At-risk drinking in employed men and women
Bibliographic record
Abstract
BACKGROUND: "At-risk" drinking is associated with a variety of negative health and social consequences. However, little is known about the characteristics of at-risk drinkers or of changes in at-risk status over time. PURPOSE: The objective was to examine the correlates of at-risk drinking and the prospective predictors of maintenance or change in at-risk status. METHOD: Participants were 4,322 employed individuals assessed at baseline and 4 years later. At-risk drinking was defined as 2 or more drinks per day for men and 1 or more drinks per day for women. RESULTS: The baseline prevalence of at-risk drinking was 11%. Four percent of baseline not-at-risk individuals transitioned to at-risk drinking at follow-up, and 54% of the baseline at-risk individuals remained at-risk at follow-up. Several demographic-, work-, and tobacco-related variables differentiated at-risk groups and were prospective predictors of change in at-risk drinking status among those individuals who were not at risk at baseline. However, none of the constructs predicted change among at-risk drinkers. CONCLUSION: The data suggest that at-risk drinking is of public health concern. Eleven percent of the participants met criteria for at-risk drinking. Further, at-risk and not-at-risk drinkers differed on numerous characteristics, and their drinking may be influenced by different factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".