Perceptions and Prevalence of Cannabis Use in Women With Inflammatory Bowel Disease of Reproductive Age: A Cross-Sectional Study
Bibliographic record
Abstract
Background: Many patients with inflammatory bowel disease (IBD) may use cannabis for relief of symptoms. During pregnancy, however, cannabis exposure may be associated with adverse pregnancy outcomes. We aimed to determine the prevalence and perceptions of cannabis use in women with IBD. Methods: Through recruitment at Mount Sinai Hospital and online platforms such as Twitter, women with IBD (age 18-45) were asked to complete anonymous surveys on demographics, cannabis use, perception of use during pregnancy, and discussing its use with healthcare providers (HCP). Categorical variables were reported as frequencies and compared across groups with the chi-square test. Results: One-hundred and two pregnant patients with IBD were included in this study, 19 (18.6%) reported using cannabis. Current users were more likely to report constant pain in the last 12 months and discuss its use with their HCP. Fifty-three (52.0%) women were unsure of the specific risks associated with cannabis use during pregnancy, and only 15 (14.7%) had ever discussed its use with their HCP. Those who had discussed cannabis use with their HCP were more likely to have prior IBD-related surgery, perceive its use unsafe during pregnancy, and be more likely to be using cannabis. Conclusion: Many women with IBD report uncertainty of the risks of cannabis use during pregnancy and the majority have never discussed cannabis use with their providers. With the increasing legalization of cannabis in many jurisdictions, it is imperative patients and healthcare providers discuss the risks and benefits of its use, particularly during vulnerable times such as pregnancy.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".