Medicinal cannabis use among young adults during California's transition from legalized medical use to adult-use: a longitudinal analysis.

Background: In 2016, California transitioned from legalized medical cannabis use to adult-use. Little is known about how this policy change affected medicinal cannabis use among young adults.Objectives: To identify longitudinal groups of medicinal cannabis users and concurrent changes in health- and cannabis use-related characteristics among young adults in Los Angeles between 2014 and 2021.Methods: Cannabis users (210 patients and 156 non-patients; 34% female; ages 18-26 at baseline) were surveyed annually across six waves. Longitudinal latent class analysis derived groups from two factors - cannabis patient status and self-reported medicinal use. Trajectories of health symptoms, cannabis use motives, and cannabis use (daily/near daily use, concentrate use, and problematic use) were estimated across groups.Results: Three longitudinal latent classes emerged: Recreational Users (39.3%) - low self-reported medicinal use and low-to-decreasing patient status; Recreational Patients (40.4%) - low self-reported medicinal use and high-to-decreasing patient status; Medicinal Patients (20.3%) - high self-reported medicinal use and high-to-decreasing patient status. At baseline, Medicinal Patients had higher levels of physical health symptoms and motives than recreational groups (p < .05); both patient groups reported higher level of daily/near daily and concentrate use (p < .01). Over time, mental health symptoms increased in recreational groups (p < .05) and problematic cannabis use increased among Recreational Patients (p < .01).Conclusions: During the transition to legalized adult-use, patterns of medicinal cannabis use varied among young adults. Clinicians should monitor increases in mental health symptoms and cannabis-related problems among young adults who report recreational - but not medicinal - cannabis use.

Who Benefits from School-Based Teen Pregnancy Prevention Programs? Examining Multidimensional Moderators of Program Effectiveness Across Four Studies.

Recent research has suggested the importance of understanding for whom programs are most effective (Supplee et al., 2013) and that multidimensional profiles of risk and protective factors may moderate the effectiveness of programs (Lanza & Rhoades, 2012). For school-based prevention programs, moderators of program effectiveness may occur at both the individual and school levels. However, due to the relatively small number of schools in most individual trials, integrative data analysis across multiple studies may be necessary to fully understand the multidimensional individual and school factors that may influence program effectiveness. In this study, we applied multilevel latent class analysis to integrated data across four studies of a middle school pregnancy prevention program to examine moderators of program effectiveness on initiation of vaginal sex. Findings suggest that the program may be particularly effective for schools with USA-born students who speak another language at home. In addition, findings suggest potential positive outcomes of the program for individuals who are lower risk and engaging in normative dating or individuals with family risk. Findings suggest potential mechanisms by which teen pregnancy prevention programs may be effective.

Transactional sex work and HIV among women in conflict-affected Northeastern Uganda: a population-based study.

BACKGROUND: Armed conflict and the HIV pandemic are significant global health issues. Evidence of the association between armed conflict and HIV infection has been conflicting. Our objective was to examine the role of mediating risk factors, such as engagement in transactional sex work, to elucidate the relation between armed conflict and HIV infection. METHODS: We used multistage sampling across three Northeastern Ugandan districts to randomly select 605 women aged 13 to 49 to answer cross-sectional surveys from January to May of 2016. We used multivariate logistic regression model with R 4.0.3 to examine if exposure to armed conflict has an indirect effect on reporting having an HIV-positive serostatus through engagement in transactional sex work. Age and district residence were included as covariates. RESULTS: Exposure to armed conflict ß = .16, SE = .04, p < .05, OR = 1.17, 95% [CI .08, .23] was significantly associated with reporting a HIV-positive serostatus. For each 1-unit increase in exposure to armed conflict (i.e., additional type of armed conflict exposure), there was a 17% increase in the odds of reporting a HIV-positive serostatus. Engagement in transactional sex work was not associated with reporting a HIV-positive serostatus ß = .04, SE = .05, p = .37, 95% [CI - .051, .138]. We found district of residence, age, and interaction effects. CONCLUSIONS: Although exposure to armed was associated with reporting an HIV-positive serostatus, this relationship was not mediated by engagement in transactional sex. Further research is needed on risk factors that mediate this relationship. The likelihood of reporting a HIV-positive serostatus increased with each additional type of exposure to armed conflict. Thus, screening for exposure to multiple traumatic stressors should occur in HIV prevention settings. Healthcare services that are trauma-informed and consider mental distress would likely improve HIV outcomes.

Reflection on modern methods: planned missing data designs for epidemiological research.

Taking advantage of the ability of modern missing data treatments in epidemiological research (e.g. multiple imputation) to recover power while avoiding bias in the presence of data that is missing completely at random, planned missing data designs allow researchers to deliberately incorporate missing data into a research design. A planned missing data design may be done by randomly assigning participants to have missing items in a questionnaire (multiform design) or missing occasions of measurement in a longitudinal study (wave-missing design), or by administering an expensive gold-standard measure to a random subset of participants while the whole sample is administered a cheaper measure (two-method design). Although not common in epidemiology, these designs have been recommended for decades by methodologists for their benefits-notably that data collection costs are minimized and participant burden is reduced, which can increase validity. This paper describes the multiform, wave-missing and two-method designs, including their benefits, their impact on bias and power, and other factors that must be taken into consideration when implementing them in an epidemiological study design.