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Introduction: Cannabis use to alleviate medical symptoms is increasing in middle-aged and older adults. Cognitive impairment associated with cannabis use may be especially detrimental to these understudied age groups. We hypothesized that among middle-aged and older adults who used cannabis for 12 months, frequent (≥3 days/week) compared with nonfrequent (≤2 days/week) use will be associated with cognitive impairment. Materials and Methods: We performed secondary analysis on data from a clinical trial of cannabis use for medical symptoms. Participants ( n =62) were ≥45 years, and completed a baseline and at least one postbaseline visit. Cognitive domains were assessed through the Cambridge Neuropsychological Test Automated Battery. Cannabis use was assessed prospectively through daily smartphone diaries. Frequency of cannabis use was a binary predictor in a mixed-effects logistic regression model predicting cognitive impairment adjusted for baseline cognitive functioning. Results: At baseline, participants were primarily nonfrequent cannabis users; however, in all other time periods, most participants were frequent users (range: 55-58%). Cognitive outcomes did not differ between frequent and nonfrequent cannabis users. However, in sensitivity analyses, respondents with problematic cannabis use scored significantly worse on one cognitive domain compared to those without problematic cannabis use. Conclusions: In a clinical sample of adults aged ≥45 years, no longitudinal associations were found between cannabis use and cognitive functioning. However, a few significant associations were observed between problematic use and cognitive functioning. Further research is needed to assess the impact of cannabis use on adults, particularly those aged ≥65 years, and to investigate potential subtler influences of cannabis use on cognition. ClinicalTrials.gov ID: NCT03224468.

Introduction: Quantification of consumption patterns of the primary psychoactive compounds in cannabis, which cause euphoria or intoxication, is sorely needed to identify potential risks and benefits of use and to provide meaningful safety information to the public. The diversity of products available, multiple methods of administration, and lack of labeling of products have made such quantification challenging. Our group is developing a survey instrument for estimating the quantity of delta 9-tetrahydrocannabinol (THC) consumed in population samples, which is flexible and incorporates individualized reports of patterns of consumption. This study provides an illustration of a procedure for translating self-reported consumption into milligrams of THC (mgTHC), which may serve as a working model for future quantification efforts. Methods: Social media advertising was leveraged to enroll 5627 adults who use cannabis into an online, anonymous survey study. Only those who used cannabis in the past 7 days, used flower or concentrate products, and who chose to report their quantity of use in hits per day or grams per week ( n =3211) were included in this report. Formulas were used to estimate mgTHC used per day, in hits per day or grams per week; potency (%THC); constants for estimating the amount of material consumed for each hit; and a method of administration efficiency constant to account for THC loss due to the administration method. Results: The estimate for mgTHC used per day was M =92.8 mg/day (SD=97.2 mg; 1st-3rd quartile range=25-132 mg). The estimated quantity of use was much lower for those reporting in hits ( M =43.7 mg, SD=43.8) than for those reporting in grams ( M =115.1 mg, SD=107.0). The estimated rate of binge use in the past week, arbitrarily defined as more than 50 mgTHC within any one daily time quadrant, was 6.8%, which increased to 29.3% if 25 mgTHC was used. Conclusions: The approach illustrated in this study goes beyond existing cannabis measures by asking participants to provide highly detailed estimates of their past 7-day use patterns and then applying a logical formula to translate this information into mgTHC. This initial procedure has limitations and lacks generalization; however, we hope this demonstration stimulates testing of similar approaches and relevant laboratory experiments that will enhance the validity of cannabis consumption estimation procedures.

Aim: Standardized survey measures that capture diverse cannabis consumption patterns are needed to inform public health and policy. Our team is developing a flexible, personalized, low-burden survey item inventory to measure cannabis use patterns and estimate milligrams of THC (mgTHC) consumption in large samples. This study aimed to identify measurement gaps and analysis implications associated with an initial pool of candidate items that assessed use of cannabis flower and concentrate products (smoked and/or vaporized). Methods: Adult cannabis consumers ( n =4247) completed an online survey assessing cannabis use frequency, quantity, product types, product potencies (%THC), and methods of administration. Participants chose to report their consumption quantities using one of three units: "hits per day," "grams per week," or "joints per week." Respondents also indicated whether their past 7-day consumption pattern represented their typical pattern. Results: Eighty-one percent had used cannabis daily in the past week. Thirty-two percent, 53%, and 15% chose to report flower and concentrate consumption quantity in hits, grams, and joints, respectively. Approximately 80-90% of responses for the number of hits, grams, and joints consumed were less than the maximum response option-suggesting that response options captured the full range of potential cannabis consumption behaviors. Those who chose grams or joints units were generally more likely to endorse higher risk cannabis use (e.g., morning use, high %THC products) in the past week than those who chose the hits unit (adjusted Odds Ratio range: 1.2-3.9). Among those who reported that the past week represented their typical behavior (83%), past 30-day and past 7-day frequencies were highly correlated (Spearman's Rho=0.77)-supporting the feasibility of using lower burden "typical week" items to extrapolate patterns beyond a 1-week time frame. Conclusion: Results from this online convenience sample of frequent cannabis consumers suggest that the current items yield coherent and expected response patterns. Although additional testing is required, a standardized, flexible survey instrument for large-scale assessment of cannabis patterns and calculation of mgTHC seems within reach.