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The Learning Revolution: When Artificial Intelligence Transcends The Training Of Nurses And Midwives

Year: 2025
Type: book-chapter
Study design: Observational Study
Abstract: In our era of rapid technological progress, artificial intelligence (AI) is omnipresent, reshaping our lives and strengthening our interconnectedness through increased digitization.AI is transforming healthcare practices using technologies like machine learning, natural language processing, and physical robots, thereby enhancing patient outcomes and offering realistic simulations for healthcare education.This study aimed to assess the knowledge, experiences, and to analyze opinions of nursing and midwifery students regarding AI's usage in their education and future professional practice.Carried out with 189 Moroccan nursing and midwifery students, the study utilized a structured questionnaire via Google Forms to gauge their understanding, exposure, and views on AI in education and practice.Data collected anonymously adhered to ethical standards emphasizing voluntary participation and confidentiality.Results revealed a predominantly feminine (77%) sample, mainly in their twenties, with 61% identifying as nursing students and 39% as midwives.Notably, 71% of respondents were familiar with AI.Concerning AI's educational role, 63% reported positive experiences.Additionally, 62% viewed AI as essential for task automatization to boost work efficiency, crafting personalized care plans (45%), and early diagnosis of complications (39%).Vital skills identified for future professionals to effectively leverage AI encompass understanding AI (92%), technical knowledge (83%), communication skills (76%), critical thinking (69%), and emotional support (67%).It's imperative to raise awareness about AI's benefits to facilitate its integration into healthcare through training programs and communication initiatives.Despite AI's potential to revolutionize nursing and midwifery practices, further research is necessary to ensure seamless integration.
Language: English
Field: Medicine
Open Access status: hybrid
OpenAlex ID: W4411398658
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