Evidence map›Paper›PMID 42129729›Full record

ArticleBMC nursing2026

Virtual simulator prototype for teaching natural childbirth care: a validation study.

Daianny Cristina de Almeida Silva, Saiwori de Jesus Silva Bezerra Dos Anjos, Keila Maria Carvalho Martins, Antonio Rodrigues FerreiraJúnior, Dafne Paiva Rodrigues, Rhanna Emanuela Fontenele Lima de Carvalho

Abstract read
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Article in BMC nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Daianny Cristina de Almeida SilvaAcademic Master's Course of the Postgraduate Program Clinical Care in Nursing and Health, State University of Ceará, Fortaleza, Brazil.
Saiwori de Jesus Silva Bezerra Dos AnjosPostgraduate Program Clinical Care in Nursing and Health, State University of Ceará, Fortaleza, Brazil.
Keila Maria Carvalho MartinsDoctoral Course of the Postgraduate Program Clinical Care in Nursing and Health, State University of Ceará, Fortaleza, Brazil. keilamcm@gmail.com.
Antonio Rodrigues FerreiraJúniorPostgraduate Program in Public Health, State University of Ceará, Fortaleza, Brazil.
Dafne Paiva RodriguesPostgraduate Program Clinical Care in Nursing and Health, State University of Ceará, Fortaleza, Brazil.
Rhanna Emanuela Fontenele Lima de CarvalhoPostgraduate Program Clinical Care in Nursing and Health, State University of Ceará, Fortaleza, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObstetric care demands clinical reasoning, technical skills and timely decisions. Persistent training gaps highlight the need for strategies that integrate theory and practice. Educational technologies, especially virtual clinical simulation, offer safe, realistic environments for skill development. Thus, this study aimed to validate a virtual simulation prototype for teaching natural childbirth care.

methodThis methodological study, conducted between May 2021 and June 2022, involved three stages: construction of the storyboard of a virtual simulation prototype including two clinical scenarios (normal labor and postpartum hemorrhage); content validation by 26 experts who assessed the scenarios and storyboard interfaces using the Suitability Assessment of Materials (SAM), analysis based on the Agreement Index (AI); and appearance validation by 16 obstetric nursing residents using the Instrument for Validation of the Appearance of Educational Technologies in Health (IVAETH). Ethical approval was obtained, and all participants provided informed consent.

resultsThe design and storyboard of the simulator demonstrated adequacy for its intended educational purpose. The sample, composed of 26 nurse specialists with experience in technology validation, positively validated all screens of the constructed storyboard, with an agreement index greater than 0.90 in the six evaluation domains (Content; Language appropriate for the population; Graphic illustrations, lists, tables; Layout and typography; Learning and motivation; and Cultural adaptation). Sixteen obstetric nursing residents, predominantly at the State University of Ceará, participated in this study. The evaluation of the domains for appearance validation yielded an average agreement index greater than 0.80 among residents.

conclusionThe storyboard developed for virtual reality simulation scenarios in childbirth care demonstrated high levels of agreement in both content and appearance validation, indicating its adequacy as an educational tool for obstetric nursing training. The validated structure provides a foundation for the future development of the Birth Now virtual simulator to support clinical decision-making in childbirth care.

Indexed as

ChildbirthLaborNursing assistanceObstetric nursingSimulationTeachingTechnology

Identifiers

PMID42129729
PMCPMC13339397

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.