JMIR Publications

ABSTRACT

Background:

The use of AI technologies in radiography practice is increasing. As this advanced technology becomes more embedded in radiography systems, clinical practice and the role of radiographers will evolve. In the context of these anticipated changes, it may be reasonable to expect modifications to the competencies and educational requirements of current and future practitioners to ensure successful AI adoption.

Objective:

The aim of this scoping review is to explore and synthesise the literature on the adjustments needed in the radiography curriculum to prepare radiography students for the demands of AI-assisted healthcare environments.

Methods:

Using the Joanna Briggs Institute methodology, an initial search was run in Scopus to determine whether the search strategy that was developed with a library specialist would capture the relevant literature by screening the title and abstract of the first 50 articles. Additional search terms identified in the articles were added to the search strategy. Next, EBSCOhost, PubMed, and Web of Science databases were searched. Two reviewers will independently review the title, abstract, and full-text articles according to the predefined inclusion and exclusion criteria, with conflicts resolved by a third reviewer. The final scoping review will present the data analysis as findings in tabular form and through narrative descriptions.

Results:

The search results will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The final database searches were completed in October 2024 and yielded 2 224 records. Title and abstract screening of 1 930 articles is underway after removing the 294 duplicates. The scoping review is expected to be finalised by the end of March 2025.

Conclusions:

The scoping review aims to systematically map the evidence on the adjustments needed in the radiography curriculum to prepare radiography students for the integration of AI technologies in the healthcare environment. It is relevant to map the evidence because increased integration of AI-based technologies in clinical practice has been noted and changes in practice must be underpinned by appropriate education and training. The findings in this study will provide a better understanding of how the radiography curriculum should adapt to meet the educational needs of current and future radiographers to ensure competent and safe practice in response to AI technologies.