The development and structural validity testing of the Person-centred Practice Inventory-Care (PCPI-C).

BACKGROUND: Person-centred healthcare focuses on placing the beliefs and values of service users at the centre of decision-making and creating the context for practitioners to do this effectively. Measuring the outcomes arising from person-centred practices is complex and challenging and often adopts multiple perspectives and approaches. Few measurement frameworks are grounded in an explicit person-centred theoretical framework. AIMS: In the study reported in this paper, the aim was to develop a valid and reliable instrument to measure the experience of person-centred care by service users (patients)-The Person-centred Practice Inventory-Care (PCPI-C). METHODS: Based on the 'person-centred processes' construct of an established Person-centred Practice Framework (PCPF), a service user instrument was developed to complement existing instruments informed by the same theoretical framework-the PCPF. An exploratory sequential mixed methods design was used to construct and test the instrument, working with international partners and service users in Scotland, Northern Ireland, Australia and Austria. A three-phase approach was adopted to the development and testing of the PCPI-C: Phase 1 -Item Selection: following an iterative process a list of 20 items were agreed upon by the research team for use in phase 2 of the project; Phase 2 -Instrument Development and Refinement: Development of the PCPI-C was undertaken through two stages. Stage 1 involved three sequential rounds of data collection using focus groups in Scotland, Australia and Northern Ireland; Stage 2 involved distributing the instrument to members of a global community of practice for person-centred practice for review and feedback, as well as refinement and translation through one: one interviews in Austria. Phase 3: Testing Structural Validity of the PCPI-C: A sample of 452 participants participated in this phase of the study. Service users participating in existing cancer research in the UK, Malta, Poland and Portugal, as well as care homes research in Austria completed the draft PCPI-C. Data were collected over a 14month period (January 2021-March 2022). Descriptive and measures of dispersion statistics were generated for all items to help inform subsequent analysis. Confirmatory factor analysis was conducted using maximum likelihood robust extraction testing of the 5-factor model of the PCPI-C. RESULTS: The testing of the PCPI-C resulted in a final 18 item instrument. The results demonstrate that the PCPI-C is a psychometrically sound instrument, supporting a five-factor model that examines the service user's perspective of what constitutes person-centred care. CONCLUSION AND IMPLICATIONS: This new instrument is generic in nature and so can be used to evaluate how person-centredness is perceived by service users in different healthcare contexts and at different levels of an organisation. Thus, it brings a service user perspective to an organisation-wide evaluation framework.

Responsible AI practice and AI education are central to AI implementation: a rapid review for all medical imaging professionals in Europe.

Artificial intelligence (AI) has transitioned from the lab to the bedside, and it is increasingly being used in healthcare. Radiology and Radiography are on the frontline of AI implementation, because of the use of big data for medical imaging and diagnosis for different patient groups. Safe and effective AI implementation requires that responsible and ethical practices are upheld by all key stakeholders, that there is harmonious collaboration between different professional groups, and customised educational provisions for all involved. This paper outlines key principles of ethical and responsible AI, highlights recent educational initiatives for clinical practitioners and discusses the synergies between all medical imaging professionals as they prepare for the digital future in Europe. Responsible and ethical AI is vital to enhance a culture of safety and trust for healthcare professionals and patients alike. Educational and training provisions for medical imaging professionals on AI is central to the understanding of basic AI principles and applications and there are many offerings currently in Europe. Education can facilitate the transparency of AI tools, but more formalised, university-led training is needed to ensure the academic scrutiny, appropriate pedagogy, multidisciplinarity and customisation to the learners' unique needs are being adhered to. As radiographers and radiologists work together and with other professionals to understand and harness the benefits of AI in medical imaging, it becomes clear that they are faced with the same challenges and that they have the same needs. The digital future belongs to multidisciplinary teams that work seamlessly together, learn together, manage risk collectively and collaborate for the benefit of the patients they serve.

An experimental machine learning study investigating the decision-making process of students and qualified radiographers when interpreting radiographic images.

AI is becoming more prevalent in healthcare and is predicted to be further integrated into workflows to ease the pressure on an already stretched service. The National Health Service in the UK has prioritised AI and Digital health as part of its Long-Term Plan. Few studies have examined the human interaction with such systems in healthcare, despite reports of biases being present with the use of AI in other technologically advanced fields, such as finance and aviation. Understanding is needed of how certain user characteristics may impact how radiographers engage with AI systems in use in the clinical setting to mitigate against problems before they arise. The aim of this study is to determine correlations of skills, confidence in AI and perceived knowledge amongst student and qualified radiographers in the UK healthcare system. A machine learning based AI model was built to predict if the interpreter was either a student (n = 67) or a qualified radiographer (n = 39) in advance, using important variables from a feature selection technique named Boruta. A survey, which required the participant to interpret a series of plain radiographic examinations with and without AI assistance, was created on the Qualtrics survey platform and promoted via social media (Twitter/LinkedIn), therefore adopting convenience, snowball sampling This survey was open to all UK radiographers, including students and retired radiographers. Pearson's correlation analysis revealed that males who were proficient in their profession were more likely than females to trust AI. Trust in AI was negatively correlated with age and with level of experience. A machine learning model was built, the best model predicted the image interpreter to be qualified radiographers with 0.93 area under curve and a prediction accuracy of 93%. Further testing in prospective validation cohorts using a larger sample size is required to determine the clinical utility of the proposed machine learning model.

A systematic review examining the clinical and health-care outcomes for congenital heart disease patients using home monitoring programmes.

OBJECTIVES: This review aimed to present the clinical and health-care outcomes for patients with congenital heart disease (CHD) who use home monitoring technologies. METHODS: Five databases were systematically searched from inception to November 2020 for quantitative studies in this area. Data were extracted using a pre-formatted data-collection table which included information on participants, interventions, outcome measures and results. Risk of bias was determined using the Cochrane Risk of Bias 2 tool for randomised controlled trials (RCTs), the Newcastle-Ottawa Quality Assessment Scale for cohort studies and the Institute of Health Economics quality appraisal checklist for case-series studies.Data synthesis: Twenty-two studies were included in this systematic review, which included four RCTs, 12 cohort studies and six case-series studies. Seventeen studies reported on mortality rates, with 59% reporting that home monitoring programmes were associated with either a significant reduction or trend for lower mortality and 12% reporting that mortality trended higher. Fourteen studies reported on unplanned readmissions/health-care resource use, with 29% of studies reporting that this outcome was significantly decreased or trended lower with home monitoring and 21% reported an increase. Impact on treatment was reported in 15 studies, with 67% of studies finding that either treatment was undertaken significantly earlier or significantly more interventions were undertaken in the home monitoring groups. CONCLUSION: The use of home monitoring programmes may be beneficial in reducing mortality, enabling earlier and more timely detection and treatment of CHD complication. However, currently, this evidence is limited due to weakness in study designs.

Participatory peer research exploring the experience of learning during Covid-19 for allied health and healthcare science students.

INTRODUCTION: The teaching and learning experience of allied health and healthcare science students has altered because of the Covid-19 pandemic. Limited research has explored the experience on the future healthcare workforce using participatory research design. The aim of this study was to explore the impact of a global pandemic on the clinical and academic experiences of healthcare student using a co-production approach with student peer researchers. METHODS: A participatory research approach adopting online focus groups facilitated by students trained as peer researchers was adopted. First, second and final year students from occupational therapy, physiotherapy, podiatry, healthcare science, diagnostic radiography and imaging, radiotherapy and oncology, and speech and language therapy were recruited to six focus groups. Data generated through focus groups were analysed thematically using the DEPICT model to support a partnership approach. RESULTS: Twenty-three participants took part in six focus groups. The themes identified were: rapid changes to learning; living alongside Covid-19 and psychological impact. Students preferred blended learning approaches when available, as reduced peer interaction, studying and sleeping in the same space, and technology fatigue decreased motivation. CONCLUSION: Due to rapid changes in learning and the stress, anxiety and isolation created by the pandemic, managing study, personal life and placement resulted in a gap in confidence in clinical skills development for students. Students took their professional identity seriously, engaged in behaviours to reduce transmission of Covid-19 and employed a range of coping strategies to protect wellbeing. A challenge with the move to online delivery was the absence of informal peer learning and students indicated that moving forward they would value a hybrid approach to delivery. Higher Education should capitalise on innovative learning experiences developed during the pandemic however it is important to research the impact this has on student skill acquisition and learning experience.

Academic, clinical and personal experiences of undergraduate healthcare students during the COVID-19 pandemic: A prospective cohort study.

BACKGROUND: Coronavirus disease 2019 has impacted upon the role and safety of healthcare workers, with the potential to have a lasting effect on their wellbeing. Limited research has been conducted during previous pandemics exploring how student healthcare workers are impacted as they study and train for their professional careers. OBJECTIVE: The aim of the current study was to examine the specific impact of COVID-19 on the academic, clinical and personal experiences of healthcare students. METHOD: Undergraduate students across three year groups within the School of Health Sciences at Ulster University completed online Qualtrics surveys at three timepoints during one academic year (2020/2021). Quantitative survey data was downloaded from Qualtrics into SPSS Version 25 for descriptive analysis of each cross-sectional sample. Qualitative survey data was downloaded into text format, which was thematically analysed using content analysis. RESULTS: 412 students completed the survey at Time 1 (October 2020), n = 309 at Time 2 (December 2020) and n = 259 at Time 3 (April 2021). Academically, the pandemic had mostly a negative impact on the learning environment, the development of practical skills, the assessment process and opportunities for peer learning and support. Students reported increased stress and challenges managing their workload and maintaining a sense of motivation and routine. Clinically, they felt unprepared by the university for placement where the pandemic had an increasingly negative impact over time on learning and skill development. In terms of personal experiences, despite the majority of students taking steps to keep physically and mentally well, negative impacts on friendships, mental wellbeing and concerns for family were reported. The pandemic had not impacted upon career choice for most students. CONCLUSION: Consideration must be given to the development of practical skills so students feel prepared for their professional careers given the practical nature of their roles. Programme coordinators should adopt a holistic approach to student wellbeing.

An insight into the current perceptions of UK radiographers on the future impact of AI on the profession: A cross-sectional survey.

INTRODUCTION: As a profession, radiographers have always been keen on adapting and integrating new technologies. The increasing integration of artificial intelligence (AI) into clinical practice in the last five years has been met with scepticism by some, who predict the demise of the profession, whilst others suggest a bright future with AI, full of opportunities and synergies. Post COVID-19 pandemic need for economic recovery and a backlog of medical imaging and reporting may accelerate the adoption of AI. It is therefore timely to appreciate practitioners' perceptions of AI used in clinical practice and their perception of the short-term impact on the profession. AIM: This study aims to explore the perceptions of AI in the UK radiography workforce and to investigate its current AI applications and future technological expectations of radiographers. METHODS: An online survey (QualtricsⓇ) was created by a team of radiography AI experts. The survey was disseminated via social media and professional networks in the UK. Demographic information and perceptions of the impact of AI on several aspects of the radiography profession were gathered, including the current use of AI in practice, future expectations and the perceived impact of AI on the profession. RESULTS: 411 responses were collected (80% diagnostic radiographers (DR); 20% therapeutic radiographers (TR)). Awareness of AI used in clinical practice is low, with DR respondents suggesting AI will have the most value/potential in cross sectional imaging and image reporting. TR responses linked AI as having most value in treatment planning, contouring, and image acquisition/matching. Respondents felt that AI will impact radiographers' daily work (DR, 79.6%; TR, 88.9%) by standardising some aspects of patient care and technical factors of radiography practice. A mixed response about impact on careers was reported. CONCLUSIONS: Respondents were unsure about the ways in which AI is currently used in practice and how AI will impact on careers in the future. It was felt that AI integration will lead to increased job opportunities to contribute to decision making as an end user. Job security was not identified as a cause for concern.

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.

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.

"Take My Bone Away?" Hypoxia and bone: A narrative review.

To maintain normal cellular and physiological function, sufficient oxygen is required. Recently, evidence has suggested that hypoxia, either pathological or environmental, may influence bone health. It appears that bone cells are distinctly responsive to hypoxic stimuli; for better or worse, this is still yet to be elucidated. Hypoxia has been shown to offer potentially therapeutic effects for bone by inducing an osteogenic-angiogenic response, although, others have noted excessive osteoclastic bone resorption instead. Much evidence suggests that the hypoxic-inducible pathway is integral in mediating the changes in bone metabolism. Furthermore, many factors associated with hypoxia including changes in energy metabolism, acid-base balance and the increased generation of reactive oxygen species, are known to influence bone metabolism. This review aims to examine some of the putative mechanisms responsible for hypoxic-induced alterations of bone metabolism, with regard to osteoclasts and osteoblasts, both positive and negative.

Impact of the COVID-19 pandemic on radiography practice: findings from a UK radiography workforce survey.

OBJECTIVES: Radiographers are key patient-facing healthcare professionals involved in many aspects of patient care. The working patterns and professional practice of the radiography workforce (RW) has been altered during the COVID-19 pandemic. This survey aimed to assess the impact of the pandemic on radiography practice in the United Kingdom (UK). METHODS: An online cross-sectional survey of the UK RW was performed (March 25th to April 26th, 2020). The survey sought information regarding 1. Demographics 2. Impact of the pandemic on professional practice 3. Infection prevention/control and 4. COVID-19 related stress. Data collected was analysed using the Statistical Package for Social Sciences (v.26). RESULTS: A total of 522 responses were received, comprising n = 412 (78.9%) diagnostic and n = 110 (21.1%) therapeutic RW categories from across the UK. 12.5% (65/522) of the respondents were redeployed. Redeployment did not appear to contribute (p = 0.31) to work-related stress. However, fear of contracting the infection and perceived inadequate personal protective equipment (PPE) were identified as key contributors to stress during the study period. Compared to the therapeutic RW, a significantly higher proportion of the diagnostic RW identified fear of being infected as a major stressor (166/412 (40.3%) vs 30/110 (27.3%), p = 0.01). CONCLUSION: This survey has demonstrated changes to clinical practice, in particular to working patterns, service delivery and infection prevention and control were key contributors to workplace-related stress during the pandemic. ADVANCES IN KNOWLEDGE: Timely and adequate staff training and availability of PPE as well as psychosocial support during future pandemics would enhance quality patient and staff safety.

Removal of scatter radiation in paediatric cardiac catheterisation: a randomised controlled clinical trial.

OBJECTIVE: This study sought to determine if DNA integrity was compromised by ionising radiation from paediatric cardiac catheterisations and if dose optimisation techniques allowed DNA integrity to be maintained. MATERIALS AND METHODS: Children were imaged using either: (i) an anti-scatter grid (current departmental protocol), (ii) no anti-scatter grid or, (iii) no anti-scatter grid and a 15 cm air-gap between the child and the x-ray detector. Dose area product and image quality were assessed, lifetime attributable cancer risk estimates were calculated and DNA double-strand breakages quantified using the γH2AX assay. RESULTS: Consent was obtained from 70 parents/guardians/children. Image quality was sufficient for each procedure performed. Removal of the anti-scatter grid resulted in dose reductions of 20% (no anti-scatter grid) and 30% (15 cm air-gap), DNA double-strand break reductions of 30% (no anti-scatter grid) and 20% (15 cm air-gap) and a reduction of radiation-induced cancer mortality risk of up to 45%. CONCLUSION: Radiation doses received during paediatric cardiac catheterisation procedures resulted in a significant increase in DNA damage while maintaining acceptable image quality and diagnostic efficacy. It is feasible to remove the anti-scatter grid resulting in a reduction in DNA damage to the patient. The γH2AX assay may be used for assessment of dose optimisation strategies in children.

Computing eye gaze metrics for the automatic assessment of radiographer performance during X-ray image interpretation.

AIM: To investigate image interpretation performance by diagnostic radiography students, diagnostic radiographers and reporting radiographers by computing eye gaze metrics using eye tracking technology. METHODS: Three groups of participants were studied during their interpretation of 8 digital radiographic images including the axial and appendicular skeleton, and chest (prevalence of normal images was 12.5%). A total of 464 image interpretations were collected. Participants consisted of 21 radiography students, 19 qualified radiographers and 18 qualified reporting radiographers who were further qualified to report on the musculoskeletal (MSK) system. OUTCOME MEASURES: Eye tracking data was collected using the Tobii X60 eye tracker and subsequently eye gaze metrics were computed. Voice recordings, confidence levels and diagnoses provided a clear demonstration of the image interpretation and the cognitive processes undertaken by each participant. A questionnaire afforded the participants an opportunity to offer information on their experience in image interpretation and their opinion on the eye tracking technology. RESULTS: Reporting radiographers demonstrated a 15% greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took a mean of 2.4s longer to clinically decide on all features compared to students. Reporting radiographers also had a 15% greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took longer to clinically decide on an image diagnosis (p=0.02) than radiographers. Reporting radiographers had a greater mean fixation duration (p=0.01), mean fixation count (p=0.04) and mean visit count (p=0.04) within the areas of pathology compared to students. Eye tracking patterns, presented within heat maps, were a good reflection of group expertise and search strategies. Eye gaze metrics such as time to first fixate, fixation count, fixation duration and visit count within the areas of pathology were indicative of the radiographer's competency. CONCLUSION: The accuracy and confidence of each group could be reflected in the variability of their eye tracking heat maps. Participants' thoughts and decisions were quantified using the eye tracking data. Eye tracking metrics also reflected the different search strategies that each group of participants adopted during their image interpretations. This is the first study to use eye tracking technology to assess image interpretation skills between various groups of different levels of experience in radiography, especially on a combination of the MSK system, chest cavity and a variety of pathologies.

Assessment of DNA double-strand breaks induced by intravascular iodinated contrast media following in vitro irradiation and in vivo, during paediatric cardiac catheterization.

Paediatric cardiac catheterizations may result in the administration of substantial amounts of iodinated contrast media and ionizing radiation. The aim of this work was to investigate the effect of iodinated contrast media in combination with in vitro and in vivo X-ray radiation on lymphocyte DNA. Six concentrations of iodine (15, 17.5, 30, 35, 45, and 52.5 mg of iodine per mL blood) represented volumes of iodinated contrast media used in the clinical setting. Blood obtained from healthy volunteers was mixed with iodinated contrast media and exposed to radiation doses commonly used in paediatric cardiac catheterizations (0 mGy, 70 mGy, 140 mGy, 250 mGy and 450 mGy). Control samples contained no iodine. For in vivo experimentation, pre and post blood samples were collected from children undergoing cardiac catheterization, receiving iodine concentrations of up to 51 mg of iodine per mL blood and radiation doses of up to 400 mGy. Fluorescence microscopy was performed to assess γH2AX-foci induction, which corresponded to the number of DNA double-strand breaks. The presence of iodine in vitro resulted in significant increases of DNA double-strand breaks beyond that induced by radiation for ≥ 17.5 mg/mL iodine to blood. The in vivo effects of contrast media on children undergoing cardiac catheterization resulted in a 19% increase in DNA double-strand breaks in children receiving an average concentration of 19 mg/mL iodine to blood. A larger investigation is required to provide further information of the potential benefit of lowering the amount of iodinated contrast media received during X-ray radiation investigations.