Cannabidiol (CBD) Use by Older Adults for Acute and Chronic Pain.

Legalization of cannabidiol (CBD) products has ignited interest in clinical practice and research. One desired indication includes possible pain-relieving effects of CBD. The purposes of the current article are to (1) clarify terminology relevant to cannabinoids; (2) explain and understand the pharmacotherapeutics of CBD; (3) examine research of the current use of CBD by older adults for treating pain; (4) discuss safety considerations with using CBD products; and (5) provide best practice recommendations for clinicians as they advise their older adult patients. A review of the literature demonstrated mixed results on the efficacy of CBD in relieving pain in older adults. There is inconsistency in the labeling of over-the-counter CBD products that can result in safety issues and will require more federal quality control. Likewise, gaps in knowledge regarding safety and efficacy of CBD use in older adults are vast and require further research. [Journal of Gerontological Nursing, 47(7), 6-15.].

Geographic variation in inhaled corticosteroid use for children with persistent asthma in Medicaid.

OBJECTIVE: Geographic variation in the rates of inhaled corticosteroid (ICS) use for children with persistent asthma in Medicaid has been reported, but the source of this variation is unknown. The objective of this study was to quantify the geographic variation in ICS use for children with persistent asthma in Medicaid that remains after adjusting for the characteristics of children in an area. METHODS: Data from the 2005-2007 Medicaid Analytic eXtract files were used. Frequent fills of short-acting beta2-agonist (SABA) were used to identify children 5-18 years of age with persistent asthma across the United States. A child was considered to have used an ICS if the child initially filled an ICS following frequent SABA use. Areas were determined using published methods, and the unadjusted ICS rate and the area treatment ratio for ICS, which adjusted for demographic and clinical characteristics, were calculated for each area. RESULTS: Of 15,917 children, 13% used an ICS. The median unadjusted ICS rate for all areas was 10% but ranged from 0% to 64%. ICS use was less than expected for more than half of the areas based on the characteristics of the children in the area, but use was nearly five times what was expected in some areas. Areas with higher than expected ICS use were found contiguous to areas with lower than expected use. CONCLUSIONS: Geographic variation in ICS not attributable to the demographic and clinical characteristics of the children in an area exists and could prove useful in the struggle to reduce asthma exacerbation rates.

Effect of Blood Collection Time on Measured Δ9-Tetrahydrocannabinol Concentrations: Implications for Driving Interpretation and Drug Policy.

BACKGROUND: In driving-under-the-influence cases, blood typically is collected approximately 1.5-4 h after an incident, with unknown last intake time. This complicates blood Δ(9)-tetrahydrocannabinol (THC) interpretation, owing to rapidly decreasing concentrations immediately after inhalation. We evaluated how decreases in blood THC concentration before collection may affect interpretation of toxicological results. METHODS: Adult cannabis smokers (≥1×/3 months, ≤3 days/week) drank placebo or low-dose alcohol (approximately 0.065% peak breath alcohol concentration) 10 min before inhaling 500 mg placebo, 2.9%, or 6.7% vaporized THC (within-individuals), then took simulated drives 0.5-1.3 h postdose. Blood THC concentrations were determined before and up to 8.3 h postdose (limit of quantification 1 µg/L). RESULTS: In 18 participants, observed Cmax (at 0.17 h) for active (2.9 or 6.7% THC) cannabis were [median (range)] 38.2 µg/L (11.4-137) without alcohol and 47.9 µg/L (13.0-210) with alcohol. THC Cmax concentration decreased 73.5% (3.3%-89.5%) without alcohol and 75.1% (11.5%-85.4%) with alcohol in the first half-hour after active cannabis and 90.3% (76.1%-100%) and 91.3% (53.8%-97.0%), respectively, by 1.4 h postdose. When residual THC (from previous self-administration) was present, concentrations rapidly decreased to preinhalation baselines and fluctuated around them. During-drive THC concentrations previously associated with impairment (≥8.2 µg/L) decreased to median <5 µg/L by 3.3 h postdose and <2 µg/L by 4.8 h postdose; only 1 participant had THC ≥5 µg/L after 3.3 h. CONCLUSIONS: Forensic blood THC concentrations may be lower than common per se cutoffs despite greatly exceeding them while driving. Concentrations during driving cannot be back-extrapolated because of unknown time after intake and interindividual variability in rates of decrease.

Cannabis effects on driving longitudinal control with and without alcohol.

Although evidence suggests cannabis impairs driving, its driving-performance effects are not fully characterized. We aimed to establish cannabis' effects on driving longitudinal control (with and without alcohol, drivers' most common drug combination) relative to psychoactive ∆(9) -tetrahydrocannabinol (THC) blood concentrations. Current occasional (≥1×/last 3 months, ≤3 days per week) cannabis smokers drank placebo or low-dose alcohol, and inhaled 500 mg placebo, low (2.9%), or high (6.7%) THC vaporized cannabis over 10 min ad libitum in separate sessions (within-subject, six conditions). Participants drove (National Advanced Driving Simulator, University of Iowa) simulated drives 0.5-1.3 h post-inhalation. Blood and breath alcohol samples were collected before (0.17 and 0.42 h) and after (1.4 and 2.3 h) driving. We evaluated the mean speed (relative to limit), standard deviation (SD) of speed, percent time spent >10% above/below the speed limit (percent speed high/percent speed low), longitudinal acceleration, and ability to maintain headway relative to a lead vehicle (headway maintenance) against blood THC and breath alcohol concentrations (BrAC). In N=18 completing drivers, THC was associated with a decreased mean speed, increased percent speed low and increased mean following distance during headway maintenance. BrAC was associated with increased SD speed and increased percent speed high, whereas THC was not. Neither was associated with altered longitudinal acceleration. A less-than-additive THC*BrAC interaction was detected in percent speed high (considering only non-zero data and excluding an outlying drive event), suggesting cannabis mitigated drivers' tendency to drive faster with alcohol. Cannabis was associated with slower driving and greater headway, suggesting a possible awareness of impairment and attempt to compensate. Copyright © 2016 John Wiley & Sons, Ltd.

Controlled Cannabis Vaporizer Administration: Blood and Plasma Cannabinoids with and without Alcohol.

BACKGROUND: Increased medical and legal cannabis intake is accompanied by greater use of cannabis vaporization and more cases of driving under the influence of cannabis. Although simultaneous Δ(9)-tetrahydrocannabinol (THC) and alcohol use is frequent, potential pharmacokinetic interactions are poorly understood. Here we studied blood and plasma vaporized cannabinoid disposition, with and without simultaneous oral low-dose alcohol. METHODS: Thirty-two adult cannabis smokers (≥1 time/3 months, ≤3 days/week) drank placebo or low-dose alcohol (target approximately 0.065% peak breath-alcohol concentration) 10 min before inhaling 500 mg placebo, low-dose (2.9%) THC, or high-dose (6.7%) THC vaporized cannabis (6 within-individual alcohol-cannabis combinations). Blood and plasma were obtained before and up to 8.3 h after ingestion. RESULTS: Nineteen participants completed all sessions. Median (range) maximum blood concentrations (Cmax) for low and high THC doses (no alcohol) were 32.7 (11.4-66.2) and 42.2 (15.2-137) µg/L THC, respectively, and 2.8 (0-9.1) and 5.0 (0-14.2) µg/L 11-OH-THC. With alcohol, low and high dose Cmax values were 35.3 (13.0-71.4) and 67.5 (18.1-210) µg/L THC and 3.7 (1.4-6.0) and 6.0 (0-23.3) µg/L 11-OH-THC, significantly higher than without alcohol. With a THC detection cutoff of ≥1 µg/L, ≥16.7% of participants remained positive 8.3 h postdose, whereas ≤21.1% were positive by 2.3 h with a cutoff of ≥5 µg/L. CONCLUSIONS: Vaporization is an effective THC delivery route. The significantly higher blood THC and 11-OH-THC Cmax values with alcohol possibly explain increased performance impairment observed from cannabis-alcohol combinations. Chosen driving-related THC cutoffs should be considered carefully to best reflect performance impairment windows. Our results will help facilitate forensic interpretation and inform the debate on drugged driving legislation.

Predicting changes in driving performance in individuals who use cannabis following acute use based on self-reported readiness to drive.

OBJECTIVE: It is unclear to what extent individuals who use cannabis can accurately assess their ability to drive safely following cannabis use, and lack of understanding as to what factors influence changes in driving performance following cannabis use. This research explores whether self-reported readiness to drive (RTD) and previous experience (PE) using cannabis within 2 h of driving can predict observed changes in driving performance following acute cannabis use. METHODS: Individuals who used cannabis at least monthly completed a baseline simulated drive, were dosed with cannabis of approximately 6.18% THC, then drove at approximately 30-minutes, 90-minutes, and 180-minutes post-dose. Before each drive, participants were asked if they felt safe to drive (on real roadways, not the simulator), a yes/no question (RTD-yes/RTD-no). Venous blood was drawn at baseline and approximately 15-minutes post-dose. Cannabis use history was obtained and included whether the participant had ever driven within 2 h of use (PE-yes/PE-no) and how many days out of the past 30 they had done so (NPD). Drives were segmented into events delineated by changes in the driving environment. Within events, standard deviation of lateral position (SDLP), average speed, and number of lane departures were calculated, and differences from baseline were modeled using mixed-effects regression. Models considered covariates of time, event, and speed, and used RTD-yes/RTD-no, PE-yes/PE-no, NPD, and their interactions as potential predictors. Conditional R2 was used to compare the predictive ability of RTD versus change in Delta-9-THC. DATA SOURCES: Data were collected from 30 individuals who use cannabis and included cannabis use patterns, driving behaviors after use, self-reported RTD, measures of driving performance, and cannabinoid blood levels. RESULTS: RTD-no predicted a 2.60 cm increase in SDLP relative to baseline (95 % CI: 0.43, 4.73, p = 0.018). Average speeds generally decreased relative to baseline, except for RTD-yes with PE-yes (+1.08 mph, 95 % CI: 0.05, 2.11). NPD predicted increased speed among RTD-yes (+0.11 mph per additional day, 95 % CI: 0.01, 0.22) and decreased speed among RTD-no (-0.06 mph per additional day, 95 % CI: -0.18, 0.32). The difference in these effects was statistically significant (p = 0.038). RTD, PE, and NPD were not significant predictors of changes in number of lane departures. For all outcomes, models using RTD achieved higher conditional R2 than models that replaced this variable with change in Delta-9-THC. Differences were most prominent when modeling change in speed with NPD (R2=0.544 with RTD vs. R2=0.481 with change in Delta-9-THC). SIGNIFICANCE OF RESULTS: These results suggest individuals who use cannabis can somewhat self-identify when they are likely to exhibit greater degraded lateral control, although RTD does not fully explain observed degradation in performance. Past research suggests drivers may reduce speed to compensate for recognized impairment following acute cannabis use. Our findings suggest this to be true for those who reported never having previously driven within 2 h of cannabis use or reported RTD-no, but not for those who had previously driven within 2 h of cannabis use and reported RTD-yes. This indicates compensatory behavior is not uniform and helps focus public health outreach efforts.

Unrelenting Growth and Diversification: Using the Health and Retirement Study to Illuminate Cannabis Use Among Aging Americans.

BACKGROUND AND OBJECTIVES: Cannabis use among aging Americans continues to increase. We examine correlates of cannabis use including attitudes, state of residence, health status, and service use. RESEARCH DESIGN AND METHODS: Using the 2018 Health and Retirement Study Cannabis module completed by 1,372 respondents aged 50 and older, we distinguished current cannabis users from those who have never used or have some prior use. We linked 2018 and 2016 core HRS data and used multinomial regressions to identify associations among current use, attitudes, place of residence, as well as current (2018) and past (2016) medical conditions, pain, and sleep issues. We also examined associations among cannabis use, hospital stays, and outpatient medical visits. RESULTS: Past-year cannabis use reached 10.3% among aging Americans. Attitudes toward cannabis have changed over time with 4 of 5 survey respondents currently holding a favorable attitude. Attitude and state of residence were associated with current use. Cannabis users reported higher levels of pain, were more likely to use prescription opioids, and report activity limitations in both 2016 and 2018. Associations between cannabis use and sleep issues or concurrent healthcare use were not observed. DISCUSSION AND IMPLICATIONS: Changing attitudes and state legalization appear important for late middle-aged and older persons, and as many as 1 of every 5 persons over 50 may be using cannabis by 2030. Cannabis use among aging Americans warrants increased attention from care providers, program administrators, and policymakers, especially as a prevention or harm reduction strategy relative to prescription opioids.

Offering an Alternative to Persons with Chronic Pain: How Access to Cannabis May Provide an Off-Ramp from Undesired Prescription Opioid Use.

Background: Chronic pain (CP) is experienced by as many as 50 million Americans and can negatively impact physical and mental health. Prescribing opioids is the most common approach to address moderate to severe CP though these potent analgesics are associated with a significant number of side effects. One alternative some Americans are turning to for CP management is cannabis. In addition to serving as an alternative, many individuals with CP use cannabis in addition to using prescription opioids. This study examined individuals with CP who enrolled in the state of Illinois' opioid diversion program, the Opioid Alternative Pilot Program (OAPP), which offers individuals aged 21 and older a separate pathway to access medical cannabis if they have or could receive a prescription for opioids as certified by a licensed physician. Methods: Cross-sectional survey data were collected from 450 participants. We described participants and compared those who use only cannabis with those who use cannabis and opioids. Results: While 16% of the respondents were cannabis-only users, 84% of the respondents were co-users of opioids and cannabis. Both groups considered opioid use risky (100% cannabis-only, 89% co-users,). The majority (73%) of respondents sought to completely stop or never start using opioids for CP. Cannabis-only users reported lower levels of pain compared to co-users. Co-users (85%) were more likely to have their routine provider as a cannabis certifying physician than cannabis-only users (69%). Conclusion: With increasing clinical evidence, legalization and acceptance, researchers should continue to examine how cannabis may be a viable alternative to reduce the risk of prescription opioid side effects, misuse, or dependence. Our findings also inform health care providers and state policymakers who increasingly are being asked to consider how cannabis may reduce the potential for harmful outcomes among persons with CP who use prescription opioids.

Dispelling vaccine myths: MMR and considerations for practicing pharmacists.

OBJECTIVES: To discuss information surrounding the erroneous association between the measles-mumps-rubella (MMR) vaccine and autism spectrum disorders (ASDs) and to provide pharmacists with information to dispel vaccine myths. DATA SOURCES: Pharmaceutical and medical literature and public media (e.g., newspapers). SUMMARY: The diagnosis of ASDs is on the rise, and many speculations have been made as to the cause, including the MMR vaccine. A small case series article published in The Lancet in 1998 and later retracted has been the center of the controversy over whether the MMR vaccine causes ASDs. New definitive research demonstrates no link, and medical organizations state that evidence does not support a link between the MMR vaccine and ASDs. CONCLUSION: Pharmacists can play a role in providing up-do-date information to patients to dispel myths concerning vaccine safety. Accurate peer review remains an important step to ensure correct information is given to health care providers and the public.

Perceived effects of cannabis: Generalizability of changes in driving performance.

OBJECTIVE: The objective of this analysis was to determine the generalizability of the relationship between different samples of a driver's perceived state after cannabis use and related performance while operating a motor vehicle. METHODS: Data were collected from 52 subjects in a study examining the effects of cannabis on driving performance. Data were analyzed using the SAS GLM Select procedure, using stepwise selection, with subjective effects, dosing condition (placebo vs. 6.18% delta-9-tetrahydrocannabinol [THC]), and driving context as independent measures. Correlation matrices of measures of driving performance against subjective responses and dosing condition used Pearson's and Spearman's test statistics, respectively. Results were compared to a prior study from a sample of 10 subjects. RESULTS: Subjective perceptions of acute cannabis impairment remain significant predictors of driving performance and explain individual variability in driving performance degradation as well as the data, beyond that which can be explained by acute use of cannabis alone. However, the significant subjective predictors of driving performance differ between the current and prior studies. To better understand these differences, correlations between subjective effects and performance measures were evaluated, which revealed that most correlations matched directionally (e.g., an increase in "good drug effect" was correlated with an increase in standard deviation of lane position [SDLP]). When there was a mismatch, 1 or more correlations were insignificant. Dosing condition and "stoned" were perfectly consistent; "high" and "sedated" contained 1 mismatch; and "anxious," "good drug effect" and "restless" contained 3 or more mismatches. CONCLUSIONS: The results indicate that across both studies, differences in the perceived effects of cannabis are reflected in changes in both lateral and longitudinal control beyond the acute effects of cannabis, which may help explain individual variability in response to acute intoxication. However, the generalizability of these findings is lacking, as shown by inconsistencies in when and where subjective effects were significant. Other factors such as frequency of use, usage type, the evolving profile of a cannabis user, as well as other individual differences should be considered to explain this additional variability.

A study of self-reported personal cannabis use and state legal status and associations with engagement in and perceptions of cannabis-impaired driving.

Objective: The objectives of the current study were to (1) characterize predictors of perceived risk of driving within 2 h of cannabis use and driving after cannabis use in a sample of adults who have used cannabis in the past year and (2) determine whether the influence of these predictors vary by state legalizations status.Methods: Data for this study were from online surveys. Study participants from Colorado, Iowa, and Illinois were included if they reported being between 25 and 40 years old and had a history of cannabis use. Outcome variables included (1) days of cannabis use per month, (2) reported driving within 2 h of cannabis use (vs. not driving within 2 h as reference), (3) proportion of driving after cannabis use days per month (days of driving a car within 2 h of cannabis use per month/days of cannabis use per month), and (4) perception of safety of driving after cannabis use. Potential predictors included age of first use of cannabis, gender, education status, and state of residence. The SAS GLMSELECT Procedure was used for the analysis.Results: Increased age of first use of cannabis was associated with decreased days of cannabis use per month (B = -0.51 days/month per year), a reduction in the proportion of driving after cannabis use days per month (B = -0.02 per month), and decreased perception of safety of driving after cannabis use (B = -0.06 per year). Female gender was also associated with less use (B = -2.3 days per month), a lower proportion of driving following use (B = -0.06 days driving/days used), and decreased perception of safety (B = -0.29). In addition, residents of Colorado reported using the most days, had the highest likelihood of driving within 2 h of use, and had the most positive perceptions of being able to safely drive after cannabis use.Conclusions: The delay in onset of cannabis use may mitigate its use among adults and driving after cannabis use. This has important implications for driver safety. Intervention programs for reducing cannabis's effects on driving should focus on individuals with early onset of use, male drivers, and drivers in states where cannabis for adult recreational use is legalized.

Mechanisms of cannabis impairment: Implications for modeling driving performance.

Past research on cannabis has been limited in scope to THC potencies lower than legally available and efforts to integrate the effects into models of driving performance have not been attempted to date. The purpose of this systematic review is to understand the implications for modeling driving performance and describe future research needs. The risk of motor vehicle crashes increases 2-fold after smoking marijuana. Driving during acute cannabis intoxication impairs concentration, reaction time, along with a variety of other necessary driving-related skills. Changes to legislation in North America and abroad have led to an increase in cannabis' popularity. This has given rise to more potent strains, with higher THC concentrations than ever before. There is also rising usage of novel ingestion methods other than smoking, such as oral cannabis products (e.g., brownies, infused drinks, candies), vaping, and topicals. The PRISMA guidelines were followed to perform a systematic search of the PubMed database for peer-reviewed literature. Search terms were combined with keywords for driving performance: driving, performance, impairment. Grey literature was also reviewed, including congressional reports, committee reports, and roadside surveys. There is a large discrepancy between the types of cannabis products sold and what is researched. Almost all studies that used inhalation as the mode of ingestion with cannabis that is around 6% THC. This pales in comparison to the more potent strains being sold today which can exceed 20%. Which is to say nothing of extracts, which can contain 60% or more THC. Experimental protocol is another gap in research that needs to be filled. Methodologies that involve naturalistic (real world) driving environments, smoked rather than vaporized cannabis, and non-lab certified products introduce uncontrollable variables. When considering the available literature and the implications of modeling the impacts of cannabis on driving performance, two critical areas emerge that require additional research: The first is the role of cannabis potency. Second is the route of administration. Does the lower peak THC level result in smaller impacts on performance? How long does potential impairment last along the longer time-course associated with different pharmacokinetic profiles. It is critical for modeling efforts to understand the answers to these questions, accurately model the effects on driver performance, and by extension understand the risk to the public.

Older Cannabis Users Are Not All Alike: Lifespan Cannabis Use Patterns.

Although several studies have examined individual-level correlates of cannabis use in later life, there is scant evidence identifying heterogeneity among older users. Using data from Colorado, this study examines variability in lifespan patterns of cannabis use among individuals aged 60 years and older. Sample respondents reported cannabis use in the past year and frequency of use in four periods of adulthood. Analyses used a multi-way contingency table to identify mutually exclusive subgroups of cannabis users based on lifetime reports of use and linear probability models to identify predictors of group identity. Three subgroups of older cannabis users were identified: new users, stop-out or intermittent users, and consistent users. The three groups varied on current use frequency and method of ingestion, as well as social and health characteristics. Screening for past history of cannabis use may help health care providers identify older adults who need health information and monitoring related to cannabis use.

Perceived effects of cannabis and changes in driving performance under the influence of cannabis.

OBJECTIVE: Reports indicate that cannabis users will adapt their driving to compensate for the perceived drug effects of cannabis. This analysis examined the relationship between driver perceptions of their state contrasted with objective measures of their performance while operating a motor vehicle. METHODS: Data was collected from ten subjects in a study examining the effects of cannabis on driving performance. Driving performance was collected on the NADS quarter-cab miniSim, a limited field of view non-motion simulator, approximately two hours after cannabis inhalation. Driving measures of both lateral and longitudinal control were included in our analysis. Subjective measures of the effects of cannabis were collected at peak and prior to driving, using visual analog scales. Data were analyzed using the SAS GLM Select procedure with subjective effect, dosing condition (placebo vs 6.9% THC), and driving event as independent measures. The stepwise selection method was used. RESULTS: The analysis of each of the subjective effects showed significant differences between the placebo and the active cannabis dosed conditions. While we found variance in difference between group means, there was greater variability between subject values. We found that subjective measures were predictive of variance in driver inputs, such as steering frequency and steering reversal rate. Variance in SDLP and other driving performance measures, however, were predicted by dosing condition. CONCLUSIONS: Overall, some of the effects perceived by the driver were better related to changes in driver inputs rather than the presence of cannabis itself. Changes in performance measures such as SDLP are better explained by dosing condition. Thus, driver's perceptions may result in changes to driving behavior that could mitigate the effect of cannabis. For both lateral and longitudinal control, an increasing perception of stimulation produced a positive effect on performance. Our results provide a better understanding of how different strains of cannabis, which produce different subjective experiences for users, could impact driving safety. Specifically, we found drug effects that produce more stimulation results in less impact on driving, while those that produce a more stoned or high feeling results in a greater negative effect on driving.

Simulated driving performance among daily and occasional cannabis users.

OBJECTIVE: Daily cannabis users develop tolerance to some drug effects, but the extent to which this diminishes driving impairment is uncertain. This study compared the impact of acute cannabis use on driving performance in occasional and daily cannabis users using a driving simulator. METHODS: We used a within-subjects design to observe driving performance in adults age 25 to 45 years with different cannabis use histories. Eighty-five participants (43 males, 42 females) were included in the final analysis: 24 occasional users (1 to 2 times per week), 31 daily users and 30 non-users. A car-based driving simulator (MiniSim™, National Advanced Driving Simulator) was used to obtain two measures of driving performance, standard deviation of lateral placement (SDLP) and speed relative to posted speed limit, in simulated urban driving scenarios at baseline and 30 min after a 15 min ad libitum cannabis smoking period. Participants smoked self-supplied cannabis flower product (15% to 30% tetrahydrocannabinol (THC). Blood samples were collected before and after smoking (30 min after the start of smoking). Non-users performed the same driving scenarios before and after an equivalent rest interval. Changes in driving performance were analyzed by repeated measures general linear models. RESULTS: Mean whole blood THC cannabinoids concentrations post smoking were use THC = 6.4 ± 5.6 ng/ml, THC-COOH = 10.9 ± 8.79 ng/mL for occasional users and THC = 36.4 ± 37.4 ng/mL, THC-COOH = 98.1 ± 90.6 ng/mL for daily users. On a scale of 0 to 100, the mean post-use score of subjective high was similar in occasional users and daily users (52.4 and 47.2, respectively). In covariate-adjusted analysis, occasional users had a significant increase in SDLP in the straight road segment from pre to post compared to non-users; non-users decreased by a mean of 1.1 cm (25.5 cm to 24.4 cm) while occasional users increased by a mean of 1.9 cm (21.7 cm to 23.6 cm; p = 0.02). Daily users also increased adjusted SDLP in straight road segments from baseline to post-use (23.2 cm to 25.0 cm), but the change relative to non-users was not statistically significant (p = 0.08). The standardized mean difference in unadjusted SDLP from baseline to post-use in the straight road segments comparing occasional users to non-users was 0.64 (95% CI 0.09 - 1.19), a statistically significant moderate increase. When occasional users were contrasted with daily users, the baseline to post changes in SDLP were not statistically significant. Daily users exhibited a mean decrease in baseline to post-use adjusted speed in straight road segments of 1.16 mph; a significant change compared to slight speed increases in the non-users and occasional users (p = 0.02 and p = 0.01, respectively). CONCLUSION: We observed a decrement in driving performance assessed by SDLP after acute cannabis smoking that was statistically significant only in the occasional users in comparison to the nonusers. Direct contrasts between the occasional users and daily users in SDLP were not statistically significant. Daily users drove slower after cannabis use as compared to the occasional use group and non-users. The study results do not conclusively establish that occasional users exhibit more driving impairment than daily users when both smoke cannabis ad libitum.

Model-based Meta-analysis to Compare Primary Efficacy-endpoint, Efficacy-time Course, Safety, and Tolerability of Opioids Used in the Management of Osteoarthritic Pain in Humans.

BACKGROUND: Despite recent therapeutic advances, osteoarthritis continues to be a challenging health problem, especially in the elderly population. Opioids, which are potent analgesics, have shown an extraordinary ability to reduce intense pain in many osteoarthritic clinical trials; however, there is an increased need for a study to integrate the reported outcomes and utilize them to achieve a better understanding. Herein, efficacy and safety aspects of opioids used to manage osteoarthritic pain were assessed and compared using a model-based meta-analysis (MBMA). METHODS: To perform the analysis, a comprehensive database consisting of pain relief compounds with information on summary-level of efficacy over time, adverse events and dropout rates was compiled from multiple sources. MBMA was conducted using a nonlinear mixed-effects modeling approach. RESULTS: The results of primary efficacy endpoint analysis indicated that the doses of oxycodone, oxymorphone, and tramadol required to produce 50% of the maximum effect were 47, 84, and 247 mg per day, respectively. Efficacytime course analysis showed that opioids had rapid time to efficacy onset, suggesting potentially powerful painrelieving effects. It was also found that gastrointestinal adverse events were the most opioid-associated and dosedependent adverse effects. In addition, the analysis revealed that opioids were well-tolerated at low to moderate doses. CONCLUSION: This MBMA provides clinically meaningful insights into the efficacy and safety profiles of oxycodone, oxymorphone, and tramadol. Resultantly, the presented framework analysis can have an impact in the clinic on drug development where it can guide: the optimization of doses of opioids required to manage osteoarthritic pain; the making of precise key decisions for the positioning of new drugs, and; the design of more efficient trials.

Measuring Attitudes Toward Medical and Recreational Cannabis Among Older Adults in Colorado.

BACKGROUND AND OBJECTIVES: Cannabis use among older adults is on the rise. Despite growing interest in the topic, there exists a paucity of standardized measures capturing cannabis-specific attitudes among older adults. Using data from a survey of older Coloradans, we create two scales that separately measure medical and recreational cannabis attitudes. We also examine how these two attitudes relate to individual-level characteristics. RESEARCH DESIGN AND METHODS: We assess reliability using Cronbach's alpha and item-rest correlations and perform confirmatory factor analyses to test the two attitude models. We conduct a seemingly unrelated regression estimation to assess how individual characteristics predict medical and recreational cannabis attitude scores. RESULTS: Twelve indicators combined into two valid and reliable scales. Both scales had a three-factor structure with affect, cognition and social perception as latent dimensions. For both scales, fit indices for the three-factor model were statistically superior when compared with other models. The three-factor structure for both scales was invariant across age groups. Age, physical health, and being a caregiver differentially predicted medical and recreational cannabis attitude scores. DISCUSSION AND IMPLICATIONS: Medical and recreational cannabis attitude scales can inform the development and evaluation of tailored interventions targeting older adult attitudes that aim to influence cannabis use behaviors. These scales also enable researchers to measure cannabis-specific attitudes among older adults more accurately and parsimoniously, which in turn can facilitate a better understanding of the complex interplay between cannabis policy, use, and attitudes.

Impact of cannabis and low alcohol concentration on divided attention tasks during driving.

OBJECTIVE: To assess divided-attention performance when driving under the influence of cannabis with and without alcohol. Three divided-attention tasks were performed following administration of placebo, cannabis, and/or alcohol. METHODS: Healthy adult cannabis users participated in 6 sessions, receiving combinations of cannabis (placebo/low-THC/high-THC) and alcohol (placebo/active) in randomized order, separated by washout periods of ≥1 week. At 0.5 hours post-dosing, participants performed simulator drives in the University of Iowa National Advanced Driving Simulator (NADS-1), a full vehicle cab simulator with a 360° horizontal field of view and motion base that provides realistic feedback. Drives contained repeated instances of three tasks: a side-mirror task (reaction to a triangle appearing in the side-mirrors), an artist-search task (select a specified artist from a navigable menu on the vehicle's console), and a message-reading task (read aloud a message displayed on the console). Blood THC and breath alcohol concentration (BrAC) were interpolated using individual power curves from samples collected approximately 0.17, 0.42, 1.4, and 2.3 hours post-dose. Driving measures during tasks were compared to equal-duration control periods occurring just prior to the task. Performance shifts, task completion, and lane departures were modeled relative to blood THC and BrAC using mixed-effects regression models. RESULTS: Each 1 µg/L increase in blood THC concentration predicted increased odds of failing to complete the artist-search task (OR: 1.05, 95% CI: 1.01-1.11, p = 0.046), increased odds of selecting at least one incorrect response (OR: 1.05, 95% CI: 1.00-1.09, p = 0.041), declines in speed during the side-mirror task (0.005 m/s, 95% CI: 0.001-0.009, p = 0.023), and longer lane departure durations during the artist-search task (0.74% of task-period, 95% CI: 0.12-1.36 p = 0.020). BrAC (approximately 0.05%) was not associated with task performance, though each 0.01 g/210 L increase predicted longer departure durations during the side-mirror task (1.41% of task-period, 95% CI: 0.08-2.76, p = 0.040) and increased standard deviation of lane position in the message-reading task (0.61 cm, 95% CI: 0.14-1.08, p = 0.011). CONCLUSIONS: With increasing medical and legal cannabis use, understanding the impact of acute cannabis use on driving performance, including divided-attention, is essential. These data indicate that impaired divided-attention performance is a safety concern.

EEG biomarkers acquired during a short, straight-line simulated drive to predict impairment from cannabis intoxication.

OBJECTIVE: As cannabis use becomes more widely accepted, there is growing interest in its effects on brain function, specifically how it may impact daily functional activities such as driving, operating machinery, and other safety-related tasks. There are currently no validated methods for quantifying impairment from acute cannabis intoxication. The objective of this study was to identify neurophysiological correlates associated with driving simulator performance in subjects who were acutely intoxicated with cannabis. These signatures could help create an EEG-based profile of impairment due to acute cannabis intoxication. METHODS: Each subject completed a three-visit study protocol. Subjects were consented and screened on the first visit. On the second and third visits, subjects were administered either 500 mg of cannabis with 6.7% delta-9-tetrahydrocannabinol (THC) or placebo using a Volcano© Digit Vaporizer in a counterbalanced fashion. EEG was acquired from subjects as they performed a series of neurocognitive tasks and an approximately 45-minute simulated drive that included a rural straight-away absent of any other cars or obstacles during the final 10 minutes.EEG data was acquired using a STAT X24 wireless sensor headset during a simulated driving scenario from 10 subjects during the THC and placebo visits. Metrics of driving performance were extracted from the driving simulator and synchronized with EEG data using a common clock. RESULTS: A within-subjects analysis showed that the standard deviation of lane position (SDLP) was significantly worse and heart rate was elevated during the dosed visit compared to the placebo visit. Consistent with our prior findings, EEG power in the Theta frequency band (4-7 Hz) in the dosed condition was significantly decreased from the placebo condition. Theta power was negatively correlated with the SDLP driving performance metric, while there were no significant correlations between any EEG measure and SDLP in the placebo condition. CONCLUSIONS: These results, in combination with prior work on the effect of cannabis intoxication during neurocognitive tasks, suggest that neurophysiological signatures associated with acute cannabis intoxication are robust and consistent across tasks, and that these signatures are significantly correlated with impaired performance in a driving simulator. Taken together, EEG data acquired during a short neurocognitive testbed and during a simulated drive may provide specific profiles of impairment associated with acute cannabis intoxication. Further research is needed to establish the impaired cognitive processes associated with these EEG biomarkers.