Although hallucinations are prevalent in psychiatric disorders, such as psychosis or dementia, no studies were to be found in literature about the nursing process addressing the focus "Hallucination". This literature review, which is integrated with a scoping study framework, was performed to determine a clinical data model addressing the focus "Hallucination". PRISMA checklist for scoping reviews was followed. From the total of 328 papers found, 32 were selected. The findings of this review were summarized according to the nursing process addressing the focus "Hallucination". These findings led to determine a clinical data model addressing the focus "Hallucination", comprising the elements of the nursing process. This clinical data model may contribute toward improving nursing decision-making and nursing care quality in relation to a client suffering from hallucination, as well as contribute toward producing more reliable nursing-sensitive indicators.

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Article Synopsis
  • Generative AI can have issues like bias, data privacy concerns, misinterpretation of prompts, and generating inaccurate information, which are known as hallucinations.
  • A scoping review analyzing 120 articles on generative AI in medicine identifies key challenges and suggests solutions for digital health practitioners to navigate these pitfalls.
  • The review highlights frequent issues such as bias, privacy, and compliance, while also noting less discussed topics like overreliance on AI and adversarial attacks.
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