Positive perception of pharmacogenetic testing for psychotropic medications
Bibliographic record
Abstract
INTRODUCTION: Pharmacogenetics attempts to identify inter-individual genetic differences that are predictive of variable drug response and propensity to side effects, with the prospect of assisting physicians to select the most appropriate drug and dosage for treatment. However, many concerns regarding genetic tests exist. We sought to test the opinions of undergraduate science and medical students in southern Ontario universities toward pharmacogenetic testing. METHODS AND RESULTS: Questionnaires were completed by 910 undergraduate medicine and science students from 2005 to 2007. Despite students' concerns that the results of genetic tests may be used for other purposes without consent (71%) or lead to discrimination (78%), an overwhelming number of students were in favor of pharmacogenetic testing (90%). DISCUSSION: To our knowledge, this study is the first to survey a large sample for their attitude toward pharmacogenetic testing for psychotropic medications. Our results indicate that, although concerns remain and scientific advancements are required, respondents were in support of pharmacogenetic testing for medications used to treat schizophrenia. © 2014 The Authors. Human Psychopharmacology: Clinical and Experimental published by John Wiley & Sons, Ltd.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".