Study inclusion criteria were currently or formerly in treatment for marijuana use or, alternatively, having used marijuana heavily in the past year and reduced the marijuana use since then, and able to provide informed consent. To reduce recall bias and selection bias, we excluded participants who received any treatment for substances other than marijuana, had used marijuana heavily more than one year ago, and had been decreasing marijuana use for less than a month. Given the lack of a standard definition for heavy cannabis use , in part due to variability in amount, frequency, and methods of cannabis use, heavy use and reduction were self-defined by the participant. Participants were recruited through flyers and advertisements in local substance use treatment clinics and other sources . A total of 123 interested individuals answered open-ended questions that required them to self-identify as eligible to participate the study. All respondents were eligible to participate. After prospective participants gave informed consent, small groups of approximately 10 eligible participants were provided instructions on how to complete questionnaires regarding marijuana use patterns and other functional outcomes. Research assistants provided assistance to the groups to facilitate self-administration of assessments. The group sessions lasted about two hours, and participants were compensated for their time. All responses were anonymous. The study was approved by the Institutional Review Boards at the University of California, Los Angeles.Relationships between marijuana use frequency,flood tray severity of marijuana-related problems. and HRQoL were analyzed, controlling for mental health symptoms and physical health conditions for the respective outcome measures. Multiple imputations were used due to missing data.
We used the structural equation model for the analyses. SEM is a multivariate method that combines factor analysis and path analysis, which allows relationships among multiple measures or constructs to be tested simultaneously . A latent construct is a factor indicated by multiple indicators and therefore is free of random error. A path analysis allows the evaluation of causal relationships in which an independent variable produces both direct and indirect effects on a dependent variable , in our case, we are testing if marijuana use produces direct effects on HRQoL and indirect effects on HRQoL via the marijuana-related problems as a mediator. The analysis was conducted in three steps. First, a preliminary analysis and Pearson’s r correlation coefficients for all variables were computed and reported. Second, confirmatory factor analysis was conducted to assess the associations between latent variables and factors to support the subsequent assessment of the SEM. There are three latent variables in the model. One was marijuana use frequency with two indicators: number of days of marijuana use and number of times marijuana was used per day. The second was mental health symptoms . The third construct was physical health conditions, with indicators including sleep disturbance, respiratory function, pain intensity, and appetite. Finally, SEM was performed with SAS version 9.4 PROC PATH by the maximum likelihood estimation. Model fit was assessed by the chi-square test statistic and the values in the following goodness-of-fit indices: comparative fit index of equal to or greater than 0.95, root mean square error of approximation of less than or equal to 0.08, standardized root mean square residual of < 0.09, and Adjusted Goodness of Fit Index of equal to or greater than 0.90, in accordance with the recommendations . The study findings are mostly consistent with our hypotheses. Using SEM to examine the relationships between marijuana use frequency, severity of marijuana-related problems, and the physical and mental HRQoL domains, separately, we found that marijuana use frequency was positively associated with severity of marijuana-related problems, which in turn had negative effects on mental HRQoL but non-significant relationship with physical HRQoL.
The relationship between marijuana use frequency and either mental or physical HRQoL domains was not significant. Overall, the hypothesized model explained 48% of the variance on the mental HRQoL measure, while it explained only 11% of the variance on the physical HRQoL. A prior study reported an effect of marijuana use frequency on mental HRQoL but not physical HRQoL . However, our study did not support the direct association between marijuana use frequency and either mental HRQoL or physical HRQoL. Instead, we found that marijuana use frequency was associated with severity of marijuana related problems, which affected mental HRQoL. This finding suggests that individuals who frequently use marijuana subsequently had more marijuana-related problems, and this relationship further affected their mental HRQoL. The present study results suggest a new insight that reducing problems associated with marijuana use may be an important clinical target for patients to improve their HRQoL and attain better treatment outcomes. Our findings suggest that reductions in marijuana use alone may not affect mental health-related quality of life if perceived problems are still active. Based on the participants’ responses, the most common marijuana-related problems included financial difficulties, procrastination, and poor relationships with family or partner. These problems may more directly affect mental health and have less impact on physical health related quality of life. The primary problems reported in this study were similar to those observed in prior studies among college students . Marijuana-related problems may be diverse among adolescent and adult populations, warranting more research to clarify their relationships with HRQoL. The hypothesis that mental health symptoms was negatively associated with mental HRQoL was supported by the present study. Prior research demonstrated similar findings that marijuana use was associated with poorer mental HRQoL among patients with anxiety and depression who were already at risk for low mental HRQoL .
Our study has found that anxiety and depression were significant mental health symptoms affecting mental HRQoL. Additionally,ebb and flow tray our study findings suggest that stress and paranoia are also important mental health symptoms among marijuana users, but these symptoms have not been well examined in prior marijuana-focused studies. More research regarding stress and paranoia as well as other mental health symptoms are needed to further examine their relationship to mental HRQoL among marijuana users. It is not surprising that the study also showed that severity of physical health conditions was negatively associated with physical HRQoL. A positive relationship between marijuana use and poor physical health conditions was found in this study, which is consistent with prior studies . In the past, there has been limited research to evaluate the relationship between physical health problems and physical HRQoL among marijuana users. In the present study, we found that marijuana users who reported these physical symptoms or conditions had poor HRQoL for physical domain. It is worth noting that sleep disturbance and respiratory function were two of the greatest health problem contributors to physical HRQoL as indicated by high factor loadings on physical health conditions. Nevertheless, our study findings reveal that neither the marijuana use frequency nor the marijuana-related problems were significantly associated with physical HRQoL domain. A prior longitudinal study of stimulant users reported similar results, suggesting that reductions in use over time contributed to only minor improvements in physical HRQoL . Still, given the limited research examining marijuana use and physical HRQoL, additional research efforts are needed to shed light on relevant physical health problems in relation to marijuana use and HRQoL. There were several limitations in the present study. First, the causal relationships between marijuana use frequency, severity of marijuana-related problems, and mental and physical HRQoL cannot be determined because the study is based on data from a cross-sectional survey. Longitudinal studies would be needed to reveal temporal relationships between marijuana use frequency and mental health problems and to confirm the findings. Second, selection biases might exist because this study involved a cross-sectional survey of participants who were recruited by flyers and advertisements. Third, functional assessments were collected by self-report, without verification by objective measurements. However, scales used had been tested in other studies with good validity and reliability. Also, past month marijuana use patterns were based on participants’ self-report, which may be influenced by recall bias. Finally, the sample size was too small to investigate more complex relationships between variables using additional potential constructs and covariates .
Despite these limitations, this study provides better understanding of the relationships between marijuana use frequency, severity of problems related to marijuana use, and HRQoL, controlling for mental and physical symptoms. Our findings suggest that to improve marijuana users’ HRQoL, treatment should incorporate interventions that address not only marijuana use reduction but also problems caused by marijuana use that may take additional time to address even after use levels have been reduced. For example, interventions could be designed to enhance and optimize skills related to time management, coping with stress, and improving family relationships. Also, severity of marijuana-related problems could be used as an indicator for efficacy of treatments , as individuals with more severe problems related to marijuana use are generally more likely to seek treatment for marijuana use . Additionally, our findings show that more frequent marijuana users have concurrent mental health symptoms and worse physical health conditions that may negatively impact their HRQoL. Integrated treatment models simultaneously addressing marijuana use and mental health symptoms have been recommended . In conclusion, this study extends previous research and improves the understanding of the relationships among marijuana use, marijuana-related problems, and HRQoL.Marijuana legalization and the rising popularity of new delivery systems for psychoactive substances or vaporizers are changing the landscape of substance use. Uruguay legalized non-medical marijuana in 2013 and Canada will propose similar legislation in 2017. Eight US states and the District of Columbia have passed ballot initiatives legalizing adult possession and use, and 28 states have legalized medical marijuana. Marijuana and tobacco are consumed similarly: rolled in paper, smoked in pipes, or electronic vaporizers . Tobacco and marijuana can also be consumed together through “blunts” or “spliffs” . Tobacco is the leading cause of preventable disease and premature death in the United States and the second major cause of mortality worldwide. US Federal prohibition of marijuana impeded studies quantifying the effects of marijuana use on population health. Many drug experts agreed that marijuana carries less personal and societal harm than drugs like alcohol, tobacco, heroin, and cocaine. Emerging evidence, however, has linked marijuana use with negative physiological and psychological outcomes. Compared to non-smokers, chronic, heavy marijuana smokers have been found to have impaired lung function. Though marijuana smoke contains known carcinogens, light and moderate use does not seem to be linked to lung cancer, with mixed evidence linking heavy use to lung cancer. Marijuana use, however, has been associated with increased cardiovascular disease including stroke and myocardial infarction. Exposure to THC increases risk for depression, anxiety, and psychosis. Long-term and heavy use likely results in persistent cognitive impairments especially if use begins during adolescence. Often, marijuana users also consume tobacco products, posing a challenge to determine effects solely of marijuana use not confounded by concomitant tobacco use. Administering nicotine and THC without combustion is arguably safer, but not harmless. Policy and product transformations may affect comparative harm and benefit perceptions of various products and administration routes. Research on comparative perceptions of tobacco and marijuana has been limited to a few quantitative surveys: US college students rated marijuana as safer than tobacco products; a convenience sample of US marijuana users believed marijuana flower was less harmful than marijuana concentrates; and an Australian population survey found a majority believed marijuana use can cause health, behavioral, and social problems. In one qualitative study, California adolescents identified acute and chronic negative health outcomes for cigarettes, but were less certain about negative effects of e-cigarettes or marijuana. The effect of changing delivery and potency of marijuana products, and the shifting legal landscape on perceptions of comparative harm or benefit remains largely unexplored. To begin filling these gaps, we conducted a qualitative study with young adults in Colorado to understand comparative perceptions of tobacco and marijuana products. We chose Colorado as the case study because it was the first state to legalize retail marijuana sales and distribution in 2014, five years after introducing a state licensing system for medical marijuana dispensaries in 2009. We focused on young adults because they have the highest rates of marijuana and tobacco use in the US compared to other age groups, and had legal access to at least the medical marijuana market. Thirty-two young adults were recruited based on current use of at least one of three products .