Como a inteligência artificial generativa pode facilitar o ensino do raciocínio clínico

uma revisão de escopo

Autores

DOI:

https://doi.org/10.35699/2237-5864.2025.58339

Palavras-chave:

ensino em saúde, inteligência artificial, inteligência artificial generativa, raciocínio clínico, revisão de escopo

Resumo

Esta revisão tem como objetivo mapear e resumir o estado atual da pesquisa para identificar a aplicabilidade dos chatbots no ensino do raciocínio clínico durante a formação médica, considerando as melhores evidências disponíveis. Foi realizada uma busca sistemática e abrangente nas bases de dados PubMed/MEDLINE, Web of Science e Google Scholar, entre agosto de 2023 e agosto de 2024. Foram incluídos estudos originais que descreveram aplicações educacionais alinhadas a estratégias com evidência para o ensino do raciocínio clínico (autoexplicação, reflexão estruturada, prática com casos e feedback). A seleção foi complementada por snowballing e consulta a especialistas. Foram incluídas 21 publicações. Todos os estudos exploraram o uso do ChatGPT (OpenAI); três (14%) também analisaram o Bard (Google), dois (9,5%) investigaram o Bing (Microsoft) e um (5%) explorou outras ferramentas de inteligência artificial. Nossos achados sugerem que chatbots podem apoiar o desenvolvimento de habilidades de raciocínio clínico por meio de estratégias educacionais eficazes. As respostas dos chatbots podem ajudar os estudantes a construir compreensão, promover reflexão deliberada, incentivar feedback ao praticar com casos escritos e adaptar o conteúdo ao estágio de aprendizagem. Poucos estudos levantaram preocupações sobre riscos e questões éticas. Esta revisão demonstrou que os chatbots apresentam um grande potencial para aprimorar o desenvolvimento do raciocínio clínico durante a formação médica. No entanto, é fundamental abordar as limitações inerentes, como os riscos de alucinações e explicações imprecisas, para maximizar o potencial educacional da tecnologia.

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Biografia do Autor

  • Guilherme Freitas Bernardo Ferreira, Universidade Professor Edson Antonio Velano

    Guilherme Freitas Bernardo Ferreira is a neurologist with a master’s degree in Health Education/Clinical Reasoning Education. He served as a professor at Unifenas-BH from 2021 to 2025.

  • Alexandre Sampaio Moura, Faculdade Santa Casa

    Alexandre Sampaio Moura is an infectious diseases physician working as a full professor at the Graduate Program in Medicine and Biomedicine at Faculdade Santa Casa, Belo Horizonte, Brazil. Prof. Moura conducts research in medical education, with a particular interest in clinical reasoning and competence-based assessment.

  • Lígia Maria Cayres Ribeiro, University Medical Center Groningen

    Ligia Cayres Ribeiro is an internal medicine physician with a PhD in Clinical Reasoning. She is a researcher at the University Medical Center Groningen, where she investigates how technology can enhance evidence-informed educational practices.

  • Maria Aparecida Turci, Universidade Professor Edson Antonio Velano

    Maria Aparecida Turci is a public health professional working as a full professor at the Graduate Program in Medicine at Professor Edson Antônio Velano University, Belo Horizonte, Brazil. Prof. Turci conducts research in public health and health professions education.

  • Sílvia Mamede, University Medical Center Groningen

    Sílvia Mamede is a guest professor at the Wenckebach Institute (WIOO), Lifelong Learning, Education and Assessment Research Network (LEARN), University Medical Center Groningen, Netherlands. She conducts research on clinical reasoning and diagnostic error in medicine; educational strategies for the teaching of clinical reasoning; reflection and experiential learning in medical education and clinical practice.

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Seção especial: IA nos processos de ensino-aprendizagem

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06-02-2026

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v. 15 (2025)

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Seção especial: IA nos processos de ensino-aprendizagem

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Copyright (c) 2026 Guilherme Freitas Bernardo Ferreira, Alexandre Sampaio Moura, Lígia Maria Cayres Ribeiro, Maria Aparecida Turci, Sílvia Mamede

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FREITAS BERNARDO FERREIRA, Guilherme; MOURA, Alexandre Sampaio; RIBEIRO, Lígia Maria Cayres; TURCI, Maria Aparecida; MAMEDE, Sílvia. Como a inteligência artificial generativa pode facilitar o ensino do raciocínio clínico: uma revisão de escopo. Revista Docência do Ensino Superior, Belo Horizonte, v. 15, p. 1–27, 2026. DOI: 10.35699/2237-5864.2025.58339. Disponível em: https://periodicos.ufmg.br/index.php/rdes/article/view/58339. Acesso em: 2 nov. 2026.