A. meyeri was highly enriched in the saliva from chronic cannabis smokers compared to those of non-smokers, and oral enrichment of A. meyeri was associated with the age of first cannabis use. We further investigated if direct administration of this bacterium, in the absence of cannabis or the psychoactive THC component, could elicit alteration in the brain-immune axis in a mouse model. Long-term oral inoculation of A. meyeri bacterium to mice resulted in behavioral changes, macrophage infiltration into the brain, and increased Ab 42 protein production in the brain. Oral flora plays a role in maintaining oral health; however, environmental changes can result in dysbiosis. Prior results have shown tobacco smoking alter the oral micro-biome. Decreased abundance of Neisseria and Capnocytophaga and increased abundance of Streptococcus were found in tobacco smokers compared with those of non-smokers. Consistent with these findings, here we found that the abundance of Neisseria, Capnocytophaga, and Cardiobacterium genera was reduced and the abundance of Streptococcus was increased in cannabis smokers compared to non-smokers. In contrast, cannabis use was associated with increases in the genera, Actinomyces, Atopobium, Megasphaera, and Veillonella. A previous study demonstrated a strikingly similarity in the physical and chemical properties produced by cannabis and tobacco smoking, which contained large amounts of hydrocarbon and changed the acidity of saliva. Thus, Streptococcus and Actinomyces, acid-tolerant and facultative anaerobes, may preferentially grow in a smoking-mediated environment. In contrast, bacteria such as Neisseria sp. and Corynebacterium sp. were decreased in cannabis smokers, suggesting that smoking renders an unfavorable environment to facultative or strict anaerobes.

Although some oral micro-biome is shared between tobacco smokers and cannabis smokers, including increased Streptococcus and decreased Neisseria genus bacteria compared to non-smokers, A. meyeri was only increased in cannabis smokers. Moreover, the younger the age of first cannabis use, the more A. meyeri was orally enriched. Although the gut micro-biome has been shown to play a crucial role in the CNS activities via the bidirectional gut-brain axis,pollen trim tray strong connections between the oral micro-biome and the CNS have been reported as well. P. gingivalis, a key pathogen in chronic periodontitis was identified to contribute to Alzheimer’s disease. Besides P. gingivalis, other oral resident microbes were shown to associate with neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease. Moreover, oral bacteria Treponema and N. meningitidis can infect the brain through the trigeminal or olfactory nerve. The perturbations of intestinal microbiota resulted in the impairment of memory formation and cognition in the hippocampus. To test the effect of cannabis use-associated oral dysbiosis on CNS functions, we performed various behavioral tests in mice following bacteria oral inoculations but did not observe significant memory changes. Actinomyces are gram-positive facultatively anaerobic bacteria. Some Actinomyces species are commensal bacteria in the skin, oral, gut, and vagina of humans, but can also become opportunistic pathogens leading to infections in the dental cavity and other systemic sites. A. meyeri is associated with brain infection or dysfunction, but the causality and mechanisms of A. meyeri-mediated CNS dysfunction have never been reported. In this study, A. meyeri enrichment in the oral micro-biome was inversely correlated with the age of first cannabis use, which indicates that the longer duration of cannabis exposure, the more enrichment of A. meyeri in the oral cavity.

A previous study found younger age of first cannabis use was associated with decreased orbital prefrontal cortex volume. Another study found negative correlations between the age of initiation of cannabis use and altered thickness of the right superior frontal gyrus. Our study implies that the age of first cannabis use may be critical for particular oral micro-biome development and its potential impact on cognitive function. Given the many toxicant components found in cannabis smokers, it is not surprising that cannabis smoking notably alters the oral microbial ecology. Importantly, long-term repeated oral inoculation of A. meyeri, which mimicked cannabis exposure-increased oral A. meyeri in humans, resulted in the development of CNS abnormalities. Recent studies have found correlations between Actinomyces and Alzheimer’s disease. For example, brains from patients with Alzheimer’s disease have been reported to have strikingly large bacterialloads compared to controls. Actinobacteria, a phylum of Actinomyces, were exclusively detected in the post mortem brain samples from patients with Alzheimer’s disease compared with those of normal brains. Actinobacteria were also found enriched in the gut microbiota of patients with Alzheimer’s disease. Another study using 16S rDNA sequencing in the brain cell lysates further found Actinomycetales, Prevotella, Treponema, and Veillonella were exclusively present in the brain of patients with Alzheimer’s disease. In a previous study, oral micro-biome and resting-state functional magnetic resonance imaging scans were conducted in cannabis smokers; the enrichment of Actinomyces in the oral micro-biome was positively correlated with brain resting-state functional networks which are significantly perturbed with Alzheimer’s disease. Neuropathological hallmarks of Alzheimer’s disease include loss of neurons, progressive impairments in synaptic function, and deposition of amyloid plaques within the neuropil. Although mice do not readily develop amyloid plaques, our results show Ab 42 deposition was increased in the brain from A. meyeri-treated mice compared with controls, suggesting oral micro-biome-induced neuronal responses that have relevance to Alzheimer’s disease neuropathology. Previous studies have suggested that bacteria in the oral cavity were initially taken up by tissue macrophages which may facilitate CNS infection.

In the current study, A. meyeri treatment resulted in increased myeloid cell migration and phagocytosis in vitro and elevated macrophage infiltration into the mouse brain in vivo, compared with those of N. elongata treatment. The cytokines that differed in cannabis users and non-users and in A. meyeri-treated mice and control mice are related to monocyte/macrophage functions. The TNF super family cytokine promoted a compromised blood-brain barrier , and monocytes migrated across the BBB into the brain in response to MCP-1. Although it is not clear if macrophage infiltration results in CNS abnormalities in the setting of disease-associated immune perturbations, macrophage infifiltration into the brain has been demonstrated in the pathogenesis of several diseases. MIP-1 cytokines are induced in myeloid cells in response to bacterial endotoxins or membrane components. In the current study, A. meyeri administration increased plasma levels of MIP-1a in some mice. However, cannabis smoking altered oral micro-biome not limited to A. meyeri; thus, the decreased plasma levels of MIP-1a in cannabis users may stem from myeloid cell activation by other bacteria or by reduced total bacterial translocation due to cannabisreduced barrier permeability. In general, bacterial stimulation reduces phagocytosis and promotes proinflammatory cytokine production by myeloid cells. Unexpectedly, A. meyeri did not affect phagocytosis and did not induce proinflammatory cytokines but did increase myeloid cell infiltration and amyloid production in the brain. It is possible that A. meyeri maybe a new exposure to mice which induces the immune responses and CNS effect. However, there is no evidence on the causal link between a new bacterial exposure in the oral cavity and neuropathology in mice. Thus, we believe that A. meyeri is a unique oral bacterium that is linked to CNS function. We have tested novel object recognition in C57/B6 mice after 6- month exposure to A. meyeri, but did not find significant memory deficits. The reasons for the null finding are as follows: 1) more than 6- month exposure is necessary to see memory changes, 2) the nature of wildtype C57/B6 mice, and 3) the age of mice might play an important role with our mice being too young to detect any changes.

To date, there were few to no published studies measuring effects of a specific oral microbial dysbiosis pathobiont on behavior in wild type mice. In 2018, the study of P. gingivalis found that this pathobiont induces memory impairment in 13-month-old mice and not 2-month-old mice suggesting an age-related effect, but without enough age cross sections to determine when susceptibility occurred. Thus, we have refined our future strategy to analyze other neurological defects or pathological signs and started to conduct studies that use mice at different ages and include memory-related longitudinal measures, such as the Novel Object Recognition task that focuses on the hippocampus and prefrontal cortex memory functions, the Novel Tactile Recognition task that focuses on the hippocampus and parietal cortex memory functions, and finally the Water radial arm maze that focuses on spatial memory and cognitive flexibility. We have identified a rotarod and marble burying methods and will add these to the battery of tests in future studies.In 2018, Canada became the second country in the world to legalize adult recreational cannabis use , following its legalization for medical use in 2001 . Canada’s Cannabis Act dictates that cannabis policies should “keep cannabis out of the hands of youth”, “keep profits out of the pockets of criminals” and “protect public health and safety by allowing adults access to legal cannabis” .Earlier and more frequent adolescent cannabis use is associated with greater risk of harm to the developing brain and multiple adverse outcomes including impaired neurocognitive functioning, affective problems, suicidality, psychosis, cannabis dependence syndrome, and cannabis-related morbidity in later years . With the legalization of adult recreational cannabis use, however, adolescents may experience increased cannabis availability,grow tent increased social acceptance of cannabis, and confusing messages about whether cannabis use is safe . Evidence regarding the effects of adult cannabis legalization on adolescents is mixed. Some studies show that more permissive cannabis laws increase rates of adolescent cannabis use while others do not . Although research surrounding the impact of recreational cannabis legalization on youth in Canada is scarce, national survey data show a gradual increase in cannabis use among youth coinciding with increased public discourse on the topic .

The extent to which Canada’s shift towards more liberal cannabis policies, practices and culture will impact youth cannabis attitudes, intentions, and use are largely unknown. A key influence on youth cannabis attitudes, beliefs, expectancies, and intentions to use, is cannabis-related marketing . Though it is illegal to market cannabis products to youth in Canada, recent studies , and a long history of research on other age-restricted substances with abuse potential , demonstrate that companies ignore these laws and intentionally target their products to youth . Research on alcohol and tobacco marketing shows strong correlations between youth exposure to marketing and earlier initiation, and higher consumption among those already using . All told, exposure to cannabis marketing could similarly spur youth cannabis use . While emerging research suggests that cannabis marketing puts Canadian youth at risk , preliminary studies are limited because they use inexact measures such as general awareness of marketing and receptivity to marketing that rely on retrospective recall, which are subject to participant recall error and bias . Existing studies also describe marketing exposures in aggregate, obfuscating the context of individual exposures, such as when and where exposures occur, and other psychosocial factors which could influence their effects . In particular, existing research does not describe the channels through which cannabis marketing exposures occur, nor the ways in which federal marketing prohibitions are violated. Policymakers also need research that shows whether cannabis marketing of different types and through different channels has varying impacts on youth. Real-time, real-world assessment techniques such as Ecological Momentary Assessment  may be used to reduce bias and increase the reliability, accuracy, and acuity of information about adolescents’ exposures to cannabis marketing. In EMA protocols, participants use smartphone technology – that they already use throughout the day in multiple settings – to track a range of phenomena as they occur in participants’ natural environments. Previously, we created an EMA protocol for tracking youth exposure to alcohol and tobacco marketing . Middle- and high-school participants made electronic time-stamped recordings of tobacco and alcohol marketing exposures, demonstrating that exposures primarily occurred in the afternoon, at point-of-sale locations, and on days leading up to the weekend . To our knowledge, no research has similarly documented Canadian adolescent cannabis marketing exposures using an EMA approach. The goal of this pilot study was to assess the feasibility of a 9-day, smartphone-based EMA protocol to obtain a preliminary understanding of the frequency of Canadian adolescents’ exposures to cannabis marketing, their reactions to such exposures, and the context in which exposures occur in the real-world and in real-time.

The list of residual solvents and their associated toxicological limits were obtained from the International Council for Harmonisation guidelines for residual solvents. Ethanol concentration was converted into alcohol by volume to provide an estimate of ethanol content using the density of ethanol and average density of the cannabis oil samples . The average volume consumed by the child per day was calculated from original study data, with the typical serving administered either in mL or drops . The list of pesticides and their associated toxicological limits were obtained from the European Pharmacopeia 10th Edition as per Australian government requirements. The Globally Harmonised System was used to categorize pesticides based on their toxicity ranging from ‘extremely hazardous’ to ‘unlikely to present acute hazard’. Limit of reporting was defined as the lower limit of quantification , adjusted for volume for each individual sample. In cases where LLOQ exceeded the toxicity limit for a specific analyte, the data were deemed as inconclusive . In cases where LLOQ was less than the toxicity limit but not quantifiable, the specific analyte was deemed as ‘below safety limit’ . Samples where a specific contaminant was quantifiable and above the toxicity limit were deemed ‘above safety limit’. All plots were generated using GraphPad Prism 9 Software.Of the 51 cannabis samples tested for the heavy metals, concentrations of arsenic, cadmium, lead, and mercury were below the toxicity limit in 48/51 samples. Results were inconclusive for 2/51 samples for arsenic, and one sample for cadmium and mercury each . Of the 58 cannabis samples tested for residual solvents, 17/58 samples were above the limits specified for ethanol . All were liquid-based preparations. Estimated alcohol by volume percentage for these samples was 6.68 8.6% on average .

One ‘paste’-like extract tested 1.2 times above the limit for isopropanol with an estimated ABV of 0.63% v/v . Results were inconclusive in 3/58 samples for 1,2-Dichloroethane, 6/58 samples for benzene, 1/58 for hexane, and one sample for methanol. One of the 31 samples tested for pesticides contained 4.9 times higher than the acceptable limit of bifenthrin . No other sample tested above the toxicity limit for any other pesticide. A large proportion of samples had inconclusive results for at least one pesticide: 21 samples had inconclusive results for 25/76 pesticides, four samples had inconclusive results for 35/76 pesticides, three samples for 26/76 pesticides, and one sample for 71/76 pesticides .This current analysis of ‘artisanal’ cannabis samples administered to children with epilepsy in the Australian community found potentially unsafe levels of residual solvents, mainly ethanol, in approximately one quarter of the cannabis drying rack samples tested. In the manufacture of artisanal cannabis preparations, the incomplete evaporation of ethanol and other solvents prior to reconstitution with an oil-based diluent can lead to consumers ingesting higher amounts of residual solvents than anticipated, particularly if products are taken at high doses and/or for prolonged periods of time. There are legitimate concerns around the potential harmful effects of ethanol on the developing brain, as well as the fact that alcohol consumption, particularly chronic and/or acute use of considerably large amounts of alcohol , and sudden alcohol withdrawal, can increase the risk of seizures. Other alcohol-related factors for increased seizure risk include impaired sleep quality and interactions with antiepileptic drugs. The effect of chronic low-level ethanol exposure on seizure frequency and neurodevelopment of children has not been systematically evaluated, with the current literature mostly focused on acute poisonings, fetal alcohol syndrome/effects or extrapolated from preclinical studies.

Children and adolescents exposed to serum ethanol concentrations of >0.125 mg/L may be asymptomatic or present with mild symptoms such as drowsiness, dizziness, and ataxia, while a serum ethanol concentration of 50–100 mg/dL is considered a toxic dose in an infant or young child, with >100 mg/dL associated with central nervous system depression, vital sign abnormalities, and increased mortality in children. Despite these concerns, ethanol is commonly used as a solvent in many oral liquid preparations for pediatric populations to improve drug solubility and/or as a diluent. According to ICH guidelines, ethanol and isopropanol are ‘Class 3 solvents’ which are regarded as less toxic and of lower risk to human health. Such solvents may be administered in concentrations higher than the toxicity limit provided this is underpinned by good manufacturing practice or other quality-based requirements. In fact, the FDA-approved CBD-containing medication Epidiolex , which is prescribed to treat rare childhood epilepsies, contains 79 mg/mL of ethanol, equivalent to 10% v/v anhydrous ethanol. With Epidiolex typically dosed at up to 10 mL/day , it can be deduced that relatively small amounts of ethanol are ingested by patients relative to a single USA standard drink which contains 14 g of ethanol. The maximal amount of any extract consumed in the present study was 16 mL/day. As with the calculations for Epidiolex above, we conclude that in the ‘worst-case scenario’ presented in the current study, a child may have consumed 16 mL of a solution containing 25.1% ethanol, equivalent to 3 g/day of ethanol. The World Health Organization states that ethanol content in over-the-counter medications should be less than 0.5% in children less than 6 years old, <5% for children 6–12 years old and less than 10% for children over 12 years. Of the 17 samples that were above the toxicity limit, 12 were between 0.5 and 5%, two between 5 and 10%, and three exceeded 10%. The average age of the children and adolescents with epilepsy in our study was 8.8 4.6 years suggesting that some children were ingesting higher than appropriate levels of ethanol. However, it is reassuring that 71% of the samples tested contained less than 5% of ethanol content and this concentration is suitable for children aged 6–12 years according to WHO guidelines. In addition to these high concentrations of residual solvents in some samples, one sample also tested above the safety limit for bifenthrin, an insecticide used in cannabis cultivation that can be toxic to human health if used inappropriately. The exact implications of this observation are unclear, but it suggests that pesticide contamination is a legitimate concern which requires further investigation across a larger set of samples.

At the time the ‘PELICAN’ study was collecting samples from participants , legal pathways to accessing medical cannabis in Australia were still evolving and highly bureaucratic, time-consuming, and expensive for patients. This represents a time in history when consumers had few alternatives to accessing medicinal cannabis and, artisanal ‘black market’ cannabis products, by comparison, were cheaper and easier to access. There are now better legal options available for accessing medicinal cannabis that avoid the concerns identified with unregulated products. In Australia, Epidiolex is now a registered and government-subsidized medicine for the treatment of Dravet syndrome and Lennox– Gastaut syndrome and an array of other CBD-containing products are available on prescription via schemes overseen by the Therapeutic Goods Administration. Despite this, the use of artisanal cannabis products will undoubtedly continue because of the perception that artisanal products are more effective and/or better tolerated than pharmaceutical-grade cannabis products , and that the addition of D9 -THC and minor cannabinoids may harness a supposed ‘entourage effect’ that enhances overall efficacy. To-date, no randomized, controlled studies have compared pharmaceutical-grade CBD against artisanal cannabis preparations in a population with epilepsy, although preclinical studies are starting to shed light on the pharmacological interactions between cannabis constituents. Meanwhile, in North America, concerns continue around an overall lack of mandatory testing of cannabis products to ensure patients are obtaining safe, quality-controlled product from licensed producers. Several recent reports have described cannabis-derived products contaminated with microbes, heavy metals, pesticides, and other toxins. The potential risk of contaminants in artisanal cannabis preparations, in addition to the variability in cannabinoid content and labeling accuracy, are legitimate concerns for consumer safety. Although the samples collected in the current study were intended for the treatment of seizures in children with epilepsy, it is possible that any individual seeking ‘CBD-rich’ artisanal products for treatment of a medical condition could be susceptible to purchasing contaminated products. The use of artisanal products accessed without prescription evades the necessary medical and regulatory oversight to ensure the patient’s suitability for medicinal cannabis and subsequent monitoring for safety and adverse events. Such products are unlikely to be optimized for safety or efficacy, indicating a need for improved patient access to safe, planting racks quality-controlled prescribed products from licensed manufacturers.Cannabis consumption is estimated at 192 million users in 2018 which equals 3.9 per cent of the world community aged between 15 and 64 years.

Cannabis use represents the most commonly illicit drug intake worldwide, with around 3.8% one-year prevalence worldwide and 5% in North Africa.Cannabis use may lead to adverse health effects such as heart attacks, brain development issues, lung tissues damage and psychiatric comorbidities; It is also responsible for the decline of cannabis users’ living conditions and other social consequences such as poor schooling or week work performance, family violence stigmatisation, social discrimination and criminality. In addition, cannabis users, victims of social discrimination, are often challenged by many health system challenges such as poor and inequitable access to healthcare, qualified human resource shortage and lack of social and assistance to quit drug use. Recently, ensuring timely access to medical care and adequate support and assistance for cannabis users has become an important concern for policy makers and health system stakeholders. More specifically, increased attention has been placed in using information and communication technologies to promote access to quality health care services for cannabis users and help them overcome major health system barriers and better connect with appropriate health services. Available evidence supports the effectiveness of mobile health technologies in improving patients adherence to treatment and ensuring better symptom monitoring by health professionals. For technology users, m-Health or mobile health is the visible part of ICT iceberg. It is defined as “medical and public health practices relying on mobile devices, such as cell phones, patient monitoring systems, personal digital assistants and other wireless devices“. m-Health has benefited from the rise of digital technologies and the emergence of increasingly innovative and intuitive portable technological tools. m-Health interventions range from sending simple text messages to complex telemedicine practices using connected mobile devices and m-Health applications associated or not with sensors. Over 340 mobile and ready-to-wear devices are made available to users around the world, and more than 325,000 m-Health applications are currently available on the main commercial virtual stores “Google app” and “Apple iOS”, this number estimated at 160,000 in 2015, has doubled after two years with more than 200 mobile apps added every day. m-Health intervention have proved appropriate in managing chronic diseases, by allowing useful functionalities for both patients, and health workers. They are also useful in monitoring epidemics and allowing remote health data collection. Therefore, m-Health interventions may play a key role in the fight against cannabis intake issues.

However, little evidence exists on the functionality, usability and effectiveness of m-Health intervention for cannabis use addiction. In response, we carried out a scoping review that aims at exploring technical and functional characteristics of available m-Health-apps intended for non-medical Cannabis Use and Dependence . We aimed more specifically to identify mobile applications used as m-Health interventions, describe their characteristics and discuss evaluation outputs of CUD-focused apps. The rest of the paper is structured as follows. Section 2 presents the research methodology. General, technical and functional characteristics of CUD m-Health intervention apps are provided in Section 3 along with evaluation approaches. These results are discussed in Section 4 in terms of usability. The conclusions are included in Section 5. Tobacco companies have long employed numerous tactics to advertise their products to youth and young adults , and young people who report viewing tobacco advertisements are at greater risk for tobacco use initiation, progression to regular use, and development of nicotine dependence. As a result, the 1998 Tobacco Master Settlement Agreement limited the marketing of tobacco products in ways that might entice underaged youth to use them and movies, use of cartoon characters such as “Joe Camel”. However, following passage of the MSA, more subtle product placement strategies continued to be used in TV and movie productions with tobacco products featured as a part of the plot or character development.

User-individuals, however, showed greater regional volumes in the left putamen, lingual cortex, and rostral middle frontal cortex. There were no differences in cognitive performance indicators, suggesting minimal impact on brain structure and function . Adverse impacts of cannabis use in older-age PWUC may be influenced by or arise from interactions with independently existing age-related deficits. For example, cannabis-related impairment of cognitive and executive functions and reaction/memory may amplify age-related declines in these abilities . Furthermore, slowed metabolism/liver function and interactions with commonly used psychotropic medications may increase cannabis-related intoxication and impairment, and thereby magnify the risks of falls and injuries, including as related to driving and crash involvement . A recent, large-scale US-based case-control relative risk study found no overall association between cannabis use and risk of MVC involvement; however, significant interaction effects between age and THC emerged at age 64, resulting in significantly increasing risk of crash involvement for older THC-exposed drivers . There is some evidence of declines in lung function associated with cannabis smoking and potentially elevated risk of cardiovascular problems in older-age PWUC . Some of these older age-specific risks may be attenuated by the use of low-potency cannabis, titration of doses, and other intake precautions.

Individuals with combinations of the risk factors identified above are likely to be at markedly elevated risk of experiencing cannabis related adverse health outcomes. The combination of greatest concern is the high-frequency use of high-potency cannabis products, especially when initiated at and sustained from a young age. This pattern predicts increased risks of multiple adverse mental and physical outcomes, including neuro-cognitive, greenhouse benches psychosis and cardiovascular problems . An analysis of a sample of patients with first-episode-psychosis found that those who continued daily use of high-potency cannabis had an increased risk of relapse , shorter time-to-relapse , and required more psychiatric care after the initial episode . Similarly, adolescent-aged individuals with high-potency cannabis use were more likely to engage in daily use and report cannabis-related problems and anxiety disorders than lower-risk controls . In a systematic review, adolescent cannabis use increased the risk for psychosis ; this association was significantly moderated by age of onset and frequent cannabis use, concurrent use of other substances, and genetic risks, among other factors . As noted above, the evidence is mixed on whether an early age of-onset independently increases the risks of major adverse outcomes. It may be that individuals who report early age of onset of use more often engage in intensive cannabis use, commonly involving higher potency cannabis, that adversely affects their developmental and physiological vulnerabilities and increases their risks of neuro-cognitive impairment, poor mental health, and cannabis dependence.

A systematic review, however, found stronger evidence for the role of cannabis use intensity and potency than age-of-onset in predicting psychosis outcomes . Studies of brain structure and functioning and neurocognitive impairments in young individuals with cannabis use found deficits associated with frequency of use and possibly the potency of cannabis used.Elsewhere it has been emphasized that the earlier the onset of use and the more intensive the use, the greater the risk of adverse health and psychosocial outcomes later in life . Notably, while cannabis use was generally associated with MDD among US adolescents, individuals reporting frequent use had a significantly lower prevalence of lifetime and past year MDD than those with less frequent use . Other risk-combinations that may be relevant are understudied. For example, sex, age-of-onset and mode of use have shown associations with cannabis-related problem severity among different populations of PWUC, and their combination may differentially contribute to risk for adverse health outcomes . Combined use of cannabis with alcohol and/or tobacco increases the risk of acute and chronic adverse outcomes, such as dependence, cardiovascular problems , and potential neonatal deficits related to use during pregnancy . Similarly, frequent cannabis use among adolescents/young adults predicts an increased risk of alcohol use disorder, nicotine dependence, and CUD in mid-adulthood .While cannabis control regimes are liberalizing in many settings, evidence on the adverse health outcomes of cannabis use and related risk factors has substantially grown, but findings are mixed for some outcomes. Systematic reviews and seminal studies have expanded and enhanced the knowledge bases related to some of the earlier findings, and so allow for the strengthening of confidence in the LRCUG recommendations on risk factors and ways to reduce adverse outcomes from use.

The evidence has suggested some important additions and refinements. Notably, the role of ‘early-age-onset’ as an independent determinant of adverse outcomes has become less clear, particularly with regards to neuro-cognitive effects. Current evidence suggests increased importance of frequency of use and the potency of cannabis used, the adverse impacts of which may increase if cannabis use is also initiated at a young age . There are other major areas where evidence gaps or limitations remain. For example, comprehensive evidence is lacking on the comparative health risks of the increasingly diversified routes of cannabis administration. There is also no robust evidence to quantify thresholds for cannabis potency or THC/CBD ratios that may allow consumers to reliably reduce risks of adverse outcomes. The same is true of recommendations for driving-related risks. These require qualifications in light of the multiple factors that influence impairment. There is a need to define and quantify cannabis use in multi-factorial ways that ideally take account of the frequency, amount, and potency of cannabis used for measuring the ‘magnitude’ of use. Overall evidence on direct and causal associations between cannabis use and – much-debated – adverse outcomes, for example, mental health or reproductive harms, are limited or mixed. There is minimal evidence on the risk of cannabis use among older-aged PWUC, a growing group of user-individuals especially in settings that have liberalized cannabis use. All of these limitations add to the complexity of defining and guiding individuals to adopt ‘lower-risk’ patterns of cannabis use as clearly as possible while not being overly precise or pretending to universality . While a basic start has been made on defining cannabis consumption units , we are currently unable to quantify ‘risk-thresholds’ for harms in the way that has been done for ‘low-risk drinking’. This reflects the complexity of cannabis as a pharmacological product and of the factors influencing risks, the legal status of cannabis, the marked heterogeneity and limitations of operational definitions of use, and the limited quality of data on adverse outcomes from cannabis use . For these reasons, the present LRCUG explicitly focus on ‘lower risk’ cannabis use, and the recommendations are mostly qualitative rather than quantitative.

It should be a principal future aim of cannabis health research to generate the evidence needed to define threshold levels for at least the major adverse outcomes associated with cannabis use . While most cannabis use involvement occurs without major consequential problems, substantive sub-groups – an estimated 25 to 30% of PWUC – experience adverse outcomes that substantially burden cannabis-related public health outcomes . In summary, current evidence suggests that a substantial extent of the principal long-term adverse health effects of cannabis use can be reduced, considering the main individual risk factors, if: the initiation of use is delayed until after puberty; the frequency of use is ‘occasional’ rather than frequent ; THC-potency of cannabis used is kept low; and use occurs in ways other than smoking. These recommendations need to be qualified for persons with increased pre-existing risks for select adverse outcomes. It deserves note that possible acute harms of cannabis use, such as injury or even death occur infrequently but may arise from singluse episodes .The LRCUG require some important qualifications. First, they have been developed chiefly for non-medical cannabis use . This differs from the use of or exposure to cannabinoids that is mainly for medicinal reasons, for which there is good evidence of therapeutic benefit for selected conditions . Survey data suggest that as many as two in five PWUC report their consumption to be for medical purposes, although this includes extensive self-medication practices , whereas rates of prescribed medical cannabis use are much lower . In the case of PWUC for medical purposes, some of the LRCUG recommendations may conflict with therapeutic use needs or practices, while some risks for harm identified may still apply and so should be considered. Second, PWUC can only act on some of the LRCUG recommendations if there are legal markets and complementary regulatory provisions that aim and aid to reduce risks, such as labelling of THC-strength and other product composition and availability restrictions . Other recommendations are based solely on scientific evidence and geared towards improving health outcomes regardless of applicable laws or regulations for use, such as those concerning age-of-onset and driving under the influence of cannabis use . Third, a considerable number of PWUC, and especially those with frequent use over long periods of time may meet at least some criteria of CUD, characterized by craving, withdrawal symptoms, compulsive use,growers equipment and neglect of obligations . Recent estimates suggest that 60-80% of cannabis is consumed by 10-20% of individuals with high-frequency use, many of whom likely meet criteria for CUD . It is unrealistic to expect these user-individuals to be helped principally by information-based behavior change advice such as the LRCUG.

Neither are the LRCUG intended as a diagnostic tool for CUD, but they may allow some PWUC to recognize the presence of problems related to their cannabis use. It is crucial for PWUC experiencing persistent severe problems associated with their use, including potential CUD symptoms to seek professional assessment and assistance, which may need to include treatment . Fourth, the principal objective of the LRCUG is to reduce adverse effects on the health of users rather than the social or legal outcomes for users or their adverse effects on the health and welfare of others. Nonetheless, cannabis use is an activity common in ‘social’ contexts or interaction settings that, hence, may cause harm to others. The LRCUG recommendations as framed by public health principles, therefore, acknowledge in basic terms that individuals who choose to engage in cannabis use have a social responsibility to protect others from any adverse consequences of their use .There is limited and mixed evidence on the impact of educational/behavioral interventions like the LRCUG on population-level harms in other areas of health or substance use . In recent assessments of population-level data in North America, sizable subgroups of PWUC did not adhere to key LRCUG recommendations, including the mode of cannabis use, use frequency, and driving under the influence . Recent data from jurisdictions where cannabis has been legalized suggest that selected higher-risk use behaviours persist or may even be increasing. The prevalence of these risk behaviors may be increasing in these contexts as a result of expanding availability and marketing of cannabis at the population level and the socio-cultural ‘normalization’ of use . Altogether, this suggests considerable room and potential for the LRCUG to provide and serve as an intervention tool that contributes to protecting and improving cannabis use-related public health especially in contexts of liberalized control. The LRCUG may serve at least two didactic functions. One is to create general awareness among PWUC that there are gradations of risk for adverse outcomes from cannabis use that are within the individual-user’s control. They underscore the fact that PWUC can substantively reduce some of these risks by actively modifying use-related behaviors and choices, and adopting safer and responsible use practices. This may also help to shape emerging norms around cannabis use, especially in new contexts of legality . The second is to provide specific advice and guidance to PWUC on how to reduce cannabis-related risk of health problems. These efforts should ideally be linked with and reinforced by other targeted intervention efforts and programs, such as targeted prevention campaigns on specific risk factors of relevance. Knowledge translation strategies are a key to the effective implementation, dissemination and uptake of the LRCUG. These may include endorsements by leading organizations and stakeholders and buy-in from science, health, and prevention experts that amplify their profile and credibility.

This group would be classified as ‘vulnerable/impaired’ based on a framework of transport disadvantage developed by Currie et al. . They are particularly reliant on car travel and face high travel difficulties related to getting on and off buses, trains or trams, being able to get around alone, feeling safe when travelling, and experience an overall heightened risk of social exclusion due to transport disadvantage . Documented effects of lack of car transport include exclusion from accessing basic goods and services, social/recreational opportunities, and employment and education, with greater impacts identified in rural and remote areas . Lack of car access has also been identified as an important barrier to healthcare access, contributing to poorer chronic illness management and health outcomes. identified effects include an increase in missed appointments, delayed care, and poorer medication adherence, with one study quantifying an 88% increase in odds of ED presentation among individuals citing ‘lack of transport’ as a barrier to primary care use . For medicinal cannabis patients who do drive, when not impaired, they face the possibility of conviction under the presence offences and associated serious penalties including fines, licence suspensions or even imprisonment, a situation noted as problematic in a recent Australian Senate inquiry . However, they may also incur further substantial financial penalties if claiming compensation following a traffic-related accident and THC is detected in their blood or oral fluids. For example, in Victoria, patients who have THC detected in blood or oral fluids within 3 hours of driving following an accident, even if not at fault, can have their income compensation reduced by a third .

Driving restrictions have also been reported to be the major impediment to recruiting patients to medicinal cannabis clinical trials in Australia . Prohibiting driving for the length of a clinical trial, ebb and flow which can run for several weeks or months, is an onerous requirement that deters participants and results in reduced access to novel medicinal cannabis treatments.As international jurisdictions continue to move toward legalising and regulating access to cannabis, the issue of driving impairment and how to manage or deter such behaviour has gained greater attention. While some research has attempted to evaluate international approaches to deter driving under the influence of cannabis , there has been little attention given to how different jurisdictions have managed the legalisation of medicinal cannabis in relation to drug driving legislation. Although many jurisdictions have introduced medicinal cannabis access schemes over the last decade, some of these, such as Canada and most states within the United States, are far more permissive than Australia’s medical access model . Several of these overseas jurisdictions have also decriminalised or legalised the recreational use of cannabis and are therefore not comparable to Australia when considering road safety risks . An examination of regulatory and policy documents sourced primarily from governmental websites, identified several international jurisdictions which have introduced similar medical-only access models to Australia, with pharmaceutical grade products available only via prescription from a doctor. These jurisdictions include Norway, Ireland, the United Kingdom, Germany, and New Zealand. These countries, other than New Zealand, have drug driving presence offences relating to THC, similar to those that exist in Australia. However, in all cases they have adopted some form of medical defence enabling patients to drive when using a prescribed product as directed and not impaired .

In all countries listed, other than New Zealand, it remains an offence to drive if impaired. In many of these countries the medical defence applies to various prescription medicines that can be tested for and that have per se limits attached . However, in Ireland, where only illicit substances are tested for, a medical defence specific to medicinal cannabis was introduced and utilises a statutory medical exemption certificate . In Norway the medical exemption applies to registered medicines and health guidance recommends the patient not drive for 2 weeks after starting treatment . Other than medicinal cannabis, the only international example of a medical drug being included in zero-tolerance offences is benzodiazepines in Sweden, but patients there are not guilty of this offence if using the drug as directed by a doctor .As the number of patients accessing medicinal cannabis in Australia continues to increase, achieving the appropriate balance between road safety and patient access objectives is likely to gain further attention. Extensive experimental and epidemiological research indicates that the recreational use of cannabis is associated with a low to moderate increase in crash risk, which is of a similar or lower magnitude than several other potentially impairing prescription medications available and widely prescribed in Australia. However, the crash risk for prescribed medicinal cannabis is likely to be substantially lower due to a range of factors, with this outcome supported by available international epidemiological data that suggests a null road safety impact in jurisdictions introducing ‘medical only’ access models. Given this risk profile, the appropriateness of the current regulatory approach criminalising the presence of THC for medicinal cannabis patients irrespective of impairment is questionable.In all other jurisdictions, patients risk criminal conviction for the presence of THC, even when not impaired and using the medicine as directed by their doctor. This approach has serious negative impacts on patient access, health, and mobility.

It also fails to adhere to established principles that mobility should not be limited on the basis of a specific treatment, and that the potentially impairing effects of a medication should be balanced against a patient’s improvement in health and safe driving ability . These principles are incorporated into the risk minimisation framework used for other impairing prescription medications, coordinated via the TGA and state health and transport agencies. The discrepancy in the treatment of medicinal cannabis patients compared with patients using other impairing medications is particularly marked when considering that medical defences are currently in place for all other potentially impairing prescription medications that are included in drug driving presence offences in Australian jurisdictions . This creates a strange situation where medicinal cannabis patients are more vulnerable to prosecution than users of some illicit drugs who are able to drive while the drug is detectable in their bodily fluids if not impaired. Similarly, even recreational users of alcohol with a BAC 0.01 to 0.05, who have crash-risk odds of 1.2-1.8, face no restrictions on driving in normal circumstances . The question then arises whether there may be other specific issues relating to medicinal cannabis that necessitate a harsher approach for these patients. Some potential concerns include possible misuse or supplementation of medicinal cannabis with black market products, and the difficulty in communicating why medicinal cannabis patients can drive , but not recreational users. Both issues are common to, and currently managed for, other potentially impairing prescription medications, with the public now well-accustomed to different legal frameworks being in place for medical and illicit cannabis.But the value or justification for such an apparent higher evidence bar for medicinal cannabis is unclear, given the large number of observational and epidemiological studies that have already been undertaken in relation to THC, as well as agreement of recent meta-analyses of a relatively low risk profile even among recreational users . These studies provide an evidence base far exceeding numerous other known impairing medications.

It is also noteworthy that other countries with medicinal cannabis schemes similar to Australia’s tightly controlled, medical only access model, have implemented some form of exemption from usual drug driving offences for patients. In the UK, Norway, Germany, New Zealand and Ireland, patients with a valid prescription for medicinal cannabis who have taken the drug in accordance with instructions from a health practitioner are permitted to drive, as long as they are not impaired. While it is beyond the scope of this paper to examine the issue of how to define ‘impairment’ and the most effective means of establishing it at the roadside, standardised sobriety tests remain the most widely used method of screening for impairment internationally. They are also currently accepted by legal authorities in Australia as a valid screening tool for impairment caused by other potentially impairing prescription drugs, which are being prescribed at vastly higher rates than medicinal cannabis Although research assessing sensitivity and specificity to drugs aside from alcohol is limited and interactions with medical condition symptoms may complicate such assessments, sobriety tests have been found to be a moderate predictor of cannabis impairment . As such, we see little justification for not applying this method of detecting impairment to patients prescribed medicinal cannabis in Australia. There are also further policy options that may be considered alongside a medical defence or exemption for THC presence offences, including: requiring a zero blood alcohol limit for medicinal cannabis patients; prohibition from driving during the first weeks of treatment to allow for dose finding and tolerance development; specifying a maximum daily prescribed THC limit, above which the medical exemption would not apply; and simply improving patient education and advice. Due to the nature of THC metabolism and elimination, lack of correlation between oral fluid or blood levels and impairment in high frequency users, and the inability to provide accurate advice to patients regarding THC clearance, the use of oral fluid or blood threshold levels is near unworkable.

Even in Norway, for example, where an upper blood threshold of 9ng/ml has been adopted for the general population, an exemption from this limit is in place when medicinal cannabis has been prescribed by a doctor and is being used as directed . Ongoing improvement in roadside impairment detection, including the potential application of new technologies such as apps and artificial intelligence, is also important for improving enforcement of DUI/DWI offences and relevant for all potentially impairing medications, including medicinal cannabis. The current regulatory approach to medicinal cannabis and driving in most Australian jurisdictions, which criminalises the presence of THC in bodily fluids while driving irrespective of impairment, appears to derive from the historical status of cannabis as a Schedule 9 substance with no recognised medical value. There is little evidence to justify this differential treatment of medicinal cannabis patients, compared with those taking other potentially impairing medications. The relatively low risk profile of medicinal cannabis, dry racks harms associated with the current regulatory approach, and successful implementation of alternative policies in comparable countries suggest that a review of the regulatory framework for prescribed medicinal cannabis and driving in Australia is warranted. More broadly, our analysis suggests that in jurisdictions utilising doctor-supervised, medical-only access models, where medicinal cannabis is captured in broader medicines safety frameworks, patient exemptions from road safety THC ‘zero tolerance’ presence offences, as well as those based on per se limits, should be considered.Cannabis is commonly used for non-medical purposes throughout the world, where it remains illegal in most countries while undergoing legal status changes in selected others. In 2018, the prevalence of past-year cannabis use among 15-64 year-olds was estimated to be 3.8% , or about 200 million people who use cannabis globally .

Regional use is highest in North America, Oceania, and West Africa, with a past-year prevalence of 10-25%, followed by Europe and other regions. Moreover, and important for potential life-course outcomes, cannabis use is most common among adolescents and young adults . In this group, past-year prevalence is 25% or higher in high-use regions, often greater than tobacco use . An extensive body of literature documents the association of cannabis use with an increased risk for a variety of acute and long term health harms . These include: acute intoxication with impaired cognitive, memory and psychomotor skills; increased involvement in motor-vehicle crashes and related injury and deaths; impaired neurocognitive and psychosocial functioning; mental health problems ; cannabis use disorder/dependence; and select respiratory, reproductive, cardiovascular, gastro-intestinal conditions . Some of these associations are stronger than others, and causality is not always firmly established. reflecting the social epidemiology and specific vulnerabilities of this phenomenon, cannabis use-related problems are disproportionately concentrated in young adult males. However, the overall probabilities of cannabis-related harms need to be put into perspective. The vast majority of PWUC do not experience severe problems from their use, even with long-term exposure . The most serious problems arise in a sub-group of high-risk users, where up to half are estimated to develop cannabis use disorder.

For exclusive e-cigarette use frequency, we adopted previously employed criteria: infrequent use defined as 1–5 days; intermediate use defined as 6–29 days; and daily use defined as all 30 days . To assess concurrent use frequency, we assessed the distribution and quartiles of cannabis use, which yielded a six-group variable to classify students as: infrequent exclusive e-cigarette users ; intermediate exclusive e-cigarette users ; daily exclusive ecigarette users ; infrequent concurrent e-cigarette and cannabis users ; intermediate concurrent users ; and frequent concurrent users . We calculated descriptive statistics for all variables of interest. To assess potential differences in current e-cigarette and cannabis use based on covariates, we performed a series of chi-square tests for the categorical covariates  and an independent t test for the continuous covariate . Then, a series of multivariable logistic regression models were fitted to explore the associations between exclusive ecigarette use and concurrent e-cigarette and cannabis use and COVID-19 symptoms, testing, and diagnosis. All models controlled for demographics, university site, fraternity/sorority membership, residence, combustible cigarette smoking, cigar smoking, and smokeless tobacco use. To assess frequency of e-cigarette and cannabis use, we built three similar logistic regression models adjusting for the covariates. We present adjusted odds ratios  and 95%CIs. Missing data were removed prior to analyses, and all analyses were two-tailed with statistical significance set at p < 0.05 and performed using Stata SE version 16 . This study provides evidence college student e-cigarette users who concurrently use cannabis in the past 30-days are at greater likelihood of experiencing COVID-19 symptoms and having a positive COVID-19 diagnosis, compared with exclusive e-cigarette users.

Confirming our hypothesis, frequency of concurrent e-cigarette and cannabis use was associated with increased odds of COVID-19 symptoms and diagnosis, with more pronounced odds observed as frequency of use groups increased, independent of student demographics and current use of combustible cigarettes, cigars, and smokeless tobacco. Thus, there appears to be a dose-related relationship, such that as use increased so too did the risk of experiencing COVID-19 symptoms and receiving a positive diagnosis. Specifically, for COVID-19 symptoms, effect size estimates were 3.5-fold among concurrent e-cigarette and cannabis grow equipment users at any frequency of use, and these estimates ranged from nearly 5-fold to 7.5-fold among infrequent, intermediate, and frequent concurrent users. Similar findings were indicated for COVID-19 diagnosis, with odds of nearly two times for concurrent users at any frequency of use, and approximately a 3-fold increase among both intermediate and frequent concurrent users. There are several potential explanations of why concurrent e-cigarette and cannabis users, especially those with more frequent use patterns, were at higher risk of experiencing COVID-19 symptoms when compared with exclusive e-cigarette users. First, combustible cannabis and tobacco smoke contain similar carcinogenic and other harmful chemical toxins, but cannabis topography results in higher tar and gas per-puff exposures than that of combustible tobacco smoke . This can lead to acute respiratory health symptoms , and potentially airway inflammation and infection especially among heavy or long-term cannabis users . Second, e-liquids of nicotine- and THC-containing vaping products vary in constituents and are a potential source of inhaled toxic metal exposure , and there are over 400 brands that provide diverse products . THC-containing e-liquids may be distinct from nicotine-containing e-liquids and can lead to higher respiratory illness likely due to varying inhaled chemical constituents . For example, it is important to note e-cigarette, or vaping, product use-associated lung injury  was linked to illicit THC-containing vaping products and vitamin E acetate in nearly all  of cases, with median EVALI case patient age of 23 years and the majority being male For these and other reasons, the Centers for Disease Control and Prevention recommends individuals not use THC-containing vaping products due to the potential of tampering with e-liquids .

While law enforcement seized vaping products containing vitamin E acetate intended for the illicit market , the clinical manifestations and symptoms of EVALI and COVID-19 and other respiratory illness overlap . Further research is needed to assess the associations of e-cigarette and cannabis use with COVID-19 outcomes based on use patterns including cannabis inhalation route, and device type and ingredients among vapers. Current smokeless tobacco use increased student e-cigarette users’ odds by nearly 3-fold for reporting COVID-19 symptoms, which aligns with previous research documenting increased risk of respiratory symptoms from smokeless tobacco use . Combustible cigarette smoking and cigar smoking were not significant covariates of COVID-19 symptoms, despite prior research linking dual ecigarette and combustible cigarette use with increased self-reported respiratory symptoms compared to exclusive e-cigarette use . Additionally, no differences were found based on current combustible cigarette, cigar, or smokeless tobacco use and COVID-19 diagnosis. Prior research indicates all forms of tobacco use may increase COVID-19 infection susceptibility via the ACE2 receptor  and the furin enzyme found in oral mucosa , and has been recognized as a risk factor for severe COVID-19 manifestations . Future research using objective measures is warranted to better understand the complex associations between tobacco product type and COVID-19-related outcomes. As posited, no differences were detected between current use groups and COVID-19 testing, likely based on similar random testing policies at each university during the data collection period. Concerning our findings on COVID-19 diagnosis, the active ingredients of THC and nicotine and toxic substances vary among cannabis and e-cigarette products, respectively, and cannabis chemicals are metabolized slower in the body, placing cannabis users at increased risk of COVID-19 infection . Interestingly, this study found those who were male and White had the highest percentages of having a COVID-19 diagnosis. Notably, the literature indicates the highest prevalence of EVALI cases are among those who are male and White .

Although this diagnosis was not assessed in this study, future work should examine the associations of e-cigarette and cannabis use and COVID-19 diagnoses and other specific diagnoses such as EVALI or pneumonia. Other explanations for higher odds of concurrent users having a COVID-19 diagnosis are behavior-related, including tendencies of sharing devices with others and hand-to-lip contact while using these products , 2021, which also increases COVID-19 risk via contact and fomite transmission . About 1-in-2 young adult lifetime e-cigarette users report sharing devices with others , which may explain this study’s finding that fraternity/sorority members had a higher likelihood of reporting a COVID-19 diagnosis. Moreover, e-cigarette use may ultimately increase risk-taking behaviors during young adulthood, including but not limited to concurrent cannabis use . Research indicates dual e-cigarette and combustible cigarette use is associated with poor compliance with COVID-19- related social distancing behaviors . Thus, it is highly likely e-cigarette users who engage in concurrent use of cannabis did not engage in recommended preventive health behaviors . While this study has several strengths, limitations should be noted. First, while students were enrolled at four geographically diverse universities across the U.S., our cross-sectional sample is not nationally representative and therefore our results are not generalizable to all U.S. student e-cigarette users. Longitudinal research is needed to assess causal associations between e-cigarette and cannabis use patterns with COVID-19-related outcomes. In a similar vein, we were unable to objectively measure COVID-19 symptoms, testing, and diagnosis. For example, the survey language specifically asked whether students were currently experiencing any COVID-19 symptoms from the Centers for Disease Control and Prevention’s COVID-19 symptoms list ; but since some of the symptoms were nonspecific to COVID-19, students may have reported a symptom  while not having COVID-19 concerns. Additionally, since our student sample included those who currently used e-cigarettes, we were unable to compare exclusive e-cigarette use versus non-use nor exclusive cannabis use. We assessed self-reported e-cigarette use frequency in number of days and cannabis use frequency in number of times used in the past 30 days and used categorical cut points to minimize the potential for recall bias.

We used standard national survey question language  to collect data on past 30-day cannabis use frequency based on number of times . Thus, we did not collect cannabis use frequency in number of days, and suggest this as a measure to be used in further research. Additionally, we did not collect information on cannabis use route . Future research should consider the use of biomarkers , and THC carboxylic acid the major metabolite of delta-9-tetrahydrocannabinol and patient medical records to cross-validate self-reported responses. Additionally, studies should take into consideration overall preventive health behaviors  and statewide and local policies  that may reduce infectious disease risk. Due to our recruitment methods , we could not calculate response rates, which resulted in varying participation rates that may have biased the sample. All four university campuses remained “open” during data collection. While we did not collect course engagement data ,vertical grow system future research should account for frequency of in-person class participation, which may have increased COVID-19 exposure and susceptibility. We did not have access to information on COVID-19 random testing rates at each university. COVID-19 testing rates may have varied at each campus based on test availability and accessibility on and off campuses . Cannabis is one of the most commonly used drugs worldwide  and young adults report some of the highest past-year rates of cannabis use. For example, data from South America indicates that around 14% of young adults in Argentina and 18% in Uruguay reported past-year cannabis use . In Europe, 19.1% of young adults in Spain and 13.4% in the United Kingdom  consumed cannabis during the last year.Studies from Canada show past 12-month cannabis use prevalence of 44% in young adults aged 16–19, 52% aged 20–24, and 24% aged 25 years or older . While in the U.S., the prevalence was 27% in young adults aged 18–34.Among young adults, college students are a specific high-risk subgroup. For example, annual prevalence of cannabis use is at historic high among U.S. college students  and daily cannabis consumption increased among U.S. university students in 2019 to 5.9% . Furthermore, college students who engage in a high-intensity or high-frequency pattern of use, are at greater risk of experiencing negative consequences , including addiction . Therefore, it is necessary to develop assessment measures to screen for problematic cannabis consumption among college students in order to increase identification and treatment of at risk students .

In a relevant review, among all potential instruments that assess cannabis-related problems, the Cannabis Use Disorders Identification Test  was selected as one of the most appropriate instruments for use in general population surveys because is simple and easy to understand, is brief and available in a public domain, encompasses a broad spectrum of cannabis-related problems and has been validated in general population samples and in samples of adolescents and young adults . The CUDIT was developed by Adamson and Sellman  based on the Alcohol Use Disorders Identification Test  in a cannabis-using alcohol-dependent sample . The questionnaire was later revised and improved  using a higher sample size of clinical patients . The most updated version of the CUDIT-R suggests a one-factor solution composed of 8 items, assessing: consumption , cannabis problems , physical dependence , and psychological features . Scores can range from 0 to 32, with a cut-off score of 13 indicative of a probable DSM-IV diagnosis of CUD Compared with the CUDIT , the CUDIT-R  has shown equivalent internal consistency , improved discriminant validity ; and an improved test–retest reliability index . To our knowledge, only two recent studies have provided validity and reliability evidence of the CUDIT-R scores among college students. Schultz et al. , in a sample of 229 undergraduates from the U.S. who reported past 30-day cannabis consumption, found good internal consistency of the questionnaire  and concurrent validity with cannabis related outcomes. They also found that a cut-off of six was adequate to differentiate between college students with and without problematic cannabis use. Risi, Sokolovsky, White, and Jackson , in a sample of 1,390 undergraduates from the U.S., found a one-factor structure for the CUDIT-R and configural and metric invariance across gender. Despite high rates of cannabis use globally, minimal research has examined the evidence of validity and reliability of the CUDIT-R among college students outside the U.S.

However, although these interventions have been associated with positive CUD outcomes, sustained abstinence is still only achieved in a minority of youth with CUD and treatment response tends to wane at follow-ups . Furthermore, most psychosocial treatment interventions require multiple sessions over several weeks or months and require high motivation and patient stability. Combining brief evidence-based psychosocial treatment options with pharmacotherapy represents a potentially important avenue to reach young cannabis users and improve treatment outcomes, e.g., through a potential increase in short-term recovery, which may help increase motivation into longer-term psychosocial interventions. Despite great effort, there are no approved pharmacotherapies for CUD in youth or adults. A 2019 Cochrane review found that abstinence at the end of treatment was no more likely with active pharmacotherapy with selective serotonin reuptake inhibitor  antidepressants, mixed action antidepressants, anticonvulsants and mood stabilisers, buspirone and N-acetylcysteine compared to placebo . Of note, one RCT among adolescents with CUD  found that eight-week treatment with N-acetylcysteine doubled the odds of abstinence from cannabis during treatment compared to placebo . However, a subsequent larger RCT in adults with CUD  did not find evidence for benefits of 12-week N-acetylcysteine treatment on abstinence from cannabis compared to placebo . Of relevance, abstinence at the end of treatment may not be a developmentally-appropriate intervention goal in cannabis using youth , and recent expert consensus on clinical outcomes for CUD trials recommend that sustained abstinence should not be the primary outcome for all clinical trials of CUD . Thus, taking a harm reduction approach in treatment of CUD may weigh towards future studies on how to best attract youth with a frequent cannabis use/CUD to treatment that does not require abstinence, but targets reduction in use and in adverse consequences related to use.

The growing research and recognition of medical cannabis grow supplies indicate the potential utility of cannabinoid-based-medicines as a strategy in treatment of CUD. Although it may sound initially counterintuitive, cannabinoids are receiving growing global interest as a safe and tolerated option for individuals with CUD. Because the divide between recreational and medical use of a drug may often overlap, the use of cannabis in CUD treatment makes it imperative to address the many questions in order to be able to minimize potential harms of medical cannabis use. Generally speaking, an increasing number of countries have recognized potential medicinal uses of cannabinoid-based products and cannabinoids across Europe , the U. S. , Canada , and Australia , providing greater flexibility for prescribers and facilitating research which has been difficult to conduct due to restrictions laid down on cannabinoid medicinal products . For example, there has been an increase in synthetic cannabinoid formulations such as nabilone  licensed for the treatment of chemotherapy-induced nausea and vomiting, as well as nabiximols  for the treatment of spasticity and multiple sclerosis, and Epidiolex  for the treatment of severe treatment resistant epilepsy in children . So far, all studies on use of cannabinoids in treatment of CUD have been conducted in adults, while studies in youth are lacking. In the next sections, we review evidence from studies examining the effects of cannabinoids on cannabis use pathology among adult non-treatment seekers and patients in treatment and discuss the relevance of these findings for youth. Studies were found by searching PubMed, Embase, and PsycInfo databases with the terms “cannabis use disorder” or “cannabis dependence” or “cannabis treatment” combined with “cannabinoid” or “tetrahydrocannabinol” or “THC” or “cannabidiol” or “CBD” or “fatty acid amide hydrolase inhibitor” or “FAAH inhibitor”; and by checking reference lists of existing studies and reviews up to June 1st 2021. We did not include qualitative studies and case studies. THC is a partial agonist at CB1 and CB2 receptors . Partial agonist action at CB1 receptor is responsible for the psychotropic effects associated with cannabis use as well as potentially therapeutic effects such as pain- and appetite-modulating actions. These clinical effects are mediated through CB1 receptor activation via inhibition of nociception, activation of reward pathways and regulation of mood, memory, and cognition.A number of studies have examined the effect of dronabinol or nabilone  or nabiximols  on CUD symptoms in adults .

In general, THC based medicines are aimed at ameliorating cannabis withdrawal symptoms and craving when patients with CUD cease or reduce their use of illicit cannabis, because such compounds directly substitute the cannabis THC content. This treatment principle is similar to opioid and nicotine replacement therapy and is thought to provide a safer alternative that better facilitates participation in psychosocial and other treatment interventions . By this mechanism, THC based cannabinoid agonist medicines may help decrease the risk of relapse due to withdrawal symptoms . Several laboratory studies have shown that dronabinol can reduce withdrawal symptoms in adult non-treatment seeking daily cannabis users ). In an inpatient setting  , 10 mg of dronabinol 5 times/day decreased withdrawal symptoms and craving and produced no intoxication, compared to placebo. In an outpatient setting  , dronabinol  dose-dependently decreased withdrawal symptoms compared to placebo, with greater reductions following the high dose . However, the high dose produced symptoms of cannabis intoxication and drug effects compared to placebo. Vandrey et al. replicated the ability of dronabinol to dose-dependently decrease withdrawal symptoms in adult, daily cannabis users . There was a significant effect of the high dose on dry mouth, rapid heart rate and flushing, and decrements in a minority of the cognitive performance measures. There is also some evidence that dronabinol combined with an alpha2-adrenergic receptor agonist, lofexidine , produces synergistic effects for decreasing withdrawal symptoms, craving and relapse in adult non-treatment seeking daily cannabis users. A randomized controlled trial with cannabis dependent adults  compared dronabinol with placebo over 12 weeks with concomitant weekly MI. Compared to placebo, dronabinol improved treatment retention and reduced withdrawal symptoms, but not cannabis use and 2-week abstinence. An RCT  with cannabis dependent adults compared a higher dose of concurrent dronabinol and lofexidine with placebo over 11 weeks with concomitant weekly MI, and found no effect of drug treatment on 3-week abstinence, withdrawal symptoms, or treatment retention. A laboratory study of nabilone , which has a higher bioavailability than dronabinol, found that compared to placebo, 6 and 8 mg nabilone/day decreased withdrawal symptoms and relapse behavior in adult non-treatment seeking daily cannabis users . Nabilone did not increase ratings of “liking” or “desire to take again” compared to placebo, but 8 mg/day worsened cognitive task performance. A pilot RCT comparing placebo and nabilone  over 10 weeks in adults with cannabis dependence , found that nabilone was safe and tolerated, but had no effect on cannabis use compared to placebo. So far, findings from studies examining nabiximols’ efficacy on cannabis use pathology in adults are more mixed. A proof of concept study of fixed and self-titrated nabiximols use  in non-treatment seeking cannabis dependent adults , showed that high fixed doses were well tolerated and reduced withdrawal symptoms, but not craving, compared to placebo .

Self-titrated doses were lower and had limited efficacy compared to high fixed doses. A two-site inpatient RCT in treatment-seeking adult patients with CUD receiving 6 days of nabiximols  or placebo with concomitant MI/CBT during a 9-day admission, found that nabiximols reduced withdrawal and improved treatment retention , but did not reduce cannabis use, dependence or cannabis-related problems compared to placebo . Nabiximols was not associated with greater intoxication or adverse events. A pilot, outpatient RCT  in treatment seeking cannabis dependent adults  receiving 12-week treatment with self-titrated nabiximols use or placebo, concurrent with weekly MI and CBT, found that nabiximols was well tolerated with no serious adverse events, but had no effect on withdrawal symptoms, cannabis use and abstinence, compared to placebo. In contrast, a multi-site, outpatient RCT  in cannabis dependent adults receiving 12-week treatment with self-titrated nabiximols use or placebo, concurrent with 6 sessions of CBT, found that nabiximols was well tolerated with few adverse events, had no effect on withdrawal symptoms, craving and cannabis-related problems, but reduced cannabis use during the trial, compared with placebo. The reduction in cannabis use in the nabiximols group, compared to placebo, was maintained 12 weeks after treatment . To summarize, the evidence from placebo-controlled laboratory studies suggests that treatment with dronabinol dose-dependently decrease withdrawal symptoms, with some evidence that higher doses produce cannabis intoxication and drug liking. Evidence from large placebo-controlled RCTs in cannabis dependent adults  combining dronabinol with MI over 11-12 weeks partly supports this: 40 mg/day reduced withdrawal symptoms and improved treatment retention, but not cannabis use and abstinence , but a higher dose, 60 mg/day combined with lofexidine had no effect on neither withdrawal symptoms nor abstinence or treatment retention . Nabilone has been less examined, but the evidence from placebo-controlled studies is similar: a laboratory study suggests that 6 or 8 mg/day reduces withdrawal symptoms , and a small RCT  in cannabis dependent adults found no effect on cannabis use. Evidence from placebo-controlled studies of nabiximols combined with MI and CBT is more mixed: out of the three conducted RCTs in cannabis grow facility dependent adults, self-titrated nabiximols reduced withdrawal symptoms, but had no effect on cannabis use, dependence or cannabis-related problems in one study; had no effect on neither withdrawal symptoms nor cannabis use or abstinence in another study with a higher dose; and had no effect on withdrawal symptoms, craving and cannabis-realted problems, but reduced cannabis use in a large study. Recently, studies have also examined the effect of FAAH inhibitors or CBD in adults with CUD .

FAAH forms a part of the endocannabinoid system by breaking down endocannabinoids such as anandamide. By inhibiting this breakdown process, FAAH inhibitors increase endocannabinoid levels, which may represent a therapeutic mechanism for the treatment of CUD. Preclinical research has shown that FAAH inhibitors can attenuate cannabis withdrawal symptoms in THC-dependent mice . So far, only one RCT has examined the effects of FAAH inhibitor treatment on cannabis use and cannabis pathology in humans . In a double-blind, place-controlled, parallel group phase 2a trial in adults with cannabis dependence , participants received 4 mg daily PF-04457845  or placebo  during 4 weeks. Relative to placebo, treatment with PF-04457845 reduced symptoms of cannabis withdrawal, and self-reported cannabis use at 4 weeks, which was confirmed by lower urinary THC-COOH concentrations. Further, there was no difference between reported adverse events and retention in the two groups. A novel strategy with promising findings is also underway in preclinical and clinical studies of CBD . For example, preclinical studies show that CBD attenuates drug-seeking behavior , and a study found that CBD reversed the reinforcing effects of cannabis in youth , supporting CUD treatment potential. The multiple receptor mechanisms of CBD outlined earlier are believed to form the neurobiological underpinnings of the effects of CBD on the regulation of reinforcing, motivational and withdrawal-related effects as documented in preclinical and clinical studies . It is still not known precisely how CBD interacts with the dopaminergic system to modify the motivational effects of psychoactive drugs, but available data suggest a role for CBD in regulating the activity of the mesolimbic dopaminergic system . This role has been emphasized by the localization of cannabinoid receptors in the mesolimbic circuit orchestrating the synthesis and release of dopamine . Apart from the interaction with the endocannabinoid system through alteration of endocannabinoid signaling, the effect of CBD on drug addiction has been shown to involve modest affinity agonist action at 5-HT1A receptors . So far, two studies have examined the effects of CBD in adult cannabis users . A pragmatic open-label clinical trial evaluated the effect of 10 weeks of 200 mg daily CBD administration on psychological symptoms and cognition in adults with frequent cannabis use , while participants continued cannabis use . Compared with baseline, participants reported fewer depressive and psychotic symptoms, but more state anxiety symptoms after CBD treatment, and demonstrated improvement in attentional switching, verbal learning, and memory. CBD was well tolerated with no reported side effects, in line with a recent meta-analysis of CBD clinical trials reflecting that CBD tends to be very well-tolerated with few serious adverse effects.

BERL, an economic consultancy firm tasked by the New Zealand Ministry of Justice to model the impacts of the CLCB, estimated that the legal cannabis sector facilitated by the CLCB would create 5000 full time jobs, representing wages and salaries of $210 million per year, and contribute $440 million to GDP . One rurally based Māori medicinal cannabis company has been established with these development and employment goals in mind . Conversely, there was strong opposition to the CLCB amongst right leaning voters in New Zealand , again consistent with findings from the U.S . The opposition of National Party voters is understandable given the party’s traditional right-wing conservative base. The opposition of ACT voters is, on the face of it, less easy to understand given ACT describes itself as a “classical liberalism” political party that promotes “individual choice” and “small government”.However, economic conservatives in Western democracies often adopt conservative views on not only economic issues but also social issues to more closely align themselves with their socially conservative allies . We also found an association between considering frequent cannabis use to be a high health risk and not supporting the CLCB. The health risks of cannabis use are also cited in the U.S. as a leading reason to oppose legalisation . It is interesting to note that perceptions of the health risk of frequent cannabis use , as opposed to merely “trying” or “using cannabis weekly or less often”, is the dominant predictor. This suggests there is a somewhat nuanced understanding of the health risks of cannabis, consistent with the findings from New Zealand longitudinal research . Those who had tried illegal drugs other than cannabis in their lifetimes were more likely to oppose the CLCB once we controlled for moral views of cannabis use. Recent use of other drug types has also been found to be associated with opposition to marijuana grow system legalisation amongst young adults in the U.S. . This may represent specific concerns or views about cannabis, as opposed to other drug types.

Lifetime experience of other illegal drug use may include those who have experienced negative experiences from drug use in the past, and this may translate into opposition to drug liberalisation in the present. In the U.S., a lack of support for cannabis legalisation in some counties has been explained by high levels of illegal cannabis cultivation in these areas and the desire to maintain black market income streams . Finally, we found that reading summaries, parts of, or the whole CLCB was a significant predictor of support for the bill. It appears that knowledge of the regulatory controls of the legal cannabis market proposed in the CLCB increased the likelihood respondents would support legalisation. However, the causality of this association can be questioned. One interpretation is people were convinced to support the CLCB once they actually read the Bill’s content. An alternative explanation is that those already positively inclined to support legalisation were more likely to spend time reading the CLCB, and thus the details merely served to reinforce their pre-existing voting intentions.On March 11th, 2020 the World Health Organization  declared the severe acute respiratory syndrome coronavirus  a pandemic , and by March 13th, the United States  president declared it a National Emergency . Within weeks of these declarations, states and localities across the US began to institute stay-at-home orders, closure of non-essential businesses, and many Americans began the transition to remote work . These disruptions have led to rising unemployment , market volatility , housing and food insecurity , and social isolation . As a result, concerns about a ‘second pandemic’, constituting an increase in psychiatric and substance use disorders, began to emerge . Since the early 2000′s, the US has seen a shift in state cannabis policies, which have been found to be associated with increased prevalence of cannabis use and cannabis use disorders among sections of the population , with 29 states operating medical cannabis dispensaries and an additional 8 states operating both recreational and medical dispensaries as of March 2020 . Studies of the effects of cannabis policies on adult use have shown increased cannabis use and use disorders in states with medical cannabis policies . In addition, epidemiological surveys of substance use in the US have shown increases in cannabis use since 2002, with significant increases among certain sociodemographic groups including men, Black people, young adults, low-income groups, and those never-married .

With regards to accessibility of cannabis products, most states with operating dispensaries declared them essential businesses during the COVID- 19 pandemic , along with liquor and tobacco retailers, which should have provided continued access to cannabis products for purchase. However, it is unclear how accessibility to cannabis products was impacted in states with no legal cannabis options. Moreover, other factors beyond cannabis accessibility may have impacted cannabis use behavior during the COVID-19 pandemic  and studies investigating trends in cannabis use over the course of the pandemic are needed. Emerging literature on the effects of the pandemic on mental health and substance use have shown symptoms of depression , anxiety , loneliness , and alcohol consumption  increasing in some segments of the population early on in the pandemic. Elevated mental distress in the population due to COVID-related stressors may increase the use of cannabis as a coping strategy or self-medicating behavior. A cross-sectional study of emerging adults in Canada found that self-isolation and motives to use cannabis for coping with depression were associated with cannabis use during the pandemic . A study of individuals who used cannabis in the Netherlands showed that 41% of respondents reported increased cannabis use since lockdown measures were instituted, with stress and mental health significantly associated with reported increases . However, studies on cannabis use in the US during the COVID-19 pandemic remain sparse and further investigation of long-term outcomes of the pandemic, including potential changes in substance use behaviors, is warranted. As the literature grows in monitoring the effects of the pandemic on mental health and alcohol use in the US, it is also important to examine potential changes in cannabis use. The aims of this study were to  describe changes in days of past-week cannabis use from March 10th through November 11th, 2020 among US adults who reported cannabis use in a nationally representative panel and  characterize differences in trends of use within sociodemographic subgroups and by state cannabis policy status.Participants were sampled from the Understanding America Study , a probability-based, nationally representative Internet panel of adults .

The UAS has recruited participants using Address Based Sampling  since 2014, in which postal records are used to select a simple random sample from a listing of residential addresses across the US. The recruitment involved invitation by mail, with potential participants without prior internet access were provided with tablets and broadband internet connections to facilitate data collection. Once respondents enrolled in the panel, they were surveyed via computer, mobile device, or tablet. Individuals are considered eligible to join the panel if they are aged 18 years or older and are a member of the contacted household . Additional details regarding the UAS methodology can be found at the UAS website . This study used data from 16 waves of the UAS’s COVID-19 Longitudinal Survey, a high-frequency longitudinal data collection with baseline data collection running from March 10 to March 31, 2020. All existing members of the UAS were invited to participate in the survey. Starting on April 1, respondents were invited to participate in bi-weekly surveys according to a staggered schedule, whereby one fourteenth of the sample was invited every day. Every respondent had 14 days to complete the survey; thus, the waves following baseline overlap in calendar time. In the initial survey, respondents were asked for consent to participate in the bi-weekly surveys. Only respondents who consented were asked to complete a subsequent survey on their assigned day. As not all eligible participants had consented by the start of the second wave, the response rate as a percentage of the complete UAS sample was lower in earlier follow-ups. Overall, there were 8547 eligible panel members invited to participate in the March survey. Among those invited, 6932  completed the survey at baseline, March 10 – March 31, 2020. For purposes of our analyses, we included only those participants who reported at least one day of cannabis use across the survey period. The percentage of participants reporting cannabis vertical farming use at each wave ranged from 9.2% in wave 14 to 11.3% in wave 3 . On average, those who reported ever using cannabis included higher proportions of individuals who were younger, identified as being Black or Hispanic/Latinx, were living at or below the Federal Poverty Level, and came from states with both medical and recreational cannabis policies.

Comparisons between adults who reported using cannabis and those who did not report using cannabis during the survey period are displayed in the online supplement Table S2. Surveys with complete data on cannabis use and all sociodemographic characteristics of interest were included in the analytic sample. In total, 1761 unique participants were included; 39.9% completed 16 surveys, 12.6% completed 15 surveys, 7.6% completed 14 surveys, and the remaining 39.9% completed between one and thirteen surveys . Details for participant inclusion and exclusion at each survey are displayed as a flow diagram in online supplement Figure S1.Analyses were conducted in three parts. First, the associations between each of the sociodemographic characteristics and the frequency of cannabis use were examined across the full survey period. Second, a single model with the splines for days since March 10 as covariates examined trends in cannabis use across time. Third, a sequence of models with interactions between the splines for days since March 10 and each of the identified sociodemographic characteristics determined whether trends in cannabis use over time differed between subgroups. We used mixed-effects linear regression models with a random intercept for participants to accommodate repeated measures. The general specification for these models is provided in the online supplement. Joint Wald tests were used to determine if interactions were significant. The margins and the xbrcspline commands in Stata were used to generate linear predictions of cannabis use and to estimate differences in the frequency of cannabis use on given survey dates compared to March 11, respectively, in the overall analytic sample and stratified by each sociodemographic subgroup . March 11 was used as the reference date rather than March 10 due to a higher number of observations on that survey date . We conducted additional sensitivity analyses using the entire UAS sample, including participants who reported no cannabis use over the entire study period. All analyses incorporated survey weights that accounted for probabilities of sample selection and survey non-response at baseline and are aligned with Current Population Survey benchmarks. Statistical significance was assessed at the p<.05 level. Analyses were conducted using Stata version 16  and R .To our knowledge, this is the first study to examine trends of cannabis use during the COVID-19 pandemic in a general population sample of U.S. adults.

The prevalence of cannabis use in this study population ranged between 9.2 and 11.3% at each wave. This is slightly lower compared to national estimates of past month cannabis use of 11.9% in 2019 among US adults 18 or older . Our analyses show that, within the overall sample of adults who reported any cannabis use during the study period, there were statistically significant increases in the number of past-week cannabis use days at the start of the pandemic  compared to baseline ; thereafter, these increases returned to levels comparable to March for the remainder of the study period . When comparing cannabis use at the first of each month to the start of the study, several of the identified sociodemographic groups also demonstrated increased cannabis use in April, May, and June, including: women, non-Hispanic White people; individuals living with only their partner; those reporting a household income not at the FPL; and those living in states with medical cannabis but not recreational only policies.

Therefore, it is important to document ethnomedicinal knowledge of plants before it vanishes completelyIt was found that the inhabitants of the study area used different plant species for the treatment of a wide range of diseases. The most reported diseases from this study area, include coughs, colds, skin infections, stomach disorders, oral diseases, and diarrhea. Data about traditional medicinal uses of plants were collected from 88 informants, including 57 males and 31 females. The local communities residing in the study area were highly dependent on forest produce to fulfil their daily requirements of fuel, food, fodder, shelter, and medicines. After noting the demographic data and literacy rate of the inhabitants, it was found that aged people possessed an immense knowledge of ethnomedicinal plants compared to the younger generation. The rural people of the study area used 110 plant species from 102 genera belonging to 57 families for ethnomedicinal purposes. In this study, it was found that Rosaceae, Asteraceae, and Lamiaceae were the most reported families. The Rosaceae and Asteraceae families had 12 plant species each, followed by the Lamiaceae family with 6 plant species. The Apiaceae, Pinaceae, Brassicaceae, and Solanaceae families each contributed 3 plant species, while the Fabaceae, Ranunculaceae and Polygonaceae families each contributed 4 plant species. The Amaranthaceae, Berberidaceae, Oxalidaceae, Poaceae, Primulaceae, Pteridaceae, Plantaginaceae, Scrophulariaceae and Utricaceae contributed 2 species .Plants remain necessary for people’s well-being, as they provide a significant number of traditional and modern treatments or techniques used in healthcare. Today, the knowledge of wild plants can play an important role worldwide, not only because of their therapeutic properties, but also because they can represent a source of innovative products in many sectors, such as defense of plants from pest disease, bio-preservatives, nutraceuticals, functional foods, cosmetics,trim trays and agrochemical industries . The wild plants are used by the inhabitants of the state for the treatment of diseases related to human beings .

These include ease of access, therapeutic efficacy, and a low cost of health services . Medicinal plants are the primary source of traditional medicine for people living in backward or remote areas of developing countries . Traditional healers have been found to play an essential part in rural people’s primary health care system, as healthcare in these regions treat those with limited affordability and access to modern medication. Plants have always been important to indigenous communities as they provide food, shelter, and fodder. Plants contain a variety of pharmacologically active chemical compounds which are the reason for their medicinal potential .The bioactive substances such as flavonoids, lignin, coumarins, alkaloids, sterols, glycosides, and terpenoids, present in these ethnomedicinal plant species, might contribute to their therapeutic activities . For example, alkaloids, glycosides, rumicin, nepalin, nepodin, and rumicin in R. hastatus, flavonoids, phenolic acids, protocatechuic acid, fatty acids, and carbohydrates in S. nigrum . Taraxacin, taraxacerine, cerylalcohol, lactuce-roltaraxacin, choline, inulin, tannin, etereal oil, vitamin C, xanthophylls, potassium and vitamin A in T. officinale . Alkaloids, amino acids, carbohydrates, protein polymer, carotenoids, and saponins in U. dioica , Curculigenin in C. orchioides . All of these compounds are responsible for their bioactivity, such as antibacterial, antidiabetic, wound healing, hepatoprotective, and anti-inflammatory properties . The essential oil extracted from the aerial part of A. vestita is very well-known for its anti-inflammatory properties . The cannabinoids in C. sativa have anti-inflammatory properties , and the compounds extracted from the parts of C. bursa-pastoris confirm its anti-inflammatory properties . The phytochemical study of C. dactylon revealed details of its constituents like flavonoids, glycosides, alkaloids, tannins, flavonoids etc. are responsible for its dermatological action . Similarly, the anti-diabetic activities of A. parviflorahave been confirmed by various researchers . Several studies have revealed that today’s youth are uninterested in the traditional medical system . They have little or no knowledge of plants, not even about the species of plants found in their surroundings.

Only a few old people are left to pass on their knowledge to the next generation, but it has not been very effective . The knowledge of medicinal plants of the Himalayan region has been reduced due to the absence of proper documentation and knowledge in the present-day generation . Therefore, it is important to preserve ethnomedicinal knowledge by documenting literature and by proper interaction with the younger generation. Cannabis policy is a topic of constant discussion and changes worldwide. This is because, notwithstanding the coordinated efforts to disrupt cannabis market, both supply and consumption indicators have constantly increased over the past decades . It is estimated that in Europe around 15% of young adults used cannabis in 2019, and the prevalence reaches 19% when only 15- to 24-year-olds are considered . Since 2013, Uruguay, 10 jurisdictions in the United States and Canada have passed laws that license the production and retail sale of cannabis to adults for non-medical purposes, often referred to as recreational use. In parallel, a renewed debate about reforms to the national cannabis policies has developed in Europe . In fact, although there is some European Union regulation concerning cannabis trafficking offences, legislative responses to unauthorised cannabis use and minor possession are still primarily responsibility of individual member states and therefore little harmonised . As an example, cannabis policies range from the more liberal example of the Netherlands, with a system of limited distribution, to countries like Hungary, where personal possession of cannabis is punishable with imprisonment. Furthermore, some countries legally treat cannabis like other drugs, whilst in others penalties for cannabis are lower, typically because the level of harm that the use of the drug may cause is taken into consideration . As an outcome, over the past years several European countries have implemented policy reforms modifying the size of the penalties for cannabis possession for personal use: despite a general trend to reduce punishments, few countries moved in the opposite direction. Some countries have reduced penalties for low-level offences, have removed criminal sanctions for possession or use, or have introduced formal or informal procedures that decrease the likelihood of sanctions being applied . Others have increased penalties for personal possession, either treating them as criminal or administrative offences . This results in a variety of policy approaches running in parallel in Europe, which range from administrative to criminal offences for personal cannabis possession , with the notable exception of the Dutch system.

The potential effect of policy reforms to the treatment of cannabis possession for recreational use on rates of cannabis use is a topic of considerable debate . However, empirical research on the effects of the different types of control policies is still limited . Gathering scientific evidence firstly on whether and which type of cannabis policy reforms are able to affect the availability of the substance and the prevalence of use, and secondly by which type of users and by how much seems crucial in order to understand their public health impacts . In particular, while cannabis policy changes are currently limited to adults, increasing attention is being devoted to the effects that these might have on adolescents . This is because cannabis is by far the most popular illicit substance among youth, particularly in Europe, where adolescents report high rates of easy access to the substance and show higher prevalence of cannabis use compared to the adult population . Furthermore, research shows that initiation into cannabis use typically occurs during the mid to late teens and that there is a strong positive relationship between early first use and the length and intensity of cannabis consumption during adulthood , with a range of possible associated poorer outcomes later in life . In general, policies ruling cannabis related offences are primarily targeted at adults and some authors suggest that they do not affect adolescent consumption . Despite this, several authors suggest that policy changes might indirectly affect adolescents by modifying their access to cannabis and by contributing to shape the social norms of a society . Most of the existing studies on cannabis use associated with cannabis control policy reforms has been conducted in the United States, Australia and Canada, and mainly focused on the adult population. The most recent studies analysing the possible effects of drug policies on youth participation have investigated two specific types of policy changes, i.e., legalisation of cannabis for recreational purposes and legalisation of medical cannabis . Findings are mixed, and overall they suggest that the passage of the laws did not relevantly affect youth. In Europe, due to the scarcity of comparable data, very little work has been performed, and mainly focused on a single-country perspective . To the best of our knowledge, only one study examined the associations between country-level cannabis control policies and cannabis use in the adolescent population including many European countries . Although results suggested that liberalisation policies in general were associated with higher odds of some measures of adolescent cannabis use, a later study conducted on the same data did not confirm this result .

Despite the scarcity of previous studies, Europe constitutes an interesting case for conducting this type of research, particularly because the cannabis law reforms passed over the last 20 years in many countries generated significant variations in the intensity and trajectory of policy changes , vertical grow system which offer and optimal ground for research . Although data to assess the implementation and evolution of policies “on the ground” are limited, recent studies have highlighted the importance of paying attention to variability in specific policy provisions when trying to evaluate their effects, instead of using simple categorisations, for example binary variables to classify legalisation and non-legalisation . Although challenging, the European case offers an optimal setting for this exercise.In this study, we examine the association between changes in cannabis control policies and changes in adolescent perceived availability and self-reported use of cannabis in 20 European countries over a period of more than 15 years . specifically, we reviewed existing literature to characterize the types of cannabis control policy changes in each country, and applied a Differences-in-Differences model to a novel database of the European school Survey on Alcohol and other Drugs . The DiD is a popular statistical technique that attempts to mimic an experimental research design using observational study data. It allows to find the effects of an intervention on specific outcomes, by comparing the differences in outcomes after and before the intervention between treated and untreated groups of units. In our context, DiD is applied to statistically assess the association between types of cannabis policy changes and cannabis perceived availability and use among adolescents . The main contribution of this paper is to address the scarcity of an European perspective in the study of the links between cannabis policy reforms and cannabis-related outcomes among adolescent. We aim to do so by going beyond a simple categorisation of policy changes and try to capture their variability. Also, to better investigate their links with adolescent perceived availability and use, we take into account different patterns of cannabis use. In fact, as for adults, also when focusing on teenagers, it is important to acknowledge that cannabis market is segmented into a number of different types of consumers and that they might react to the same policy in different ways .Data from the European school Survey Project on Alcohol and other Drugs were used in this study. ESPAD is a repeated cross-sectional multinational survey conducted every four years since 1995, designed to provide nationally representative and comparable data on substance use and other risk behaviours among 16 years-old students in Europe . In this survey, a cluster sampling design is used to sample the students who turn 16 years of age in the given survey year. In the majority of countries, class is the last unit in a multistage stratified sampling procedure.

Participating countries adhere to common research guidelines to guarantee consistency in sampling, questionnaires, and survey implementation, and conform to the respective national ethics and data protection regulations. A standardised anonymous questionnaire is voluntarily completed in the classroom setting with paper-and-pencil or computer-assisted format. Sampling frame coverage, school, class and student participation rates were generally high in the considered period. Detailed information about survey representativeness, data collection methodology, and country participation rates in each survey year are reported in the dedicated reports . For the present analysis, starting from the individual level data about 306,693 students from 20 countries collected in five ESPAD data collection waves , annual prevalences were calculated for each country for the set of variables referring to cannabis use and perceived availability, obtaining a balanced panel covering 20 countries in the interval 1999–2015 .

Responses on hypothetical purchase tasks have been shown to be an accurate reflection of demand for the real substance , as well as a key determinant of patterns of use and misuse . For cannabis specifically, higher Amplitude is associated with increased cannabis use quantity and frequency, increased craving, and more symptoms of cannabis dependence.Increased demand for cannabis has also been linked to hazardous behaviors, such as driving after using cannabis . Efforts have been made to identify and better understand the etiological and maintaining factors of substance use disorders.However, currently there is little research on which mechanisms explain the relationship of greater demand for cannabis with its use and associated problems One potentially relevant factor that may account for the relationship between cannabis demand and outcomes is specific motives for use. Previous research has indicated that for other substances like alcohol, substance demand and specific motives for use are both implicated in consumption and related problems . Those with elevated demand may be more likely to use cannabis for specific reasons or under particular circumstances. Understanding the specific motives for substance use can shed light on when and how much someone is likely to use as well as the potential consequences of their use . Motives for cannabis use generally vary along two dimensions: valence  and source of reinforcement . The internal motives of coping and mood enhancement appear to be especially related to negative outcomes, showing associations with worse mental health functioning, greater quantities of cannabis use, and more cannabis-related problems . Research with alcohol demand has indicated that the demand indices of intensity  and Omax  are positively related with alcohol use and problems, and this relationship is mediated by elevated motives of enhancement and coping . Additionally, a study among veterans demonstrated that those with a high valuation of alcohol were more likely to use alcohol for coping and enhancement motives, grow tent indoor which in turn predicted more alcohol-related consequences .

Enhancement and coping motives for use are relevant to the COVID-19 pandemic, as individuals with higher levels of demand may be at higher risk of escalating substance use to alleviate the elevated levels of boredom or negative affect. Previous meta-analytic research has demonstrated this contextual link, with alcohol demand indices showing significant increases following stress- or negative affectinducing paradigms . The extant literature suggests that motivations to use play a mediational role between elevated substance demand and problems, but comparable mechanistic research has yet to be done on the effects of cannabis demand on cannabis use patterns. This is an especially important area to explore as we see increased levels of cannabis use as the COVID-19 pandemic continues. The current study is the first to our knowledge to investigate internal cannabis use motives as a potential mediating factor between cannabis demand pre-declaration of COVID-19 emergency measures and cannabis use patterns and problems after the implementation of COVID-19 emergency measures in Canada. To do this, we used a crowdsourcing platform  to examine how pre-existing levels of cannabis demand related to changes in cannabis use and problems during the first 30 days of the COVID-19 state of emergency. Then, we examined the mediating role of internal motives . We hypothesized that higher levels of cannabis demand pre-COVID-19 may lead to greater coping or enhancement motives to use cannabis during the COVID-19 pandemic and associated emergency measures. Further, we hypothesized that this mechanism may lead to increased cannabis use and/or problems after the enactment of COVID-19 emergency measures. Participants for the study were recruited through Prolific. Prolific is an online recruiting platform where individuals are able to access and complete a host of surveys and studies run by researchers.

Prolific ensures the application of proper recruitment standards and informing participants on their role in research . Data were drawn from a larger study of alcohol use during the COVID-19 pandemic among Canadian adults . Four attention check items, as recommended by Prolific’s guidelines, were implemented in this study to ensure data quality  . Participants’ data were automatically excluded from the study if they failed 2 or more attention checks and completed all questions in an unrealistically short time . Of the 400 remaining participants, we selected a subsample that endorsed having used any type of cannabis in the past three months  for the present analyses. Participants’ data were further excluded for missing  or non-systematic  data on the Marijuana Purchase Task . The final sample was comprised of 137 participants. Data collection was completed from April 30, 2020 to May 4, 2020, approximately 7–8 weeks after the COVID-19 pandemic was declared. A majority of the measures required participants to respond to items by referencing either a month prior to the COVID-19 state of emergency in their area or in reference to the past month . This study was approved by York University’s Office of Research Ethics. All participants were given $13 CAD as compensation.The present study is among the first to investigate mediational pathways to cannabis use and problems during the COVID-19 pandemic. We aimed to understand the role of indices of cannabis demand on motives for use and patterns of cannabis use and misuse. Previous research has indicated that individual differences in substance demand is a pre-existing factor that may place an individual at vulnerability for increased substance use and problems . In line with previous alcohol demand research, we hypothesized that internal motives for cannabis use, specifically coping and enhancement, may mediate this relationship. Our results indicate that two indices of demand, Persistence and Amplitude, were related to increased cannabis problems via the use motive of coping during the COVID-19 pandemic. This model did not support the role of enhancement motives. This finding indicates that those with increased cannabis demand who tend to use cannabis to cope are at increased risk of experiencing negative cannabis-related consequences.

This is largely in line with previous research implicating increased cannabis demand in increased cannabis craving, use quantity and frequency, and dependence symptoms . Of particular note is the finding that the demand facet of Persistence was implicated in this model. Previous research  has indicated that Amplitude was more associated with increased cannabis use and cannabis-related problems. This difference in finding may be attributable to differences in sample characteristics. The participants in Aston et al.  recruited pre-pandemic from Rhode Island, a U.S. state in which recreational cannabis use is illegal. In contrast, participants in the current study were from across Canada during the COVID-19 pandemic, a country in which recreational cannabis use has been legal for over two years. Elevated cannabis demand appears to be a vulnerability factor for experiencing cannabis-related problems, and as such early identification and prevention efforts should be targeted at these individuals. This is especially relevant as the COVID-19 pandemic continues, with its associated unprecedented levels of stress and anxiety, both about the virus itself as well as caused by the associated lockdowns and emergency measures, . Cannabis use has been wellestablished as a method to cope with stress for some, and this method may be especially salient to those individuals who perceive cannabis tohave a higher reinforcement value . Using cannabis to cope is especially relevant in the context of a largescale external stressor like the COVID-19 pandemic. Other research has shown that COVID-19-related worry is associated with using cannabis to cope . Those that use cannabis to deal with stressors may be more likely to experience heavier cannabis use and more cannabisrelated problems . Specifically focusing cannabis interventions on skills for coping with general and traumatic stress might be an important target to improve treatment outcomes . In extreme situations like the COVID-19 pandemic and associated lockdowns in which access to formal interventions might be limited, encouraging stress-reducing activities like exercise and yoga may be beneficial . Broadly, grow tent hydroponic encouraging the use of more adaptive coping strategies rather than cannabis use is a clear implication of the current research. The findings of this study must be considered in light of certain limitations. The most significant limitation is the use of cross-sectional data to test a mediational model, and therefore being unable to determine the temporal precedence of variables.

Despite this limitation, participants reported their pre-pandemic cannabis use so that we were able to control for retrospective use. The current research is also limited to the initial period of the pandemic. Since restrictions have been variously lifted and re-implemented in response to COVID-19 case counts, it is important to examine longer term effects of the pandemic on cannabis used and the role of demand using a longitudinal model. Furthermore, the sample size for the current study is modest for testing the hypothesized path model. However, our large R2 effect sizes suggest that we captured strong predictors of cannabis motives and problems during COVID-19 in our study. Next, since the MPT is a measure of hypothetical consumption of cannabis, actual cannabis consumption is not measured by this task. However, previous research has provided evidence for the validity of hypothetical purchase tasks for other substances . Future research is needed to support the validity of the MPT. Moreover, the MPT instructional set refers to smoking “hits” of cannabis, which may impact its use among those whose primary form of cannabis use is vaping or consuming edibles. Though the majority of the sample in the current study indicated that dried cannabis was their primary form of use, this presents a clear limitation to the ecological validity of the MPT. Recent qualitative research on the MPT has recommended against the use of the term “hits” in favor of “grams” and that the specific mode of cannabis administration be incorporated into future iterations of the MPT . A further potential limitation is that the study measures were administered online rather than in a laboratory context. This presents several drawbacks when administering the MPT, namely that the research team was not able to emphasize important parts of the instructions or answer questions; it is possible that participants’ performance was impacted in a negative way by these factors . Also, because our sample was drawn from a larger sample of Canadian drinkers it is possible that cannabis use motives in our sample may have differed systematically from those of cannabis-only users. Co-use of cannabis and alcohol is associated with elevated alcohol demand , so it is possible that co-use may also systematically impact both cannabis demand and motives for use. Finally, we acknowledge that our sample had a rather high level of income . While household income was unrelated to cannabis use variables in this study, our findings may not generalize to samples with lower income. In conclusion, this study replicates a modest body of previous research linking cannabis demand to cannabis-related problems and provides evidence for the role of coping motives in the increased cannabis-related problems experienced by those with elevated cannabis demand.

Further research is needed to replicate this research within a sample of cannabis-only users and in a real-world, offline setting. This research will inform best practices for targeted problematic cannabis use interventions. C. sativa is the subject of one of the most common drug law offenses in Europe. Since 2014, cannabis accounted for almost 60% of an overall estimate of 1.6 million offenses including possession and trafficking. Cannabis can be classified into legal fiber type  and illegal drug type . Marijuana differs from hemp based on the high level of Δ9-tetrahydrocannabinol . In Italy, the possession of limited amounts of marijuana, i.e., containing 500 mg of Δ9-THC, is considered only a civil offense. On the contrary, trafficking and selling cannabis is prohibited and punished by law. On the other hand, support and promotion of hemp crops is allowed for textiles, food, cosmetic production and bioengineering industry. The Scientific Working Group for the Analysis of Seized Drugs  recommended a series of analyses to confirm the presence of cannabis. Nevertheless, none of these analytical tests are able to individualize cannabis plants or crop type. During 1990′s, different C. sativa DNA methods were developed to individualize and to determine the origin of plants for forensic purposes. Thus, various molecular techniques have been applied including, random amplified polymorphic DNA , amplified fragment length polymorphism  and short tandem repeats.