ArticleJournal of midwifery & women's health
Telehealth Simulations with Generative Artificial Intelligence in Midwifery Education: Practice for Person-Centered and Culturally Responsive Care.
Article in Journal of midwifery & women's health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI-Powered Simulation for Nursing Education: Mixed Methods Systematic Review.Journal of medical Internet research · 2026Pooled it
- AI integration in healthcare simulation debriefing: support or substitute?Advances in simulation (London, England) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The International Confederation of Midwives Essential Competencies and the American College of Nurse-Midwives Core Competencies for Basic Midwifery Practice include essential skills needed for safe entry-level practice and provision of person-centered care to individuals from diverse backgrounds. However, opportunities for midwifery students to interact with diverse patient populations may be limited, especially in homogenous areas. Education programs struggle to recruit standardized patients from wide-ranging social, cultural, ethnic, and religious backgrounds. In addition, midwifery students may lack skills or experience in providing culturally responsive care, potentially affecting patients and exacerbating health disparities. This article reports on the pilot use of an online artificial intelligence (AI) simulation platform to prepare midwifery students for person-centered telehealth with culturally and socially diverse, underserved patients. The platform used generative technology to produce interactive avatars with detailed histories and allowed spontaneous and adaptive conversations between the virtual patient and midwife-in-training. Ease of use, avatar fidelity, ability to incorporate diverse cultural elements, student learning, time, and cost in the development were assessed. Case development requires collaboration and an iterative approach. Similar to traditional simulation, AI-based simulations require careful planning, pre- and debriefing discussions, and continuous improvement efforts for maximal student learning. Generative AI-based simulations can enable efficient, flexible preparation for patient-centered, culturally appropriate telehealth.
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What OpenQuestion holds
Registered trials
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.