Cannabis (Albuquerque, N.M.)最新文献

Objective: The Diagnostic and Statistical Manual of Mental Disorders version 5 (DSM-5) defines cannabis use disorder as a polythetic unidimensional diagnosis (>2 symptoms from up to 11), but few studies have empirically evaluated the latent structure of CUD. Rasch analysis is a psychometric technique that has previously been used to validate unidimensional scales, like DSM-5 CUD.

Method: In this study, the Rasch model was used to evaluate the DSM-5 CUD criteria in a clinical sample of adults receiving inpatient treatment for substance use disorder (n = 249) reporting active cannabis use at admission. The unidimensionality of the criteria was evaluated using the Martin-Löf test and the nonparametric -T₂ test of Ponocny. Model fit was assessed using the χ² goodness of fit test for individual items.

Results: Results supported the unidimensional structure of the criteria. Symptom # 3 was the least endorsed, highest severity item. Conversely, symptom #9 was the most endorsed and had the lowest severity estimate. Overall, the data fit the Rasch model well, although misfit was observed for symptom # 8.

Conclusions: Rasch's analysis of CUD symptoms in an inpatient sample broadly supports the DSM-5 CUD syndrome. Further examination is needed to determine if removing or revising the hazardous use symptom criterion in future DSM revisions would improve diagnostic measurement.

Objective: Medical cannabis has emerged as a promising therapeutic option, but its market acceptance faces significant regulatory, societal, and scientific challenges. This study explores pharmaceutical business managers' perspectives on marketing strategies, brand architecture, and the value proposition of medical cannabis, aiming to identify approaches to overcome these barriers and guide policymaking.

Method: Semi-structured interviews were conducted with 12 pharmaceutical managers to explore key challenges and strategies.

Results: Key themes included the need for extensive scientific research, targeted communication to address stigma, effective marketing tactics, and long-term sustainability. Participants stressed the importance of rigorous, disease-specific research to establish medical cannabis' therapeutic efficacy and build trust with healthcare providers and patients. Societal stigma was identified as a major barrier, with participants advocating for communication strategies that distinguish medical cannabis from recreational use and educate stakeholders. Marketing strategies focused on creating a unique value proposition, strong brand identity, and adaptive approaches to meet the diverse needs of healthcare professionals, regulators, and patients. Additionally, phased market entry strategies, beginning with pilot programs in regions with progressive regulatory environments, were recommended to pave the way for broader market expansion.

Conclusions: This study offers valuable insights into the marketing management and policymaking necessary for integrating medical cannabis into the pharmaceutical market. By addressing regulatory uncertainties, societal stigma, and scientific gaps, pharmaceutical companies can unlock the full potential of medical cannabis as a credible therapeutic product. These findings lay the groundwork for future research and policymaking to promote sustainable growth in the emerging medical cannabis market.

Objective: Estimating delta-9 tetrahydrocannabinol (mgTHC) using hits involves converting hits to grams via a grams-per-hit ratio (GPHR). Previous studies assumed a single hit size (SHS), ignoring individual hit size variations. This study investigates a multiple qualitative hit size (MQHS) approach based on self-reported hit sizes (small, medium, large) to improve mgTHC estimates.

Method: Adults (N = 1,824) who used cannabis in the past week completed an online survey on cannabis consumption, reporting quantities in hits and grams, and estimating their hit sizes. We calculated mgTHC using both SHS (0.06g/hit for flower, 0.012g/hit for concentrate) and MQHS. For the MQHS approach, we calculated median GPHRs for each hit size group and assigned those medians to individuals within that group.

Results: For flower, median GPHR increased with hit size (small: 0.042, medium: 0.062, large: 0.093). The MQHS estimate for mgTHC from flower was higher than SHS for large hits (95% CI: [12.4, 50.0]) but showed no difference for medium or small hits (95% CI: [-3.2, 8.1]; 95% CI: [-27.6, 3.4]). For concentrate, median GPHR was similar for small and medium hits but lower than large hits (small: 0.024, medium: 0.025, large: 0.035). MQHS estimates for mgTHC were higher than SHS for all hit sizes (95% CI: [46.3, 86.3]; 95% CI: [24.8, 45.5]; 95% CI: [11.5, 36.5] for large, medium, small hits, respectively).

Conclusions: The MQHS estimates captures hit size variability for flower. The floor effect with median GPHRs for concentrates suggests further investigation is needed for MQHS estimates with concentrates. The MQHS approach illustrates a method to develop new standard GPHRs for each qualitative hit size group, after further investigation.

Objective: Cannabis retail dispensaries have proliferated in the United States in recent years, making it an important time for conducting research. Research is needed to learn more about consumer purchasing behaviors, including the impact of product marketing both inside and outside of retail spaces, and studies are needed to explore how both consumers and retail staff interpret the health benefits and potential risks associated with cannabis products within these environments. Current research on cannabis dispensaries often involves surveys or interviews with customers and dispensary staff outside of dispensary environments, but much can be learned through observational and experimental methods within dispensaries themselves. However, researchers have traditionally relied on surveillance methods, where researchers visit dispensaries to gain a deeper understanding of real-world encounters in these environments. Although these methods provide helpful insights into purchasing and selling behavior, as well as regulatory compliance, these studies are conducted in an uncontrolled environment, as products, messaging, and interactions are specific to the dispensaries in which the research is conducted.

Method: We therefore created a mock cannabis dispensary to offer participants a retail experience that can be controlled and manipulated (e.g., adjustable cannabis product prices, placement of health and risk information in the dispensary, scripted interactions with dispensary staff) to help balance ecological and internal validity and answer questions about purchasing and selling behavior beyond what current methods allow.

Results: We describe the process of developing and stocking the first known mock cannabis dispensary for research purposes, the Cannabis Annex ("The CANNEX"), including interior design, product selection, feedback solicitation from 20 cannabis industry workers, and plans for future research studies within the environment.

Conclusions: By describing our process, we hope to aid researchers in developing their own similar mock dispensaries to continue learning about the health benefits, risks from use, and policy implications of cannabis in an increasingly legal recreational atmosphere.

Objective: Cannabis use among adults over age 50 is increasing, but data on specific products, co-use, and cannabis-related problems in this age group are lacking. The current study assessed differences in cannabis use patterns and alcohol and nicotine co-use by select demographic factors and medical cannabis status, as well as associations with problem cannabis use, among adults over 50.

Method: Adults over age 50 who used cannabis use in the past 30 days were recruited from a healthcare system and invited to complete an online survey.

Results: Participants (N = 367) were 43% female, with an average age of 65.9 (SD = 8.6), and predominantly White (67.9%), Native Hawaiian or Pacific Islander (NHPI; 12.3%), or Asian (9.3%). Mean frequency of cannabis use within the past 30 days was 18.7 days (SD = 11.5), and 27% reported use of non-medical cannabis-only. Co-use of cannabis with other substances was common, especially alcohol. Although group comparisons showed several differences by age, sex, and medical cannabis status, greater differences were found by race/ethnicity. White participants were more likely than others to have a state medical cannabis card, source their cannabis solely from medical dispensaries, and report alcohol co-use. NHPI participants were most likely to smoke cannabis and use tobacco. Smoking, as compared to consuming edibles and "other" methods, and greater cannabis frequency, were associated with problem cannabis use.

Conclusions: Findings illustrate patterns of cannabis and other substance use, with important demographic differences. Future research among older adults should include development of targeted interventions to address cannabis use problems and polysubstance use.

Objective: Expectancies play a critical role in cannabis use behavior and are influenced by sociodemographic and intrapersonal factors. This study examined daily endorsement of positive and negative cannabis use expectancies using 28 days of ecological momentary assessments (EMAs) in relation to sociodemographics, mental health symptoms, and cannabis use disorder (CUD) among young adult cannabis-tobacco co-users.

Method: Ninety-seven young adult (ages 18-24) cannabis and tobacco co-users reported on anxiety symptoms, depressive symptoms, and possible CUD at baseline. During the 28 days of EMAs, participants reported on 16 positive (n = 7) and negative (n = 9) cannabis use expectancies they anticipated would occur in the next 24 hours. Descriptive statistics examined the proportion of EMA days each expectancy was endorsed. Multivariable logistic regressions examined associations of expectancies with anxiety symptoms, depressive symptoms, and possible CUD, controlling for sociodemographics.

Results: The most frequently endorsed expectancies were positive (e.g., feeling good, getting along with others), while the least frequently endorsed were negative (e.g., drinking too much, having an argument). In regression models, participants endorsing more days of expecting to feel anxious displayed higher odds of anxiety and depressive symptoms; those endorsing more days of expecting to be in a bad mood displayed higher odds of depressive symptoms; those endorsing more days of expecting to feel tired or unmotivated displayed higher odds of possible CUD.

Conclusions: Expectancies of cannabis benefits and consequences are heterogeneous, endorsed in different frequencies across days, and they may have important implications for mental health symptoms and cannabis use severity among young adults who co-use.

Objective: Increasingly, cannabis is being prescribed/used to help manage posttraumatic stress symptoms (PTSS) or chronic pain, as cannabis has been argued to be beneficial for both types of symptoms. However, the evidence on efficacy is conflicting with evidence of risks mounting, leading some to caution against the use of cannabis for the management of PTSS and/or chronic pain. We examined the main and interactive effects of PTSS and chronic pain interference on adverse cannabis outcomes (a composite of cannabis use levels and cannabis use disorder, CUD, symptoms). We hypothesized that chronic pain interference and PTSS would each significantly predict adverse cannabis outcomes, and that chronic pain interference effects on adverse cannabis outcomes would be strongest among those with greater PTSS.

Method: Forty-seven current cannabis users with trauma histories and chronic pain (34% male; mean age = 32.45 years) were assessed for current PTSS, daily chronic pain interference, past month cannabis use levels (grams), and CUD symptom count.

Results: Moderator regression analyses demonstrated chronic pain interference significantly predicted the adverse cannabis outcomes composite, but only at high levels of PTSS.

Conclusions: Cannabis users with trauma histories may be at greatest risk for heavier/more problematic cannabis use if they are experiencing both chronic pain interference and PTSS.

Objective: This study investigated young adults' (YAs) experiences with tolerance breaks (temporary abstinence from cannabis; T-breaks).

Method: In Study 1, 15 YAs who used cannabis completed a qualitative interview. In Study 2, 66 YAs who used cannabis at least 2x/week completed online survey items assessing T-break familiarity, definitions, motivations, and experiences. Data were analyzed using qualitative thematic analysis.

Results: In Study 1, five themes were identified: (1) time frames for T-breaks were variable but brief and temporary, (2) T-breaks were motivated by tolerance reduction (3) and other motives, (4) withdrawal is an early barrier; positive outcomes occurred with longer breaks, (5) some YAs viewed T-breaks as unnecessary/unachievable. Study 2 findings demonstrated that YAs were familiar with T-breaks and most had attempted a T-break in the past year; greater variability in T-break motivations was apparent in Study 2.

Conclusions: Results suggest that YAs define T-breaks as an intentional and temporary period of abstinence from cannabis, regardless of motivation.

Objective: Due to little knowledge regarding the contextual factors related to cannabis use, we aimed to provide descriptive statistics regarding contextual factors related to use and examine the predictive ability of contextual factors.

Method: We included college student participants (n = 5,700; male = 2,893, female = 3,702, other gender identity = 48, missing = 57) from three multi-site studies in our analyses. We examined the means and standard deviations of contextual factors related to cannabis use (social context/setting, form of cannabis, route of administration, source of purchase, and proxies of use). Additionally, we tested the predictive ability of the contextual factors on cannabis use consequences, protective behavioral strategies, and severity of cannabis use disorder, via an exploratory machine learning model (random forest).

Results: Descriptive statistics and the correlations between the contextual factors and the three outcomes are provided. Exploratory random forests indicated that contextual factors may be helpful in predicting consequences and protective behavioral strategies and especially useful in predicting the severity of cannabis use disorder.

Conclusions: Contextual factors of cannabis use warrants further exploration, especially considering the difficulty in assessing dosage when individuals are likely to consume in a group context. We propose considering measuring contextual factors along with use in the past 30 days and consequences of use.

Objective: Driving after cannabis use (DACU) has become an increasing public health concern nationwide. Although previous research has linked perceived peer approval, perceptions of dangerousness, and negative effect expectancies to DACU, no previous work has examined whether these constructs can be successfully targeted in an intervention or whether changes in these variables lead to changes in DACU. The present study is a secondary data analysis to investigate within-subject change and potential mechanisms of change in a pilot trial for a mobile phone-based intervention shown to significantly reduce DACU over time.

Method: Participants were 66 emerging adults who completed the mobile-based intervention and provided 3-month follow-up data. Participants completed measures that assessed rates of DACU, negative cannabis expectancies, perceptions of dangerousness, and perceived peer-approval.

Results: Results indicated that negative effect expectancies significantly increased from baseline to three-month follow-up, while perceived peer approval for DACU significantly decreased from baseline to three-month follow-up. Though significant within-subject change was found for all variables of interest, none of the variables of interest significantly mediated changes in instances of DACU over time. The results of the current study suggest that key variables associated with DACU-perceived peer approval and negative cannabis expectancies can be successfully targeted in a mobile-based brief intervention.

Conclusions: Continued research investigating moderators and mediators of intervention outcomes is warranted.