Prescription Drug Advertising and Patient Compliance: A Physician Agency Approach
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
Abstract This paper proposes an analysis of both doctors and patients' behavior in an agency model that accounts for the interplay between two highly debated health issues: drug advertising toward doctors and/or patients, and the serious problem of patients' noncompliance with their doctors' prescriptions. Due to the lack of individual data, we propose a structural approach inspired from the industrial organization literature. The model is estimated semiparametrically with product level data on the U.S. market for anti-glaucoma drugs. The results suggest that doctors' prescriptions are directly influenced by the probability of noncompliance, as well as advertising aimed at both doctors and patients. Advertisement toward patients (respectively, doctors) appears to have contributed to (respectively, slowed down) the reduction of the estimated average noncompliance rate.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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