The advice is aimed at those working in a health library setting. There are also some articles that give a background on AI in healthcare to understand the everyday implications of AI on healthcare professionals.

I found this video very good and although it has similar content to some of the research papers O’ Connor presented the information in and easy to follow way that was nursing focused.

From the research conducted it seems these modules leave no stone unturned to cover health data science, ‘Omics and AI to a high level for healthcare professionals. The flexibility of training means that nurses can pick and choose what is applicable to them.

The desired audience of this article is nurse authors. The article discusses the benefits AI tools can bring to academic writing including the creating of text, tables and figures. It is being used for researching, drafting, revising and editing manuscripts. It also covers the disadvantages of AI and the importance of nurse authors using their judgement and expertise to check AI generated material in academic writing.

The author of the article gives guidelines for using AI for scholarly writing that would be very helpful for nurses involved in research. These guidelines include helpful tips including an example of how to reference AI.

The article discusses three digital information literacy initiatives created by librarians to help students to use Gen AI in academic research. The digital initiatives give great ideas for other teaching librarians. It includes suggestions like two minute tutorials which would be very useful for accessing busy healthcare professionals in a non-traditional way.

This article provides a frame work for AI integration in nursing using the acronym N.U.R.S.E.S (Navigate AI basics, Utilise AI strategically, Recognise AI pitfalls, Skills support, Ethics in action and Shape the future).

I felt this was a useful and easy to remember framework for teaching. It is a detailed article which also gives clinical examples of AI in healthcare. The author mentions workshops, webinars and online courses as ways of effectively providing training for nurses on AI.

The author identified a gap in research of Large Language Models across the nursing profession. There are several papers discussing LLM in healthcare but this paper focuses on a nursing perspective. She highlights the practical implications of LLM on nurses including creating careplans, improving patient communication and synthesising research articles.

Similar to other research papers it also discusses the limitations of AI and where care should be taken.

This article I felt was beneficial for nurses as well as librarians as it gives everyday examples of AI in nursing.  

The author suggests adjusting the content for each group. The article discusses the planning and running of a two hour professional development workshop.

Lo’s CLEAR framework as mentioned previously is presented along with a brief overview of the growing impact of AI in academic libraries. The larger group in attendance was split into smaller groups to explore AI tools for 1 hour. There is a link above for the LibGuide used which contained the links for the AI tools.

The article discusses a professional development day focused on AI literacy. It covers the challenges, successes and practicalities on the day. There was a session on the role of Gen AI in medical education followed by a hands on library workshop. Prompt engineering was also an element to this workshop. There was virtual and in-person attendees.

Sze also discusses the role of health science librarians in bridging the AI literacy gap in healthcare and healthcare education. This is a very relevant article as it is focused at health science librarians.

This library also has a LibGuide to aid with Generative AI.

This article covers the need for AI literacy for public health education but it is similar to the needs of health care professionals. The author highlights the lack of AI literacy training available in public health education and notes that some students are acquiring their skills through informal and ad hoc methods.

Similar to the N.U.R.S.E.S framework discussed earlier, Acosta has developed a framework of five pillars to organise the core domains of AI literacy. These include technical foundations, ethics, experimental learning, governance and equity.

Similar to the other authors he suggests short courses and workshops as methods of building these skills.

In the article he refers the University of Helsinki’s “Elements of AI”. This is a free, open access AI literacy course, which I have linked above.