Interestingly, though marijuana tweets exhibited the highest proportion of positive tweets, they also exhibited the highest proportion of neutral tweets and the lowest proportion of tweets with negative sentiment. This finding may suggest relative homogeneity regarding marijuana attitudes, possibly as a consequence of debate regarding marijuana legalization during this time period. As the majority of all sentiment-containing tweets were positive, results from this study may suggest that outreach efforts to raise awareness about the health risks of tobacco and ATPs on college campuses may have limited resonance. However, these preliminary data also suggest discrepancies in sentiment between tobacco products, as well as differences in sentiment toward smoking across California universities. Therefore, policymakers and health promotion advocates should consider tailoring policy implementation and health communication for specific college students in California based upon evidence of latent receptivity toward anti-tobacco approaches and existing community sentiment toward smoking behaviors as detected in this study. Furthermore, future studies should more explicitly assess user reaction and sentiment to debate, communication and implementation of state-level policies that both legalize and restrict use of tobacco and smoking products, as well as how these macro policies interact with campus-specific smoke free policy perceptions for different tobacco, marijuana, and e-cigarette product categories. For example, actionable insights based on preliminary findings from this study indicate that users generally express more positive sentiment about tobacco use and smoking behavior. This may necessitate the use of campus-based health promotion and education activities that focus on reducing appeal of these products, such as restricting any form of marketing and promotion in or near campus communities. This should be coupled with broader state legislation to further restrict marketing and promotion that targets young adults and college communities. Further, perceived penalties for violating smoke- and tobacco-free campus policies may also impact compliance based on socioeconomic factors. For example, one user from UC Riverside tweeted, “other places might be more lenient,planting racks but UCs have a shitty tobacco and smoking policy and I got caught and now it’s over” [emphasis added to denote correction of misspelling].
Hence, data-driven approaches to assess receptivity and the impact enforcement has on smoking behavior should be built into smoke free program implementation iteratively. Importantly, the breakdown of smoking-related tweets between numerous college campuses as detected in this study presents challenges with respect to whether the distribution of tweet characteristics accurately reflects distributions in the underlying college populations. Nevertheless, similar work has been conducted which presents correlational evidence between characteristics of geospatially-specific social media posts and characteristics of populations in those areas . Furthermore, as over half of college students in California are between the ages of 18 and 24 , academic and demographic distributions of tobacco consumption within colleges may be the consequence of socioeconomic disparities in childhood and potential effects of these disparities on attitudes about smoking among parents, high schools, and/or neighborhoods that warrant further study . Results from our study are limited in generalizability, though complement work by others on examining the impact of tobacco free policies on US college campuses. This includes a recent study from 2020 of small colleges in Massachusetts that found that a college with a smoke-free policy had significantly more anti smoking attitude than a control campus, but did not have lower rates of smoking itself . Relatedly, a separate earlier study from 2005 that analyzed undergraduates in Texas found that campuses with preventive education programs had lower odds of smoking, whereas designated smoking areas and cessations programs were associated with higher odds of smoking . Collectively, these prior studies and our own work helps to better characterize knowledge, attitudes and behaviors of college campus communities toward smoking, as well as the smoke-free policies attempting to discourage smoking, which in turn should aid in the development of more targeted approaches to educate college-aged populations about the health harms of tobacco and also enable better implementation of anti-tobacco policies in these critical populations.This study was exploratory in nature and collected social media messages for which latitude and longitude coordinates could be collected from the Twitter API, but this data collection methodology is limited to collecting messages from Twitter users that enabled geolocation, a specific limitation to generating a more generalizable dataset on Twitter as it is estimated that only 1% of all tweets are geocoded .
Hence, the dataset used in this study after filtering for keywords was small and likely biased, limiting the generalizability of results. This method of data collection may have introduced bias in the types of tweets collected, thereby limiting the generalizability of findings as the majority of Twitter users do not geolocate their posts. Potential sampling biases for Twitter include oversampling for certain geographic areas , filtering for specific features , and the limitations of the Twitter public streaming API in lieu of other data collection approaches . Future studies should examine the use of multiple Twitter APIs to generate a more representative Twitter dataset and compliment findings with other traditional sources of data to generate findings that are more robust and generalizable, as well as use complementary Twitter and social media datasets made publicly available by other researchers. specific to identification of Twitter users and conversations associated with colleges and universities, using keyword searches, and selecting accounts affiliated with higher education should be explored in future studies. Also, inclusion criteria required tweets to be posted from college campuses, which would not have accounted for variability in smoking related tweets from off-campus housing or areas/neighborhoods at the borders of campus properties where college students may reside. Furthermore, though the study design permitted searches of the Twitter API to return different volume of tweets for different keywords, there was a smaller number of original keywords for substances containing marijuana/cannabis than those for e-cigarettes or products containing tobacco due to our purposeful filtering for tobacco and alternative tobacco product keywords . Additionally, the majority of tweets analyzed for this study were from 2015, a period prior to major public scrutiny about default privacy settings for location sharing on Twitter . Finally, this study is an ecological study and should therefore be considered hypothesis generating and not generalizable to individuals on college campuses until further studies among individuals confirm these correlational findings. Adolescence has been argued to be the only developmental period bookended by highly disparate events . It commences with biology, defined as the onset of puberty,sub irrigation cannabis and concludes via social construct, typified by the achievement of “independent functioning” such as obtaining a job, completing training, and beginning a family . While the ages for this window vary widely throughout the globe, most agree that the central work of adolescence largely encapsulates ages 13-18 . Across cultures and societies, it is during this precise developmental period that substance use is most often initiated , with peak age of first misuse, and related problems following soon thereafter .
Given that adolescents have goals, cognitions, and social contexts distinct from adults, it is critical that clinicians and researchers consider adolescent substance use through a neuro developmental lens. In the present review, we engage a developmental neuroscience framework to characterize the prevalence, and related health and safety implications of substance use within this age group; identify the nature of the adolescent brain, including characteristic features of this phase of neuro development relevant for adolescent substance use treatment; and provide an overview of current adolescent addiction interventions and avenues to improve clinical treatment and clinical research efforts for adolescents. We then conclude by examining the intersection between the nature of the developing brain and adolescent substance use, and utilize that information to inform alternative routes and highlight promising future directions for substance use treatment in this critical age group. Due to the inherently poly substance-using nature of this age group , we focus this review primarily on the three most frequently used substances by adolescents: alcohol, cannabis and tobacco . We have not integrated examination of prescription pain/opioid misuse here due to its relatively recent history within adolescent addiction clinical research and treatment settings, and the related dearth of empirical adolescent opioid treatment research in this area . The rates and patterns of adolescent substance use have maintained historical consistency throughout the past several decades.Noted in top United States surveys , despite the legal age being 21 years, alcohol is highly accessible for American youth, with most accessing alcohol through peers or other individuals . In turn, it is no surprise that half of American 14-year-olds have consumed alcohol. This rises to 75% by age 18, with half drinking to intoxication . Relevant to potential neurotoxicity and health impact , 20% of adolescents start drinking by age 13 . Interestingly, U.S. surveys reflect a current 10-year low in youth drinking. Yet, rates of youth alcohol use and related problems still remain consequential, in terms of safety and health impact . One currently debated reason for the decline in adolescent alcohol use in the U.S. revolves around recent changes in cannabis legislation . For example, treatment providers in states where cannabis is medically and/or recreationally legal are observing some degree of youths’ increasing preference for cannabis over alcohol . Presently, one quarter of U.S. youth report cannabis use by age 14, with 8% starting by age 13. Of relevance, rates of cannabis use have recently begun to approximate adolescent alcohol use patterns, with half of U.S. teens now using cannabis by age 18 . This reflects a 22% rise in adolescent cannabis use during the past decade . These startling trends raise the question of whether increased recreational and medical legalization of cannabis are contributing to observed increases in adolescent use . Unfortunately, requisite data needed to identify causal relationships between changes in cannabis legislation and adolescent use are not yet available, and thus far, evidence has been mixed regarding effects on both adolescent consumption and perceived harmfulness. Further, effects may vary substantially across states/contexts . Active efforts by scientists and practitioners in recreationally and medically legal areas are needed to disaggregate directional impacts between public policy legislation and adolescent use . For example, in 2017, national survey databases indicated adolescents reported significant drops in their estimations of potential harm and disapproval of cannabis use ; how this aligns with patterns of adolescent cannabis use and intersects with alcohol use is a critical, and increasingly pressing, empirical public health question that has direct implications for addiction treatment providers working with adolescents in this field . In terms of tobacco, one quarter of American youth have tried tobacco, with 7% initiating use before age 13; this rises to a third of youth by age 18, with 10% smoking 10+ cigarettes/day . National data reflect that American adolescents are moving away from tobacco use, as represented by a 71% drop in past 11 year cigarette use . Part of this may be due to teens’ transition to electronic vapor products , a recent newcomer to the world of adolescent substance use. Adolescents report vaping nicotine and cannabis , preferring flavor-based cartridges , contentiously marketed toward children . Surveys reflect 20% of U.S. youth have vaped an e-liquid containing nicotine and/or cannabis by age 14, rising to one third by age 18 . For many clinicians, the most pressing public health concern around adolescent substance use is not that it represents an entry point into a life-long course of protracted addiction. Rather, the more imminent concern for parents and providers is that adolescents will make a risky choice while trying to obtain, use, and/or dispose of substances that result in consequences that cannot be undone , and that render their life trajectory much more difficult . One of the central challenges in this area is that experimentation with substance use is so typical among adolescents that for decades it has been interpreted as largely “normative”, and to some degree to-be-anticipated, and some argue, even developmentally appropriate . While the initial part of this trajectory has been interpreted as largely “harmless” in terms of behavioral impact, conferring a degree of social advantage, for some, during high school , the nature of substance use shifts for many during this period.