Concurrent validity of the alcohol purchase task in relation to alcohol involvement: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Alcohol demand, as measured by an alcohol purchase task (APT), provides a multidimensional assessment of the relative reinforcing efficacy of alcohol. The objective of this meta-analysis is to critically appraise the existing literature on the concurrent validity of the APT by meta-analysing the cross-sectional relationships between indices of the APT (ie, breakpoint, Omax, Pmax, elasticity and intensity) and alcohol-related measures. It also aims to examine methodological procedures used to obtain APT indices and individual variables as potential moderators on the assessed estimations. Methods and analysis A comprehensive literature search conducted from inception to April 2020 will be conducted in the PubMed, PsycINFO, Web of Science and Scopus databases. Two authors will independently screen and extract data from articles using a predefined protocol search and extraction forms. Disagreements will be resolved through discussion with two additional reviewers. All results will be tabulated, and a random-effect meta-analysis will be conducted. Participants’ sex, number of prices and APT methodological procedures will be examined as potential moderators on the observed effect sizes. Ethics and dissemination Results of this meta-analysis will characterise the concurrent validity of the APT in the existing literature. Further, the results are anticipated to provide evidence on which index (or indices) is most robustly associated with alcohol use and severity. Ethics approval was not required for this study and the results will be published in a peer-reviewed journal. PROSPERO registration number CRD42019137512
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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 | 0.090 | 0.137 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.023 | 0.035 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.053 | 0.006 |
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".