Web-Based Training for Nurses on Shared Decision Making and Prenatal Screening for Down Syndrome: Protocol for a Randomized Controlled Trial (Preprint)
Notice bibliographique
Résumé
BACKGROUND Pregnant women often find it difficult to choose from among the wide variety of available prenatal screening options. To help pregnant women and their partners make informed decisions based on their values, needs, and preferences, a decision aid and a web-based shared decision making (SDM) training program for health professionals have been developed. In Canada, nurses provide maternity care and thus can train as decision coaches for prenatal screening. However, there is a knowledge gap about the effectiveness of SDM interventions in maternity care in nursing practice. OBJECTIVE This study aims to assess the impact of an SDM training program on nurses’ intentions to use a decision aid for prenatal screening and on their knowledge and to assess their overall impressions of the training. METHODS This is a 2-arm parallel randomized trial. French-speaking nurses working with pregnant women in the province of Quebec were recruited online by a private survey firm. They were randomly allocated (1:1 ratio) to either an experimental group, which completed a web-based SDM training program that included prenatal screening, or a control group, which completed a web-based training program focusing on prenatal screening alone. The experimental intervention consisted of a 3-hour web-based training hosted on the Université Laval platform with 4 modules: (1) SDM; (2) Down syndrome prenatal screening; (3) decision aids; and (4) communication between health care professionals and the patient. For the control group, the topic of SDM in Module 1 was replaced with “Context and history of prenatal screening,” and the topic of decision aids in Module 3 was replaced with “Consent in prenatal screening.” Participants completed a self-administered sociodemographic questionnaire with close-ended questions. We also assessed the participants' (1) intention to use a decision aid in prenatal screening clinical practice, (2) knowledge, (3) satisfaction with the training, (4) acceptability, and (5) perceived usefulness of the training. The randomization was done using a predetermined sequence and included 40 nurses. Participants and researchers were blinded. Intention to use a decision aid will be assessed by a t test. Bivariate and multivariate analysis will be performed to assess knowledge and overall impressions of the training. RESULTS This study was funded in 2017 and approved by Genome Canada. Data were collected from September 2019 to late January 2020. This paper was initially submitted before data analysis began. Results are expected to be published in winter 2020. CONCLUSIONS Study results will inform us on the impact of an SDM training program on nurses’ intention to use and knowledge of decision aids for prenatal screening and their overall impressions of the training. Participant feedback will also inform an upgrade of the program, if needed. CLINICALTRIAL ClinicalTrials.gov NCT04162288; https://clinicaltrials.gov/ct2/show/NCT04162288 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/17878
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,034 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,004 |
| Méta-épidémiologie (sens large) | 0,012 | 0,007 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,008 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,109 | 0,015 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».