Exploring daily variations of drinking in the Swiss general population. A growth curve analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aims to address the underlying trajectories of weekly individual drinking patterns by growth models and to relate differences in drinking patterns to socio-demographic and drinking characteristics of respondents. Data came from a two-stage stratified random subsample of 747 persons aged 15 years or more from a Swiss study on alcohol consumption using a within-subject design conducted between March 1999 and July 1999. Beverage specific assessment of daily alcohol consumption was obtained by a weekly drinking diary and other characteristics via telephone interviews. The diary had to be filled out on seven consecutive days. The growth models accounted for up to 37.6% of the initial error variance and provided evidence for two distinct, negatively correlated underlying trajectories of drinking patterns. The first trajectory described an increase in consumption from Monday to Sunday. The second trajectory was about a specific weekend consumption culminating on Saturday with a significantly higher growth rate among young people and heavy episodic drinkers than in other subgroups. Therefore, young and heavy episodic drinkers may be exposed to sudden adverse consequences of alcohol consumption during the weekend. Prevention efforts which are targeted to this subgroup should take its specific drinking pattern into account.
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.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| 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 it