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Record W2736017262 · doi:10.1007/s10897-017-0126-3

Patients’ Knowledge of Prenatal Screening for Trisomy 21

2017· article· en· W2736017262 on OpenAlexaffabout
Michal Sheinis, Kira Bensimon, Amanda Selk

Bibliographic record

VenueJournal of Genetic Counseling · 2017
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsCanada Research ChairsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsTrisomyMedicineFamily medicineHealth literacyDemographicsPrenatal screeningGenetic counselingTest (biology)LiteracyDown syndromeCross-sectional studyInformed consentHealth carePrenatal diagnosisPregnancyAlternative medicinePsychologyPsychiatryDemographyFetusPathology

Abstract

fetched live from OpenAlex

This study's objective was to assess the knowledge of prenatal screening for Trisomy 21 in pregnant women in one institution in Canada. A cross-sectional survey measuring demographics, knowledge of screening, and health literacy, was administered to pregnant women. Of the 135 women who completed the survey, 74% had adequate knowledge of Trisomy 21 and associated screening procedures. Twenty-eight point one percent of women did not receive any counseling. Overall, 29.5% of women did not know that the screening test was optional and 10.2% of women underwent screening prior to having been counseled. Multigravidity (p < 0.05) and prior counseling (p < 0.001) were positively correlated with knowledge while first language other than English (p < 0.001) was negatively correlated with knowledge. Given these findings, an effort needs to be made on the part of health care providers to increase counseling rates to 100%, stressing the optional nature of the test to attain true informed consent.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.311
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2017
Admission routes2
Has abstractyes

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