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BACKGROUND: In 2018, New York City (NYC) implemented a tobacco-free pharmacy law as part of a comprehensive policy approach to curb tobacco use. This study models the reduction in tobacco retailer density following the ban to examine differences in the policy's impact across neighbourhoods. METHODS: Tobacco retailer density per 1000 residents was calculated in July 2017 for each of NYC's Neighborhood Tabulation Areas (NTAs, n=188) before and after removing pharmacies as licensed tobacco retailers. Pearson correlations and linear regression (with predictors scaled to 10 unit increments) measured associations between the projected change in retailer density after the ban and NTA demographic characteristics. RESULTS: On average, retailer density decreased by 6.8% across neighbourhoods (SD: 6.3), with 17 NTAs experiencing reductions over 15%. Density reduction was greater in NTAs with higher median household income (r: 0.41, B: 1.00, p<0.0001) and a higher proportion of non-Hispanic white residents (r: 0.35, B: 0.79, p<0.0001). NTAs with a higher percentage of adults with less than a high school education (r: −0.44, B: −2.60, p<0.0001) and a higher proportion of Hispanic residents (r: −0.36, B: −1.07, p<0.0001) benefited less from the policy. These relationships held after assessing absolute changes in density (vs per cent change). CONCLUSIONS: NYC's tobacco-free pharmacy law substantially reduces tobacco retailer density overall, but the impact is not equal across neighbourhoods. In order to minimise disparities in the tobacco retail environment, local governments considering a similar ban should supplement this strategy with other retailer restrictions to achieve equitable outcomes.

BACKGROUND: Nearly half of marijuana users in the United States also smoke cigarillos, with many using the products as marijuana "blunts." The relationship between marijuana legalization and tobacco retail has not yet been examined. This study uses tobacco sales data to compare the cigarillo marketplace in states with legalized recreational marijuana to the overall U.S. marketplace in 2016. METHODS: Cigarillo sales data from 2016 were obtained from the Nielsen Research Company in the following market regions: Denver, CO; Seattle, WA; Portland, OR; and the overall U.S. Descriptive statistics highlighted differences in the market share of various product features (e.g., flavors, brand, pack size) across regions. RESULTS: Characteristics such as fruit flavors, single sticks, and 2–3 packs were more popular in legal marijuana regions compared to the overall U.S. Black & Mild, a brand not traditionally used for blunts, was the top brand nationally (32.8% market share), but Swisher was the top brand in legal marijuana regions. In Seattle and Portland, for example, over half the of cigarillo sales were for Swisher products (59.1% and 52.1%, respectively). Cigarillo wraps (i.e., no tobacco filler) were particularly popular in Denver, constituting 11.4% all cigarillo sales versus 2.8% nationally. CONCLUSIONS: Cigarillo product characteristics traditionally associated with blunt use may shape the tobacco market in legal marijuana regions. As more states continue to legalize recreational marijuana, state and local governments should anticipate the potential impact on the tobacco marketplace and implement tobacco control policies (e.g., flavor bans, minimum pack sizes) that discourage product use.

Background and Aims Most US states have passed medical marijuana laws (MMLs), with great variation in program regulation impacting enrollment rates. We aimed to compare changes in rates of marijuana use, heavy use and cannabis use disorder across age groups while accounting for whether states enacted medicalized (highly regulated) or non-medical mml programs. Design Difference-in-differences estimates with time-varying state-level MML coded by program type (medicalized versus non-medical). Multi-level linear regression models adjusted for state-level random effects and covariates as well as historical trends in use. Setting Nation-wide cross-sectional survey data from the US National Survey of Drug Use and Health (NSDUH) restricted use data portal aggregated at the state level. Participants Participants comprised 2004–13 NSDUH respondents (n ~ 67 500/year); age groups 12–17, 18–25 and 26+ years. States had implemented eight medicalized and 15 non-medical MML programs. Measurements Primary outcome measures included (1) active (past-month) marijuana use; (2) heavy use (> 300 days/year); and (3) cannabis use disorder diagnosis, based on DSM-IV criteria. Covariates included program type, age group and state-level characteristics throughout the study period. Findings Adults 26+ years of age living in states with non-medical MML programs increased past-month marijuana use 1.46% (from 4.13 to 6.59%, P = 0.01), skewing towards greater heavy marijuana by 2.36% (from 14.94 to 17.30, P = 0.09) after MMLs were enacted. However, no associated increase in the prevalence of cannabis use disorder was found during the study period. Our findings do not show increases in prevalence of marijuana use among adults in states with medicalized MML programs. Additionally, there were no increases in adolescent or young adult marijuana outcomes following MML passage, irrespective of program type. Conclusions Non-medical marijuana laws enacted in US states are associated with increased marijuana use, but only among adults aged 26+ years. Researchers and policymakers should consider program regulation and subgroup characteristics (i.e. demographics) when assessing for population level outcomes. Researchers and policymakers should consider program regulation and subgroup characteristics (i.e. demographics) when assessing for population level outcomes.

ABSTRACTGiven the burden of HIV and other sexually transmitted infections among adolescents who are legal minors, it is critical that they be included in biomedical sexual health trials to ensure that new prevention and treatment interventions are safe, effective, and acceptable for their use. However, adolescents are often not well represented in clinical trials. We provide an overview of the available evidence regarding adolescent and parent willingness for adolescents to participate in biomedical sexual health trials, parental involvement in the permission‐consent process, management of differences and discord among adolescents and parents, and parental involvement throughout the study period. We also outline recommendations for current practice and areas for future research.

There is considerable interest in the effects of medical marijuana laws (MML) on marijuana use in the USA, particularly among youth. The article by Stolzenberg et al. (2015) "The effect of medical cannabis laws on juvenile cannabis use" concludes that "implementation of medical cannabis laws increase juvenile cannabis use". This result is opposite to the findings of other studies that analysed the same US National Survey on Drug Use in Households data as well as opposite to studies analysing other national data which show no increase or even a decrease in youth marijuana use after the passage of MML. We provide a replication of the Stolzenberg et al. results and demonstrate how the comparison they are making is actually driven by differences between states with and without MML rather than being driven by pre and post-MML changes within states. We show that Stolzenberg et al. do not properly control for the fact that states that pass MML during 2002–2011 tend to already have higher past-month marijuana use before passing the MML in the first place. We further show that when within-state changes are properly considered and pre-MML prevalence is properly controlled, there is no evidence of a differential increase in past-month marijuana use in youth that can be attributed to state MML.

There is considerable interest in the effects of medical marijuana laws (MML) on marijuana use in the USA, particularly among youth. The article by Stolzenberg et al. (2015) "The effect of medical cannabis laws on juvenile cannabis use" concludes that "implementation of medical cannabis laws increase juvenile cannabis use". This result is opposite to the findings of other studies that analysed the same US National Survey on Drug Use in Households data as well as opposite to studies analysing other national data which show no increase or even a decrease in youth marijuana use after the passage of MML. We provide a replication of the Stolzenberg et al. results and demonstrate how the comparison they are making is actually driven by differences between states with and without MML rather than being driven by pre and post-MML changes within states. We show that Stolzenberg et al. do not properly control for the fact that states that pass MML during 2002–2011 tend to already have higher past-month marijuana use before passing the MML in the first place. We further show that when within-state changes are properly considered and pre-MML prevalence is properly controlled, there is no evidence of a differential increase in past-month marijuana use in youth that can be attributed to state MML.

BACKGROUND: Medical cannabis laws (MCL) have received increased attention as potential drivers of cannabis use (CU), but little work has explored how the broader policy climate, independent of MCL, may impact CU outcomes. We explored the association between state-level policy liberalism and past-year cannabis use (CU) and cannabis use disorder (CUD). METHODS: We obtained state-level prevalence of past-year CU and CUD for ages 12-17, 18-25, and 26+ from the 2004-2006 and 2010-2012 National Surveys on Drug Use and Health. States were categorized as liberal, moderate, or conservative based on state-level policy liberalism rankings in 2005 and 2011. Linear models with random state effects examined the association between policy liberalism and past-year CU and CUD, adjusting for state-level social and economic covariates and medical cannabis laws. RESULTS: In adjusted models, liberal states had higher average past-year CU than conservative states for ages 12-17 (+1.58 percentage points; p=0.03) and 18-25 (+2.96 percentage points; p=0.01) but not for 26+ (p=0.19). CUD prevalence among past year users was significantly lower in liberal compared to conservative states for ages 12-17 (−2.87 percentage points; p=0.045) and marginally lower for ages 26+ (−2.45 percentage points; p=0.05). CONCLUSION: Liberal states had higher past-year CU, but lower CUD prevalence among users, compared to conservative states. Researchers and policy makers should consider how the broader policy environment, independent of MCL, may contribute to CU outcomes.

Little is known about how adolescents' and parents' thoughts about participation in clinical trials change over time. In this study, adolescent (14-17 years)–parent dyads were asked about willingness to participate in a hypothetical reproductive health study. A year later, they were asked how their thoughts about the study had changed. Qualitative responses were coded and analyzed using framework analysis. Thirty-two percent of adolescents and 18% of parents reported changes in thoughts; reasons included general changes in perception, clearer understanding, new knowledge or experiences, increased maturity/age of adolescents, and changes in participants independent of the study. Adolescents and parents may benefit from learning about studies multiple times, and investigators should account for development and new experiences to optimize adolescent research enrollment.

Objectives. To assess the association between medical marijuana laws (MMLs) and the odds of a positive opioid test, an indicator for prior use. Methods. We analyzed 1999–2013 Fatality Analysis Reporting System (FARS) data from 18 states that tested for alcohol and other drugs in at least 80% of drivers who died within 1 hour of crashing (n = 68 394). Within-state and between-state comparisons assessed opioid positivity among drivers crashing in states with an operational MML (i.e., allowances for home cultivation or active dispensaries) versus drivers crashing in states before a future MML was operational. Results. State-specific estimates indicated a reduction in opioid positivity for most states after implementation of an operational MML, although none of these estimates were significant. When we combined states, we observed no significant overall association (odds ratio [OR] = 0.79; 95% confidence interval [CI] = 0.61, 1.03). However, age-stratified analyses indicated a significant reduction in opioid positivity for drivers aged 21 to 40 years (OR = 0.50; 95% CI = 0.37, 0.67; interaction P < .001). Conclusions. Operational MMLs are associated with reductions in opioid positivity among 21- to 40-year-old fatally injured drivers and may reduce opioid use and overdose.

Objectives. To determine the association of medical marijuana laws (MMLs) with traffic fatality rates. Methods. Using data from the 1985–2014 Fatality Analysis Reporting System, we examined the association between MMLs and traffic fatalities in multilevel regression models while controlling for contemporaneous secular trends. We examined this association separately for each state enacting MMLs. We also evaluated the association between marijuana dispensaries and traffic fatalities. Results. On average, MML states had lower traffic fatality rates than non-MML states. Medical marijuana laws were associated with immediate reductions in traffic fatalities in those aged 15 to 24 and 25 to 44 years, and with additional yearly gradual reductions in those aged 25 to 44 years. However, state-specific results showed that only 7 states experienced post-MML reductions. Dispensaries were also associated with traffic fatality reductions in those aged 25 to 44 years. Conclusions. Both MMLs and dispensaries were associated with reductions in traffic fatalities, especially among those aged 25 to 44 years. State-specific analysis showed heterogeneity of the MML–traffic fatalities association, suggesting moderation by other local factors. These findings could influence policy decisions on the enactment or repealing of MMLs and how they are implemented.

Background: Little is known on how perceived availability of marijuana is associated with medical marijuana laws. We examined the relationship between medical marijuana laws (MML) and the prevalence of past-month marijuana use, with perceived availability of marijuana. Methods: Data were from respondents included in the National Survey of Drug Use and Health restricted use data portal 2004–2013. Multilevel logistic regression of individual-level data was used to test differences between MML and non-MML states and changes in prevalence of past-month marijuana use and perceived availability from before to after passage of MML among adolescents, young adults and older adults controlling for demographics. Results: Among adults 26+, past-month prevalence of marijuana use increased from 5.87% to 7.15% after MML passage (Adjusted Odds Ratio (AOR): 1.24 [1.16–1.31]), but no change in prevalence of use was found for 12–17 or 18–25 year-olds. Perceived availability of marijuana increased after MML was enacted among those 26+ but not in younger groups. Among all age groups, prevalence of marijuana use and perception of it being easily available was higher in states that would eventually pass MML by 2013 compared to those that had not. Perceived availability was significantly associated with increased risk of past-month marijuana use in all age groups. Conclusion: Evidence suggests perceived availability as a driver of change in use of marijuana due to MML. To date, this has only occurred in adults 26+ and different scenarios that could explain this change need to be further explored.

BackgroundDistinguishing a disorder of persistent and impairing grief from normative grief allows clinicians to identify this often undetected and disabling condition. As four diagnostic criteria sets for a grief disorder have been proposed, their similarities and differences need to be elucidated.MethodsParticipants were family members bereaved by US military service death (N = 1732). We conducted analyses to assess the accuracy of each criteria set in identifying threshold cases (participants who endorsed baseline Inventory of Complicated Grief ⩾30 and Work and Social Adjustment Scale ⩾20) and excluding those below this threshold. We also calculated agreement among criteria sets by varying numbers of required associated symptoms.ResultsAll four criteria sets accurately excluded participants below our identified clinical threshold (i.e. correctly excluding 86-96% of those subthreshold), but they varied in identification of threshold cases (i.e. correctly identifying 47-82%). When the number of associated symptoms was held constant, criteria sets performed similarly. Accurate case identification was optimized when one or two associated symptoms were required. When employing optimized symptom numbers, pairwise agreements among criteria became correspondingly 'very good' (κ = 0.86-0.96).ConclusionsThe four proposed criteria sets describe a similar condition of persistent and impairing grief, but differ primarily in criteria restrictiveness. Diagnostic guidance for prolonged grief disorder in International Classification of Diseases, 11th Edition (ICD-11) functions well, whereas the criteria put forth in Section III of Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) are unnecessarily restrictive.