Feigning Symptoms to Obtain Prescription Stimulants: A Vignette-Based Study on Its Conditions
Bibliographic record
Abstract
This vignette-based study examined the willingness to feign symptoms to obtain a prescription following an analysis on who might use prescription stimulants to enhance performance ( N = 3,468). It experimentally manipulated three factors: the social disapproval of prescription stimulant use for enhancement purposes, the physicians’ diagnostic efforts, and the medical condition (attention-deficit/hyperactivity disorder and narcolepsy); respondent characteristics of self-control, personal morality, and self-efficacy were also measured. Our results showed that social disapproval of prescription drug use, a personal morality that disapproves of drug use, high self-control, and high self-efficacy were negatively associated with the willingness to use. Willingness increased especially in situations of social approval when there was a stronger personal approval of drug use, or surprisingly when physicians’ diagnostic efforts were higher. The feigning willingness was lower in situations of social disapproval and when personal morality disapproved of feigning. Thus, personal and situational characteristics are relevant to understand both behaviors.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".