Patient and Health Care Provider Needs and Preferences in Understanding Pharmacogenomic and Genomic Testing: A Meta-Data Analysis
Bibliographic record
Abstract
Tests that feature genomic indicators can now be used to guide the pharmacological treatment of patients. To better identify the needs and preferences of patients and health care providers in facilitating their understanding of information related to such pharmacogenomic tests (PGx), a review of literature on knowledge translation and health literacy in the context of testing was conducted. Using a grounded theory-based approach, a comparative analysis of data from 36 studies meeting the criteria for the meta-data analysis has revealed the recurrence of three principal themes: (a) knowledge and understanding of genetics and pharmacogenomics; (b) experiences with genetic, genomic, or PGx testing (decision about the test, information delivery, and understanding of test results); and (c) educational/informational resources. This synthesis sheds light on each theme from the standpoint of both patients and health care providers and suggests avenues in which to direct efforts to support the introduction of pharmacogenomic tests in current practice.
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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 | 0.047 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.013 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".