Radiographers’ perspectives on the emerging integration of artificial intelligence into diagnostic imaging: The Ghana study

Botwe, Benard Ohene; Antwi, William Kwadwo; Arkoh, Samuel; Akudjedu, Theophilus N.

doi:10.1002/jmrs.460

Cited by 32 publications

(44 citation statements)

References 18 publications

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“…The current study sought to identify the concerns and readiness of radiographers in Ghana to take the COVID-19 vaccination. Out of 234 registered radiographers in Ghana, the study had a response rate of 46.1%, which is lower than the values obtained in quite recent studies among radiographers in Ghana 48,49 but is a reasonable range to yield comparable for similar inferences. 50 The awareness among the radiographers about the intent of the government to pursue COVID-19 vaccination was found to be encouraging which is attributed to the promotion of the vaccination process in the media.…”

Section: Discussioncontrasting

confidence: 63%

COVID-19 vaccine hesitancy concerns: Findings from a Ghana clinical radiography workforce survey

et al. 2022

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Introduction: Vaccination is a key global strategy to mitigate the clinical impact of the COVID-19 virus. As part of local efforts to manage the outbreak, the government of Ghana announced its intention to vaccinate its population starting with essential and high-risk workers including radiographers. However, there were reports of hesitance to receiving the vaccine among the radiography workforce. This study was undertaken prior to the intended vaccination exercise to assess the willingness and concerns of radiographers to undergo the COVID-19 vaccination and to suggest recommendations to improve the vaccine uptake. Methods: An ethically-approved online survey strategy was employed for this cross-sectional study conducted between 24the28th February 2021. The survey employed quantitative questions and open text response options. Quantitative and open text responses were analysed using statistical and thematic analyses, respectively. Results: There were 108 responses (response rate of 46.3%). The majority (n ¼ 64, 59.3%) were willing to have the vaccine, however, some (n ¼ 44, 40.7%) were not. The main reason behind their willingness to have the vaccine was its ability to reduce the spread of infections and lower mortality (n ¼ 35, 54.7%). However, doubts about the vaccine's efficacy and side effects (n ¼ 26, 56.8%), conspiracy theory concerns about its effects on the Ghanaian race (n ¼ 4, 9.1%), and fertility concerns (n ¼ 2, 4.5%) were some reasons for their hesitance to receive the vaccine. The open text commentary further revealed that the vaccine was thought of as a lifesaving medication, however, clinical safety concerns, lack of education/information and religious beliefs were affecting peoples' willingness to be vaccinated. Conclusion: Our findings demonstrate the need for an urgent public health educational intervention to address the COVID-19 vaccine hesitancy concerns raised by radiographers to help increase the vaccine uptake.Implication for practice: The study provides pertinent information to improve COVID-19 vaccine uptake among radiographers to limit the spread of infections.

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Section: Discussioncontrasting

confidence: 63%

COVID-19 vaccine hesitancy concerns: Findings from a Ghana clinical radiography workforce survey

et al. 2022

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“…A barrier to clinicians' confidence and understanding may be the dearth of education on the subject, with many radiographers in both diagnostic and therapeutic radiography stating that they do not consider themselves to have any skill in AI. Botwe et al ( 36 ) conducted a survey of African radiographers on their perception of AI in diagnostic imaging and reported that 82.2% of 151 respondents felt that a lack of knowledge will be a significant barrier to the implementation of AI in the clinical setting. This is supported by the responses from our survey indicating that very few respondents felt that they were well-trained to implement AI and new technologies in the clinical setting and why both professions overwhelmingly agree that there is not enough education and training available in AI for radiographers ( Figure 5 ).…”

Section: Discussionmentioning

confidence: 99%

“…Staff were excited and ready to embrace AI, however 17% of respondents stated they had no knowledge of AI, 40% were self-taught, and 73% reported difficulty accessing training courses to fill the knowledge gap for staff. Further work by Botwe et al ( 36 ) surveyed 151 radiographers in Ghana. Most respondents (83%) were positive and would embrace the implementation of AI into practise, however 83% expressed concerns about AI related errors and job displacement.…”

Section: Introductionmentioning

confidence: 99%

Beauty Is in the AI of the Beholder: Are We Ready for the Clinical Integration of Artificial Intelligence in Radiography? An Exploratory Analysis of Perceived AI Knowledge, Skills, Confidence, and Education Perspectives of UK Radiographers

Rainey

O’Regan

Matthew

et al. 2021

Front. Digit. Health

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Introduction: The use of artificial intelligence (AI) in medical imaging and radiotherapy has been met with both scepticism and excitement. However, clinical integration of AI is already well-underway. Many authors have recently reported on the AI knowledge and perceptions of radiologists/medical staff and students however there is a paucity of information regarding radiographers. Published literature agrees that AI is likely to have significant impact on radiology practice. As radiographers are at the forefront of radiology service delivery, an awareness of the current level of their perceived knowledge, skills, and confidence in AI is essential to identify any educational needs necessary for successful adoption into practice.Aim: The aim of this survey was to determine the perceived knowledge, skills, and confidence in AI amongst UK radiographers and highlight priorities for educational provisions to support a digital healthcare ecosystem.Methods: A survey was created on Qualtrics® and promoted via social media (Twitter®/LinkedIn®). This survey was open to all UK radiographers, including students and retired radiographers. Participants were recruited by convenience, snowball sampling. Demographic information was gathered as well as data on the perceived, self-reported, knowledge, skills, and confidence in AI of respondents. Insight into what the participants understand by the term “AI” was gained by means of a free text response. Quantitative analysis was performed using SPSS® and qualitative thematic analysis was performed on NVivo®.Results: Four hundred and eleven responses were collected (80% from diagnostic radiography and 20% from a radiotherapy background), broadly representative of the workforce distribution in the UK. Although many respondents stated that they understood the concept of AI in general (78.7% for diagnostic and 52.1% for therapeutic radiography respondents, respectively) there was a notable lack of sufficient knowledge of AI principles, understanding of AI terminology, skills, and confidence in the use of AI technology. Many participants, 57% of diagnostic and 49% radiotherapy respondents, do not feel adequately trained to implement AI in the clinical setting. Furthermore 52% and 64%, respectively, said they have not developed any skill in AI whilst 62% and 55%, respectively, stated that there is not enough AI training for radiographers. The majority of the respondents indicate that there is an urgent need for further education (77.4% of diagnostic and 73.9% of therapeutic radiographers feeling they have not had adequate training in AI), with many respondents stating that they had to educate themselves to gain some basic AI skills. Notable correlations between confidence in working with AI and gender, age, and highest qualification were reported.Conclusion: Knowledge of AI terminology, principles, and applications by healthcare practitioners is necessary for adoption and integration of AI applications. The results of this survey highlight the perceived lack of knowledge, skills, and confidence for radiographers in applying AI solutions but also underline the need for formalised education on AI to prepare the current and prospective workforce for the upcoming clinical integration of AI in healthcare, to safely and efficiently navigate a digital future. Focus should be given on different needs of learners depending on age, gender, and highest qualification to ensure optimal integration.

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“…To enhance validity, the authors used aspects of questions from similar which allowed for study comparison. 3,5 Further questions and answer choices were derived from extensive literature in AI technology and clinical use. 4,9e19 The population were Irish DRs and RTTs.…”

Section: Methodsmentioning

confidence: 99%

“…Botwe et al 3 have explored this area in Ghana, and whilst a positive attitude towards AI is noted, there are concerns around job security, AI-related errors, and knowledge gaps. These apprehensions were also reported in a Canadian study investigating AI impact in radiation oncology.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence: The opinions of radiographers and radiation therapists in Ireland

2021

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Introduction: Implementation of Artificial Intelligence (AI) into medical imaging is much debated. Diagnostic Radiographers (DRs) and Radiation Therapists (RTTs) are at the forefront of this technological leap, thus an understanding of their views, in particular changes to their current roles, is key to safe, optimal implementation. Methods: An online survey was designed, including themes: role changes, clinical priorities for AI, patient benefits, and education. It was distributed nationally in the Republic of Ireland via the national professional body, clinical management, and social media. Results: 318 DRs and 77 RTTs participated. Priority areas for development included quality assurance, clinical audit, radiation dose optimisation, and improved workflow for DRs and treatment planning algorithm optimisation, clinical audit, and post processing for RTTs. There was resistance regarding AI use for patient facing roles and final image interpretation. 27.6% of DRs and 40.3% of RTTs currently use AI clinically and 46.1% of DRs and 41.2% of RTTs anticipate reduced staffing levels with AI. 64.9% of DRs and 70.6% of RTTs felt AI will be positive for patients, with the majority promoting AI regulation through national legislation. 86.1% of DRs and 94.0% of RTTs were favourable to AI implementation. Conclusion: This research identifies priority AI development and implementation areas for DRs and RTTs. It thus highlights that DRs and RTTs should be involved in development of AI tools that would best support practice, and that clearly defined pathways for AI implementation into these key professions requires discussion so that optimum use and patient safety can ensue. Implications for practice: Understanding opinions of AI has significant implications for practice, for ensuring optimal product development, implementation, and training, together with planning for potential DR and RTT role changes.

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Radiographers’ perspectives on the emerging integration of artificial intelligence into diagnostic imaging: The Ghana study

Cited by 32 publications

References 18 publications

COVID-19 vaccine hesitancy concerns: Findings from a Ghana clinical radiography workforce survey

COVID-19 vaccine hesitancy concerns: Findings from a Ghana clinical radiography workforce survey

Beauty Is in the AI of the Beholder: Are We Ready for the Clinical Integration of Artificial Intelligence in Radiography? An Exploratory Analysis of Perceived AI Knowledge, Skills, Confidence, and Education Perspectives of UK Radiographers

Artificial intelligence: The opinions of radiographers and radiation therapists in Ireland

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