Development of a Discrete Choice Experiment (DCE) questionnaire to elicit values by pregnant women and decision-makers for the expansion of a NIPS-based prenatal screening program
Bibliographic record
Abstract
Abstract BackgroundIn an accountable world, being able to take into account the value given by relevant stakeholders to an intervention that could be offered to the population is considered as desirable. DCE is an approach particularly suited for the measurement of such values in the field of prenatal care. Yet, DCE studies in the field of prenatal screening have focused mainly on pregnant women and their care providers but have neglected another key actor, the decision-makers. The objective of the study was to develop a DCE instrument applicable to pregnant women and decision-makers, for the evaluation of new conditions to be added to a screening program for fetal chromosomal anomalies.MethodsAn instrument development study was undertaken. Methods employed included a literature review, a qualitative study performed on pregnant women and decision-makers, and a pilot project to validate the developed instrument and test the feasibility of its administration through an online survey platform. ResultsAn initial list of ten attributes and levels were built from the information provided by the literature review and the qualitative research component of the study. Seven attributes were built based on responses provided by participants from both groups. Two attributes were built from what was said by women only and one from what was said by decision-makers only. Search for consensus through consultations and a focus group discussion led to the retention of eight attributes. A pilot project was then performed with 33 pregnant women. This led to the exclusion of one attribute that showed poor influence on the choice making. The final version of the instrument contains seven attributes.ConclusionThis paper presents the construction of a DCE instrument that can be administered to pregnant women on the demand side, and decision-makers on the supply side. Such an instrument to measure the social desirability of an intervention could be an added value to the decision-making process of Health Technology Assessment agencies.
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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 | 0.061 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".