Validation of a Patient-Reported Experience Measures (PREMs) Questionnaire in Prenatal Screening Among Pregnant Women
Bibliographic record
Abstract
Context Addressing patient experience is crucial. There is a gap in understanding the experiences of pregnant women undergoing prenatal screening, as no validated patient-reported experience measures (PREM) questionnaire exists for this purpose. Objective Validate the PREM-PS by assessing its measurement properties, including structural validity, internal consistency, and cross-cultural validity in a population of pregnant women undergoing prenatal screening. Study Design and Analysis This instrument development study is a secondary analysis using data from a prospective, open-label, multicenter randomized trial. Setting or Dataset Data were collected in two Canadian provinces (QC and BC) from 2019 to 2022. Pregnant women received prenatal screening between 10 and 13 weeks of pregnancy and at 22 weeks, they were invited to complete the PREM-PS questionnaire. Population Studied Pregnant women aged 19 and older. Intervention/Instrument The questionnaire was adapted from an existing questionnaire addressing satisfaction with the delivery and organization of care among pregnant women (PreMaPEQ). The psychometric validation was conducted on a sample of pregnant women randomized 2:1 to first-tier non-invasive prenatal screening (NIPS) or traditional biochemical testing for chromosomal anomalies T21, T18 or T13. The administered questionnaire consists of 17 questions, 10 items being on a 5-point Likert scale. Exploratory factor analysis was conducted separately for the French and English questionnaires, by using half of the data to determine the structure of the underlying factors. A confirmatory factor analysis was carried out on the remaining data to evaluate the structural validity of the factors. Outcome Measures Internal consistency was assessed using Cronbach’s alpha. Results The sample included 7815 pregnant women. 4313 responded in French and 3502 in English. The mean age was 31.0 (±3.9). The overall response rate was 80% and the completion rate was 96%. Following factor analyses, 7 items were retained and grouped into two latent factors (i.e., human experience of the process and perception of the healthcare professional9s technical competence). Cronbach alphas were higher than 0.88 for all factors, revealing excellent internal consistency. Conclusions The PREM-PS is the first validated instrument to mesure patient experience in prenatal screening and showed strong psychometric performance.
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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 | 0.019 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".