Hemp Growing

Most respondents had either a university degree or a trade/vocational certificate  and were engaged in either full time or part time employment . The most frequently reported primary condition being treated with cannabis was pain , followed by mental health conditions  and sleep-related conditions . Inhalation  was the most common route of administration . Only a small number of respondents  accessed legal medical cannabis with a prescription, with most respondents sourcing their medical cannabis from an illicit dealer , from friends or family  or by growing their own . With regard to the type of cannabis  mainly used, 21.5% reported THC-dominant or THC only, 18% reported approximately equal amounts of THC and CBD, 12.5% reported CBD-dominant or CBD only, and 48% indicated that it varied between batches or that they did not know. The mean  duration of time until respondents felt no effect after using medical cannabis was 219  min , 253  min , 294  min  and 210  min . Fig. 1 shows responses to several statements regarding driving related behaviours. Most respondents  agreed or strongly agreed that they felt confident in their capacity to accurately assess their driving ability after consuming medical cannabis. A similar percentage  agreed or strongly agreed that their medical cannabis use does not impair their driving. A majority  felt they tended to drive more carefully following use of medical cannabis and most denied that cannabis affected reaction time, focus, speeding, drifting out of lane or risk taking. Just under half  agreed or strongly agreed that they tended to leave a larger gap between them and the car ahead after using medical cannabis. There was less certainty from respondents around whether they felt more in control of their vehicle . Fig. 2a shows the duration of time that respondents typically wait before driving after using medical cannabis relative to primary route of administration. Overall, more than a third of respondents  reported driving within 3 hours of using medical cannabis; 11.9% waited 4-6 hours and 25.9% waited 7-12 hours, while 27.5% waited at least 12 hours. Fig. 2b shows the length of time until respondents feel no effects after using medical cannabis. Most said 1-3 hours ; 27.8% said 4-6 hours while 8.8% said 4-6 hours and 0.9% said 13-24 hours.

Patients using oral products tended to report a longer duration of action when compared with smoked or vaporized cannabis. From the above, most respondents  were estimated to be unlikely to drive while under the influence of cannabis; this proportion was slightly higher for inhaled routes of administration  than for oral routes . This proportion was also higher for THC-dominant products  and THC/CBD-equivalent products  than for CBD-dominant products . Only a minority of respondents had been subjected to roadside drug testing , with very few respondents having ever been convicted of DUIC . Most respondents  indicated that the presence of roadside drug testing deterred them from driving after using medical cannabis. Table 2 shows the results of two binary logistic regression models that assessed the relationship between respondent characteristics and DUIC behaviours. In the first model, there was a strong association between frequency of cannabis use  and respondents’ belief in whether medical cannabis impairs their driving. Specifically,trimming tray respondents were 3.1% more likely to think that their cannabis use does not impair their driving for each additional day of cannabis use . Respondents’ confidence in their capacity to assess their own driving ability after using medical cannabis was strongly related to their belief in whether medical cannabis impairs their driving, with those who were confident  being far more likely than those who were not confident  to report that their medical cannabis use does not impair their driving . Respondents who were not deterred by the presence of roadside drug testing were also more likely to think that cannabis does not impair their driving  In the second model, estimated likelihood of DUIC was strongly associated with employment status, with those who unemployed being significantly more likely to engage in DUIC relative to those who were engaged in full time or part time work . Frequency of use was also related to likelihood of meeting criteria for DUIC, with a 2.7% increase in odds for each additional day of cannabis use . There was a marginal decrease in DUIC likelihood for each percentage increase in proportion of total cannabis use that was medical . Respondents who were confident they could accurately assess their driving ability were far more likely to engage in DUIC  than those who were not confident. Respondents who were not deterred by the presence of roadside drug testing were almost 3 times as likely to engage in DUIC relative to those who were deterred .The present study was designed to assess driving-related behaviours and attitudes among a convenience sample of Australian medical cannabis users recruited as part of our larger CAMS-18 survey. The term ‘medical cannabis’ was used to refer to any use of a cannabinoid product to treat or alleviate symptoms arising from a self-reported medical condition. These were in some ways an unusual medical cannabis patient group by international standards: the relatively slow roll out of official legal medical cannabis in Australia meant that the vast majority of respondents were still self-medicating with illegal products using inhaled routes of administration.

This user profile is likely to change as the official access scheme, which is dominated by orally delivered THC and CBD containing products, converts more patients from illegal to legal access. A key finding of the current study is that a substantial proportion of medical cannabis users are driving shortly after using cannabis, with some driving during the time of peak effects when impairment tends to be greatest. More than 19.0% of users reporting driving within one hour of consuming cannabis and 34.6% of all users within 3 hours of use . By comparison, 56.4% of medical cannabis users in Michigan with chronic pain drove within 2 hours of consuming cannabis. In other surveys, 9.3% of older drivers in Colorado reported driving within one hour of cannabis use, and 13.2% of Canadian non-medical cannabis users reported driving within two hours of use. While it is important to note that most respondents in the present survey reported waiting at least 7 hours before driving, with 25.9% waiting 7-12 hours, and 27.5% waiting at least 12 hours, the relatively high incidence of driving shortly after using cannabis is concerning. This suggests a need for public information campaigns that educate medical cannabis users around the risks associated with DUIC. Existing public health guidelines, such as Canada’s Lower Risk Cannabis Use Guidelines , recommend that medical cannabis patients wait at least 6 hours before driving after using cannabis. However, as other jurisdictions consider establishing similar guidelines, it is important to consider that the duration and magnitude of cannabis effects may vary with factors such as gender, body mass and consumption of alcohol and may in some cases exceed 6 hours. For example, alcohol and cannabis produce additive effects that may exacerbate and prolong driving impairment. Conversely, the magnitude and duration of cannabis effects may be decreased with increased frequency of cannabis use, most likely due to tolerance, and with use of CBD-dominant or low THC products. Further research is needed to elucidate the extent to which these factors impact the driving impairment produced by cannabis and to guide public policy in this area. It is somewhat surprising that more than 1 in 3 respondents drove within 3 hours of cannabis use given that Australia is one of the few jurisdictions in the world to have extensive, random roadside drug testing for THC in oral fluid. In our recent study, most participants tested positive for oral fluid THC at 10 min after vaporization of cannabis containing predominantly THC or equivalent amounts of THC and CBD, with some testing positive at 3 hours . Despite the relatively high prevalence of driving shortly after cannabis use, a large proportion of respondents  did say that the presence of roadside drug testing deterred them from driving after using medical cannabis. Only a small minority of the overall cohort  had been subjected to such testing at the time of the survey, however, with an even smaller proportion  indicating they had ever been convicted of DUIC. It is interesting to note that those who were not deterred from driving after using cannabis by the presence of roadside drug testing were more likely to think that cannabis does not impair their driving and more likely to engage in DUIC. The finding that 71.9% of respondents felt that their medical cannabis use does not impair their driving is consistent with previous reports showing that cannabis users tend to perceive DUIC as relatively low risk, especially when compared with alcohol . This may support the idea that cannabis users tend to show a comparative optimism bias toward thinking that that their own driving is less impaired and their accident risk lower after using cannabis relative to other cannabis users .

Indeed, in a random survey of weekend night-time drivers in California, only 1 out of 21 drivers who reported using cannabis in the past 2 hours and tested positive for THC agreed that they had taken a drug that impaired their driving. Most respondents in the current study reported that they drive more carefully and take fewer risks after consuming cannabis. Respondents did not agree that cannabis impaired their focus, reaction time or ability to stick to the speed limit. While experimental studies with non-medical cannabis users often find that respondents drive more slowly and leave a larger gap to the vehicle ahead after consuming cannabis, less than half of respondents in the present study said they tended to leave larger gap between them and the car ahead. Similarly, while studies with healthy volunteers show that cannabis can impair lateral control and increase lane weaving, particularly in the first hour and up to 3.5 hours after vaporising or smoking cannabis, most respondents denied drifting out of their lane more frequently after using medical cannabis. It is unclear whether these disparities reflect a high degree of tolerance among respondents in the present study or a lack of awareness of actual driving impairment. Logistic regression showed that respondents who were confident they could assess their driving ability after using medical cannabis were far more likely to deny impairment and to engage in DUIC relative to those who were not confident, irrespective of age or gender. Some evidence shows a poor relation between perceived and actual driving ability in both older and younger drivers and in occasional cannabis users, implying that over-confidence in driving ability after using cannabis grow racks is likely to be a risk factor for DUIC behaviours. Employment status was also strongly related to estimated likelihood of DUIC, with respondents who were unemployed being more than four times as likely to engage in DUIC relative to those who were employed.

While this may reflect greater daytime use of cannabis in this population which in turn may be due to the severity of the underlying condition for which medical cannabis is being used, it is important to note that only a small proportion of respondents  were unemployed. This possible explanation should therefore be treated with caution. Frequency of cannabis use was also strongly related to likelihood of DUIC; while the increase in odds was relatively small, a recent study likewise found that frequency of cannabis use was positively associated with the incidence of DUIC, as was the level of intoxication that respondents deemed safe for driving. This is perhaps unsurprising, as those individuals who are using cannabis more frequently  will be inherently more likely to drive when having recently using cannabis. Despite the growing use of cannabis for medical purposes, there have been no studies to date that have investigated the acute and/or chronic effects of medical cannabis use on driving. In a recent review, Celius et al. found that most patients with multiple sclerosis-related spasticity who were being treated with nabiximols actually showed an improvement in driving ability, most likely due to a reduction in spasticity and/or improved cognitive function. This finding lends support to the idea that treating medical conditions that might otherwise impair driving  with medical cannabis could conceivably have a positive, or at least neutral, effect on driving performance.

Given the similar chemical composition to tobacco smoke, the negative health effects of marijuana smoke exposure may be similar. Pediatricians are encouraged to ask about and counsel parents about tobacco use, with one goal of decreasing secondhand smoke exposure in children. In our cohort, 11% of caregivers admitted to regularly smoking or vaping marijuana, yet only a small percentage of marijuana-using caregivers  had been asked by their child’s pediatrician about marijuana use. The results of this study suggests health care providers are not starting the conversation or engaging caregivers about marijuana smoking, and the consequent secondhand smoke exposure for children. A potential limitation of the study is the under-reporting of substance use given the nature of a survey study. Many of our respondents  did not indicate any substance use, while this number may actually be lower. However, even if tobacco or marijuana-using caregivers did not accurately indicate their use, the overall impact on the results is likely very low. Another potential limitation is the single geographic location from which the study population was derived. The results may not beindicative of marijuana users and/or pediatricians across the country. Given the study population residing in a state with legalized marijuana use, it is reasonable to assume the pediatricians in this state are more likely than others to be familiar with marijuana use among parents and more comfortable with asking about marijuana.We did not measure biochemical validation in the children, which would have provided a precise measure of tobacco smoke exposure or marijuana smoke exposure. Prior studies have evaluated tobacco exposure in children by proxy of parental report, and we used a similar method. In the state where we conducted the survey, recreational use of marijuana is legal, yet it remains illegal to use marijuana on public property, raising the likelihood of caregivers using marijuana on their private property.

The survey did not ask the participants to clarify the exact location of use. Medical marijuana  has attracted a great deal of attention as an adjunct to conventional pharmacologic approaches to symptom management for patients with cancer. Gynecologic cancer patients commonly experience nausea, vomiting, pain, anorexia, and fatigue related to cancer-directed therapy or to their cancer itself, that may be treated with MM or synthetic cannabinoids. A meta-analysis by Whiting et al found a trend towards benefit for cannabinoids compared to either placebo or anti-emetics for nausea and vomiting due to chemotherapy, but no statistically significant improvement across studies . In the United States, both dronabinol and nabilone are FDA-approved for the treatment of chemotherapy-induced nausea/vomiting that has not responded to conventional antiemetics. Several small randomized trials have compared dronabinol or nabilone in combination with or versus standard anti-emetics in preventing chemotherapy-induced nausea/vomiting . Dronabinol was found to be equivalent to ondansetron with no benefit for combined therapy . The National Comprehensive Cancer Network includes dronabinol and nabilone as therapeutic options for breakthrough nausea/vomiting . The American Society of Clinical Oncology considers the evidence insufficient to recommend cannabis grow equipment for prevention of nausea/ vomiting or as an alternative to dronabinol and nabilone for chemotherapy-induced nausea/vomiting . There is limited evidence regarding the effectiveness of MM or synthetic cannabinoids for pain management compared to multimodality symptom management with conventional medications. In cancer patients with inadequately controlled pain on opioids, the addition of THC: CBD containing compounds and nabiximols improves pain scores compared to placebo in some, but not all studies . In preclinical and pilot studies investigating the modulation of the cannabinoid pathway for the treatment of cancer-associated neuropathic pain, preliminary data suggest a benefit . Improved pain control, however, may come at the cost of side effects associated with cannabinoids, including somnolence, dizziness, confusion, and nausea . Medical marijuana use is common among patients with cancer. Among respondents to the U.S. National Health and Nutrition Examination Survey between 2005 and 2014 with cancer, 40% had used marijuana within the past year and the likelihood of marijuana use increased over time . Among 290 gynecologic cancer patients in California and Colorado surveyed by Blake et al, 27% reported using cannabis products following their diagnosis and an additional 36% were interested in doing so if facilitated by their treating physician . A survey of 36 patients in Connecticut with gynecologic cancer who were prescribed MM found 83% experienced relief of at least one cancer or treatment-related symptom . As of November 10, 2020, 40 states and territories have approved medical marijuana/cannabis programs .

Medical marijuana was legalized for patients with cancer and other serious medical conditions in New York in 2016; New Jersey legalized cannabis for recreational use in 2020. Gynecologic cancer patients commonly report nausea, vomitinand pain associated with both thei cancer itself and cancer-directed treatments. The Society of Gynecologic Oncology recently published a clinical practice statement summarizing the evidence for MM for chemotherapy-induced nausea/vomiting, prevention of neuropathy secondary to taxanes, and cancer-related pain . Despite this guidance, relatively little is known about the utilization and efficacy of MM in this population. We evaluated the effect of MM for symptom management in gynecologic cancer patients at our institution. Women with gynecologic cancer who used MM between May 2016 and February 2019 were identified through our institution’s electronic medical record. Medical marijuana was prescribed by one gynecologic oncologist at our institution  or an authorized palliative care physician. Clinicopathologic and demographic data, including age, race/ ethnicity, insurance status, cancer diagnosis, and treatment information were collected. Detailed information regarding dosage form, including the ratio of THC to CBD, quantity prescribed, self-reported usage, and length of treatment were collected from the electronic medical record. Prior to MM prescription, patients were asked what symptoms they hoped to alleviate with cannabinoids. Follow-up questions to assess efficacy and tolerance in clinic were routinely implemented with the use of a standardized EPIC smart phase after starting MM. This queried if patients had used MM, how long they used it for, efficacy for specific symptoms, and any side effects experienced. For patients where information on efficacy and tolerance was not obtained, follow-up data was not considered to be available. This study was approved by the institutional review board at our institution and the requirement for obtaining informed consent was waived. Descriptive statistics were calculated. Categorical variables were compared using Fisher’s exact test and a p-value of <0.05 was considered statistically significant. From May 2016 to February 2019, 45 gynecologic cancer patients at our institution were prescribed MM. Table 1 shows the baseline clinicopathologic and demographic characteristics of the study cohort. Patients were a median of 60 years old  when MM was first prescribed. The majority of patients  were non-Hispanic White; 9% each were non-Hispanic Black or Asian, and 7% of patients were Hispanic and White. Just over half of patients  had Medicare insurance, with 33% insured privately and 16% insured by Medicaid. Those with ovarian, fallopian tube, or primary peritoneal cancer  made up the majority of the patient population, with the remainder split between cervical and uterine cancer. Almost all patients  were receiving chemotherapy when prescribed MM and just over half were undergoing primary treatment . There was significant heterogeneity in the formulation and THC:CBD ratio prescribed, as shown in Table 2.

The majority of patients  were prescribed formulations with a 1:1 THC:CBD ratio, but this data was missing for almost a quarter of patients. Administration route also varied: while inhaled and sublingual formulations were most commonly prescribed , free form, edible, and oil preparations were also utilized. Many patients were prescribed more than one formulation, either initially, or following a trial period of another formulation. Among 41 patients with follow-up information available, MM was used for a median of 5.2  months. The most common indications for MM in patients were: pain, 25 ; nausea/vomiting, 21 ; anorexia, 15 ; and insomnia, 12 . Fig. 1 illustrates commonly prescribed indications and self-reported effectiveness by symptom. More than 70% of patients reported that use of marijuanaimproved nausea/vomiting, while only 36% of patients using MM for pain reported symptom improvement . Among the 41 patients with follow-up information, 29  reported medical marijuana improved at least one symptom. The most common reasons for discontinuation were death from disease progression  and no improvement in symptoms . Only one patient specifically cited side effects  as a reason for stopping use of MM. Other reported side effects included: euphoria, dizziness, feeling ‘high’, nausea, headache, and fatigue. Four patients were still using MM at the time of last follow-up. The reason for discontinuation was missing for 17 patients . Among gynecologic cancer patients prescribed MM for symptom management, follow-up indicated symptom relief for the majority of patients and minimal therapy-related side effects. Almost 90% of patients were receiving chemotherapy when first prescribed MM, most of whom were undergoing primary treatment. Patients used MM for a median of almost six months, vertical grow system with significant variation in length of use; some patients had continued to use it for more than two years at time of last follow-up. Although MM use is legal in a majority of states and commonly utilized by cancer patients, few oncology providers feel comfortable prescribing it. Braun and colleagues surveyed a nationally representative population of medical oncologists; only 29% felt sufficiently knowledgeable to prescribe MM. Of providers surveyed, 56% recommended MM to their patients . A follow-up survey by Braun and colleagues found the most perceived benefit for patients at the end of life  compared to those with early stage disease  and cancer survivors. Given the prevalence of MM use among cancer patients, improved education of both patients and providers may help increase its utilization for symptom management throughout the disease continuum. This data provides one of the initial reports of the symptom relief profile of MM among patients on cancer-directed therapy in women with gynecologic malignancy. In this limited cohort of gynecologic oncology patients, MM was effective for the relief of nausea/vomiting, anorexia, and insomnia in a majority of patients but was less helpful for pain management. This is consistent with the findings of Webster et al, where the majority of patients reported symptom relief with medical cannabis use, but details were not provided on efficacy for specific symptoms.

Patients were not, however, queried on the adjunctive use of other medications or interventions for cancer-associated symptoms while using MM. Although patients reported MM provided symptom relief, this could have been affected by recall bias and we did not assess for the relative efficacy of any other approaches  compared to MM. Patients were also not queried on the specific type or location of pain they hoped to improve with MM use. Additionally, there was no standardized collection of the type and frequency with which other pain medications were used concurrent with MM. The use of cannabis products as an adjunct has been shown to improve pain control in patients with severe cancer-associated pain, but has not been associated with a decrease in opioid use . While there is preclinical data and studies in other diseases associated with neuropathic pain , we did not specifically query patients on the use of MM for the prevention or treatment of taxane-induced neuropathy. The heterogeneity of preparations and administration methods prescribed, with many patients being prescribed more than one formulation, limits our ability to comment on the effectiveness of specific THC: CBD ratios or preparations for specific symptoms. For patients prescribed more than one formulation, we did not assess whether or not they were used simultaneously or query why an alternate preparation was not effective. We also did not explicitly exclude patients who used marijuana recreationally. Larger, prospective, and more standardized studies in gynecologic cancer patients will hopefully provide further clarity on this question. Prior studies have found that many of the undesirable side effects of MM are related to high amounts of THC and optimizing the ratio between THC and CBD may maximize symptom relief while minimizing side effects . Among a small cohort of gynecologic cancer patients prescribed MM for symptom management, the majority reported improvement in at least one disease or treatment-related symptom and reported minimal side effects.

The psychoactive drug use was measured using a blunt measure, which asked the participants if they had used any psychoactive drug in the past year and this might have hindered the detection of an association with RTIs. Additionally, this study may lack the statistical power to detect a potential association between marijuana use and RTIs, considering confounders. In spite of these limitations, the strength of our study lies in the ability to use population-based controls rather than hospitalbased controls. Population-based controls are preferred due to their representativeness of the source population as compared with control selected from hospital- which may share similar essential exposures with cases and hence leading to overmatching . Additionally, we have used a validated AUDIT questionnaire, which has been pre-tested in Tanzania among trauma patients and has shown an acceptable validity and reliability . Face-to-face structured questionnaire were used in data collection, which provides an advantage of making clarifications of difficult questions if needed and ideal in population with low literacy. A further strength is that our study was able to adjust for risky driving behaviour as well as important workrelated factors, which has been shown to be common among commercial motorcyclists . Based on individual-level self-concept theory  and previous research , identification as a substance user is a risk factor for deleterious substance use. A drinking/marijuana identity, for example, reflects the extent to which alcohol/marijuana use is an integral part of how one sees one’s self. Identity is viewed in the current study from the perspective of one’s personal identity which emphasizes aspects of the selfthat are independent of group or role identities .

Less clearly understood are factors that might mediate the relationship between identity and alcohol/marijuana-related outcomes . Given that past research has examined protective behavioral strategies  and their use as a harm reduction strategy with PBS defined as “strategies employed before, during, or after drinking [or marijuana use] that reduce alcohol [marijuana] use, intoxication, and/or alcohol [marijuana] related harm”.PBS more broadly may be a mediator of the relationship between identity and outcomes. The current study focuses on the extent that PBS mediate the relationship between drinking/marijuana identity and alcohol/marijuana-related outcomes. Research indicates that drinking identity is positively associated with past-month alcohol frequency , typical quantity , and alcohol-related consequences . Studies have evaluated and confirmed a similar relationship between identity and alcohol-related outcomes in more diverse populations . Studies have also reported that marijuana identity is positively associated with marijuana use-related outcomes .Elucidating mediators of the identity-outcome association has the potential to identify factors that could be targeted in future interventions. Alcohol PBS have generally been negatively associated with alcoholrelated outcomes . Further, specific alcohol PBS  have been found to be negatively associated with quantity  and consequences . With respect to cannabis grow system, marijuana PBS have generally been found to be negatively associated with marijuana frequency , quantity  and consequences . Less well understood is whether an association between identity and PBS exists, as well as whether PBS are a mediator of identity-outcome association in college student and community-based samples. Individuals may be using PBS in order to maximize the perceived benefits of substance use  while also mitigating the risk associated with substance use . However, individuals with a high level of drinking/marijuana identity may be less inclined to use strategies that would limit their engagement in identity-consistent behavior. Therefore, identity may be negatively associated with PBS. In terms of clinical implications of the examination of PBS as a mediator of the identity-outcome relationship, identity-based and PBS-based interventions that attempt to decrease an individual’s level of drinking/marijuana identification or increase an individual’s use of PBS may help to reduce/attenuate the identity-outcome association.

In the current study, PBS were hypothesized to mediate the relationship between drinking/marijuana identity and alcohol/marijuana-related outcomes . In the cross-sectional studies, PBS were found to mediate the relationship between identity and outcomes. With respect to alcohol, mediation findings were limited to MOD PBS and specific to two  alcohol-related outcomes  evaluated. In the longitudinal study, across the three models, limited support for PBS as mediator was observed. With respect to marijuana, marijuana PBS were found to mediate the relationship between marijuana identity and all three of the marijuana-related outcomes evaluated . These findings represent an important scientific contribution to the existing substance use identity and PBS literature because they support the existence of a relationship between identity and PBS, a relationship that could be targeted in prevention/intervention work. First, to our knowledge, no published studies have reported on the relationship between drinking identity and alcohol PBS. In the current study, drinking identity was consistently found to be negatively associated with MOD PBS, followed to a lesser extent by LSD PBS and SHR PBS. In addition, drinking identity was found to be predictive of change in MOD and SHR PBS although the change in PBS from baseline to 3- months in Study 1 was not found to be statistically significant . Second, similar to past PBS mediation investigations, MOD PBS was a statistically significant mediator. For example, MOD PBS have been found to mediate the relationship between college-related alcohol beliefs and alcohol-related outcomes , preparty-specific motives and event-level preparty drinking , and in the current study, drinking identity and alcohol-related outcomes. MOD PBS include drinking slowly and the avoidance of drinking games, shots of liquor, and mixing different types of alcohol. Although speculative, research indicates that individuals drink to have a good time with friends , and individuals with a higher level identification as a drinker may be reluctant to use MOD PBS because these strategies may reduce engagement in activities  that facilitate having a good time. Another explanation for the MOD PBS mediation findings is that an individual whose identity is strongly linked with using alcohol may be less inclined to use MOD PBS because these strategies may limit the ability to convey important identity-related information to others when drinking . Taken together, these findings indicate that an individual with a high level of drinking identity is likely to not use strategies that limit participation in drinking games or the consumption of shots and that the lack of use of these strategies may lead to the consumption of higher quantities of alcohol and the experiencing of alcohol-related consequences.

Future research in this area is needed to identify why individuals who report a high level of identification as a drinker may report not using specific alcohol PBS. Third, MOD PBS were found to be a statistically significant mediator in both the college and community-based samples, findings that tentatively support the generalizability of these mediation effects beyond college student populations. Across all studies, LSD PBS and SHR PBS did not mediate the relationship between drinking identity and outcomes. From a conceptual standpoint, it is unclear why drinking identity is differentially related to different forms of PBS and mixed method research is needed to elucidate these findings. However, as an example, it has been argued that some LSD PBS may not serve a protective function that helps individuals reduce alcohol use and consequences . Thus, lack of support for mediation could be a function of a weak association between specific PBS and outcomes. When alcohol quantity and consequences served as the alcohol-related outcome in the mediation models, the statistically significant cross-sectional mediation effect with MOD PBS was replicated longitudinally in Study 1  data. However, mediation effects were not replicated in the other two longitudinal models. The lack of statistical mediation in the other two models were likely due to the intervention not specifically targeting drinking identity or PBS directly. Identity and MOD PBS were not found to have significantly changed in either the control or intervention group between baseline and 3-month follow-up; thus, controlling for baseline PBS use potentially left little variability for identity to explain in MOD PBS at 3 months. Future identity-based interventions are needed to examine whether reductions in identification as a drinker are associated with greater PBS use. Future PBS-based interventions would also benefit from examining whether increased PBS use is associated with decreased identification as a drinker. Similar intervention approaches are needed to better test whether PBS mediate the association between marijuana identity and outcomes. Participants with a high level of identification as a marijuana user reported the use of fewer marijuana PBS, findings that add to the emergent literature on the relationship between marijuana identity and marijuana PBS . Similar to reasons for alcohol use, research indicates that individuals use marijuana to have a good time with friends , and it may be that the use of marijuana PBS that limit an individual’s ability to have a good time may be strategies infrequently used by individuals with a high level of cannabis grow lights identity . Additional research is needed to clarify the role marijuana PBS play as a mediator in non-college populations.Based on these findings, there may be two potential targets to reduce alcohol quantity and consequences:  increase an individual’s use of MOD PBS and/or  decrease an individual’s level of identification as a drinker. For the first, although the evidence base for PBS interventions is mixed , recent adaptions of PBS interventions have been found to be more efficacious, particularly when targeting MOD PBS . These new PBS interventions may be particularly well-suited to reduce the influence that identity has on alcohol/marijuana-related outcomes given that the message framing of PBS normative feedback within these interventions is tailored based on how common others are perceived to be using PBS. Based on findings from the current study, it would appear that an alcohol PBS intervention that attempts to increase a participant’s level of MOD PBS may help to reduce the effect that identifying as drinker may have on both the quantity of alcohol consumed and the number of alcohol-related consequences experienced.

With respect to marijuana PBS interventions, there is less specificity in terms of which specificmarijuana PBS to target. Additional research is needed to identify marijuana PBS that individuals are willing to use and which are effective at reducing marijuana use-related outcomes. It is unclear the extent to which interventions can directly target drinking identity, and relatedly, marijuana identity. Given the difficulty inherent in experimentally manipulating an individual’s level of substance use identity, it may be more feasible to target specific PBS  at the current time. Research is needed to evaluate novel approaches that may be effective at changing an individual’s level of identity as well as their PBS use, particularly for individuals who strongly identify as an alcohol/marijuana user. Findings from the current study should be considered within the context of certain study limitations. For example, the questions as well as the time frame for reporting retrospective PBS use and outcomes sometimes varied across studies. Although this is a limitation in the current study, demonstrating that MOD PBS were a statistically significant mediator and that this finding was observed despite different assessment approaches is also a notable strength. In addition, low levels of internal consistency were observed in the measurement of PBS in Study 1 thus limiting confidence in the extent that subscale items reflected different forms of PBS. Although PBS mediation effects were examined cross-sectionally/ longitudinally, the analytic approach was still correlational. Additional experimental studies are needed to disentangle the causal sequencing of the relationship between identity, PBS, and the outcomes. In Study 3, there were a sizable number of participants who were currently attending college. Caution should be exercised about the extent to which findings from Study 3 truly reflect data from non-college attending adult populations. Global health experts have raised substantial concern regarding the impact of the COVID-19 pandemic on substance use due to increased social isolation and elevated stress . Yet, the impact of the pandemic is unclear given the reduction in social gatherings where substances are commonly consumed and the potential difficulty physically obtaining or financially affording substances . The pandemic may also impact the severity of substance use disorders due to changes in frequency of substance use and the disruption of substance use treatment .

Most patients support insurance coverage of MC,suggesting that in the future insuracne coverage could potentially offset the cost barrier to MC use. Further studies are necessary to evaluate the effectiveness of MC for the treatment of common hand conditions, as well as to better define the long-term safety and side effects of MC in this patient population. Under suppressive antiretroviral therapies , infection with Human Immunodeficiency Virus  remains a challenge, both due to the maintenance of cellular reservoirs and to chronic inflammation driven by low viral replication and dysregulated immune mechanisms. In end organs such as the brain, where the majority of theHIV-1 targets and reservoirs are of myeloid origin , the remaining inflammatory environment contributes to comorbidities,including neurological and cognitive problems , particularly if ART is not introduced sufficiently early . Substance use disorders are frequent among the HIV-infected population, further contributing to cognitive impairment . Nonetheless, the mechanisms by which addictive substances and HIV interact are multi-factorial and poorly understood.Drugs of abuse impact the brain reward system, by modifying levels and balance of neurotransmitters . The HIV target cells, macrophages and microglia, as well as CD4 T cells, express receptors to neurotransmitters, so SUDs are likely to impact mechanisms of immune and inflammatory, and anti-viral responses. Biomarkers that detect the effect of SUDs, and distinguish HIV in that context, may clarify how drugs affect HIV and inflammation.Cannabis is one of the most prevalent substances among HIVt subjects,compared to the non-infected population ,either prescribed for ameliorating symptoms associated with the virus or with ART , or used recreationally, as well as a component of poly substance use , which in itself is a risk factor for HIV infection.

The effects of cannabis may drastically differ from the effects of stimulant drugs such as Methamphetamine, particularly in the context of HIV infection . Yet, similar to other drugs of abuse, cannabis drying racks may be a confoundershifting the expression of biomarkers of inflammation and cognition,masking our ability to clearly measure the impact of virus, ART or other treatments in the immune status and brain pathogenesis, or may be altogether beneficial.In terms of cognition, cannabis exposure has been linked to lower odds of impairment in people living with HIV. On the other hand, impaired verbal learning and memory, may be negatively impacted by cannabis use.Other studies report no-differences, or detrimental effects in HIV-negative populations, suggesting that the observed effects of cannabis, including its benefits, may be largely domain and context-dependent.It has been reported that cannabis use improves biomarkers of inflammation in the CSF and plasma of HIVt subjects and decreases the number of circulating inflammatory cells.We have tested the value of a large panel of transcripts associated with inflammation and neurological disorders, digitally multiplexed and detectable in peripheral blood cells from HIV-positive  and HIV-negative  subjects, users of cannabis  or not .The differences between groups were analyzed using a systems biology approach that identified associated gene networks based on pathways and molecular interfaces, for identifying and visualizing orchestrated transcriptional patterns consistent with HIV infection, CAN exposure,and their interactions. Trends in the behaviors of gene clusters and their predicted regulators revealed that effects of cannabis differ between HIV and HIVt groups. Moreover, mixed statistical models have pinpointed genes that are further influenced by cannabis in the context of poly substanceuse. These context-dependent effects of cannabis indicate the complexity of its molecular actions and properties, and the challenges of biomarker discovery in the context of SUDs. At the same time, the results suggest that cannabis in the context of HIV infection may drive benefits by promoting a decrease of pro-inflammatory and neurotoxic transcriptional patterns, changes and changes in gene clusters associated with leukocyte transmigration and neurological disorders. The impact of HIV, cannabis and their interaction on peripheral markers of cell subset, cellular function and activation was estimate dusing a combination of cell surface protein detection by flow cytometry and a targeted digital multiplex transcriptomic analysis.

The specimens were from males, with homogeneous age and education, and the same race distribution, as shown in Table 1. The examination of clinical data revealed that in HIVt individuals, cannabis did not significantly affectCD4 nadir, CD4/CD8 ratio, plasma or CSF viral load. Cannabis users were significantly more likely to engage in poly substance use, or use other drugs, including alcohol, cocaine and METH. HIV status significantly increased the incidence of lifetime major depressive disorders, which was not affected by cannabis use . Neuropsychological data indicated that cannabis had a marginal effect on Global T scores .By flow cytometry, we verified that the specimen freezing process did not impact subset distribution . For instance, HIVt subjects had significantly lower percentage of CD11btCD14t monocytes compared to HIV- subjects, particularly the ones exhibiting the inflammatory marker CD16t, regardless of cannabis use . The percentage of CD4t T cells was also decreased in HIVt specimens when compared to HIV, with no effect of cannabis . The percentage ofCD8t cells, on the other hand, was significantly increased in HIVtnon-cannabis users, but not in cannabis users, compared to respective controls . Molecular markers of neuro inflammation, activation and leukocytetransmigration were measured in the peripheral blood cells under the hypothesis that cannabis use has an effect by itself and on modulating the effects of HIV. A panel of 784 markers relevant to neurological disorders and inflammation were tested by Nanostring. Of these 381 did not produce any signal in any of the specimens and were excluded from the analysis. The expression of genes with significant signal over noise in more than arbitrarily 10% of the samples was normalized by an average of 8 housekeeping genes. Hierarchical clustering performed using average normalization method applied to digital gene expression data has revealed similarities between HIV-/CANt, HIVt/CAN- and HIVt/CANt, but all these groups were distinct from HIV-/CAN-. Clustering also allowed to identify individual specimens that showed patterns distinct from the majority within groups .Systems biology strategies were used to identify defining expression patterns in transcriptional data, and gene clusters exhibiting orchestrated behaviors perturbed by HIV infection, by the use of cannabis, or by their interaction.

We have identified significant trends in a number of gene clusters functionally annotated to biological processes and pathways of relevance to the neuropathogenesis of HIV. Overall, the analysis indicates context-dependent effects of cannabis.The majority of the digitally multiplexed genes  exhibited detectable and overlapping interactions based on pathway, as indicated in Fig. 4. The effects of HIV alone were estimated by the ratio comparison between HIVt/CAN- versus  HIV-/CAN-. The effects of cannabis alone were estimated by the ratio between HIV-/CANt vs. HIV-/CAN-.The overall combined effects were estimated by the ratio between HIVt/CANt vs. HIV-/CAN-. The effects of HIV in the context of cannabis were measured by the ratio between HIV-/CANt vs. HIVt/CANt. The effects of cannabis in the context of HIV were detected by the ratio between HIVt/CAN- vs. HIVt/CANt. The visual inspection of the cluster in Fig. 4 shows that both HIV and cannabis alone increase the expression of a number of genes indicated by nodes with orange color . In cells from HIVt/CANt individuals, a number of genes showed decreased expression compared to HIV-/CAN- . HIV infection in the context of cannabis, revealed by the comparison of HIVt/CANt and HIV-/CANt , was characterized by strong erupregulation of genes, but also several genes with decreased expression.The effects of cannabis in the context of HIV  measured by the ratio between HIVt/CANt and HIVt/CAN-, were characterized by a higher number of down regulated genes, and a more modest upregulation,as suggested by overall lighter orange shades. A complete list of the genes in this network and T ratio in indicated comparisons can be found in Supplementary Materials 1.Pathway-based interactions were subdivided for identification of embedded functional annotations impacted by HIV and/or cannabis grow tray,identified by DAVID Bio informatics Resources with a gene list input.Individual functional annotations were then assembled in Gene Mania forvisualization of effects. A complete list of significant pathways and functional annotations can be found in Supplementary Materials 1. The pathways selected for visualization were curated based on the expression of inflammatory genes, significance to neurological disorders in the context of HIV, viral infection, pathogenesis and networks with interventional value. For instance, a gene network functionally annotated to viral host interactions was identified , where the ratio between HIVt/CAN- and HIV-/CAN-  indicated that HIV increased a number of genes annotated to that function. The ratio between HIV-/CANt and HIV-/CAN- , as well as between HIVt/CANt subjects were compared to HIV-/CANt,indicated that both cannabis alone and HIV in the context of cannabis use increased a largenumber of genes in this cluster, but several genes were also decreased in both conditions, including the Ras homolog gene family GTPase RhoA,the Proteasome 20S Subunit Beta 8 , the intracellular cholesterol transporter , the E1A Binding Protein P300  and the histone deacetylase Sirtuin 1 . The ratio between HIVt/CANt and HIVt/CAN- indicated that cannabis in the context of HIV was associated with a mild increase of genes in viral host interaction function, and a decrease in the general transcription factor IIB  and the ubiquitin protein ligase 3A  were characteristic of this comparison.Apoptosis was also identified as a relevant functional annotation, showing differential effects of HIV and/or cannabis.

HIV alone decreased Caspase 7 CASP7, but increased CASP9 and the apoptosis regulator BCL2. The effect of cannabis, on the other hand , indicated decrease in BCL2. Likewise, HIV in the context of cannabis  had a decrease in BCL2 . On the other hand, the ratio between HIVt/CANt and HIVt/CAN- indicated that cannabis decreased or had mild effects on the expression of genes associated with apoptotic functions detectable in peripheral leukocytes.Given the large degree of overlap between these networks , we applied a merge network function in Cytoscape,which is shown in Fig. 7. The visualization of this gene network indicates that both HIV and cannabis increase genes with functions inneurode generation and inflammation,but cannabis decreased key contributors to the inflammatory process such asIL1b, TLR2, MyD88 and PARK7, as well as RASGRP1 . HIV infection in the context of cannabis  indicated patterns that were similar to cannabis alone, with decreased expression in the same genes.Moreover, cannabis in the context of HIV elevated TLR2, TLR4 andMyD88, but had no or mild effects, or decreased a number of genes in this network . Functional annotations associated with leukocyte-vascular adhesion and transmigration capacity were also sorted from pathway interactions.These functions were affected by HIV and cannabis . A large number of genes in this network were differentially increased by HIV and by cannabis . Yet cannabis lowered the expression of a large number of genes with cytoskeleton and signaling properties, including RHOA, AKT3, RAC1, BRAF and BCL2 . HIV in the context of cannabis had also lower MAPK1 and CTNNB1 compared to uninfected cannabis users . HIVt cannabis users had a high number of genes that were lower or mildly changed compared to HIV non-cannabis users .Inflammation is highly regulated by a kinases. HIV and cannabis affected the expression of a number of kinases and genes involved inkinase regulation. The effects were differential and context-dependent.All the conditions showed decrease in CAMK4, in comparison to respective controls . HIV alone decreased mTOR, CSF1R, EPHA4,PDPK1 and DGKE . Cannabis alone, as well as HIV in the context of cannabis , decreased ATK3 andMAPKPK2. Cannabis alone decreased CALM1 . HIV in the context of cannabis decreased the expression of PGK1 and RAF1. Cannabis in the context of HIV decreased several genes in this network that were either not modified or increased by the other conditions. These included MAP2K1, MAPK9, MAPK3, PRKCA andPDPK1 . The screening of a large number of transcripts associated with neurological disorders has shown that the effects of cannabis differed drastically between HIV- and HIVt groups, particularly in gene networks playing a role in inflammation, neurodegeneration,apoptosis and leukocyte adhesion and transmigration. The results indicate that cannabis in the context of HIV may have beneficial effects. However, in individual genes, we identified detrimental effects that were associated with polysubstance use as a covariate, particularly methamphetamine.

GLCM texture parameters such as contrast, homogeneity, energy, variance, and correlation have been proven to be successful in increasing classification accuracies by providing important textural characteristics that help in discriminating land cover . Additionally, GLCM texture metrics have been used in combination with SAR S1 data for crop discrimination . When classifying different crop types in an agricultural field, extracting information from neighboring pixels could be of great importance in improving classification accuracy. Texture features involve this information and help in identifying the intensity variations in an image which can further contribute to improving overall accuracy. We further observe that the addition of texture features can decrease the accuracy of a classifier, similar to what happened when using a CART classifier. Although RF and CART are tree-based machine learning algorithms, this decrease in accuracy was not observed using the RF classifier. This is because RF is an ensemble machine learning algorithm which makes it more robust and stable compared to a single decision tree classifier. In terms of comparing classifiers, the highest overall accuracy was observed using the SVM classifier, followed by GBT, RF, and finally CART. Similar findings were observed in a study that compares machine learning algorithms  by Mustak et al. , where authors report SVM classifier achieving better accuracy in crop discrimination compared to RF and CART. Moreover, Sonobe et al.  evaluated the potential of Terra-SAR-X data for crop mapping by comparing the performance of CART, RF, and SVM. Authors arrive at similar findings, with SVM being the optimum algorithm used. RF and GBT yielded similar results which have been observed earlier by Freeman et al.  when predicting tree canopy cover in four study regions. We further assess the average accuracy in classifying cannabis by computing the F1-measure, which Yang et al.  defined as the harmonic mean of the user’s accuracy and producer’s accuracy. In the 2016 classification, the average F1-measure achieved by RF, GBT, and SVM is 0.88. Thus, we assume that the three classifiers achieve similar results in identifying cannabis fields. In 2018, classification SVM and GBT achieve a similar average F1-measure , and RF achieves a slightly lower value . Since the classification models in 2016 achieved promising results in identifying cannabis, we use them to classify cannabis in 2017.

The models classify cannabis vertical farming with an average accuracy of 83% for SVM, 73% for RF, and 52% for GBT. Therefore, it is possible to detect illegal cannabis fields early in the season since it is usually harvested end of September – early October, and the classification period ends in August. The novelty of our study lies in classifying a non-dominant crop type  with high accuracy as well as in the comparative analysis of the four most used machine-learning classifiers in Google Earth Engine. Previous crop classification research classifies crops that are dominantly present in study areas. To our knowledge, there has been no similar work carried out on cannabis classification.  The Agricultural Improvement Act of 2018 permits the cultivation and legal trade of industrial hemp in the United States. This act defines hemp as Cannabis sativa and any part or derivative of the plant including seeds, extracts, cannabinoids, isomers, acids, salts, and salts of isomers with a total delta-9 tetrahydrocannabinol  concentration below 0.3 %  on a dry weight basis . This statute removed hemp-cannabis from its schedule I classification by using this definition to separate it from marijuana-type cannabis. Currently, there are no standardized methods to distinguish hemp from marijuana. Most forensic laboratories use chromatographic methods such as Gas Chromatography  or High-Performance Liquid Chromatography  methods coupled to mass spectrometry to quantitate the THC in suspicious plant materials. Furthermore, colorimetric tests that were once used to presumptively identify cannabis are not able to differentiate between hemp and marijuana, creating the need for an effective field test that can differentiate between hemp-type cannabis and marijuana-type cannabis. Hemp and marijuana are two different strains of the Cannabis plant with the main difference between the two being the concentration of cannabinoids contained in them. The two most important cannabinoids in these plants are THC and cannabidiol . THC is the cannabinoid that causes a psychoactive response in the body giving the person a “high”. It also has anti-inflammatory and analgesic properties, which make it desirable for medical use . CBD is also known for these beneficial properties but is non-psychoactive, so it does not give a person a “high” when used . Typically, hemp is CBD-rich containing low concentrations of THC causing its THC:CBD ratio to be below 1. Cannabis is considered marijuana when it has a concertation of total Δ9- THC ≥ 0.3% , but usually has a THC:CBD ratio above 1 . Elsohly et. al. reported that from 2009 to 2019 marijuana in the U.S. increased in THC potency across the decade from an average of 10% THC in 2009 to 14% THC in 2019. In 2019, the average CBD concentration in marijuana was found to be 0.6% , and that the THC:CBD ratio was above 20 across the decade . This difference in THC:CBD ratios can be used in the design of an effective field test for the identification of marijuana-type cannabis.

These tests are considered presumptive as they only indicate the possibility of the analyte being present in the substance . Until the Agricultural Improvement Act of 2018, the modified Duquenois-Levine  test was the color test used to presumptively identify a suspicious plant material as cannabis. Although used for many years, the D-L test is known to produce false positives with reaction of molecules containing a resorcinol backbone and an aliphatic chain . Therefore, the D-L test is to produce false positive results from plants such as patchouli, spearmint, and eucalyptus. Furthermore, THC, CBD, and many other cannabinoids contain both a resorcinol group and an aliphatic chain, resulting in a D-L test that is not selective enough to differentiate between the cannabinoids. This shortcoming is the reason that the D-L test is no longer a suitable field test for the identification of marijuana-type cannabis. There is now an urgent need for color tests that can differentiate between hemp  and marijuana . One colorimetric test that is currently being used to differentiate between hemp and marijuana is the 4-aminophenol  test developed by the Swiss Forensic Institute in Zurich . A recent validation study has shown that a pink color forms when the THC:CBD ratio is below 0.3  and a blue color forms when the plant has a THC: CBD ratio above 3  . A confirmatory chemical test such as GC-FID or GC–MS is still required after a positive 4-AP test. The test requires the use of at least 1 mL of one of its reagents, 4-aminophenol, to produce a color result. Although the 4-AP test has demonstrated capability as a presumptive test for cannabis, it has also been reported that it may not be selective for THC. False positive results have been obtained with sage, oregano, and several cannabinoids, such as cannabinol.A more selective and smaller-scale alternative presumptive test could improve the presumptive confirmation for marijuana in the field. A colorimetric reagent that has been used for many years as a visualization reagent for cannabinoids when analyzing cannabis extracts through thin layer chromatography  is the Fast Blue BB  reagent . The FBBB test is selective among major cannabinoids, providing a red color for THC, an orange color for CBD, and a purple color for CBN. Ultraviolet-Visible Spectroscopy has shown that the FBBB + THC chromophore has an absorption band at 471 nm, which is responsible for its red color. The Almirall lab previously reported the structure of the FBBB + THC chromophore using results from high-resolution mass spectrometry  and Hydrogen Nuclear Magnetic Resonance . It was determined that, in basic conditions THC becomes a phenolate anion and that this anion attacks the diazo group in FBBB at the para position to form the chromophore  . A bathochromic  shift results from the extended conjugation in the chromophore and the n→π* transition caused by the electrons in the diazo group of FBBB . In addition to characterizing the chromophore, the previous study evaluated the selectivity of FBBB for THC detection. Eight different types of tea, 3 hop products, and 3 authentic hemp buds were extracted and tested using FBBB. This test was performed by adding 10 μL of the extract to a filter paper, followed by 10 μL of 0.1% FBBB and 0.1 N NaOH. Extracts that were made from methylene chloride produced only 1 false positive with one of the teas . Of note, none of the hemp samples produced a false positive result, displaying an orange color indicative of CBD . These results support the selective nature of the FBBB test for use as a presumptive field test to distinguish between hemp, marijuana, and other plant materials. In the previous study, filter paper, a Capillary Microextraction of Volatiles  device, and CMV strips were used as possible substrates to perform the FBBB test.

A CMV device is an open-ended 2 cm glass capillary tube that contains seven 2 cm by 2 mm glass filter strips have been coated with vinyl-terminated polydimethylsiloxane that was developed by the Almirall lab as an alternative to Solid Phase Microextraction. The modified glass filters that make up the CMV, known as Planar SPME , have excellent absorption/ adsorption capabilities and can withstand high temperatures. It was found that when the FBBB test is performed on one of the PSPME strips the LOD for THC was 100 ng, which is significantly lower than the known LOD for the D-L test, 5000 ng of THC . Using PSPME as a substrate is advantageous over regular filter paper since it can withstand high temperatures allowing the chromophores formed to be detected using DART-MS with very little background . In this current study, the capabilities of using FBBB as a presumptive field test to differentiate between hemp and marijuana are presented. We also report a fast and easy extraction method for plant material that can be used in the field. A previously reported substrate  known as PSPME support  was used for the FBBB reaction . Six cannabinoids, 5 retail hemp samples, vertical grow system 20 authentic cannabis samples, tobacco, hops, herbs, and essential oils were tested with the FBBB reagent. RGB  numerical codes were obtained for each color result to confirm the color produced by the reaction in an objective manner. The fluorescence results of the FBBB + THC fluorophore is reported for the first time. The fluorescence spectra of the FBBB + THC product are distinguishable from the spectra of FBBB + CBD chromophores. The RGB score combined with the fluorescence of the FBBB + THC chromophore/fluorophore enhances the selectivity of the FBBB test for marijuana. Linear Discriminant Analysis was performed to determine whether FBBB could be used to classify cannabis correctly as hemp-type and marijuana type. The FBBB test was used to evaluate 6 different cannabinoids, 5 commercial hemp strains, 20 cannabis samples, and various herbs and spices. It was determined that when FBBB reacts with THC, it forms a red chromophore that fluoresces under 480 nm light. Conversely, when reacted with CBD or CBD-rich products, such as hemp, an orange chromophore is formed, and this chromophore does not fluoresce. This is the first time, to the author’s knowledge, that the fluorescence of the FBBB + THC chromophore/fluorophore is reported for a colorimetric test. This fluorescence is easily visualized using a portable Dino-Lite microscope and its spectra obtained with a VSC2000 spectrometer. The intensity and wavelength of the fluorescence for the chromophore combined with the distinct red color it displays makes for a more selective and sensitive test to differentiate between marijuana and hemp. The structure for FBBB + THC has been previously determined by the Almirall lab, as shown in Fig. 1 . The chromophore results from an extended conjugation of π-bonds decreasing the distance between energy transitions between the ground state and excited state. This extended conjugation causes a “red shift” of the FBBB chromophore, which is responsible for the red color and the fluorescence that is observed when THC reacts with FBBB. One theory for CBD + FBBB lacking fluorescence intensity is that CBD has a less rigid structure than THC. It is known that structure rigidity and a fused ring structure increases the quantum efficiency, and therefore fluorescence of a molecule. Since CBD is less rigid than THC and does not have a fused ring structure, it is prone to relaxation through internal conversion rather than through radiative means . Therefore, FBBB + CBD likely relaxes through nonradiative mechanisms, which decreases overall fluorescence. The difference in both color and fluorescence that is observed for FBBB + THC and FBBB + CBD is an advantage that the FBBB test has compared to other tests for presumptive analysis of cannabis, which only use color.

Whether they used cannabis or not, results showed that students who had the lowest executive and memory scores were more addicted to tobacco and had higher trait anxiety. An association with tobacco use has been shown to be prevalent in both BD and cannabis users . In another context, chronic tobacco smoking was found to be related to neuropsychological impairment, notably for memory and flexibility . Like tobacco, anxiety can represent a risk factor for neuropsychological impairments, above all by affecting executive functioning . In the present study, college students who exhibited cognitive impairments tended to be more anxious. Students used alcohol to cope, especially those with higher levels of anxiety . The relationship between BD, cannabis use, and anxiety remains unclear, especially in college students . Tobacco and a high anxiety level, added to BD and/or cannabis use, may worsen the cognitive impairments highlighted in our study, as they seem to impair the same cognitive areas. Although the nature of our study did not allow us to establish any causal relationship between these variables, our results do suggest that they should be taken into account in prevention. The circularity of the possible risk factors for developing cognitive impairments between substance use, anxiety, and substance use to cope with anxiety is alarming, especially so regarding the current health context. With the SARS-CoV-2 pandemic, students have had to contend with high levels of anxiety . Regardless of context, these findings highlight the importance of prevention, so that students can be identified and psychologically supported at an early stage-even before they indulge in BD or substance use, or develop anxiety. Complementary analyses suggested that students with neuropsychological impairments spent more money on cannabis than those with preserved performance .

Even if this result has yet to be properly analyzed, it highlights the problem of how to measure cannabis intake. Unlike alcohol, with its standard drink units, cannabis lacks a precise measure that would reflect the actual amount consumed, and this issue needs to be further explored. One limitation of this study is that some patterns of students’ consumption were not represented in our sample, and consumption was self-reported. We chose to divide participants into three groups, based on available data, mobile grow system in order to examine the impact of co-occurring BD and cannabis use on neuropsychological profiles. However, the study sample did not encompass students who consumed cannabis without BD, as this profile is scarce in college students, and was particularly lacking in our sample. Future studies will therefore have to be conducted among cannabis users without BD to further focus on the aggravating effects of combined BD and cannabis use. Moreover, the three groups in our sample differed in size, which may have influenced statistical power and Type I errors. Furthermore, the neuropsychological assessment we used in this study was a screening test  with multicomponent tasks that rely on executive and memory abilities. This tool was designed to screen alcohol-related neuropsychological impairments and was not initially intended to assess cannabis consumption. However, the fact that alcohol and cannabis share the same cognitive impairment spectrum encouraged researchers to extend its use. The present study nonetheless represents a first step in understanding the neuropsychological consequences of BD and cannabis co-use. Further research is required to perform more detailed and extended neuropsychological assessments to overcome the above-mentioned limitations. This could be the opportunity to adapt the BEARNI’s cut-offs and psychometrics to educated young people. The assessment of neuropsychological impairment among college students engaging in BD associated with cannabis use demonstrated that these two practices have an additive effect, especially for memory and executive impairments.

They seem to have specific harmful effects on students’ cognition and consumption patterns. As BD and cannabis co-use can lead to cognitive impairments, it may partly explain the reduced academic success reported in the literature . Clinical practice could greatly benefit from this information, as it emphasizes the need to better characterize the different consumption and psychological profiles, especially in young students. As we know that neuropsychological impairments can hinder the motivation to quit or reduce consumption  and may also diminish the efficiency of prevention protocols, asking BD if they also use cannabis could be highly beneficial in clinical practice, for both prevention and research. Furthermore, it could allow prevention and care strategies to be adapted to each person’s neuropsychological profile. This study suggests that future prevention programs should take memory and executive impairments into account, as well as consumption profiles and anxiety levels, in order to improve the impact and efficiency of these programs in college students.  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” . Canada’s emphasis on youth cannabis prevention or delayed initiation is evidence-based. 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, 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.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,mobile vertical rack 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 intent of this research was not to provide a definitive description of how and how often Canadian adolescents are exposed to cannabis marketing, but to provide and test a tool that could facilitate such future research.

With this tool, we also aim to provide preliminary data demonstrating the existence and potential impacts of cannabis advertising on youth. Historical research on other legalized, recreational drugs  suggests that Canadian youth are likely cannabis marketing targets, but to date,almost no data exists regarding the scope and impact of cannabis marketing on Canadian youth in a post-legalization context . This study presents some of the very first data that demonstrate that cannabis marketing to youth is actively occurring in Canada, and that researchers and policymakers must begin to take action on the issue in order to protect youth and public health. To our knowledge, this is the very first study to use EMA to capture adolescent cannabis marketing exposures, in Canada or elsewhere. A particular strength of the EMA approach is that it enables detailed data collection about each exposure , and its immediate impacts, that are otherwise obscured or blurred in retrospective self-report. . Thus, the current study provides novel evidence for a powerful tool that researchers and policymakers can use to obtain detailed information about cannabis marketing exposure characteristics , and strategies for assessing their subsequent effect on adolescents’ cannabis-related expectancies and intentions. We recognize that EMA methods overall are not new, and that Shiffman  and others have been advancing the science of EMA for more than 30 years. The newness of cannabis legalization in Canada and the associated taboo of cannabis in some communities , however, necessitated this extensive pilot work, not only to demonstrate the concept of the work , but also that our recruitment procedures, messaging, and protections were acceptable to adolescents and their guardians, as all of these components of the study are essential to effectively conduct the research. Overall, our results show that the protocol is feasible. Although overall rates of compliance  were slightly lower than previous EMA studies of adolescents, rates among the participants whose app was working well were directly in-line with other work . Unexpectedly, a major task of this pilot research was to resolve software compatibility issues between the Expiwell app and older versions of Android platforms, including identifying device setting issues such as “do not disturb” or “battery saver” mode on individuals’ phones that interfered with participants receiving notifications from the study app. Participant compliance rates were much better among those with newer phones whose platforms were more compatible with the app. Researchers replicating or extending this research will need to consider the pros and cons of allowing participants to use their own devices for data capture  as compared to using a study-issued device  . Despite it’s feasibility design, this study also provides new, albeit very preliminary knowledge regarding the quantity and characteristics of cannabis marketing currently reaching Canadian adolescents; information that has previously only been described in aggregate, retrospectively, and by self-report. Overall, data showed that nearly all participating adolescents had cannabis marketing exposures during the study period. This included an average of about two cannabis-related marketing exposures per week, substantiating previous research . This finding demonstrates cannabis companies’ success in skirting current cannabis-related marketing laws which categorically prohibit marketing of cannabis products to youth. Our data also showed that most cannabis-related exposures occurred through promotion by public figures and through ads on the internet. This finding is likely influenced by the COVID-19 context  in which data were collected, and it is consistent with a significant increase among youth in the use of social media, streaming services, gaming sites and apps . At the same time, previous research has demonstrated that cannabis has an established and sophisticated presence specific to the internet based on creative advertisements designed for social media platforms , regardless of legality or media company policies . Indeed, while alcohol and tobacco industries developed their original marketing campaigns decades ago using traditional media channels , Canada’s sale and legalization of cannabis began in the digital age, and as a result, cannabis companies rely mostly on social media to market their products .

While some studies have suggested these impairments may be reversible after abstaining from use,  others found heavy use  may worsen attention and memory if initiated during adolescence.  Additionally, adolescent cannabis use is related to poor educational outcomes, lower career achievement, and lower relationship and life satisfaction.  Despite these risks, adolescents’ cannabis use has risen and their overall perception that cannabis use is harmful has declined over the past two decades.  These shifts could be attributed to the rapidly changing policies regarding cannabis legalization. While results have been inconsistent in the role legalization plays in adolescent cannabis use,  there is an increased need for public health campaigns and interventions designed to address misperceptions of cannabis use. Due to emerging pro-cannabis messaging on social media, adolescents are exposed to less information about the health-related risks of using grow lights for cannabis while there is an increasing amount of data promoting its potential benefits, such as pain reduction.  Increased information about cannabis use risks alone has not been found to help change adolescent behaviors.  

Additionally, pro-substance use media messages have been recognized as having a strong association with adolescents’ substance use,  further emphasizing the influences that may offset the effects of media exposures on adolescents. Given the significant inverse relationship between perception of risk and substance use,  it is essential to further investigate modifiable factors that contribute to the perception of risk. Previous studies have indicated there may be protective effects on an adolescent’s decision to use cannabis from parental,  peer,  and school-related  factors.Using a nationally representative sample, Simantov, Schoen, and Klein  found that strong parental support reduces the risk of adolescents smoking and drinking.  Barrera and colleagues  obtained similar results in a sample of seventh-grade students in Oregon; those with greater parental monitoring had stronger family relationships and less involvement with peers who used substances.Following adolescents from age 12 to age 23, Van Ryzin and colleagues  identified different influential roles for family and friends; with family playing a stronger role among younger adolescents  and friends being more influential in early adulthood.

Moreover, parental monitoring and family relations may play a role in how adolescents choose their friends.As adolescents decrease their time with parents and family, their relationships with their peers increase, and these relationships could play a critical role in their decision to use substances.  When their peers disapprove of using substances, adolescents have lower odds of substance use themselves.Conversely, the perception of peers engaging in use  and deviant peer association  predict the onset of substance use. An examination of peer influences on adolescent substance use using the 2010 National Survey on Drug Use and Health  found that adolescents with close friends who disapprove of grow cannabis were 87% less likely to use, which was a stronger influence than when friends disapproved of cigarette and alcohol use.  Adolescents’ perceptions of their peers engaging in substance use also appears important.

Brook and colleagues  conducted an integrated analysis from three longitudinal studies to examine predictors of cannabis use among adolescents and consistently found that adolescents were more likely to use cannabis if they believed their peers used it as well.Urberg and others found similar results where adolescents with close friendships with peers who drink alcohol and/or smoke cigarettes were more likely to use those respective substances.To have a holistic understanding of an adolescent’s life, it is necessary to account for school-related factors, since adolescents spend most of their time in school. Positive school perception  and participating in extracurricular activities  have been identified as protective factors in preventing adolescent substance use.A longitudinal school-based survey of students in 7th and 9th grade conducted in Washington State, USA, and Victoria, Australia found that those who were more likely to report low school commitment  had higher odds of using cannabis.Furthermore, results from a cross-sectional study conducted in Connecticut found adolescents who participated in extracurricular activities had lower odds for both lifetime and 30-day cannabis use.

Another study investigating even higher doses of CBD  also observed no cognitive or psychomotor impairments . This is particularly relevant for medical cannabis users, who commonly use CBD in the daytime to control symptoms. In line with a safety-focused approach, we recommend initiating cannabis when the patient is not performing safety sensitive activities until the absence of impairment has been established, as is done with many other pharmacotherapies. Generally, it is believed cannabis can be safely used with the majority of medications . A common concern is the concomitant use with CNS depressants leading to potential pharmacodynamic interactions. While importantly there are few formal drug-drug interactions, additive pharmacodynamic effects could lead to sedative or cognitively impairing adverse events. Clinicians should screen for recreational, prescription, and over-the-counter medications. Common depressants such as alcohol, opioids, antipsychotics, benzodiazepines, tricyclic antidepressants,vertical grow rack or antiepileptics may worsen sedation & cognitive impairment when coingested with cannabis .

Cannabis is metabolized in the liver by CYP 450 isoenzymes. THC is predominantly oxidized by CYP2C9, CYP2C19, and CYP3A4. CBD is predominantly metabolized by CYP2C19 and CYP3A4. As such, CYP inhibitors or inducers may alter serum levels of these cannabinoids via pharmacokinetic drug interactions. Notably, CBD is a potent CYP 3A4 inhibitor and risks interacting with some medications in the following table  Currently known cannabinoid drug interactions are summarized in Table 2. It should be noted that although cannabis could theoretically impact drugs metabolized by the CYP enzyme family, in many cases, the relevance of cell or animal experimental findings has not yet been established in humans . Clinical trials involving Nabiximols have the most robust data surrounding clinical drug interactions and found most to be not clinically significant. Instead, pharmacodynamic interactions are more common with compounded sedation being seen with a number of drugs. However, more safety and drug interaction studies are needed. If a patient is at high risk, using high doses of cannabinoids, or is using a medication with a known or potential drug interaction careful monitoring should be implemented .

Each route of administration has different pharmacokinetic properties, and thus different onset and duration of action.The two most common medical cannabis routes of administration are inhalation and oral . Oral oil is preferred in most patients as it eliminates respiratory risk and allows for accurate dosing. Inhalation can be used, however, there is an increased risk for respiratory harm, especially in those with pre-existing respiratory conditions. If inhalation is deemed necessary, dried cannabis vaporization is recommended. Concentrates should be avoided due to the potential for contaminants, difficulties in accurate dosing, and the potential for health harms such as EVALI. Other dosage forms are available  but there is insufficient safety evidence to make recommendations at this time. Regulatory protocols within a region and the source patients are obtaining their cannabis from dictates the risk of exposure to product contaminants. For example, in the legal Canadian market, cannabis grow racks producers must pass strict federal government mandated regulations with standardized testing for contaminants. In unregulated markets, there is a much greater risk that products may contain harmful matter.

Extraction processes to form concentrated cannabis products  can involve solvents, which may leave toxic residues for consumption.High-quality cannabis products, free of contaminants and toxins, and from a regulated source, which has been tested according to regulatory requirements, are preferred for all patients . Clinicians in collaboration with their patients should consider product safety risks of concentrated products if they are being used in treatment . THC is the primary psychoactive component of cannabis. The majority of adverse events related to cannabis are THC-dose dependent. By contrast, CBD has a greatly reduced adverse event profile of cannabis use. Patient circumstance should be carefully considered when choosing an appropriate strain, as each strain could lead to a difference in response . In particular, there is a safety risk of high THC products in specific groups  such as the elderly, under 25, history of mental health, heart conditions, other conditions where there may be sensitivities with THC  with symptoms that may compound the effects of THC, and those in safety sensitive occupations .

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

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

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

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

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

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

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

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