Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study

Riaan van de Venter^{1

2}, Emily Skelton^{3

4}, Jacqueline Matthew^{4

5}, Nick Woznitza^{6

7}, Giacomo Tarroni^{8

9}, Shashivadan P Hirani¹⁰, Amrita Kumar¹¹, Rizwan Malik^{3

12}, Christina Malamateniou^{13

14

15}

Affiliations

¹ Department of Radiography, Faculty of Health Sciences, School of Clinical Care Sciences, Nelson Mandela University, Port Elizabeth, South Africa. riaan.vandeventer@mandela.ac.za.
² Division of Midwifery and Radiography, School of Health and Psychological Sciences, City, University of London, London, UK. riaan.vandeventer@mandela.ac.za.
³ Division of Midwifery and Radiography, School of Health and Psychological Sciences, City, University of London, London, UK.
⁴ Department of Perinatal Imaging and Health, King's College London, London, UK.
⁵ Guy's and St Thomas' NHS Foundation Trust, London, UK.
⁶ Radiology Department, University College London Hospitals, London, UK.
⁷ School of Allied and Public Health Professionals, Canterbury Christ Church University, Canterbury, UK.
⁸ Cit-AI, Department of Computer Science, City, University of London, London, UK.
⁹ BioMedIA, Department of Computing, Imperial College London, London, UK.
¹⁰ Centre for Healthcare Innovation Research, City, University of London, London, UK.
¹¹ Frimley Health NHS Foundation Trust, London, UK.
¹² Royal Bolton Hospital, Farnworth, UK.
¹³ Division of Midwifery and Radiography, School of Health and Psychological Sciences, City, University of London, London, UK. Christina.Malamateniou@city.ac.uk.
¹⁴ Department of Perinatal Imaging and Health, King's College London, London, UK. Christina.Malamateniou@city.ac.uk.
¹⁵ Department of Radiography, HESAV University, Lausanne, Switzerland. Christina.Malamateniou@city.ac.uk.

PMID: 36735172
PMCID: PMC9897152
DOI: 10.1186/s13244-023-01372-2

Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study

Riaan van de Venter et al. Insights Imaging. 2023.

. 2023 Feb 3;14(1):25.

doi: 10.1186/s13244-023-01372-2.

Authors

Affiliations

¹ Department of Radiography, Faculty of Health Sciences, School of Clinical Care Sciences, Nelson Mandela University, Port Elizabeth, South Africa. riaan.vandeventer@mandela.ac.za.
² Division of Midwifery and Radiography, School of Health and Psychological Sciences, City, University of London, London, UK. riaan.vandeventer@mandela.ac.za.
³ Division of Midwifery and Radiography, School of Health and Psychological Sciences, City, University of London, London, UK.
⁴ Department of Perinatal Imaging and Health, King's College London, London, UK.
⁵ Guy's and St Thomas' NHS Foundation Trust, London, UK.
⁶ Radiology Department, University College London Hospitals, London, UK.
⁷ School of Allied and Public Health Professionals, Canterbury Christ Church University, Canterbury, UK.
⁸ Cit-AI, Department of Computer Science, City, University of London, London, UK.
⁹ BioMedIA, Department of Computing, Imperial College London, London, UK.
¹⁰ Centre for Healthcare Innovation Research, City, University of London, London, UK.
¹¹ Frimley Health NHS Foundation Trust, London, UK.
¹² Royal Bolton Hospital, Farnworth, UK.
¹³ Division of Midwifery and Radiography, School of Health and Psychological Sciences, City, University of London, London, UK. Christina.Malamateniou@city.ac.uk.
¹⁴ Department of Perinatal Imaging and Health, King's College London, London, UK. Christina.Malamateniou@city.ac.uk.
¹⁵ Department of Radiography, HESAV University, Lausanne, Switzerland. Christina.Malamateniou@city.ac.uk.

PMID: 36735172
PMCID: PMC9897152
DOI: 10.1186/s13244-023-01372-2

Abstract

Background: Artificial intelligence (AI)-enabled applications are increasingly being used in providing healthcare services, such as medical imaging support. Sufficient and appropriate education for medical imaging professionals is required for successful AI adoption. Although, currently, there are AI training programmes for radiologists, formal AI education for radiographers is lacking. Therefore, this study aimed to evaluate and discuss a postgraduate-level module on AI developed in the UK for radiographers.

Methodology: A participatory action research methodology was applied, with participants recruited from the first cohort of students enrolled in this module and faculty members. Data were collected using online, semi-structured, individual interviews and focus group discussions. Textual data were processed using data-driven thematic analysis.

Results: Seven students and six faculty members participated in this evaluation. Results can be summarised in the following four themes: a. participants' professional and educational backgrounds influenced their experiences, b. participants found the learning experience meaningful concerning module design, organisation, and pedagogical approaches, c. some module design and delivery aspects were identified as barriers to learning, and d. participants suggested how the ideal AI course could look like based on their experiences.

Conclusions: The findings of our work show that an AI module can assist educators/academics in developing similar AI education provisions for radiographers and other medical imaging and radiation sciences professionals. A blended learning delivery format, combined with customisable and contextualised content, using an interprofessional faculty approach is recommended for future similar courses.

Keywords: Action research; Artificial intelligence; Education; Evaluation; Radiography.

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Conflict of interest statement

The authors have no competing interests to declare that may have influenced the integrity of the reported research study.

Figures

**Fig. 1**
Visual summary of the participatory action research cycle, as applied in this study. This cycle can be used to continuously improve the module over time, based on student and faculty feedback

See this image and copyright information in PMC

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Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study

Affiliations

Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study

Authors

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Abstract

Conflict of interest statement

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