Virtual, Augmented, Mixed, and Immersive Technologies for Prenatal and Childbirth Education: Scoping Review
Notice bibliographique
Résumé
Background: Virtual, augmented, mixed, and other immersive technologies, collectively referred to as extended reality (XR), are increasingly used to enhance experiential learning in health education. By creating interactive 3-dimensional or 360° environments, these technologies allow expectant parents to engage in realistic prenatal and childbirth scenarios, promoting emotional preparedness, knowledge acquisition, and confidence. Although XR has been widely studied in clinical training, its application in prenatal and childbirth education for parents remains less systematically explored. Objective: This scoping review aims to map and synthesize the current evidence on the use of virtual, augmented, mixed, and immersive technologies in prenatal and childbirth education, highlighting their educational benefits, methodological approaches, and implementation challenges. Methods: A comprehensive search was conducted across Scopus, Web of Science, PubMed, CINAHL, IEEE Xplore, APA PsycINFO, and APA PsycArticles from inception to October 16, 2025. Search terms included "virtual reality," "augmented reality," "mixed reality," "extended reality," and "immersive technology," combined with prenatal and childbirth education descriptors. Studies were included if they applied immersive or XR technologies to deliver prenatal or childbirth education for expectant parents. Screening and data extraction were performed independently by 2 reviewers following PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The review was registered on Open Science Framework (OSF). Results: From 1861 records, 11 studies from 8 countries were included, spanning randomized controlled, quasi-experimental, feasibility, and qualitative designs. Interventions comprised head-mounted display-based virtual reality, 360° video, and mixed reality simulations. Outcomes covered psychological, physiological, educational, and experiential domains. Most studies reported feasibility and high engagement, with encouraging signals for reduced anxiety and improved birth preparedness and, in some cases, reductions in pain and intrapartum indicators. No serious adverse events were reported; nausea and discomfort were infrequent and transient. Thematic analysis identified 5 recurring themes: enhanced birth preparedness, realism and presence as a key mechanism, usability barriers and the need for guided facilitation, motivational and educational potential, and limited partner inclusion. Methodological quality was heterogeneous, with small samples, nonstandardized measures, and short follow-up. Conclusions: Evidence for XR in prenatal education is promising yet preliminary. Rigorous multicenter studies with standardized outcomes, longer follow-up, and greater partner involvement, alongside attention to equitable access and digital literacy, are needed to support integration into maternity care pathways.
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 | 0,010 | 0,051 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,005 |
| Bibliométrie | 0,019 | 0,018 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».