Perception of non-layperson advisory committee members on the application of a discrete choice experiment instrument to patients and advisory committee members: a qualitative study
Bibliographic record
Abstract
OBJECTIVES: To explore the view of nonlayperson committee members on the added value of a discrete choice experiment (DCE) instrument to measure patient and committee member preferences for a health intervention. METHODS: Nine semistructured interviews were conducted with voting members from two types of advisory committees in Quebec, Canada: one from the Ministry of Health and Social Services, and eight from the Health Technology Assessment (HTA) agency. The DCE instrument, administrable to patients (i.e., pregnant women) and committee members, was developed and administered to both groups to measure their preferences about the addition of fetal chromosomal anomalies to a prenatal screening program. A conceptual framework consisting of three dimensions (relative advantage, compatibility, and complexity) was used for data collection and analyses. RESULTS: Committee members considered the DCE instrument, when used with both patients and committee members, to be particularly valuable in raising awareness of potential biases. These biases, generated by committee members' interests and disciplinary perspectives, can reduce the importance of the patient perspective in decision making by advisory committees. CONCLUSIONS: This qualitative study provides insight into the perceptions of nonlayperson advisory committee members regarding the added value of a DCE instrument administered to patients and committee members regarding an intervention. Additional studies are required to explore the perceptions of other stakeholders (e.g., managers, patients, and public representatives) regarding the application of DCE and to assess its impact on HTA recommendations regarding the value of new health interventions.
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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 | 0.065 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".