T-ACE and predictors of self-reported alcohol use during pregnancy in a large, population-based urban cohort
Bibliographic record
Abstract
Hicks, M., Tough, S., Johnston, D., Siever, J., Clarke, M., Sauve, R., Brant, R., & Lyon, A. (2014). T-ACE and predictors of self-reported alcohol use during pregnancy in a large, population-based urban cohort. The International Journal Of Alcohol And Drug Research, 3(1), 51-61. doi:10.7895/ijadr.v3i1.117Aims: To determine 1) the relationship between T-ACE score and maternal self-reported alcohol use prior to and during pregnancy, and 2) the relationship between T-ACE score and maternal demographics, mental health and life circumstances.Design: Prospective, population-based cohort study.Setting: Three urban maternity clinics in Calgary, Canada.Participants: 1,929 pregnant women attended by family physicians at low-risk maternity clinics.Measures: Women completed three standardized questionnaires over the telephone in the first and third trimesters and eight weeks post-delivery, including the T-ACE and questions about drug and alcohol use, demographics, mental health and life circumstances.Findings: 43.6% of subjects had a positive T-ACE score at intake (score 2 or greater). A positive T-ACE score was predictive of alcohol use throughout pregnancy, although most women reported no alcohol after the first trimester (93.1%). Multivariate analysis indicated that a positive T-ACE score was significantly associated with being less than 30 years of age; being Caucasian; smoking during pregnancy; having an income of less than $80,000 per annum; having a history of depression; having a history of alcohol use and binge drinking during a previous pregnancy; lower social support; and poor network orientation.Conclusions: There was a positive association between the T-ACE score and maternal self-report of alcohol use, poor mental health and poor social support. Routine use of the T-ACE to assess for risk of an alcohol-exposed pregnancy may also help identify women with complex needs who could benefit from additional prenatal support.
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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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".