Observational studyRevista brasileira de enfermagem2023
Artificial intelligence in the analysis of emotions of nursing students undergoing clinical simulation.
Observational study in Revista brasileira de enfermagem, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Integrative review of artificial intelligence applications in nursing: education, clinical practice, workload management, and professional perceptions.Frontiers in public health · 2025Pooled it
- Building a predictive model for nursing students' use of artificial intelligence: advancing technology acceptance and application in nursing education.BMC nursing · 2026Article
- Enhancing Medical Education: The Role of Artificial Intelligence Tools in the Teaching-Learning Process.Advances in medical education and practice · 2026Review
- Artificial intelligence in nursing: an integrative review of clinical and operational impacts.Frontiers in digital health · 2025Review
- Artificial intelligence to predict bed bath time in Intensive Care Units.Revista brasileira de enfermagem · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveto assess nursing students' emotions undergoing maternal-child clinical simulation.
methodsan observational study, carried out between June and July 2019. The Focus Group technique was used, with 28 nursing students, randomly distributed into three groups, with qualitative (Bardin technique) and quantitative data (Artificial Intelligence) analysis, to analyze emotions through facial expressions, tone of voice and description of speeches.
resultswe defined two categories: "It was not easy, it was very stressful"; and "Very valuable experience". In Artificial Intelligence, emotional distribution between face, voice and speech revealed a prevalence of negative valence, medium-high degree of passivity, medium power to control the situation and medium-high degree of obstruction in task accomplishment. FINAL CONSIDERATIONS: this study revealed an oscillation between positive and negative emotions, and shows to the importance of recognizing them in the teaching-learning process in mother-child simulation.
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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.