Just Say “I Don't”: Lack of Concordance Between Teen Report and Biological Measures of Drug Use
Bibliographic record
Abstract
BACKGROUND: Prevalence estimates of illicit drug use by teens are typically generated from confidential or anonymous self-report. While data comparing teen self-report with biological measures are limited, adult studies identify varying degrees of under-reporting. METHODS: Hair analyses for cocaine, opiates and marijuana were compared to confidential teen self- and parent-reported teen drug use in a longitudinal cohort of >400 high-risk urban teens and parents. RESULTS: Both teens and parents substantially underreported recent teen cocaine and opiate use. However, compared with parents, teens were more likely to deny biomarker-verified cocaine use. Teen specimens (hair) were 52 times more likely to identify cocaine use compared with self-report. Parent hair analyses for cocaine and opiate use were 6.5 times and 5.5 times, respectively, more likely to indicate drug use than were parental self-report. The lack of concordance between self-report and bioassay occurred despite participant's knowledge that a "certificate of confidentiality" protected both teen and adult participants, and that the biological specimens would be tested for drugs. CONCLUSIONS: These findings confirm prior reports of adult under-reporting of their own drug use while extending our understanding of teen's self-admitted drug use. The lack of concordance between teen self- or parent-reported teen drug use and biomarkers confirm our concerns that both teen- and parent-reported teen drug use is limited, at least for youth in high-risk urban settings. Methods of ascertainment other than self- or parent-report must be considered when health care providers, researchers and public health agencies attempt to estimate teen drug-use prevalence.
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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 | 0.027 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".