Cannabidiol-Only Product Use in Pregnancy in the United States and Canada
Bibliographic record
Abstract
This study aimed to characterize pregnant individuals' use of cannabidiol (CBD). Data are from the International Cannabis Policy Study (2019-2021), a repeated cross-sectional survey of individuals aged 16-65 years in the United States and Canada (N=66,457 women, including 1,096 pregnant women). The primary analysis compared pregnant and nonpregnant women's CBD-only product use patterns and reasons for use. The prevalence of CBD-only use in pregnant women was 20.4% compared with 11.3% among nonpregnant women, P <.001. Reasons for CBD use among pregnant women included anxiety (58.4%), depression (40.3%), posttraumatic stress disorder (32.1%); pain (52.3%), headache (35.6%), and nausea or vomiting (31.9%). Thus, CBD-only product use was prevalent in this large sample, with one in five pregnant women reporting use. Characterization of prenatal CBD use is an important first step to exploring potential risks to exposed offspring.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".