Commentary on Terry‐McElrath <i>et al</i>. (2019): Will persistent patterns of youth marijuana use compromise their futures?
Bibliographic record
Abstract
Recent increases in the prevalence of frequent marijuana use that extend well into adulthood raise concerns about the long-term consequences for population health and for the individuals engaging in these use patterns. With the context of marijuana use changing rapidly and marijuana use prevalence continuing to increase in the United States 1, 2, the public is in great need of rigorous science on the consequences of these trends to guide policymaking. Terry-McElrath and colleagues address this need by answering important questions regarding the continuation of youth marijuana use patterns to age 30 years 3. Using data from the Monitoring the Future Survey, a national school-based sample, they find that more recent cohorts are at the highest risk for continued frequent marijuana use. Moreover, 60% of individuals who use marijuana frequently in high school continue to use marijuana at some level when assessed at age 30, and almost a quarter continued a frequent use pattern. The authors point to decreases in perceived risk, increased tetrahydrocannabinol (THC) potency and changes in the transition to adult roles as possible reasons for these findings. The prevalence of long-term frequent use, however, is probably much greater than this study indicates. The latent classes estimated were identified using data collected during the study participants’ senior year of high school. As mentioned in the limitations 3, this school-based sample excludes those who have dropped out of high school or who do not attend regularly. This exclusion may be a result of marijuana use, as our previous research, and that of others, shows a wide range of academic performance problems associated with frequent marijuana use, including school dropout 4, 5. Moreover, the exclusion might be even greater among vulnerable groups, such as racial minorities, where school dropout is more common 6 and marijuana use is increasing 7. The educational consequences of frequent marijuana use also seem to extend past high school 8. Terry-McElrath et al. find college enrollment and completion are low among frequent adolescent marijuana users 3. Their analyses show that just 23.8% of 12th grade frequent marijuana users graduate college, with an additional 11.3% attending college but not graduating. This compares nationally to approximately 60–70% of high school graduates enrolling in college, depending on the cohort 9. Educational consequences are probably just the beginning of a cascade of negative effects for frequent marijuana users 4, 10. Research has shown that the effects of such use are broad, and affect domains such as social role formation, social relationships, life satisfaction and physical health symptoms, such as sleep and irritability 4, 11-13. Accumulating evidence also shows that marijuana use can precipitate or worsen existing mental health symptoms 14, 15. Interestingly, some of the purported consequences of marijuana use might be the reason for using marijuana in the first place 16. For example, many individuals who use marijuana to sleep or relieve anxiety might unknowingly be alleviating cannabis withdrawal symptoms, which have been recently reported to occur in 12% of frequent users 17. Similarly, although under-researched, it is possible that initiating frequent use at an early age might lead to underdevelopment of adaptive coping strategies for stress and anxiety, which could drive continued use. The sharp increased prevalence of frequent marijuana use in recent cohorts is likely to continue and potentially worsen, considering the high prevalence of this behavioral pattern among current 12th graders, as well as use trajectories that might extend longer during the life-course than previously seen and evidence that relaxed marijuana legislation in the United States may impact the course of adult use 18. Moreover, the view of marijuana as a relatively harmless substance is at odds with mounting scientific evidence and it is unfortunate that public dialogue on the negative impacts of marijuana has not been more pronounced, as these consequences can dim the bright futures of our youth. Terry-McElrath et al. call for greater understanding of the possible broad impacts of long-term patterns of use 3. We propose that a crucial next step for this work is to understand how its findings, along with accumulating evidence of negative consequences from marijuana use, can guide policymaking and public health efforts, as scientists have suggested that marijuana policy has outpaced the science 19. As more states relax their marijuana policies, persistent use and related adverse consequences are likely to continue to grow. Fast-forward to 2031, when today's high school seniors are 30 years old: how prevalent will frequent patterns of use be then; and what will be the impact of these patterns on frequent marijuana users and the rest of society? None. This commentary was supported by the National Institute on Drug Abuse [NIDA, R01DA042748 (K.M.G.), U01DA040219 (A.M.A.) and R01DA014845 (A.M.A)].
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".