Nurse home visiting and prenatal substance use in a socioeconomically disadvantaged population in British Columbia: analysis of prenatal secondary outcomes in an ongoing randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Nurse-Family Partnership (NFP) involves public health nurses providing frequent home visits from early pregnancy until children reach age 2 years, focusing on first-time parents experiencing socioeconomic disadvantage. Our aim was to evaluate NFP's effectiveness in improving child and maternal health. METHODS: We conducted an analysis of prenatal secondary outcomes in an ongoing randomized controlled trial in British Columbia; the data used in this analysis were collected from January 2014 to May 2017. Participants were pregnant girls and women aged 14-24 years who were preparing to parent for the first time and experiencing socioeconomic disadvantage. They were randomly allocated 1:1 to the intervention (NFP plus existing services) or control group (existing services). Prespecified prenatal secondary outcome indicators were changes in use of nicotine cigarettes and alcohol use by 34-36-weeks' gestation. We also report on prespecified exploratory cannabis and street drug use measures. We used mixed-effect models for longitudinal and clustered data to estimate intervention effects. Analyses were by intention to treat. RESULTS: The median gestational age at baseline for the 739 participants (368 participants in the intervention group, 371 in the comparison group) was 20 weeks, 6 days. By 34-36 weeks' gestation, NFP significantly reduced cigarette counts (over the past 2 d) (difference in changes [DIC] of count -1.6, 95% confidence interval [CI] -6.4 to -1.3) in those who smoked. NFP also significantly reduced rates of prenatal cannabis use (DIC -6.4, 95% CI -17.0 to -1.7), but not rates of street drug or "any" substance use. While we observed decreased rates of cigarette and alcohol use in both groups (DIC of proportions -2.8, 95% CI -15.3 to 0.6; DIC -0.5, 95% CI -8.7 to 1.8, respectively), these changes were not statistically significant. INTERPRETATION: ClinicalTrials.gov, no. NCT01672060.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".