Despite these alterations, adolescents with cannabis use do not consistently show impaired performance in functional magnetic resonance imaging tasks, suggesting the possible employment of compensatory cognitive resources to offset performance decrements . In adult PWUC, evidence shows inconsistent associations between age-of-onset of use and brain functioning metrics . A systematic review detected a small overall reduction in cognitive functioning in youth-aged persons with frequent cannabis use but no variation with age or age-of-onset of use . A subsequent study involving persons aged 14-21 with frequent and occasional use found similar brain metrics among both adolescent and young adult cannabis using and non-using individuals , whereas other studies have have not identified long-term effects of adolescent cannabis use on neuropsychological or executive functions . Systematic and other reviews have found both more severe and persistent executive functioning impairment among adolescent compared with adult PWUC . Mental health outcomes of adolescent PWUC may also be affected by cannabis use. A systematic review found associations between adolescent cannabis use and the development of depression , suicidal ideation , and suicide attempts in young adulthood . A systematic review found adolescent PWUC at the highest risk of suicidal behaviours . Earlier age-of-initiation was associated with a higher risk for psychosis in all but one study and with increased symptoms of depression or anxiety by age 25 in a systematic review . A prospective longitudinal study found cannabis drying initiation before age 18 was associated with a higher risk for major depressive disorder , especially in individuals with higher-frequency compared with lower frequency early-onset use It is unclear, however, to which extent use and mental health disorders are causal, as they may be multi-directional and are likely to co-occur because the prevalence of mental health problems and cannabis use are both high in adolescence.

In an age-stratified placebo-controlled, double-blind cross-over trial involving exposure to equivalent doses of cannabis, adults showed greater impairment and intoxication, while adolescents showed impaired inhibitory processes and increased desire for cannabis use, suggesting differential age-based neuro-behavioral response profiles to use . Some evidence from prospective longitudinal studies suggests that adolescent PWUC have lower or declining IQs than non-using peers, but the possible role of confounders is unclear . Adolescent PWUC have shown lower educational attainment, more substance use/problems, and higher levels of antisocial behavior and other health problems in later adult life . In the US population, PWUC aged 15–19 years had a significantly higher risk of developing CUD than those aged 20 and older . In a study of cannabis-related driving skills among individuals with intensive recreational use, significant impairment was concentrated among those indicating early-onset use . Overall, it is unclear whether early-onset cannabis use has an independent effect on adverse outcomes from cannabis use, and the magnitude of any effects on brain functioning . Most adverse effects observed in individuals reporting early-onset use appear to involve frequent and/or high-potency cannabis use as relevant factors , and young people with poorer cognitive functioning are more likely to transition to frequent cannabis use patterns . While assessments of early-onset related impairments typically focus on nominal ages , neurological vulnerabilities can vary between youth of the same age. Therefore, it would be better to apply “adolescent pubertal markers” that more accurately index the stage of brain development . A systematic review failed to find evidence of the effects of cannabis use specifically on pubertal outcomes themselves .Many reviews on the adverse health effects of cannabis use have selectively focused on outcomes among those with intensive or chronic cannabis use only. Moreover, definitions of intensive use have varied, but it is commonly defined as ‘daily/near-daily’ use. On this basis, there is substantial evidence that frequent cannabis use, also when directly compared with less frequent use, represents and functions as a strong predictor of adverse health outcomes . A systematic review including multiple meta-analyses of the associations between cannabis use and brain volume found that frequent cannabis use was associated with significantly smaller volumes in the hippocampus , orbitofrontal cortex and lateral regions than in controls . While acute tetrahydrocannabinol exposure leads to acute increases in cerebral blood flow in multiple brain regions, chronic cannabis use results in an overall reduction in CBF, especially in the prefrontal cortex, in a dose-dependent manner . Other reviews have confirmed deficits are more common in persons with intensive cannabis use than controls in both brain structure and neurocognitive performance.

A systematic review and meta-analyses found a significant association between frequent, heavy cannabis use and deficits in cognitive functioning in adolescents and young adults Another systematic review of studies on cerebellar structure and functioning found that deficits in behavioral performance were associated with chronic cannabis use . Another comprehensive review identified strong associations between intensive cannabis use and short term impairments in cognition , with mixed evidence for long-term effects, and symptoms of depression, anxiety, and psychosis . Systematic reviews have found stronger associations between adverse outcomes and heavy/chronic rather than less intensive cannabis use for psychotic symptoms, suicide-related behaviors, depression,and dependence . Other systematic reviews and meta-analyses have confirmed a relationship between frequency of cannabis use and the risk of psychosis and dependence . In a US-based study, cannabis use frequency was associated with psychosis and depression symptoms among a youth cohort and with mental health symptoms in the general population at later ages A multi-country modelling study on first-episode psychosis found a linear relationship between symptom dimensions and cannabis exposure, with the highest scores observed in individuals with daily use of high-potency cannabis.In a retrospective cohort study of monozygotic twins, the twin who used cannabis more frequently was more likely to report a MDD or suicidal ideation.

Emulsification times are known to vary with the quantity of surfactant and the viscosity of the formulation. The SEDDS in this work could emulsify completely within 6.5 min. In agreement with previous work, increasing the surfactant quantity promoted faster emulsification. The Korsmeyer-Peppas model is commonly used to describe drug release from polymeric systems and was fitted to the drug release in this work based on the highest r 2 value. This model has previously been applied to drug release from microemulsions and film-forming polymeric solutions. There are three classes of non-Fickian diffusion that can be differentiated by the velocity of solvent diffusion. In this work, the release exponents of CBD and THC from SEDDS were 0.644 and 0.646, respectively. Drug dissolution with n values between 0.43 and 0.85, as in this work, is classified as anomalous transport, with the velocity of solvent diffusion and polymeric relaxation possessing similar magnitudes. The drug dissolution rate appeared constant over the first hour of the drug dissolution test. This is associated with a high drug concentration gradient and generally attributed to the release of the drug deposited on the oil droplet surface. The drug dissolution rate decreased between the first and second hours, with the diffusion rate of the drug within the oil droplet lower than that on the outer surface. As illustrated by Fick’s first law, a decreasing drug concentration gradient over time negatively affects drug dissolution. The poor water solubility of cannabis extract and cannabinoids results in their slow absorption via gastrointestinal mucosa and thus low bioavailability.Its use was reported to increase CBD plasma level, enhance bioavailability, and speed absorption as compared to hemp extract diluted with medium-chain triglycerides.

A nanoemulsion formulation of CBD composed of vitamin E acetate, ethanol, Tween® 20, and water was found to improve both the intestinal absorption of CBD and the stability and onset of activity. Cannabis extract has been prepared in olive oil–filled hard capsules, although its effect on bioavailability was not investigated. Based on the physicochemical properties of the formulations, it is unlikely that it would increase the bioavailability above that of nanoemulsions or SEDDS. Oil-based CBD formulations, such as CBD dissolved in corn oil, have been reported to decrease the time to peak plasma level and increase oral bioavailability four-fold compared to CBD powder. The work performed here successfully enhanced the dissolution of cannabis extract obtained via SFE, indicating the potential to improve the bioavailability of cannabis extract, although this will require confirmation in vivo. The last decade has seen a dramatic shift in global attitudes relating to the therapeutic use of cannabis-based medicines, with over 50 countries now having established legal access pathways allowing patients to utilise medicinal cannabis products across a wide range of medicalconditions . Reflecting this shift, the United Nations General Assembly voted in December 2020 to remove cannabis from Schedule IV of the Single Convention on Narcotic Drugs , the most restrictive of the schedules . However, this recasting of cannabis as a potentially legitimate medicine has created some tensions with other regulatory frameworks in which marijuana grow system remains positioned as a dangerous drug with no legitimate therapeutic application. A notable example of this is the so-called ‘zero tolerance’ drug driving legal frameworks that have been adopted in many countries, which criminalise the presence of a drug in a driver’s blood or oral fluid irrespective of impairment .

Here we undertake an analysis of this issue, with a focus on medical only access frameworks , based on a case study of the introduction of legal medicinal cannabis access pathways in Australia. The paper explores this policy issue by outlining the Australian medicinal cannabis access framework and considers the current regulatory approaches to reduce road safety risks associated with other potentially impairing prescription medicines and illicit drugs. It then reviews the evidence relating to cannabis and road safety risk, and unintended impacts of the ‘zerotolerance’ approach on patients taking or wanting to take medicinal cannabis. At the core of this issue is the need to optimise the regulatory framework to minimise potential harms relating to road safety risk, impediments to accessing a needed medication, and exclusion of a vulnerable patient group from motor vehicle access, while ensuring that medicinal cannabis patients are not discriminated against due to the historical status of the drug.The introduction of legal medicinal cannabis access in Australia was initiated in November 2016, via regulatory amendments implemented by the Commonwealth Government that enabled Australian patients to legally access medicinal cannabis when prescribed by their doctor with relevant Commonwealth and State/Territory Government approvals. In doing so, it brought an end to the blanket prohibition on cannabis, which had been classified as a Schedule 9 substance in the Australian Poisons Standard and was considered to have no recognised medical value. Unlike some other countries, the regulatory framework for medicinal cannabis in Australia is based on the provision of pharmaceutical grade medicines available only via prescription from a doctor after any required Commonwealth and State/Territory Government approvals have been obtained. These medicines are prescribed at precise doses and dispensed from a pharmacy. All other use of cannabis remains illegal.

There are now an estimated 190 medicinal cannabis products available in Australia, which vary in composition of the two primary cannabinoids, delta-9-tetrahydrocannabinol , and cannabidiol . Most contain at least some level of THC and many are described as ’full spectrum’, containing a wide range of other chemical constituents present in the cannabis plant . Unlike illicit cannabis , all legal medicinal products available in Australia are standardised pharmaceutical grade medicines . A wide range of product formulations are available, however recent analysis by the Commonwealth Department of Health found that the vast majority of approvals are for oral solutions , while around 10% involve preparations including wafers, transdermal gels and dried plant intended for vaporisation. As of 31 March 2021, over 100,000 approvals for medicinal cannabis products had been granted by the Australian Therapeutic Goods Administration. However, the interaction of legal medicinal cannabis and driving continues to be contentious, with most road safety agencies around Australia remaining committed to a drug driving regulatory framework that treats patients taking legally prescribed medicinal cannabis containing THC in the same manner as users of some illicit drugs, by criminalising the presence of the drug regardless of impairment. Some advocacy groups and politicians have asserted the need for change due to perceived inequitable treatment of medicinal cannabis patients . A 2015 report by the Victorian Law Reform Commission noted the right of patients ‘not to be discriminated against because of their treatment’ when managing risks such as driving. In one of the first legal tests in January 2020, a South Australian magistrate found a medicinal cannabis patient guilty of driving with a prescribed drug in his system but then exercised her legal discretion to dismiss the charge on the basis of a lack of evidence of impairment.

The magistrate did note that a conviction would be upheld if the patient was charged again .It is well-known that a range of prescription medications cause impairment that may pose a risk to the safe operation of a motor vehicle. This issue is managed in Australia via a regulatory framework including the Commonwealth Poisons Standard and corresponding state-based legislation. The Poisons Standard uses a scheduling system reflecting the differing levels of potential harms and therapeutic benefit of various substances. Drugs with a recognised medicinal value are identified as Schedule 2, 3, 4 or 8 depending on the level of regulatory control restricting their availability, while those with no recognised medicinal value and the potential for harm, abuse/misuse are listed as Schedule 9 prohibited substances. Recognised medicinal drugs may still have risks associated with their use, including causing impairment that can affect the ability of patients to drive. A significant number of medicines prescribed in Australia are known to have such effects, including anticonvulsants, opiates, antihistamines, antipsychotics, benzodiazepines, muscle relaxants, hypnotics, and antidepressants . Experimental studies have found these medicines to have negative effects on psychomotor, cognitive, and driving skills, with an increased crash risk reported in epidemiological studies . Table 1 provides a summary of such effects reported in systematic and meta-analytic reviews. However, it is important to note that there are methodological difficulties in achieving accurate estimates of impairment and crash risk, cannabis vertical farming particularly in patients. Experimental studies are almost always undertaken on healthy controls, for whom it is impossible to incorporate potential health benefits of the medication that may lead to a net reduction in impairment and improved driving ability. For epidemiological studies, which are typically observational, it is very difficult to adequately control for all potential confounding variables such as simultaneous use of other drugs , polypharmacy, time delays between crashes and drug testing, plus un-observed confounding factors.

In addition, risks associated with some medications appear to diminish after a tolerance to the impairing effects has developed .It is well-known that a range of prescription medications cause impairment that may pose a risk to the safe operation of a motor vehicle. This issue is managed in Australia via a regulatory framework including the Commonwealth Poisons Standard and corresponding state-based legislation. The Poisons Standard uses a scheduling system reflecting the differing levels of potential harms and therapeutic benefit of various substances. Drugs with a recognised medicinal value are identified as Schedule 2, 3, 4 or 8 depending on the level of regulatory control restricting their availability, while those with no recognised medicinal value and the potential for harm, abuse/misuse are listed as Schedule 9 prohibited substances. Recognised medicinal drugs may still have risks associated with their use, including causing impairment that can affect the ability of patients to drive. A significant number of medicines prescribed in Australia are known to have such effects, including anticonvulsants, opiates, antihistamines, antipsychotics, benzodiazepines, muscle relaxants, hypnotics, and antidepressants . Experimental studies have found these medicines to have negative effects on psychomotor, cognitive, and driving skills, with an increased crash risk reported in epidemiological studies . Table 1 provides a summary of such effects reported in systematic and meta-analytic reviews. However, it is important to note that there are methodological difficulties in achieving accurate estimates of impairment and crash risk, particularly in patients. Experimental studies are almost always undertaken on healthy controls, for whom it is impossible to incorporate potential health benefits of the medication that may lead to a net reduction in impairment and improved driving ability. For epidemiological studies, which are typically observational, it is very difficult to adequately control for all potential confounding variables such as simultaneous use of other drugs , polypharmacy, time delays between crashes and drug testing, plus un-observed confounding factors. In addition, risks associated with some medications appear to diminish after a tolerance to the impairing effects has developed .Impairing medications such as those described above are prescribed in very high volumes in Australia for the treatment of various medical conditions. In 2016-17, for example, there were 15.4 million prescriptions dispensed for opioids and in 2014-15 4.9 million benzodiazepine prescriptions were dispensed . To reduce road safety risks associated with the use of such medications, their use is regulated via mandatory labels and warnings, road safety legislation outlawing driving when impaired, and fitness to drive assessments.To reduce risks associated with the use of prescription drugs such as those in the table above, a product labelling and warning system has been established via several legislative instruments, including the Poisons Standard, Therapeutic Goods Orders 91 and 69 , the Medicines Advisory Statements Specification, and the Required Advisory Statements for Medicine Labels . This system includes warnings about possible sedating effects/drowsiness, recommendations not to drive or operate machinery if experiencing such effects, and to avoid alcohol or be aware that the medication may increase its effects. The label required on sedating medications, including medicinal cannabis products that contain THC, is shown in Fig. 1. Prescribing doctors and dispensing pharmacists are also required to provide patients using these medications with warnings to monitor drug effects and refrain from driving if impaired.

Moreover, minimal research has tested the measurement invariance of the CUDIT-R across countries, hindering cross-national comparisons. This is especially relevant among nations with different cannabis consumption policies , as differing use patterns may lead to differences in cannabis use problems experienced. Participants were college students recruited to participate in an online survey from 7 countries  between February 2019 and March 2020 . In the present study, participants that reported consuming cannabis at least once in their lifetime and completed the CUDIT-R  were included in the psychometric analyses. Analyses examining correlations between the CUDIT-R and non-CUDIT-R measures were limited to 2402 students that reported cannabis consumption during the last 30 days . For the U.S., Canadian, England, and South African sites, students were recruited from psychology department pools and received research participation credits. In Argentina and Uruguay, students were recruited through online social networks, e-mail listings and flyers , and those who completed the survey were entered into a raffle for prizes. In Spain an email was sent to all the students of the university inviting them to participate in the research. The participants received 5 euros for completing the survey. Study procedures were approved by the institutional review boards at the participating universities. Only students who endorsed past 30-day use of marijuana  were administered non CUDIT-R measures. Invariance testing of all non-CUDIT-R measures demonstrated metric invariance across the countries, which is necessary when examining associations between study constructs across different groups . Cannabis misuse was assessed using the CUDIT-R . In Argentina, Spain, and Uruguay, we used a version translated into Spanish. The translation was performed by two Spanish-speaking psychologists proficient in English and Spanish and with expertise in test adaptation and addictive behaviors.

Once the first drafts of the scale were performed in Castilian Spanish and Argentinian Spanish; the two versions were compared and only minor differences were kept across both Spanish versions  to facilitate the understanding of the scale in each cultural context . For both the Spanish and English versions, items 1 to 7 use a 5-point Likert scale that ranks from 0 to 4, while item 8 uses a 3-point Likert scale . In the present study, a total score was obtained by summing scores on each of the 8 items . Past 30-day typical cannabis use frequency and quantity were assessed using the Marijuana Use Grid . The measure was translated into Spanish for students in Argentina, Spain, and Uruguay. Specifically, each day of the week was broken down into six 4-hour blocks of time , and participants were asked to report at which times they used cannabis grow equipment during a “typical week” in the past 30 days as well as the quantity of grams consumed during that time block. We calculated typical frequency of cannabis use by summing the total number of time blocks for which they reported using during the typical week . We calculated typical quantity of cannabis use by summing the total number of grams consumed across time blocks . To examine the internal structure of the CUDIT-R across sites, we conducted confirmatory factor analyses  using a diagonally weighted least squares  estimator in Mplus 8.4  among lifetime cannabis users. To examine the internal consistency of the CUDIT-R, we estimated Cronbach’s alphas and ordinal omegas with 95% CIs . To determine the configural, metric and scalar invariance of the CUDIT-R across countries and gender groups, we conducted multi-group confirmatory factor analyses.Evidence of convergent and criterion validity was examined by correlating the total CUDIT-R score with the B-MACQ and cannabis outcomes scores , respectively. To explore the differences in the magnitude of the correlations across countries, the absolute value of the differences in the magnitude of the correlations for pairs of countries were computed in the sample of last 30-day cannabis users. As the statistical tests of these differences can be oversensitive to small differences when including differences in sample sizes across countries, attention was paid to the magnitude of these differences. As done in previous studies , we considered differences < 1 SD small, differences between 1 SD and 2 SD medium, those between 2 SD and 3 SD large, and any over 3 SD were considered substantial. The correlations between the CUDIT-R, the B-MACQ and the criterion variables are presented in Table 3. The correlations between the CUDIT-R with the B-MACQ were large; while correlations with quantity and frequency of cannabis use were small to moderate. Correlations with cannabis motives were from moderate to large across groups .

When partial correlations between the CUDIT-R and cannabis motives were performed  the results showed that the CUDIT-R was mainly related to the internal cannabis motives . When the absolute value of the correlations was compared between pairs of groups, the average difference in correlations was 0.077  across 143 possible comparisons. Thus, differences < 0.141 were considered small, differences between 0.141 and 0.205 were considered medium, those between 0.206 and 0.269 were considered large, and any over 0.270 were considered substantial. The correlation differences between the CUDIT-R and the rest of the criterion variables are presented in Table 4. We found large differences in the correlation of the CUDIT-R with cannabis quantity between the Argentinian sample and the sample from South Africa and Spain . The correlations between conformity motives and the CUDIT-R were higher in Spain than in Canada, South Africa and Argentina. Specifically, large and substantial differences were found between the CUDIT-R and conformmotives in South Africa and Argentina compared with Spain respectively. When the effect of the rest of motives was controlled for, large correlation differences in conformity motives between Spain and Canada were found, and substantial correlation differences in Spain compared with South Africa and Argentina were shown. The CUDIT-R  is one of the most widely used measures to assess and detect problematic cannabis use . However, limited research has tested the measurement invariance of the questionnaire across different countries. Thus, a main aim of the present research was to test the measurement invariance of the CUDIT-R among college students from seven countries. The results showed that the measure was invariant at different levels  among the U.S., Canada, Argentina, Spain, and South African samples suggesting that the CUDIT-R is a suitable measure to compare cannabis-related problems among students from these five countries. Due to their low item endorsement, it was not possible to the test the invariance of the questionnaire in Uruguay and England. Future studies with a higher sample size of students from these two countries are required. In addition, measurement invariance of the questionnaire across males and females was explored. A previous study performed with a large sample of undergraduates from the U.S. found configural and metric invariance of the measure across gender groups . Our results extend previous findings, showing that the structure , the factor loadings  and the thresholds  were similar across a sample of males and females from different nationalities and languages.

Scalar invariance of the questionnaire across groups is relevant, as differences in the CUDIT-R scores across countries and gender groups can be interpreted as differences in problematic cannabis use, rather than merely artifacts of other processes, such as the interpretation of items . To this end, when mean comparisons of the CUDIT-R total score were examined, as it is usually found, males showed higher problematic cannabis use than females . We also found lower problematic cannabis use in the Spain and Argentina than in U.S., and also in Spain compared with the rest of the countries. These differences could be related to cannabis polices, as lower rates of CUDITR were found in countries in which the access to cannabis is more difficult . The present research also provided reliability evidence of the CUDITR scores, showing that both Cronbach’s alphas and ordinal omegas were higher than the standard cut-off of 0.70, and similar to those found in previous studies that have explored the unidimensional structure of the questionnaire . Convergent validity evidence was also provided in five countries, as the CUDIT-R showed large correlations in magnitude with the B-MACQ. The magnitude of these associations was similar to that found in previous studies with undergraduates from the U.S. , suggesting that the Spanish version provided similar convergent validity evidence with the B-MACQ as the English version. Finally, criterion validity evidence of the CUDIT-R scores was provided using different measures of cannabis consumption and cannabis related motives. As expected, CUDIT-R scores positively correlated to cannabis frequency and quantity across the five countries and gender groups . Although the correlations with quantity were positive and significant across all countries, the magnitude of this correlation was lower in Argentina than in the remaining countries. This result is somewhat different to past research comprising Argentinean college students in which higher correlations between cannabis quantity and cannabis-related problems have been found . Thus, more studies are needed to better clarify the magnitude and differences of these associations. Among motives, all five cannabis motives  were associated with the CUDITR scores across groups, as found in recent meta-analysis . In the same vein, when the rest of the motives were controlled for, the CUDIT-R was mainly related to coping motives across countries and gender groups. Lower but significant associations between the CUDIT-R scores and enhancement and expansion motives were also found. Our findings and previous research performed with college students  suggest that internal cannabis motives are indicators of risk. The only exception was found in the sample of Spanish youths, in which the correlation between the CUDIT-R scores and conformity motives remained significant even when accounting for other motives.

Consequently, substantial differences in the magnitude of the correlations between the CUDIT-R scores and conformity motives in Spain compared with South Africa and Argentina arose. The higher correlation between the conformity motives and cannabis-related problems in Spain could be due to differences in cannabis policies across sites. For example, in Spain buying, selling,mobile grow system and the use of cannabis in public places is illegal, however, there are “cannabis social clubs ” in which the “private” sale and consumptions is allowed from 18 or 21 years old depending on the club or the Spanish autonomous community . Thus, in this particular context in which the cannabis use is allowed and shared with peers, it is possible that youths have lower self-efficacy to reject consumption  which in turn could be related to higher problems with cannabis. Nonetheless, further research is needed to better clarify the association between conformity motives and the CUDIT-R in Spanish youths. The present study has a number of limitations. The relatively low number of participants from Uruguay and England impeded testing the invariance of the CUDIT-R’s scores in these samples. Moreover, our convenience sampling procedures impedes generalizing our findings. Sample size and the gender distribution were different across countries which, alongside the online data collection, may have introduced unwanted bias.Despite these limitations, the present research offers encouraging evidence of the psychometric properties of the CUDIT-R scores in college student cannabis users from five countries and across gender groups. Overall, these results suggest that the CUDIT-R could be efficiently used to identify English or Spanish-speaking college students with problematic cannabis use, who would benefit from interventions aimed at reducing cannabis use and its negative consequences. Dr. Bravo was supported by a training grant  from the National Institute on Alcohol Abuse and Alcoholism  in the United States during the duration of data collection for this project. Data collection was supported, in part, by grant T32-AA018108. NIAAA had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication. Data collection in Spain was also supported by grants UJIA2019-08 from the Universitat Jaume I and RTI2018-099800-B-I00 from the Spanish Ministry of Science, Innovation and Universities . Data collection in Argentina was also supported by grants from the National Secretary of Science and Technology  and by grants from the Secretary of Science and Technology- National University of C´ ordoba . Cannabis is the most widely used substance in the United States after alcohol and tobacco, including during pregnancy .

Participants retrospectively reported reduced euphoria when smoking cannabis, in line with previous studies showing that CBD reverses the reinforcing effects of cannabis in youth . The study provided the first evidence that prolonged CBD treatment may improve psychological symptoms and cognitive function in frequent users, with greater benefits in dependent than in non-dependent cannabis users. However, the study lacked a placebo control and was not designed to examine effects on cannabis use. Recently, Freeman and colleagues offered the first empirical data supporting that a treatment package comprised of CBD + MI was able to engage non-treatment seeking adults with CUD and reduce post-treatment cannabis use. In a phase 2a dose-finding RCT, they found that synthetic CBD over a 4-week treatment period outperformed placebo at daily doses of 400 mg or 800 mg; eliminated at interim analysis due to inefficacy in reducing biological and self-report metrics of cannabis use among a sample of non-treatment seeking adults with CUD, who wanted to quit cannabis use . Reductions in use were maintained up to 24 weeks following treatment with 400 mg CBD. Results on secondary outcomes were mixed. However, there was some evidence for CBD reducing cigarette use, cannabis withdrawal symptoms, and anxiety. By contrast, there was no evidence for changes in alcohol use, and there was evidence for a decrease in sleep quality following CBD treatment. Importantly, in terms of potential disruption in functioning, use of CBD was not associated with more adverse events than placebo – in line with the open-label trial . Furthermore, the study showed impressive retention rates with 94 % retention throughout the study period.

To summarize, very few studies have examined the effect of non-THC based cannabinoid treatment strategies on CUD to date, but evidence from the first studies is promising. In the first placebo-controlled RCT in adults with cannabis grow system dependence, FAAH inhibitors  reduced withdrawal symptoms and cannabis use compared to placebo, with no difference in adverse outcomes between groups. A pragmatic open label trial of CBD  in adults who continued their frequent cannabis use found improvements in depressive and psychotic symptoms, attention, learning and memory, and reduced euphoria when smoking cannabis. In the first placebo controlled RCT of CBD in adults with cannabis dependence, CBD reduced cannabis use, with no difference in adverse outcomes between groups. Larger trials are needed to provide more precise estimates of efficacy for these novel treatment strategies. As reviewed in Section 5.1, evidence from randomized placebo controlled studies suggests that treatment with synthetic THC decreases withdrawal symptoms, but not cannabis use, in adults with daily cannabis use or CUD. Further, the same studies suggest that higher doses of THC may increase cannabis intoxication and liking, while the evidence regarding THC combined with CBD is more mixed. The lack of effect on cannabis use and abstinence in adult studies with synthetic THC conducted so far, including studies where THC is administered concomitantly with MI/CBT up to 12 weeks, suggests that the efficacy of synthetic THC as a treatment among youth with CUD should not be tested as a stand-alone pharmacological treatment. The relatively consistent effect on withdrawal symptoms may suggest potential for combining dronabinol or nabilone with other medications, however, this should be weighed against potential negative outcomes associated with administering THC in youth samples.

More specifically, the evidence from laboratory studies suggests that higher doses of THC may increase cannabis intoxication and drug liking, which naturally raises concern, as these effects may pose a risk for relapse in patients who have stopped using cannabis and may be even more problematic in patients that aim to reduce, but not stop, using cannabis. In general, administering THC as treatment for CUD carries an element of clinical and ethical concern due to the emerging evidence suggesting that cannabis products with high levels of THC have detrimental effects on mental health and cognitive function among adult and youth users . These concerns are very relevant considering the high rates of psychiatric co-morbidity and negative neurocognitive impact in youth and adults with CUD . Furthermore, the concerns are particularly pertinent with adolescents and emerging adults, as the developing brain is believed to be more susceptible to the adverse effects of cannabis exposure, and THC may interfere with neurodevelopmental processes influenced by the endocannabinoid system . The majority of studies reviewed in Section 5.1 did not examine potential effects on cognitive function. However, in the studies that included cognitive assessment, findings suggest that THC-containing cannabinoid treatment decrease cognitive performance: one study found that 8 mg/day of nabilone  worsened psychomotor task performance , and another found that dronabinol worsened psychomotor task performance and working memory . While studies of nabiximols reported no differences in adverse events between treatment and placebo groups , some studies found adverse events related to dronabinol, such as dry mouth, rapid hear, flushing and hypotension . In studies that reported serious adverse events, these were deemed not study related . A final point that is relevant to consider is that THC may interfere with daily functioning, because of its cognitive impairing effects.

For example, dronabinol has been found to impair driving performance in a dose-dependent manner , which has implications for potential risk of road accidents attributable to medicinal use of THC in treatment of CUD. As reviewed in Section 5.2, the effect of FAAH inhibitors and CBD on CUD has been much less studied, but evidence from the first two placebo-controlled RCTs in adults with cannabis dependence suggests that FAAH inhibitors can reduce withdrawal symptoms and cannabis use, and that CBD can reduce cannabis use. Furthermore, there were no differences between control groups and groups receiving FAAH inhibitors or CBD regarding adverse outcomes . A key concern about administering pharmacotherapies to youth is their safety. In the only trial to date, the FAAH inhibitor PF-04457845 was administered to male adults aged 18− 55. The trial did not include females of childbearing potential due to the previous lack of safety and toxicity data on PF-04457845. Now that these data are available, a subsequent phase 2b trial is being conducted in males and females aged 18–60 . Due to a lack of safety or toxicity data in younger people, the potential of PF-04457845 in treating youth CUD is currently unclear. There is also limited data on the safety of THC administration in youth, with only one study to date administering THC to adolescent volunteers , as well as the already mentioned concerns about the impact on the developing brain. While the safety and efficacy of CBD for treating CUD in youth is yet to be established, the potential safety of administering CBD is supported by several trials of CBD as a treatment for severe treatment-resistant epilepsy in children . Furthermore, an emerging literature suggests that CBD contains opposing neural, cognitive, and behavioral effects that interact with, and may counteract, some of the harmful effects of THC on cognitive functions, anxiety, and psychotic symptoms . Some studies also point to a greater addiction potential in products with high levels of THC and low levels of CBD .

These effects are mirrored in functional imaging studies, which have revealed opposing acute effects of THC and CBD in areas pivotal to the examined cognitive processes including amygdala ; striatum, hippocampus, and prefrontal cortex ; and auditory and visual cortex . Taken together, these findings point to a safer profile of CBD compared to THC. A potential benefit of cannabinoid treatment in general is that it may be more acceptable than traditional treatment  among cannabis grow lights using youth and adults, especially non-treatment seekers. In the only placebo-controlled RCT conducted with CBD so far, retention rates were very high: out of 82 randomized individuals with CUD, only 5 participants did not complete treatment , and in the only placebo-controlled RCT of FAAH inhibitors, 17 % dropped out of placebo and active treatment groups . Overall, drop-out rates were higher and more mixed in studies on THC-based cannabinoid treatment, see also Table 1. As such, cannabinoid medication – particularly non-THC based – may potentially help address the problem of low treatment uptake in youth. This is an extremely exciting time in the domain of adolescent and emerging adult prevention and intervention work for cannabis use and related CUD. At present, we are coming out from an era with limited prevention and treatment intervention options. To that end, the past few decades have been demarcated by addiction paradigms and related prevention and intervention approaches that were solely developed for and examined with adults. On that background, it is highly promising that the field is increasingly recognizing adolescence and emerging adulthood as a distinct neurodevelopmental period with its own unique needs and challenges that are also mirrored in the needs and challenges related to cannabis use . This review represents a comprehensive overview of how exciting advances in the domain of emergent cannabinoid treatment strategies may open a critical and important window for the abatement of youths’ struggles with cannabis. With the increase in cannabis use observed throughout the pandemic , these steps could not be more timely.These studies have yielded promising findings regarding FAAH inhibitors and CBD, but large efficacy trials are still needed to replicate the first findings. The optimal duration of treatment with cannabinoid substitution treatment has also not yet been established and needs to be systematically investigated together with risk of relapse after cannabinoid treatment has been discontinued. This is of particular importance, because of the high price of some of the cannabinoid agonist compounds recently released to the market.

With no studies to date having examined the potential of cannabinoid treatment in youth with CUD, the next critical steps include examining the impact of these novel intervention approaches  in youth samples, in order to examine potential effects and side effects, and determine which elements in the approach are driving specific changes in youth behavior and brain. To this end, translational approaches integrating examinations with behavioral, neurocognitive, and neuroimaging  can be particularly useful in disaggregating potential impact and neural- as well as behavioral- mechanisms of change in this important population . Furthermore, examinations of potential gender differences are needed – both in youth and adult samples. Fewer females use cannabis, but cannabis use is linked to more health problems in young females compared to males . However, research in females and potential gender differences is lacking in cannabis research in general , including research on cannabinoid treatment, where previous studies have either examined 100 % males or mainly males. So far, no studies have examined potential gender differences in effects of cannabinoid treatment . Together, this work represents critical next steps in the important pathway toward improving the lives of young people struggling with CUD. In the longer run, once tolerability and safety of cannabinoid treatment strategies have been established in youth, more specific target groups and treatment strategies could be further explored. For example, the therapeutic effects of pharmacological treatment with CBD  have the potential to guide the definition of CUD subgroups that might in particular benefit from this treatment strategy. Since THC-based compounds seem rather efficient in reducing withdrawal symptoms, another approach might be to examine the efficacy of administering both THC and CBD in the beginning of treatment and then gradually phase out to end with CBD monotherapy. However, due to the discussed risks and concerns associated with THC administration, this approach requires careful ethical and clinical considerations. In recent years, several countries have modified their policies regarding use of cannabis, with changes including allowing cannabis use for medical purposes, decriminalization, or legalization for recreational use . Canada is one of the countries that has now legalized cannabis for recreational use, which has led to increased availability and prevalence of use . While policies have been made more liberal, it is still important to recognize that cannabis use has health and psychosocial risks . Further, the majority of risky cannabis users, including those meeting criteria for cannabis dependence, will never seek treatment if they become concerned about their use , often because of stigma or embarrassment – and this is unlikely to change with legalization .

Similar to the overall sample, frequency of past-week cannabis use in these groups returned to levels comparable to baseline for the remainder of the study period. Collectively, these findings offer new insight into patterns of cannabis use over time throughout the pandemic among U.S. adults. Our findings are broadly consistent with studies from other countries, including some European countries and Canada . In a study of adults who use cannabis in the European Union, self-reported cannabis use remained stable overall, with 42% of participants reporting no change in use between April 8 and May 25, 2020. Increases in frequency and quantity of cannabis use were larger among those who used cannabis regularly rather than occasionally . Another repeated cross-sectional study of Canadian adults showed cannabis use in the overall population remained unchanged during the pandemic between May and June 2020. Though about 50% of the individuals who reported using cannabis stated that their cannabis use had increased, the reported number of days cannabis was used in the last seven days remained stable over the study period . Other cross-sectional studies from France and Belgium at the start of national lockdowns further reported findings of overall cannabis use remaining stable . Though these findings are generally consistent with ours, comparison is limited due to the non-representative and cross-sectional nature of these studies that report changes only in the first wave of lockdowns between March and June 2020. The U.S. context of cannabis policies and access is important to consider when reflecting on factors that may have influenced these trends. The marginal changes in cannabis use among some groups early on in the pandemic may have been influenced by public health measures implemented to reduce the spread of COVID-19.

One such consideration is the role of stay-at-home orders and social distancing measures indirectly impacting behaviors among those who obtain cannabis drying racks through illicit markets or peers. For example, our data show that in states where cannabis is prohibited, days of cannabis use had a decreasing trend, although not statistically significant, over the course of the COVID-19 pandemic, with November having the greatest decrease compared to March. The study from the European Union notes that Ireland, Italy, Poland, and Portugal were the countries with the largest proportions of cannabis use reduction or stopped use, citing Italy’s restrictions on movement within regions and Portugal’s reported decrease in availability as factors in impeding access to cannabis . On the other hand, in states where medical cannabis was legally available, the level of cannabis use across the first 8 months of the pandemic was either similar to or modestly greater than baseline. Increased use in states that allow medical cannabis use may be an indicator of an exacerbation of common conditions treated with medical cannabis, including anxiety and insomnia. A prior study of US adults who use cannabis medicinally found that those with anxiety or depression reported increased use during the pandemic . Though the current study does not indicate that cannabis use increased significantly during the pandemic, there is a need to continue public health surveillance to monitor changes in cannabis use. As states expand efforts to vaccinate the larger US population and social distancing measures begin to be lifted in parts of the US, cannabis availability may return to normal for portions of the population that may have had limited access to cannabis during earlier phases of the pandemic. In the interest of further understanding the long-term effects of the pandemic on cannabis use, monitoring and further studies are needed. Future research should also explore associations between changes in cannabis use and mental health status before, during, and following the pandemic. This study has several limitations that should be considered when interpreting findings. First, the survey only included measures of quantity, contents, or mode of cannabis consumption at two time points,Waves 4 and 5.

Therefore, we are not able to understand changes in cannabis use that may be more clinically meaningful over time, such as quantity and mode of consumption. Second, there are sociodemographic characteristics known to be associated with cannabis use behaviors, such as education  and sexual or gender identity , that were not examined in this study. In addition, although most states with operational dispensaries deemed them “essential services”, there were some time-variant changes in guidelines, including capacity limits, operating curbside pick-up, and delivery, that we were not able to account for in our analyses. These quickly evolving guidelines may have impacted individual access to cannabis and potentially cannabis use behaviors within certain populations. Further, due to small sample size, some sociodemographic groups were combined in our analyses; for example, Native Hawaiian/Pacific Islanders, American Indian/Alaskan Natives, and those reporting more than one race were categorized as “Other.” It is also noted that some categories consisted of small sample sizes that may lack the statistical power to capture differences in trends across subgroups. These groups should be considered for future research to understand trends of cannabis use among these populations. Third, the analyses were conducted among individuals who ever used cannabis during the study period  and may not be representative of all adults who use cannabis. Fourth, this panel did not have data on cannabis use prior to March 10th, and therefore we were not able to identify initiators of cannabis use or capture changes in cannabis use that may have occurred before the start of lockdown measures. Fourth, although our survey weights were adjusted for non-response using baseline characteristics, they were not post stratified to account for non-response at each follow-up wave, which may have affected the representativeness of our sample and the generalizability of our findings.The therapeutic use of cannabis dates back several thousands of years, however, during the early 20th century a global trend of cannabis prohibition emerged, resulting in an almost 100 year gap in clinical use and research advancement.

Therapeutic use among patients has continued despite legal status and recent introduction of medical cannabis regulations in more than 30 countries has permitted millions of patients to legally access medical cannabis and has revived the production of medical cannabis research. There has been growing evidence of the therapeutic effects of cannabinoid-based treatments in several conditions including chemotherapy-induced nausea and vomiting, chronic pain, drug resistant epilepsy, spasticity associated to multiple sclerosis and insomnia.2 Yet access to cannabinoid-based products and clinical knowledge of effective initiation and monitoring is still poor, partly because of a lack of proper integration of healthcare settings or formal medical education. Dedicated medical cannabis facilities can provide innovative care and education, based on and for patient’s needs. They may also assist and train physicians in prescribing personalized treatments and navigating through the complex administrative and regulatory framework of medical cannabis. Various settings have been employed over time, from buyer’s or compassion clubs to dispensaries to, more recently, private medical clinics. However, there has been virtually no literature on medical cannabis care services which has also increased barriers to the production of evidence-based policies and clinic models.3,4 Canada has long been on the frontier of medical cannabis access, with the enactment of legislation in 2001 following a Supreme Court challenge to the Charter of Rights and Freedoms.5 The regulatory system has evolved over time, most recently with the legalization of non-medical or ‘recreational’ cannabis under the Cannabis Act in October 2018. However, despite this long history of medical cannabis access, significant medical stigma and persistent barriers to prescription remain. In 2014, approximately 40,000 Canadians were authorized for medical cannabis use, however an estimated 1 million were using cannabis therapeutically via illicit sources.6,7 The aim of this article is to present the care model of a successful clinic dedicated to medical cannabis treatments. The key elements related to the clinic organization and the clinical team as well as clinic statistics and critical patients’ data are described and discussed in detail. This paper also aims to inform health care providers and other medical cannabis stakeholders on the considerations of effective medical cannabis practice that can be adapted to different clinical settings and various regulatory frameworks. The main objective of any medical cannabis treatment is to provide a complementary option to traditional treatments in order to alleviate persistent symptoms and suffering associated with the patient’s condition. This is achieved through the following sub-objectives: give the patient a sense of control over their condition; improve the symptoms experienced by each patient; and improve the patient’s health-related quality of life with a minimum of treatment related adverse effects. Moreover, as a complementary or adjunctive treatment, medical cannabis treatment must be integrated with primary and speciality care to support best outcomes.

The medical cannabis grow tray clinic model was developed by the co-founding team of medical cannabis advocates, researchers and physicians to meet the needs of patients and the medical community. In early years, the stigma of being classified as a ‘pot doctor’ required peer support among the medical team and resulted in the establishment of initiatives to support clinic credibility, including rigorous clinical practice guidelines, a strict referral model, and the initiation of a research program to collect real-world evidence about patient treatment outcomes. Maintaining the credibility of medical cannabis treatments and separating myths from realities remains a core function of the clinic as a resource centre for evidence-based medical cannabis information. Each country may have specific considerations and requirements for a clinic implementation. It may be required to develop specific protocol or reporting for each patient that is prescribed medical cannabis. Developing such protocols in a peer-reviewed environment to meet the needs of common patient diagnoses and symptom expression is important to ensure compliance and clinical efficiency. Different healthcare environments may present challenges as well as sociological impacts; integration with private health insurance providers may be necessary initially to support patients who are unable to pay for clinic visits or medical cannabis treatments.A dedicated, attentive and diverse team of experts is a key aspect to medical cannabis care. The clinic has expanded from a small team of five practicing part-time physicians and one medical cannabis educator in one location to a network of four clinics across Quebec and a team of twelve consulting physicians and fifteen nurses as part of a complete staff of fifty employees. The current core clinical team consists of clinic coordinators who supervise research assistants and administrative needs, nurse coordinators and a team of nurses with both research and patient education experience and physicians from various specialities, including family physicians and specialists in pain, palliative care, endocrinology and gastroenterology.The team provides specific, comprehensive counseling to patients taking into account their individual medical condition, lifestyle and accessibility needs. In the early years of clinic development, medical cannabis advocates or educators played a critical role to support cannabis knowledge transfer and personnel training, bridging medical cannabis and healthcare experiences. To provide sufficient support and education, patients are followed by the same physician, though nursing and education support may rotate, and all notes are documented on an electronic medical record . Such a multidisciplinary approach between healthcare professionals provides for personalized, effective and efficient recommendations and the appropriate, supportive follow-up required by most patients, as it occurs in other clinical settings.9 Peer support among healthcare providers, especially physicians, across various specialities, facilitates support and mentorship within an otherwise stigmatized and controversial treatment. The initial clinic visit is an opportunity to meet the patient, confirm eligibility for cannabinoid-based treatments and provide patient education on medical cannabis. Baseline clinical data and validated questionnaires are collected and may be used for further analysis. A complete medical history is obtained by a registered and trained nurse with a focus on factors that will determine treatment recommendations including a patient’s previous cannabis experience. Consulting physicians confirm patient eligibility and treatment decisions and determine a follow-up and monitoring schedule according to a clinic-wide protocol. A medical cannabis authorization is written in accordance with federal regulations, the authorization is akin to a prescription in practice. Patient education is led by the nurse and includes discussion of treatment objectives with the patient and family, review and management of treatment expectations, careful explanation of the individualized treatment plan, titration instructions and an original patient daily diary and education booklet that cover all general information. Furthermore, a patient treatment agreement is an indispensable tool to confirm treatment objective and clinical program limitations.

To characterise country-level cannabis control policy changes, we primarily relied on Pacula et al. and Room et al. . On this basis, a distinction is made between decriminalisation , depenalisation and increase of the penalties . Going specifically into the European case, following the European Monitoring Centre for Drugs and Drug Addiction , this distinction was further refined to perform the analysis: decriminalisation through reforms that remove the prison sentences for minor offences ; depenalisation, where the offence is still criminal, but a reduction of the maximum prison sentence is operated ; depenalisation where the offence is still criminal but the likelihood of sanctions being applied is reduced by facilitating the closure of minor cases ; increase of the penalties, where the possession for personal use is a civil offence but the reform increases the penalties attached to it ; increase of the penalties, where the possession for personal use is a criminal offence and the reform increases the penalties attached to it . To better understand how the European countries included in our study have been categorised and understand each specific policy change, Table 2 provides an overview of the broad category into which the policy changes fall, the specific type of reform and a description of the situation pre- and post-reform in each country. Seven countries that did not pass any cannabis law in the observed period were used in the analysis as a control group: France, Iceland, Latvia, Malta, the Netherlands, Norway, Sweden. Four additional countries that reformed their cannabis control policies in the observed period were excluded from the analysis because the related ESPAD data were not available for all the considered years: the United Kingdom , Estonia , Luxembourg and Belgium .This paper assessed whether the cannabis grow equipment policy changes occurred in 13 European countries in the period 2001–2014 were associated with significant outcomes among adolescent students. In particular, to inform discussions about the evaluation of policy developments related to cannabis that might increase the availability of this substance within Europe, we analysed changes in the perceived availability of cannabis.

In order to check the possible association with changes in the prevalence of use of this substance among adolescent students, we differentiated between different patterns of use . This has been done in order to account for the fact that users are not equal, and that there is a group that, although restricted, is more at risk of developing cannabis-related problems, i.e. frequent users . This study contributes to clarify the scarce and inconstant literature on European states , providing important information about policy outcomes and efficacy. Moreover, differently from previous studies that simply categorised cannabis control policies into a dichotomous measure , this study takes account of the fact that there is a great diversity of forms that relaxation or increase of prohibition can take in practice , by refining the investigation following the analysis proposed by EMCDDA . In fact, ignoring the significant heterogeneity in these policies, has been highlighted to contribute to what appear to be mixed results from evaluations.In order to better interpret the results, for each country a description of the situation pre- and post-reform has been provided. By combining data from five waves of the ESPAD survey, our data include a time span of more than 15 years, covering the period before and after the implementation of each of the national drug policy reforms. Results are based on a DiD model. Regarding the availability of cannabis, we find that none of the decriminalisation and depenalisation reforms seem to be linked to an increase in the perception of easy access to this substance by the general population of students, nor it is so among non-frequent and frequent users. This finding suggests that the common assumption that cannabis availability will increase with the relaxation of prohibition might not apply to the European cases. This means that in a country like Portugal, where the personal possession of cannabis was decriminalised in 2001, the perceived availability of cannabis did not increase as a result of the reform compared to a country like France, where the possibility of incarceration for the possession of cannabis for personal use is still foreseen. Among the policy reforms increasing the penalties for cannabis personal possession, those increasing the administrative penalties attached to this offence are actually associated to a decrease in the rate of students perceiving cannabis as easy to obtain. This result might be a good indication as it has been demonstrated that those who believe they have easy access to cannabis have also a greater risk for uptake, higher consumption frequency, as well as the progression to regular use and abuse . However, the fact that among users this association persists only for the non-frequent ones, suggests that the channels of access to the substance by frequent users, such as domestic production and supply networks , might not have undergone significant modifications.

Since to our knowledge cannabis policies and changes in the perceived availability by adolescents were not previously explored in the European context, these results offer an interesting insight into the aforementioned relationship. Concerning cannabis use outcomes, our results show that only some cannabis policy reforms were associated to significant changes in the prevalence. This can be considered an important finding in itself as it confirms that there is not an automatic link between cannabis policy and use , and that other factors may play an important role. Among these, we can mention information and prevention programs, but also the actual level of implementation and enforcement of reforms . They can affect the perception of risk and knowledge of adolescents, as well the social acceptability of drug use in a country, which are in turn associated with substance use . As highlighted by a previous study conducted in Europe , the heterogeneity found in the effects of cannabis policy reforms concerning the prevalence of use highlights the importance of making distinctions between different types of cannabis users. In fact, in line with previous findings different results are obtained for different types of consumers. When considering all types of users, two categories of policies show an effect: among the more restrictive ones, only the one increasing the non-prison penalties seem to significantly reduce overall cannabis use, and among the more liberal interventions, only the one favouring the discontinuation of criminal proceedings for minor cases is linked to an increase. These results are confirmed when focusing on experimental users or excluding frequent users from the analysis. Furthermore, those reforms reducing the maximum prison penalty for cannabis possession show a positive effect on the share of experimental users only. When finally considering only frequent users, i.e. students smoking cannabis daily or almost daily, the policy effects observed before disappear and no reforms seem to have an effect. This result is not in line with the finding from Shi et al. indicating that cannabis liberalisation in Europe was associated with higher likelihood of regular use. It is instead supported by a revision of the same study that highlighted how, by implementing some statistical improvements, this association becomes statistically non-significant . The finding is also in line with some recent within-country studies conducted to analyse some form of cannabis liberalisation policies in the US .

In these studies, no discernible pattern was detected suggesting an increases in cannabis frequent use among adolescent related to the legalisation of medical marijuana. Overall, these results offer three main insights. First, the fact that some of the reforms reducing the penalties for cannabis possession are associated to an increase in some measures of adolescent cannabis use signal that those reforms might have somehow reduced stigma and perceptions of risk associated with cannabis use . This is in light of the fact that no increase was observed concerning adolescent perceived easy access to the substance, indicating the the other main factor on which the policy reforms might have acted did not change significantly. A shift in social norms regarding cannabis use may have, instead, increased cannabis use among experimental and non-frequent users . On the contrary, in those countries where the civil penalties for cannabis possession where increased , the reduction in the share of experimental and non-frequent users was coupled by a reduction in their perception of cannabis availability. This might indicate that this kind of policy was effective in reducing access through informal channels or increasing the price of this substance on the black market for those sub-populations of users. Second, it has to be considered that one fundamental reason for increasing the level of prohibition is that positive social externalities should be larger than the social costs of repression and private benefits for users . In fact, the failure in achieving this objective has lead several countries to move towards depenalisation and legalisation in recent years . Our results confirm that some of these reforms are linked to a reduction in the share of students approaching this substance, which is in line with this objective. However, the fact that no reduction is observed in the share of frequent users, who are those at higher risk, signal a limited public health impact of this approach among adolescents at higher risk, which might in turn reduce its social externalities. A similar reasoning can be applied to the Hungarian case , which applies the more severe punishments for cannabis possession, and where no significant change was observed either in the perceived availability or in the share of cannabis users following the policy reform. Finally, the absence of a significant decrease in the share of frequent cannabis users associated to any of the policy changes, might signal a limited role of policies overall in achieving results among this high-risk population. In this light, investments in evidence based adolescent substance use prevention programs would be advisable . Given the fact that we did not find any significant decrease in the perceived accessibility to cannabis for frequent users, an interesting perspective would be to focus on resilence factors, which may increase the unwillingness to use the drug,mobile grow system even when drug use opportunities are available .This study has some limitations, some of which are common to other studies using cross-sectional data, that we aim to address in future research. First, since our estimates rely on self-reported survey data, there might be the concern that changes in drug policy influence the way individuals answer the survey.

For example, if with more liberal policies and less severe punishments in place people were more prone to admit drug use when asked about it in a survey. Although issues of truthfulness are more likely to arise when surveys are administered by personal interview, whilst in our case the ESPAD survey is anonymous and self-administered respecting privacy conditions, we cannot completely rule out this hypothesis. This is one of the trade-offs that research on socially undesirable and illegal behaviours is confronted with. Second, our analysis is based on country-level prevalence measures, which do not account for individual-level factors that may confound the relationship between cannabis policy reforms and cannabis perceived availability and use among adolescents. This is because, while a number of individual-level variables are available in the last waves of the ESPAD study for many countries, they are not available for the whole time span and countries considered. Confronted with this trade-off, consistently with our research question we opted for maintaining in the analysis many countries and the largest time span possible to be able to provide an European picture. Finally, this research, as most part of the previous studies on the topic, does not include an analysis of the actual level of enforcement of the policy reforms, nor of social approval of cannabis use, due to data limitation. This is something that would be important to explore in the future, when some more information about these aspects will possibly be available. Substance use and mental illness are strongly inter-related . Several theories have been advanced to explain the bi-directional and complex relationship between these dual diagnoses, which often co-exist in the same individual. The self-medication hypothesis postulates that mental illness might contribute to substance use and addiction due to individuals using specific substances to ameliorate specific symptoms .

STRs are the gold standard for human identification  and as such they can also be applied to C. sativa for forensic purposes. Moreover, studies that included STRs C. sativa genotyping have reached promising results for forensic purposes. In 2016, a 13-locus cannabis STR method was developed and validated according to guidelines of the International Society of Forensic Genetics and the Scientific Working Group on DNA Analysis recommendations for the use of non-human DNA. Although this STR method cannot distinguish hemp from drug type, a previous study showed that groups of cannabis seizures could be associated using phylogenetic analysis demonstrating its application for intelligence purposes. Generally, when a new method is developed, interlaboratory tests were carried out to test its robustness, reliability and reproducibility. The objective of this work was to test this newly developed cannabis STR multiplex kit through an inter-laboratory exercise with different laboratories in Europe. Up to date, this is the first collaborative exercise on STR identification of C. sativa. After approval by the Italian Forensic Geneticists  society, a collaborative exercise to test a 13-locus cannabis STR was organized. Twenty-one European laboratories from different institutions, using different DNA analysis platforms, participated in the exercise.Each box contained: two cooling tablets, a self-sealing pre-PCR bag and a self-sealing postPCR bag. The pre-PCR bag contained a PCR master mix tube , a primer mix tube  and sample set tubes in three separate bags. The sample set contained three aliquots  of C. sativa DNA . The PCR master mix and the primer mix were prepared according to Houston et al.. Lastly, an aliquot of 5 µL of allelic ladder was contained in the post-PCR self-sealing bag. Protocols for PCR amplification and DNA genotyping were also provided. Participants used their standard DNA genotyping platforms, as well as the interpretation and reporting guidelines. Some reagents used in this exercise were kindly provided by Dr.

Running conditions were chosen based on standard HID STR genotyping protocols used by each laboratory. The different genetic analyzers used by each laboratory are displayed in Table 1. Different run parameters  were applied according to each laboratory protocol. For this reason, the majority of laboratories had to adjust their bin sets appropriately. Marker panels and allelic bins files for different versions of Genemapper® software  were developed and provided by the core lab to each participant laboratory. Indeed, grow tent for sale online technical support for the calibration of bins and markers according to different electrophoretic conditions was also provided. Analytical and stochastic thresholds were set according to each laboratory’s protocols and interpretation guidelines. Participating laboratories provided a table with genotyping results and the raw data sample files  with the printouts of the obtained electropherograms. Heterozygous peak height ratio  was calculated for a given locus by dividing the peak height of an allele with a lower relative fluorescence units value by the peak height of an allele with a higher RFU value in a heterozygous pair, and then multiplying this value by 100 to express the PHR as a percentage. For the PHR, the mean, standard deviation , median, minimum and maximum were calculated. The inter-loci balance was calculated as the ratio between the mean peak height for each locus and the mean peak height across all loci multiplied by 100. Stutter percentage was calculated based on the peak height of the parent allele . Stutter peaks that were in-between two alleles on + 1/− 1 stutter position were regarded as −1 stutter of the longer allele. Stutter peak average was determined and the −1/+ 1 stutter mean obtained from each laboratory were estimated. As part of a new forensic kit in-house validation the assessment of −1 and + 1 stutter unit repeat filter application was required. To identify if a peak was a true allele or a stutter, we applied stutter ratio filters for different STR loci. Peaks below that filters were considered stutters. Results from positive control, sample 1 and sample 2, each in triplicate, were utilized to determine the −1 and + 1 stutter ratio thresholds percentage. Each sample replicate was analyzed by the software GeneMapper ID-X ; no stutter filters were applied and a detection threshold was set to 30 RFU. RFUs from 3300 to 8000 data point were collected and analyzed.

For the statistical analysis, GraphPad Prism software ver. 9.0.2  was used. Mean of Peak Height and Parent Allele Stutter , −1 and + 1 Stutter Percentage Mean  were also calculated. PHLM, PHPASLM, MSLM and PSLM were used to calculatethe Average of laboratories means and peak height  and the standard error of the mean for all laboratories. The minimum peak height of parental allele with a stutter was also estimated. To determine the limits of detection for a given analytical procedure, it is necessary to determine a Minimum Distinguishable Signal , the signal at which a peak can reliably be distinguished from noise. The MDS may be considered a relative fluorescence unit or an analytical threshold  for forensic purposes. Furthermore, the detection limit at 99.7% confidence is based on the Gaussian distribution of noise peaks height and this does not consider a possible asymmetric distribution where, the correct 99.87% confidence should be applied. The background noise level detected of each instrument were compared, to evaluate their impact on the general background noise. Three negative samples  were amplified, run through capillary electrophoresis and analyzed by setting the GeneMapper™ software at 1 RFU as detection threshold. RFU data from 3300 to 8000 data point were collected. The GeneMapper data were exported to a txt file and then imported to an excel tool or GraphPad Prism software v. 9.0.2  for the analysis. The background instrument peak heights  observed in each dye channel of each laboratory were compared. The following parameters were calculated for each laboratory: Maximum Peak Height , Average Peak Height , Standard Deviation , Limit of Detection , Limit of Quantitation , Analytical Threshold . APH and AT means were used for each dye channel to calculate the Standard Error of the Mean  for each laboratory. The percentage of genotyping success was estimated to be 96% . Genotyping errors may be due to partial DNA degradation , amplification errors, stutter calculation errors, bin error and PCR artifacts such as allelic drop-out. All of these interpretation errors and artifacts can be resolved with an optimization of this methodology through an internal validation and subsequent interpretation guidelines. A locus was labeled discordant if one or more alleles were miscalled, for example, ANUCS305 locus resulted in about 10% of incorrect allele calls for both samples . A locus was labeled concordant when all alleles were correctly called, for example 4910, 9043, B05, 1528, CS1, D02, C11 and H06 loci gave a 100% of consensus allele calls among the participant laboratories . For sample 1, laboratories 2, 6, 7, 9, 11 and 13 reported incorrect allele call for a heterozygous STR loci: 9269 , 5159 , ANUCS305  and 3735 .Moreover, laboratory 6 did not produced results for three loci: 9269, ANUCS305 and 3735.

Laboratory 13 did not produce any result for loci ANUCS501 and 9269 . For sample 2, laboratories 3 and 13 encountered a problem with incorrect allele call of the 9259 heterozygous STR locus. Moreover, laboratories 5 and 6 did not produced results on loci: ANUCS501, 9269 and ANUCS305. Indeed, laboratory 6 did not produce any result on locus 3735 . The calculations of percentage of success were based on a total of 13 STR loci. Examples of typing errors are displayed in Fig. 2. The negative controls did not show any evidence of external contamination. In the case when a laboratory failed to produce results for a specific STR locus or if only one allele at a heterozygous locus was obtained, it was considered an error and not a partial result for the purpose of the study. Results with concordant calls with those of the organizers were considered correct . In summary, twenty laboratories submitted results for cannabis STRs. Eleven laboratories obtained full and concordant profiles for the two samples without errors, two laboratories obtained full and concordant profiles with one error, four laboratories completed the exercise with two errors, one laboratory committed three errors, while two laboratories completed the test with more than three errors. The success rates for cannabis STR typing ranged from 74.4% to 100% for sample 1 and from 69.2% to 100% for sample 2. Genotyping success calculations were based on the total number of loci tested by a laboratory in this study. An example of an electropherogram of this study is displayed in Fig. 3. Peak heights for the heterozygous markers were averaged and the intra locus peak height ratio  was calculated. The final average PHR was calculate by the mean PHR for each heterozygous locus of the three samples, and resulted to be 78.2% . The mean inter-loci balance was estimated to be 100,00%. The present collaborative study of the Ge.F.I.-ISFG working group allowed to demonstrate the robustness and reproducibility of a 13-locus cannabis STR multiplex system for forensic DNA profiling. Overall, each participant, using various instrumentation, polymers, size standard and arrays, generated STR profiles for each of the 13 markers. Analysis of the electropherograms, by the core laboratory, showed a concordance of more than 96%. Data misinterpretation resulted in discordance in some markers; typing was more problematic with the analysis of the ANUCS501, 9269, ANUCS305 and 3735 loci. This problem will require further investigation and all of these discordant allele calls can be resolved with, an optimized bin set, more training and experience with this multiplex STR kit. An important limitation of this study is that the analysis was conducted with cannabis DNA extracts instead of cannabis plant tissue. An important source of variation may occur during DNA extraction of different cannabis plant material. It is important to note that this STR kit cannot differentiate hemp from drug type; therefore, chloroplast DNA markers should be used for this purpose. However, using STRs,indoor tent grow cannabis seizures can be genetically associated through phylogenetic analysis of a previously established database.

Lastly, a plant generated from clonal propagation can be genetically associated to its clones using this STR kit. Future plans include: a) a collaboration between laboratories to test this kit with a new synthetic allelic ladder , to increase allele coverage and to aid in more accurate allele calls, b) studies of variation based on different extraction methods, types of tissue and various storage conditions and c) comparison of different databases. A written consensus standard for C. sativa authentication would be useful for the forensic community to establish rules and interpretation guidelines. Points to be considered for a future consensus standard include: allelic ladder, stutter filter recommendations, DNA quantitation methods, a comparative C. sativa STRs database, and troubleshooting. Finally, this inter-laboratory exercise can be considered a milestone in the identification of C. sativa samples. For centuries, cannabis has been used with many different purposes, including medicinal use.The Shennong Ben Cao Jing encyclopedia, which dates back to 2900 BC in China, recommended the seeds as treatment for pain, constipation and malaria.Additionally, the plant was used along with wine to create an anesthetic effect for patients undergoing surgery.Around 1000 AC, cannabis flowers became popular in India, providing analgesia, hypnotic, antispasmodic, and anti-inflammatory effects.In the 21st century, cannabis began to be explored by Western medicine, however only plant extracts were used,and active ingredients, both from leaves and flowers were isolated.During the 20th century, the endocannabinoid system was further understood and in the 3rd edition of the US Pharmacopoeia, in 1851, cannabis was included as a treatment for gout, rheumatism, tetanus, cholera, hysteria, depression, delirium tremens, and uterine bleedings.Cannabis was available in the US pharmacies since 1845 and was available in British pharmacies for over a century,however, because of the rise of concerns by its psychotropic effects, it was removed from the US Pharmacopeia in 1941.In 1976, the United States Controlled Substances Act classified cannabis as a Schedule I drug, meaning it had no acceptable medical use and high potential for abuse.

However, adjusting for covariates in models 2 and 3progressively attenuated the beta estimate and increased the width of the confidence intervals to include null and positive values. All other categories of self-reported cannabis use produced wide confidence intervals that include null values. Fibrinogen. In bivariate analysis, self-reported cannabis use within the past 30 days was associated with lower levels of fibrinogen compared to nonuse with confidence intervals around the beta point estimates excluding null and positive value. Like IL-6, adjusting covariates in models 2 and 3 attenuated the point estimates and widened the confidence intervals to include the null value. Full model estimates with covariate results are included in the Supplementary Material Table S3.In this analysis of nationally representative data from Wave 1 of the PATH study, there was a pattern of lower levels of biomarkers of systemic inflammation, particularly hs-CRP among respondents self-reporting recent  cannabis use compared to never use, although the wide confidence intervals around the point estimates indicated findings were not statistically significant. Furthermore, statistical tests to determine whether the association between self-reported cannabis use and biomarkers of systemic inflammation differed by sex were also not statistically significant. The findings from our study are based on a multivariable analysis that adjusted for important confounding variables, including respondent’s BMI and use of antiinflammatory medications. The potential therapeutic effects of cannabis have been proposed to be mediated via its anti-inflammatory properties . Findings from preclinical and animal studies converge to suggest that the active constituents in the cannabis plant – particularly THC and CBD induce anti-inflammatory properties . Our study found that more recent cannabis use is associated with lower levels of biomarkers of systemic inflammation is consistent with anti-inflammatory hypothesis and with findings from prior research. Data from the National Health and Nutrition Examination Survey  showed lower serum CRP levels in active cannabis users compared to never users, but only when CRP levels were below the median . Also, self-reported cannabis use was not statistically associated with lower levels of CRP in a recent analysis using data from the Adolescent to Adult Health study, after adjusting for sociodemographic characteristics, tobacco exposure, BMI and anti-inflammatory medication use .

In a recent longitudinal analysis of participants in the CARDIA cohort study, self-reported recent cannabis use was not statistically associated with lower levels of CRP, IL-6 and fibrinogen among the CARDIA sample.In sum,trimming tray most epidemiologic studies investigating the association between self-reported cannabis use and biomarkers of inflammation have found negative  associations that were non-significant with the exception of a few that reported statistically significant negative associations . The reason for the disparate findings may be related to differences in the study sample that focused on primarily African Americans  and in the set of con-founders included in the multi-variable models . Our study adjusted for important con-founders such as anti-inflammatory medication use and BMI, which these prior studies did not address in their analysis . Indeed, our study found statistically significant associations between recent cannabis use and lower levels of hs-CRP, IL-6 and fibrinogen in limited models , which was no longer statistically significant in the fully adjusted model 3, underscoring the importance of fully adjusting for important con-founders when investigating the relationships between cannabis use and inflammation. Our study extends findings from the extant literature by utilizing a large nationally representative data to analyze the association between self-reported cannabis use and three biomarkers of systemic inflammation. Although our results suggest lower levels of biomarkers of systemic inflammation in respondents self-reporting cannabis use in the past 30 days , the estimates produced had wide confidence intervals. The wide confidence intervals observed in our study might be a source of measurement error related to the imprecise measurement of cannabis. Our study relied on self-report of cannabis use, which is prone to inaccuracies. specifically, respondents may not accurately recall the last time they used cannabis, making it possible that some respondents who reported that they used cannabis within the past year, but more than 30 days ago, might have used in the past 30 days. Also, the cannabis use measurement in this analysis did not collect data on the amount and or concentrations of the different active compounds in marijuana. This is particularly relevant as emerging evidence suggest that the two primary active constituents in cannabis – tetrahydrocannabinol  and cannabidiol  – may have opposing immunomodulatory effects . Therefore, to move the field forward, better measurement of cannabis use, that includes the amount, THC and CBD content and mode of consumption  would help us ascertain the dose-response relationship between cannabis, inflammatory markers, and symptomatology and whether findings differ by THC/CBD concentrations and mode of consumption. Our study also analyzed hs-CRP data which is a more stable and sensitive molecule  than the standard CRP test. The hs-CRP assay can detect trace amounts of CRP than the standard CRP test. Although statistically non-significant, our analysis showed that the differences between recent cannabis use and other categories of cannabis use were more prominent for hs-CRP than other sensitive biomarkers of systemic inflammation. This suggests that more sensitive biomarkers of systemic inflammation should be employed in future research.

Our analysis was based on only three biomarkers of systemic inflammation; with the blood specimen to measure these biomarkers collected on a separate visit from the visit cannabis data was collected. Future studies should include a broad panel of biomarkers, particularly anti-inflammatory molecules in order to increase our understanding of the immunomodulatory effects of cannabis use. We note that mean levels of all biomarkers of systemic inflammation were higher among respondent self-reporting cannabis use within the past year, but not in the past 30-days . It is possible that this group includes respondents who recently ceased cannabis use due to illness that can drive inflammation response. The cross-sectional design of our analysis precluded the assessment of directional relationships. Specifically, a cross-sectional finding indicates a correlational association, precluding a directional or causal relationship between cannabis use and biomarkers of systemic inflammation. Therefore, future research using longitudinal and experimental designs that follow subjects across multiple time points are needed to broaden our understanding of the cannabis and inflammation relationship, specifically whether reductions in inflammatory markers mediate the association between cannabis use and reduced self-reported chronic disease symptomatology or differences in incident or recurring inflammatory-related disease .Cannabis is the most commonly used illicit drug globally, with some 250 million estimated active  users. Policy approaches for cannabis have been shifting gradually around the world recently. While criminal prohibition has been the main control framework for decades, Canada, Uruguay, and 11 US states have recently legalized non-medical cannabis use and supply, with reference to public health and safety objectives. New Zealand, alongside other jurisdictions, is actively considering a similar policy reform towards legalization of non-medical cannabis use and supply that will be decided in a public referendum in late 2020. Public opinion polls suggest an about split for and against a legalization framework as presented in the draft ‘Cannabis Legalization and Control Bill’. This proposal is very similar to Canada’s laws in: legal use age of 20 years; no public use; commercial production and retail of diverse cannabis products; and home-growing of cannabis allowed.

New Zealand, along with North America and Australia, is part of a group of ‘high-use’ countries in which 8%–15% of the population report cannabis use, the majority of whom have tried cannabis in their teens. While survey evidence is not wholly consistent, cannabis use has increased among young adults in the general population in New Zealand but declined among adolescents. Cannabis use remains concentrated among youth/young adults , with about one in three reporting recent use but its prevalence of is lower than that of alcohol and tobacco. These include: acute cognitive,psychomotor control and memory impairment ; moderately increased driving impairment increasing risks of injury/death; cannabis use disorder/dependence ; weak to moderate associations with chronic mental health problems, primarily schizophrenia and depression ; chronic bronchitis or other pulmonary problems  among those who smoke cannabis ; select adverse reproductive/maternal health outcomes  among women using cannabis during pregnancy; and possibly cardio-vascular problems among users of high-potency cannabinoid products. With notable exceptions , there are few, if any directly attributable  deaths from cannabis. The lion’s share of the cannabis-related burden of disease is attributable to cannabis-related impairment, and consequential injuries or deaths, and cannabis use disorder . The cannabis-related disease burden is substantially lower than that for alcohol, tobacco or psychostimulants. The main adverse social consequences of cannabis use can include compromised educational attainment, and adverse consequences of arrests and convictions e.g. restrictions on travel and professional disadvantage. Arrests commonly involve young and socio-economically marginalized males as a result of selective enforcement practices with related social injustices. Among youth and young adults, adverse health and social outcomes primarily occur among sub-groups of vulnerable users characterized by select, shared risks characteristics. This fact has major implications for the foci of targeted prevention of cannabis-related harms from a public health point of view, namely the need to give priority to protecting young people from the adverse effects of their youthful cannabis use on their life chances and courses. Among its essential prospective benefits, cannabis legalization allows authorities to regulate cannabis products, distribution and use. It furthermore makes it easier to directly facilitate interventions aimed at users, and specifically to systematically provide risk reduction advise  to users. Targeted or secondary prevention measures to reduce risky or harmful cannabis use have traditionally been limited, and general prevention efforts have mostly focused on reducing availability and advising against cannabis use. This, in part, because risk reduction advice has been seen as implicitly ‘endorsing’ cannabis use as an illegal activity. Recent reviews suggest some evidence for a limited impact of individual targeted risk-reduction interventions, for example, in the form of ‘brief interventions’, for cannabis use. A tailor-made population-level targeted prevention tool for cannabis use, the ‘Lower-Risk Cannabis Use Guidelines ’, was developed, originally in 2011 and updated in 2017, in anticipation of cannabis legalization in 2018 in Canada. The LRCUG embody health-focused education and ‘behavioral choice’ models that focus on risk factors for adverse harm outcomes from cannabis use, identifified by reviews of relevant scientific evidence, trim tray pollen that users can modify if they wish to reduce risk of harm with ongoing use. The LRCUG comprise a total of 10 recommendation clusters advising users on how to reduce cannabis use-related risks developed from the consensus of an international group of addiction and health scientists. Important for general uptake and dissemination, the LRCUG have been endorsed by ten leading Canadian organizations [e.g., the Canadian Medical Association [CMA], the Canadian Public Health Association [CPHA], the Canadian Society of Addiction Medicine [CSAM], among others with health, substance use and addiction focus or mandate.

They were also included in education and prevention strategies devised by different levels of governments as part of the implementation of cannabis legalization in Canada. To practically facilitate wide dissemination and uptake, a suite of customized ‘knowledge translation’ products was developed  for different target audiences and distributed jointly with key stakeholders. The LRCUG, or similar frameworks, have been adapted for use in Latin America and other jurisdictions. Based on the proposed parameters of possible legalization policy in New Zealand, and available assessments of the impact of legalization on cannabis use and harm outcomes to date in other jurisdictions, it is possible that some of these harm indicators, at least in the short-term, may increase. Given this, the LRCUG provide a ready-made, evidence-informed population health tool with the potential to reduce the risks of adverse effects among the sizeable population of cannabis users in New Zealand. Moreover, the New Zealand government’s draft legalization bill stipulates mandatory ‘harm minimization messaging’ to be provided to users at cannabis retail interfaces, for which the LRCUG provide a ready and fitting foundation or template. While the scientific evidence informing the LRCUG is evolving and will require future updating, the LRCUG’s concept and approach resemble other, established health behavior guidelines, for example targeting nutritional, cardio-vascular, sexual health promotion or related risk reduction, and – the closely topic-related – low-risk drinking guidelines in place in many English-speaking and other countries.