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Enregistrement W2330109992 · doi:10.1097/01.ogx.0000459557.22618.3e

Factors Affecting the Uptake of Prenatal Screening Tests for Congenital Anomalies

2014· article· en· W2330109992 sur OpenAlexaff
Janneke T. Gitsels-van der Wal, Pieternel Verhoeven, Judith Manniën, Linda Martin, Hans S. Reinders, Evelien Spelten, Eileen K. Hutton

Notice bibliographique

RevueObstetrical & Gynecological Survey · 2014
Typearticle
Langueen
DomaineMedicine
ThématiquePrenatal Screening and Diagnostics
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésMedicinePrenatal screeningPrenatal carePregnancySocioeconomic statusObstetricsGestationEthnic groupDemographyFetusPrenatal diagnosisPopulationEnvironmental health

Résumé

récupéré en direct d'OpenAlex

All pregnant women in The Netherlands are eligible for prenatal screening, including the combined test (CT) at approximately 12 weeks to determine the possibility of Down syndrome and the fetal anomaly scan (FAS) at approximately 20 weeks to detect structural anomalies. These tests are not routinely offered as part of prenatal care. The mean uptake of congenital anomaly screening tests has been approximately 27% for the CT and approximately 91% (80%–99%) for the FAS. This study was performed to investigate factors influencing the uptake of these screening tests, considering that uptake is associated with religious background, age, parity, socioeconomic status, ethnicity, and proficiency in Dutch. Between 2009 and 2011, data were collected from 20 midwifery practices in The Netherlands. The response rate was 32% to 72%. Questions regarding CT and FAS uptake were posed to participants between 35 weeks’ gestation and birth and at 6 weeks postpartum. Sociodemographic characteristics were obtained from a participant’s profile in the initial questionnaire. Dichotomous variables were accepting or declining CT or FAS. Of the 7907 participants, 5216 women completed questionnaires about CT and FAS. The mean actual uptake for CT was 23% (n = 1183) and 90% for FAS (n = 4679). The mean CT uptake of 808 women with a non-Dutch background was 29% compared with 22% (P < 0.001) for native Dutch participants. The mean uptake of FAS non-Dutch women was 89%, similar to that for the Dutch participants. Women who were Protestant or living in the eastern region were significantly less likely to have CT (odds ratio [OR], 0.32; 95% confidence interval [CI], 0.13–0.80; P = 0.015; OR, 0.44; 95% CI, 0.21–0.93; P = 0.033, respectively). Older women, those with income higher than the mean, or women from the first generation were significantly more likely to have the CT (OR, 2.00; 95% CI, 1.44–2.78; P < 0.001; OR, 1.97; 95% CI, 1.12–3.45; P = 0.018; OR, 2.91; 95% CI, 1.75–4.85; P < 0.001, respectively). For FAS among western non-Dutch women, those who were Protestant or Catholic were significantly less likely to have FAS (OR, 0.13; 95% CI, 0.05–0.34; P < 0.001; OR, 0.27; 95% CI, 0.09–0.81; P = 0.020, respectively). In the CT model for nonwestern women of non-Dutch background, older women or women with a limited proficiency in Dutch were significantly more likely to have CT (OR, 1.73; 95% CI, 1.25–2.39; P < 0.001; OR, 2.18; 95% CI, 1.34–3.56; P = 0.002, respectively). For FAS among nonwestern non-Dutch women, higher education had an independent positive impact on the uptake (OR, 1.47; 95% CI, 1.02–2.14; P = 0.041), whereas being Muslim or from the first generation had an independent negative impact on uptake (OR, 0.37; 95% CI, 0.19–0.72; P = 0.003; OR, 0.27; 95% CI, 0.13–0.59; P < 0.001, respectively). Being Protestant, having an income higher than the mean, and having a limited proficiency in Dutch were not independently associated with FAS uptake. This nationwide study on factors determining the uptake of CT and FAS found an association with income, parity, religious affiliation, ethnicity, age, education, and regional place of residence. These results may explain differences among women choosing or declining early and late screening but not the large variation in the test uptake among practices or between The Netherlands and other countries.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,122
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,120
Score d'incertitude au seuil0,886

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,122
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,102
Tête enseignante GPT0,318
Écart entre enseignants0,216 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2014
Routes d'admission1
Résumé présentoui

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