Trends in alcohol consumption during pregnancy in Australia, 2001–2010
Bibliographic record
Abstract
Callinan, S., & Ferris, J. (2014). Trends in alcohol consumption during pregnancy in Australia, 2001–2010. The International Journal Of Alcohol And Drug Research, 3(1), 17-24. doi:10.7895/ijadr.v3i1.108Aim: The aim of the current study is to examine, using cross-sectional data, the role of maternal age, period (year of pregnancy) and cohort (year of birth) as predictors of alcohol consumption during pregnancy over a 10-year period.Design: Four cross-sectional surveys were examined, both separately and together.Setting: Using cross-sectional data, there does appear to be a positive relationship between maternal age and alcohol consumption during pregnancy; however, within any one survey period, it is difficult to determine if these patterns are due to period or cohort effects.Participants: The National Drug Strategy Household Survey (NDSHS) is a large-scale survey administered to more than 20,000 respondents. Across four survey periods, 3,281 women reported being pregnant in the 12 months prior to the survey.Measures: The section on pregnancy and alcohol in the NDSHS 2001, 2004, 2007 and 2010.Findings: Age was a significant positive predictor of alcohol consumption during pregnancy in 2010. However, when the four data sets were combined, period appeared to be a stronger predictor, with younger groups and cohorts decreasing consumption at a faster rate over time than older groups and cohorts.Conclusions: Although age and cohort do play a role in the likelihood of alcohol consumption among Australian women during pregnancy, period is the most important predictor, indicating that alcohol consumption among pregnant women is decreasing. Furthermore, knowledge of pregnancy results in a marked decrease in consumption, suggesting a possible focus for prevention campaigns.
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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 | 0.000 |
| 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 | 0.000 | 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".