Validation of a behavioral economic purchase task for assessing drug abuse liability
Bibliographic record
Abstract
Abstract Behavioral economic purchase tasks quantify drug demand (i.e. reinforcing value of a drug) and have been used extensively to assess the value of various drugs among current users. However, purchase tasks have been rarely used with unfamiliar drugs to address a compound's abuse liability, and the current study sought to validate the paradigm in this capacity. Using a double‐blind placebo‐controlled within‐subjects drug challenge design, the study evaluated differential drug demand on an experimental drug purchase task for a 20 mg dose of oral D‐amphetamine (versus placebo), a prototypic psychostimulant, in 98 stimulant‐naïve participants. Compared with placebo, amphetamine significantly increased intensity, breakpoint and Omax, and significantly decreased elasticity. Mechanistic analyses revealed that Omax and breakpoint mediated the relationship between subjective drug effects and ‘willingness to take again’, a putative indicator of liability via motivation for future drug‐seeking behavior. These findings validate the purchase task paradigm for quantifying the reinforcing value and, in turn, abuse liability of unfamiliar compounds, providing a foundation for a variety of future applications.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".