The availability of these services may have been especially important among SGM participants within our study population, as previous studies have shown that SGM youth experiencing homelessness are more likely to utilize service programs, such as STI and HIV testing, food access, street outreach teams, and counseling services compared to their heterosexual cisgender peers. Though the proportion of SGM study participants who utilized the specific services described above is unknown, all study participants were recruited directly through Larkin Street. Thus, the availability and use of such services by our sample of service-seeking participants may have represented a de facto substance use intervention that minimized the harmful risks of substance use observed among SGM youth in other studies with greater proportions of non-service-seeking youth. Among mental health symptoms, our study found a significant difference in generalized anxiety symptoms between SGM and heterosexual cisgender youth. However, this difference was not observed for symptoms of depression and PTSD, which stands in contrast to the previous literature demonstrating that SGM homeless youth are more likely to experience more severe symptoms of both depression and PTSD compared to heterosexual cisgender youth experiencing homelessness. Reviewed collectively,flood and drain tray our findings suggest that the minority stress experienced by unstably housed SGM youth increases their burden of day-today generalized anxiety, separate and in addition to the anxiety stemming from post-traumatic stress.
Lastly, given the over representation of Black and Hispanic individuals among youth experiencing homelessness nationwide, the racial diversity of our sample is an important strength to highlight: 78% of total participants identified as a person of color, and 73% of SGM participants identified as a person of color. Given the increased victimization, invisibility, and more difficult exits from homelessness faced by SGM youth of color, it is critically important to capture the experiences of these communities to address the disproportionate risks of homelessness they face.Because our sample was comprised of youth experiencing homelessness who already access non-profit services, our sample may have missed more extreme outlier cases related to mental health and substance use disorders and may have limited generalizability to youth experiencing homelessness who do not access services. In relation to mental health, our PTSD measure potentially overestimates the prevalence of PTSD among our study population, as some symptoms of PTSD may be related to housing instability rather than strictly symptoms of PTSD. Additionally, our participants were often exposed to a multitude of traumatic stressors, and we were unable to isolate the specific event connected to symptoms of PTSD, as participants were not asked to describe their traumatic experiences. In terms of data analysis, our study was a relatively small sample of youth experiencing homelessness compared to other studies; as a result, the power to find associations by SGM status may be limited. In particular, the number of transgender and gender minority youth in our sample was relatively small compared to sexual minority participants, which may limit generalizability of our findings to service-seeking transgender youth experiencing homelessness. Third, our participants were all ages 18 to 24, which may reduce generalizability of our findings to youth under 18 experiencing homelessness. Desirability bias may also have been present in responses surrounding substance use, although there is no evidence to suggest this would differ by SGM status.
Finally, our study design was cross-sectional, and therefore could not examine longitudinal trends nor causality between SGM status and our outcomes of interest.The concurrent or sequential usage of multiple drugs during adolescence is a critical public health problem, spawning a large literature focusing on whether usage of one substance leads to usage of others. The study of interdependence in adolescent substance use yields insight into potential patterns regarding which drugs are used sequentially or concurrently. As these risk behaviors co-occur and accumulate over time for certain individuals and social groups, there is potential to concentrate risk and negative sequelae among these concurrent users making concurrent users a high risk population that may be in need of prioritized and targeted intervention. In addition, to the extent that use of one substance affects the usage of another among adolescents, accounting for this interdependence in substance use is important as it can minimize the possibility of obtaining spurious relationships and possibly biased model estimates. While some studies indicate that cigarette smoking is a strong predictor of the concurrent or subsequent usage of alcohol and marijuana, other studies find that alcohol use increases the likelihood of cigarette smoking. In other research, a mutually reinforcing relationship was detected between adolescent alcohol use and smoking, and between cigarette smoking and marijuana use during adolescence and young adulthood. In contrast, other research found that previous use of alcohol did not predict the initiation of marijuana use. Existing studies also indicate that adolescent users of marijuana frequently smoke cigarettes, either as a substitute when marijuana is scarce, or as a means of counteracting the sedating effects of marijuana. The complementary usage of tobacco and marijuana in adolescence may contribute to the eventual dependence on nicotine.
The complementary usage of these two substances might be the greatest public health consequence from marijuana use in adolescence. There may also be complementarity in the usage of marijuana and alcohol. On the other hand, this observed correlation may be due to substituting one substance for another as a means of minimizing marijuana withdrawal symptoms. In one study, daily marijuana users who underwent a period of abstinence drank more often if they had a previous diagnosis of alcohol abuse or dependence. The importance of peers in the transmission of substance use behavior within adolescent friendship networks has given rise to a body of literature which focuses on how social networks can spread substance use behavior. These studies focus on how the co-evolution of adolescent friendship networks and substance use gives rise to peer influence and selection effects within adolescent networks regarding a specific substance use behavior . Peer influence is a type of social influence, and the latter has been theorized from numerous points of view including the Dynamic Social Impact Theory, which states that individuals will become more like those who are socially proximal and as a result their attributes will be correlated. Given the importance of concurrent or sequential usage of cigarettes, alcohol, and marijuana, the purpose of this study is to examine the co-evolution of use of these substances within the dynamic landscape of adolescent friendship networks, which are a primary socialization context for adolescent substance use. A key methodological and theoretical challenge herein is that the context of peer networks must be taken in consideration when studying adolescents’ interdependent substance use, because interpersonal association via peer influence or friendship selection likely shapes the concurrent or sequential use of substances. Not taking into account such peer network effects can result in biased estimates of the interdependence of substance use behaviors, or likewise, the effects of network influence. Fig 1 displays a hypothetical simple 2-person world in which the “true” model are the solid lines and the dashed lines show possibly spurious intra-personal effects of one substance useon another. This figure is informed by the Dynamic Social Impact Theory , as we posit that person 1 will become more like his or her peer, person 2, because of peer influence via modeling, shared opportunities, social proximity and the consolidation of attitudes and behaviors that may take place in adolescent friendship networks. This social process is captured in pathways from person 1 smoking to person 2 smoking,microgreen rack for sale and in addition from person 1 drinking to person 2 drinking. Note that certain person-specific covariates affect an adolescent’s usage of each substance: this will therefore lead to a correlation in usage across substances for the person. Not accounting for the across-person effects as shown in dotted lines–for example, how the smoking behavior of person 1 affects the smoking behavior of person 2 through a social influence or a selection effect–will result in these correlations being inappropriately captured by the dashed paths.
Such correlations would be spurious, thus highlighting why it is critical to account for these network effects when studying concurrent substance use behavior. Although we do not show them here , this figure could also represent pathways linking person 1 smoking and person 2 marijuana use, and analogously, person 1 drinking and person 2 marijuana use. These pathways may be a result of normative processes. The subjective norms construct from the Theory of Planned Behavior, which is the composite of the belief about whether most people approve or disapprove of a behavior and their corresponding motivation to comply with those important referents in their social environment, informs these normative pathways in our model. Adolescents who are smoking cigarettes, may through such normative beliefs, reinforce the use of other substances among their friends as they display pro-substance use norms and thus their friends may be motivated to comply with their attitudes and behavior, which would indirectly increase friends’ acceptability of using marijuana or alcohol. We are aware of just two existing studies that have simultaneously studied adolescent social networks and the use of more than two substances. One longitudinal study focused upon smoking, drinking, and marijuana use in a sample of 129 Scottish youth finding that while there were statistically significant peer influence effects on alcohol and marijuana use but not on smoking behavior, marijuana users smoked cigarettes more over time. However, the other study, detected neither interdependent association effects nor peer influence effects on cigarette, alcohol, and marijuana use behaviors in a longitudinal study of a sample of US school students. Note that the first study utilized a relatively small sample and the second study is limited to two waves of data, thus diminishing the statistical power of each study. Finally, social influence may not necessarily have symmetric effects on initiation and cessation of substance use. For example, Haas and Schaefer explored this idea in the context of smoking, and found some evidence that influence effects may have a stronger effect on starting smoking behavior, but weaker effects on stopping it. Although we do not have specific hypotheses regarding how such influence effects might operate for other substances such as alcohol or marijuana use, we nonetheless test this asymmetry possibility here in our analyses. Building on past studies focusing on concurrent or sequential substance use in adolescence, we examine the co-evolution of adolescent friendship network ties and whether there was interdependence in usage of cigarettes, alcohol, and marijuana among 3,128 adolescents in two large schools. We utilize three waves of social network data from the National Longitudinal Study of Adolescent to Adult Health. Ecological models of human development informed the conceptualization of this study by situating adolescents in key social contexts exerting primary socialization forces including peer selection, peer influence, and parental influences. This study is also informed by the Dynamic Social Impact Theory, which forms the basis for why youths’ behaviors will be correlated. Lastly, normative constructs from the Theory of Planned Behavior guide our examination of the normative model pathways under study.We utilize the R-based Simulation Investigation of Empirical Network Analysis software package to estimate Stochastic Actor-Based models. We specify each model with three behavior equations in which we focus on how usage of one substance is influenced by the usage of the other two substances, along with one network equation in which we model the network evolution in tie formation and dissolution among adolescents in the school. We estimated the model separately on each school. Besides the key mechanisms illustrated in Fig 1, we adopt a forward selection approach for each parameter via score-type test . In the behavior equations, the linear and quadratic effects capture the time trend of each substance use behavior; peer influence effects are measured as the sum of negative absolute difference between ego’s and alters’ behavior averaged by ego’s out-degree. Additional covariates such as in-degree, parental support, parental monitoring, race , and depressive symptoms are added given that they have been shown to be important covariates in the existing literature, and given that the results from score-type tests reject the null hypothesis that their parameters are 0s. In-degree is important to test, given the debate in the existing literature about the importance of network centrality, or popularity, for explaining substance use.