Mental Health Correlates Among Pregnant Women Who Use Cannabis in the United States
Bibliographic record
Abstract
Purpose: The purpose of the study is to examine cannabis use and mental health symptoms among a national sample of pregnant women. Background: With the increase of state level marijuana legalization and corresponding decrease in perception of harm, marijuana use in pregnant women is rising. Between 2002 and 2017, the adjusted prevalence of self-reported past month cannabis use among pregnant women doubled from 3.4% to 7.0%. Antenatal cannabis use has been linked to low birthweight, preterm birth and increased NICU admission in exposed neonates. Extant literature examining reasons for maternal use during pregnancy include managing nausea as well as coping with anxiety and stress. Extant research that has examined associations between poor mental health and cannabis in pregnant women have been limited to associations between one mental health diagnosis (e.g. depression) in large national samples of American or Canadian women or multiple diagnoses (e.g. depression, anxiety and/ or trauma) in smaller samples with limited generalizability to the general population. Methods: We employed a cross-sectional correlational design using secondary analysis of existing data from the 2008- 2014 National Survey on Drug Use and Health (NSDUH). The sample was restricted to pregnant women ages 18-44 years old who identify as pregnant (n=5,520) and self- report marijuana use in the past 30 days (n=312). Bivariate analysis using Chi-square and t-test were calculated to examine the association and strength of the relationships between variables. Logistic regression was used to identify whether past month psychological distress, past year depression, past year anxiety increase the odds for past month cannabis use after adjusting for sociodemographic characteristics Results: The sample was diverse: 55.9% identified as Non- Hispanic white, 16.0% as Non- Hispanic Black, 19.0% as Hispanic, 10% as Other. There were significant differences in sociodemographic, clinical, substance use and mental health characteristics between women who self-report versus denied cannabis use during pregnancy. The regression coefficients for psychological distress scores and past year anxiety were significant. Psychological distress was the most significant of the two mental health variables with a Wald score of 42.968 compared to 7.677 for past year anxiety. The regression coefficient for psychological distress (B = 0.079, OR = 1.08, p < .001) indicated that for a one unit increase in the psychological distress score, the odds of using cannabis during pregnancy would increase by approximately 8%. The regression coefficient for past year anxiety was significant (B = 0.531, OR = 1.70, p < .001).
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".