57 Benzodiazepine use in adolescents: Associations with mental health symptoms and polysubstance use
Bibliographic record
Abstract
In response to the increased availability of prescription drugs, the recreational use of benzodiazepine anxiolytics has more than doubled over the past two decades in high school seniors. Despite findings that youths who misuse anxiolytics are more likely to do so following the receipt of a prescription, and that 30% of adolescents with a prescription use them incorrectly, very few studies have attempted to address non-prescribed benzodiazepine use in adolescents. Such paucity of research is worrisome considering that individuals who initiate anxiolytic use prior to the age of 18 are more likely to develop future substance use disorders. The current study examines the prevalence of non-prescribed use of benzodiazepine anxiolytics (e.g. Xanax, Ativan, Valium, Klonopin) in adolescents as well as its association with mental health symptoms (anxiety, depression) and problem behaviors (aggression, delinquency). Questionnaire responses were collected in 2018 from 7012 high-school students between the ages of 12 and 19 years. Independent samples t-test and chi-square analyses were utilized to determine the relationships between benzodiazepine use, mental health symptoms, and polysubstance use. Funding for the above project comes from Wood County Alcohol, Drug Addiction, and Mental Health Services (ADAMHS). All authors report no conflicts of interest. A total of 5.3% (n = 368) high-school students reported using non-prescribed benzodiazepine medication in the past year. Of these individuals, 40.5% (n =149) reported using these medications more than 3 times in the past year. Girls were significantly more likely to report benzodiazepine use than boys. Analyses suggest that youths who used benzodiazepines at least once in the past year were more likely to report greater internalizing symptoms as well as greater externalizing behaviors. Furthermore, youths who used benzodiazepines were 8.5 times more likely to also use either cigarettes, alcohol, marijuana, or stimulants. Of particular significance was the finding that those who used benzodiazepines were 19.3 times more likely to also use stimulant drugs. Our results suggest that the recreational use of prescription sleep or anxiety drugs may be indicative of increased mental health distress, behavioral problems, and a general pattern of polysubstance use. Given their potential for abuse, medical professionals must exercise vigilance when prescribing benzodiazepine anxiolytics to adolescents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".