Case management reduces drinking during pregnancy among high-risk women
Bibliographic record
Abstract
May, P., Marais, A., Gossage, J., Barnard, R., Joubert, B., Cloete, M., Hendricks, N., Roux, S., Blom, A., Steenekamp, J., Alexander, T., Andreas, R., Human, S., Snell, C., Seedat, S., Parry, C., Kalberg, W., Buckley, D., & Blankenship, J. (2013). Case management reduces drinking during pregnancy among high-risk women. The International Journal Of Alcohol And Drug Research, 2(3), 61-70. doi:10.7895/ijadr.v2i3.79 (http://dx.doi.org/10.7895/ijadr.v2i3.79)Aim: To estimate the efficacy of Case Management (CM) for women at high risk for bearing a child with Fetal Alcohol Spectrum Disorders (FASD).Design: Women were recruited from antenatal clinics and engaged in 18 months of CM.Setting: A South African community with a subculture of heavy, regular, weekend, recreational drinking and with high documented rates of FASD. Participants: Forty-one women who were at high risk for bearing a child with FASD.Measures: Statistical analysis of trends in drinking and other risk factors.Findings: At intake, 87.8% of the women were pregnant, most had previous alcohol-exposed pregnancies, 67.5% reported that most or all of their friends drank alcohol, and 50.0% had stressful lives. CM was particularly valuable for pregnant women, as statistically significant reductions in alcohol risk were obtained for them in multiple variables: total drinks on weekends after six months of CM (p = .026) and estimated peak blood alcohol concentration (BAC) at six (p < .001) and 18 months (p < .001). For participants completing 18 months of CM, AUDIT scores improved significantly by 6-month follow-up (from 19.8 to 9.7, p = .000), and although there were increases at 12 and 18 months, AUDIT scores indicate that problematic drinking remained statistically significantly lower than baseline throughout CM. Happiness scale scores correlated significantly with reduced drinking in most time periods.Conclusions: Making an enduring change in drinking behavior is difficult in this social setting. Nonetheless, CM provided by skilled and empathic case managers reduced maternal drinking at critical times, and, therefore, alcohol exposure levels to the fetus.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".