Prevalence and determinants of attention deficit/hyperactivity disorder (ADHD) medication use during pregnancy: Results from the Quebec Pregnancy/Children Cohort
Bibliographic record
Abstract
AIMS: The use of attention deficit/hyperactivity disorder (ADHD) medications has grown over the past decade among pregnant women, but these treatments are not without risk. Updated prevalence of ADHD medication use and whether prescribed dosages follow guidelines are needed. The aim of this study is to describe the prevalence of ADHD medication use among pregnant women-dosages and switches-and identify determinants of ADHD medication use. METHOD: A population-based longitudinal cohort study within the Quebec Pregnancy/Children Cohort (QPC). Women aged 15-45 years old covered by the RAMQ prescription drug plan for at least 12 months before and during pregnancy from 1998 to 2015. ADHD medication exposure was assessed before and during pregnancy. We estimated odds ratios (ORs) for determinants of ADHD medication use during pregnancy with generalized estimating equations. RESULTS: Among 428,505 included pregnant women, 1,130 (0.26%) used ADHD medication. A 14-fold increase in the prevalence of ADHD medication use in pregnant women was observed, from 1998 (0.08%) to 2015 (1.2%). Methylphenidate was the most prevalent medication at 70.1%. ADHD medication fillings were at optimal dosage 91.8% of the time based on guidelines and 18.1% of women switched to another ADHD medication class during gestation. Main determinants of ADHD medication use during pregnancy were psychiatric disorders (aOR 2.19; 95% confidence interval [CI] 1.57, 2.96), mood and anxiety disorders (aOR 1.74; 95% CI 1.32, 2.24), and calendar year. CONCLUSIONS: The number of pregnancies exposed to ADHD medications has increased similarly to the increase reported in other countries between 1998 and 2015. In addition to the current literature, the use of ADHD medications during pregnancy is consistent with Canadian guidelines recommendations on dosage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".