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

Journal article

van de Venter, Riaan, Skelton, Emily, Matthew, Jacqueline, Woznitza, N., Tarroni, Giacomo, Hirani, Shashivadan P, Kumar, Amrita, Malik, Rizwan and Malamateniou, Christina 2023. Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study. Insights into Imaging. 14 (1), p. 25. https://doi.org/10.1186/s13244-023-01372-2
Authorsvan de Venter, Riaan, Skelton, Emily, Matthew, Jacqueline, Woznitza, N., Tarroni, Giacomo, Hirani, Shashivadan P, Kumar, Amrita, Malik, Rizwan and Malamateniou, Christina
AbstractArtificial 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. 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. 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. 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. [Abstract copyright: © 2023. The Author(s).]
KeywordsRadiography; Action research; Evaluation; Education; Artificial intelligence
Year2023
JournalInsights into Imaging
Journal citation14 (1), p. 25
PublisherSpringer
ISSN1869-4101
Digital Object Identifier (DOI)https://doi.org/10.1186/s13244-023-01372-2
Official URLhttps://insightsimaging.springeropen.com/articles/10.1186/s13244-023-01372-2
Publication dates
Online03 Feb 2023
Publication process dates
Accepted15 Jan 2023
Deposited20 Feb 2023
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Smith, Tony, Harris, J., Woznitza, N., Marese, S. and Sale, C. 2015. Conceptualisation of the characteristics of advanced practitioners in the medical radiation profession. Journal of Medical Radiation Sciences. 62 (3), pp. 204-211. https://doi.org/10.1002/jmrs.115
e-Learning for Healthcare – Image Interpretation Project
Woznitza, N., e-Learning for Healthcare and College of Radiographers 2012. e-Learning for Healthcare – Image Interpretation Project. e-Learning for Healthcare.
An unusual cause of respiratory distress
Woznitza, N., Datsopolous, S., Shukla, R. and Aladangady, N. 2012. An unusual cause of respiratory distress. Archives of Disease in Childhood. 97, pp. A12-A13. https://doi.org/10.1136/archdischild-2012-301885.30
Chest X-Ray interpretation: agreement between consultant radiologists and a reporting radiographer in clinical practice in the United Kingdom
Woznitza, N., Piper, K., Burke, S., Patel, K., Amin, S. and Grayson, K. 2013. Chest X-Ray interpretation: agreement between consultant radiologists and a reporting radiographer in clinical practice in the United Kingdom.
Radiographer clinical reporting
Woznitza, N. 2014. Radiographer clinical reporting.
Commentary: radiographer reporting
Woznitza, N. 2014. Commentary: radiographer reporting. Journal of Medical Radiation Sciences. 61 (2), pp. 66-68. https://doi.org/10.1002/jmrs.51
Do you see what I see? Clinical review of discordant chest x-ray consultant radiologist and radiographer interpretations
Woznitza, N., Piper, K., Bothamley, G. and Burke, S. 2014. Do you see what I see? Clinical review of discordant chest x-ray consultant radiologist and radiographer interpretations.
Optimizing patient care in radiology through team-working: audit data
Woznitza, N. 2014. Optimizing patient care in radiology through team-working: audit data.
Optimizing neonatal X-ray quality: results of an audit
Woznitza, N., Hayes, N., Malshava, N. and McGuinness, D. 2014. Optimizing neonatal X-ray quality: results of an audit.
Agreement in neonatal x-ray interpretation: a comparison between consultant paediatric radiologists and a reporting radiographer
Woznitza, N., Piper, K., Aladangady, N., Iliadis, K., Prakash, R. and Santos, R. 2014. Agreement in neonatal x-ray interpretation: a comparison between consultant paediatric radiologists and a reporting radiographer.
Advanced radiographic practice in adult chest imaging
Woznitza, N. 2014. Advanced radiographic practice in adult chest imaging.
Can reporting radiographers produce clinically relevant reports?
Woznitza, N. and Piper, K. 2011. Can reporting radiographers produce clinically relevant reports?