Trends in Daily Cannabis Use and Cannabis Use Disorder Among Parents in the U.S., 2012-2023
Bibliographic record
Abstract
Objective: To determine the prevalence and trends in routine cannabis use among U.S. parents of children <18. An increase in cannabis use among parents could be important because cannabis has been linked to parenting quality in cross-sectional studies.Method: Analyzed 2012-2023 data from the National Survey on Drug Use and Health (NSDUH), an annual representative survey of U.S. residents aged ≥12. We estimated the prevalence of cannabis use outcomes in parents vs. non-parents and tested whether trends in cannabis use outcomes among parents vs. non-parents differed.Results: In 2023, 7.8% of parents used cannabis on the majority of days, 4.9% of parents used cannabis daily, and 5.7% of parents met DSM-5 criteria for CUD. Since 2012, daily cannabis use has increased a nearly identical amount in parents vs. non-parents. Four times as many parents used cannabis daily in 2023 vs. 2012, and the rate of CUD among parents has increased 1.3x since 2020 (when first measured). Significant increases have occurred in parents across sociodemographic groups, but are largest in parents who are younger, unmarried, lower income, and have less than a BA.Conclusions: Daily cannabis use among parents went from quite rare in 2012 (1 in 80 parents) to fairly common in 2023 (1 in 20 parents). Back-of-the-envelope calculations suggest ≥5.7 million children in the U.S. now live with a parent who uses cannabis on the majority of days. Determining how cannabis use affects parenting is therefore an important public health question.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".