Concurrent validity of the Alcohol Purchase Task for measuring the reinforcing efficacy of alcohol: an updated systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Background and aims An early meta‐analysis testing the concurrent validity of the Alcohol Purchase Task (APT), a measure of alcohol's relative reinforcing value, reported mixed associations, but predated a large number of studies. This systematic review and meta‐analysis sought to: (1) estimate the relationships between trait‐based alcohol demand indices from the APT and multiple alcohol indicators, (2) test several moderators and (3) analyze small study effects. Methods A meta‐analysis of 50 cross‐sectional studies in four databases ( n = 18 466, females = 43.32%). Sex, year of publication, number of APT prices and index transformations (logarithmic, square root or none) were considered as moderators. Small study effects were examined by using the Begg–Mazumdar, Egger's and Duval & Tweedie's trim‐and‐fill tests. Alcohol indicators were quantity of alcohol use, number of heavy drinking episodes, alcohol‐related problems and hazardous drinking. APT indices were intensity (i.e. consumption at zero cost), elasticity (i.e. sensitivity to increases in costs), O max (i.e. maximum expenditure), P max (i.e. price associated to O max ) and breakpoint (i.e. price at which consumption ceases). Results All alcohol demand indices were significantly associated with all alcohol‐related outcomes ( r = 0.132–0.494), except P max , which was significantly associated with alcohol‐related problems only ( r = 0.064) . The greatest associations were evinced between intensity in relation to alcohol use, hazardous drinking and heavy drinking and between O max and alcohol use. All the tested moderators emerged as significant moderators. Evidence of small‐study effects was limited. Conclusions The Alcohol Purchase Task appears to have concurrent validity in alcohol research. Intensity and O max are the most relevant indices to account for alcohol involvement.
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 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 | 0.033 | 0.082 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.032 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".