Adverse childhood experiences and prescription opioid use during pregnancy: an analysis of the North and South Dakota PRAMS, 2019–2020
Bibliographic record
Abstract
OBJECTIVES: This study assesses the association between adverse childhood experiences (ACEs) and prescription opioid use during pregnancy. METHODS: This study uses data on 2,999 individuals from the 2019 and 2020 Pregnancy Risk Assessment Monitoring System (PRAMS) from North Dakota and South Dakota. The relationship between ACEs and prescription opioid use during pregnancy is examined using multiple logistic regression. RESULTS: The prevalence of prescription opioid use increases alongside more ACE exposure. Compared to those with no ACEs, recent mothers with three or more ACEs have a 2.4 greater odds of prescription opioid use during pregnancy (aOR [adjusted odds ratio] = 2.437; 95% CI [confidence interval] = 1.319, 4.503). CONCLUSION: Exposure to three or more ACEs are associated with a higherrisk of prescription opioid use during pregnancy. Additional research is needed better understand the mechanisms that link ACEs and prescription opioid use during pregnancy, as well as how to best support those with ACEs exposure in a trauma-informed manner to reduce the risk of substance use.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".