Predictive Validity of the HESI Radiography Exit Exam and Best Practices for ARRT Certification Exam Success.

PURPOSE: To determine the predictive validity of Health Education Systems Incorporated (HESI) Exit Exam scores for student first-time success on the American Registry of Radiologic Technologists (ARRT) certification exam and to analyze whether schools' policies on the HESI Exit Exam are associated with end-of-program student success. METHODS: Twenty-five radiography program directors provided retrospective data on ARRT certification exam student outcomes, and 24 program directors completed the HESI Exit Exam program policy survey. Data analysis was performed to examine the correlation between students' HESI Exit Exam scores and their first-time ARRT certification exam outcomes and to investigate the relationship between program policies and performance on both exams. RESULTS: First-time ARRT certification exam outcomes were obtained for 1265 program graduates who took the HESI Exit Exam from 2018 through 2021. Students achieving acceptable (700-749) and recommended (750-799) HESI Exit Exam scores exhibited significantly higher certification exam pass rates of 79.4% and 86.4%, respectively. ARRT certification exam pass rates were higher for those scoring 800 or above (94.5-100%). Implementation of a minimum HESI Exit Exam score requirements and a required exam preparation were significantly associated with more favorable ARRT certification exam outcomes. DISCUSSION: There was a significant positive relationship between higher HESI Exit Exam scores and more successful outcomes on the ARRT certification exam. Two program policies regarding use of the HESI Exit Exam (minimum exit exam score required, required test prep) emerged as best-practice approaches for ARRT certification exam success. CONCLUSION: The HESI Exit Exam was predictive of success on the ARRT certification exam. The results presented in this study can be used to improve radiography education. Future research on how additional educational resources affect HESI Exit Exam and ARRT certification exam success is warranted.

Student Observations Reveal Gaps Between Chest Imaging Theory and Practice.

PURPOSE: To assess whether first-year radiography students observed differences between what they were taught in didactic and laboratory courses and how technologists perform chest imaging procedures during clinical experiences. METHODS: This study used a mixed-methods approach with a cross-sectional survey, consisting of 11 quantitative and 11 qualitative items, during the fall 2020 semester. The survey asked participants to evaluate survey statements based on their observations of radiographers' behaviors during chest imaging procedures in relation to the 11 American Registry of Radiologic Technologist clinical competency areas. Participants rated their evaluations based on the degree to which they agreed or disagreed with statements regarding radiographers' behaviors using a 5-point Likert scale, ranging from strongly disagree (1) to strongly agree (5). For each statement, a follow-up, open-ended question asked participants to provide reasons why they thought technologists did or did not exhibit certain behaviors. Data were analyzed quantitatively with differential statistics and qualitatively by thematically categorizing open-ended responses. RESULTS: A total of 19 first-year radiography students (N = 19) completed the survey. Most participants somewhat agreed or strongly agreed with 8 out of the 11 competency statements based on their observations of technologists when performing chest imaging procedures: room preparation (73.7%), patient identity verification (89.5%), examination order verification (79%), patient assessment (79%), equipment operation (52.6%), patient management (100%), technique selection (73.6%), and image evaluation (94.7%). Most participants somewhat disagreed, strongly disagreed, or were neutral with 3 out of the 11 categories: patient positioning, radiation safety, and image processing. Qualitatively, participants responded that technologists only provided lead shielding for pediatric patients, were not instructing patients to take 2 inspirations before making an exposure, and were cropping their images electronically before submitting them for diagnoses. DISCUSSION: Participants reported inconsistencies between what they were taught and what they saw technologists doing during chest imaging procedures related to patient positioning, radiation safety, and imaging processing. Participants' responses stated that these inconsistencies might be because of an increase in technologist responsibilities, patient volumes, and fear of not including relative anatomy on their images. CONCLUSION: Participants reported the most disagreement with radiation safety during chest imaging procedures. Although lead shielding for abdominal and pelvic procedures is no longer recommended, shielding patients during chest imaging procedures is still recommended. Radiography programs can educate students that inconsistency between task order does not mean there is a gap between theory and practice.

[New Method of Paired Comparison for Improved Observer Shortage Using Deep Learning Models].

PURPOSE: The aim of this study was to validate the potential of substituting an observer in a paired comparison with a deep-learning observer. METHODS: Phantom images were obtained using computed tomography. Imaging conditions included a standard setting of 120 kVp and 200 mA, with tube current variations ranging from 160 mA, 120 mA, 80 mA, 40 mA, and 20 mA, resulting in six different imaging conditions. Fourteen radiologic technologists with >10 years of experience conducted pairwise comparisons using Ura's method. After training, VGG16 and VGG19 models were combined to form deep learning models, which were then evaluated for accuracy, recall, precision, specificity, and F1value. The validation results were used as the standard, and the results of the average degree of preference and significance tests between images were compared to the standard if the results of deep learning were incorporated. RESULTS: The average accuracy of the deep learning model was 82%, with a maximum difference of 0.13 from the standard regarding the average degree of preference, a minimum difference of 0, and an average difference of 0.05. Significant differences were observed in the test results when replacing human observers with AI counterparts for image pairs with tube currents of 160 mA vs. 120 mA and 200 mA vs. 160 mA. CONCLUSION: In paired comparisons with a limited phantom (7-point noise evaluation), the potential use of deep learning was suggested as one of the observers.

Incorporating Reflective Learning Practices In Medical Imaging Curriculum.

PURPOSE: To provide an overview of the reflective learning cycle, as well as common reflective learning models, as a means of informing future implementation of reflective learning assignments in medical imaging curriculum. METHODS: Journal articles were searched for in Google Scholar, ScienceDirect, and ResearchGate, as well as the university's library databases using the keywords reflective learning, Kolb's model of learning, reflective learning practices in health care, and reflective learning in radiography. Out of 19 articles found, 12 articles were selected based on inclusion and exclusion criteria. RESULTS: The literature search yielded results in health care education, nursing, medicine, medical imaging and radiography, pharmacy, physical therapy, and occupational therapy. DISCUSSION: Studies have shown that reflection is an integral aspect of learning and has substantial implications for learners' clinical practice. Reflection is a cognitive process that facilitates learning, assists in the understanding and application of knowledge to clinical situations, and develops new clinical knowledge in student radiographers. When reflective activities, such as journaling, portfolios, and problem-based learning, are scaffolded throughout the curriculum, students develop critical reflection skills that positively affect their clinical practice. CONCLUSION: Reflective learning practices can positively affect student learning, clinical decision-making skills, and patient outcomes. When reflective learning activities are incorporated throughout the curriculum, students are more effectively able to bridge the gap between theoretical knowledge and clinical practice. In addition, the reflective learning process allows learners to examine their clinical experiences while providing context for application and future clinical practice and continued learning.

Scan With Me: A Train-the-Trainer Program to Upskill MRI Personnel in Low- and Middle-Income Countries.

PURPOSE: Access to MRI in low- and middle-income countries (LMICs) remains among the poorest in the world. The lack of skilled MRI personnel exacerbates access gaps, reinforcing long-standing health disparities. The Scan With Me (SWiM) program aims to sustainably create a network of highly skilled MRI technologists in LMICs who will facilitate the transfer of MRI knowledge and skills to their peers and contribute to the implementation of highly valuable imaging protocols for effective clinical and research use. METHODS: The program introduces a case-based curriculum designed using a novel train-the-trainer approach, integrated with peer-collaborative learning to upskill practicing MRI technologists in LMICs. The 6-week curriculum uses the teach-try-use approach, which combines self-paced didactic lectures covering the basics of MR image acquisition (teach) with hands-on expert-guided scanning experience (try) and the implementation of protocols tailored to provide the best possible images on their infrastructures (use). Each program includes research translation skills training using an established advanced MRI technique relevant to LMICs. A pilot program focused on cardiac MRI (CMR) was conducted to assess the program's curriculum, delivery, and evaluation methods. RESULTS: Forty-three MRI technologists from 16 LMICs participated in the pilot CMR program and, over the course of the training, implemented optimized CMR protocols that reduced acquisition times while improving image quality. The training resources and scanner-specific standardized protocols are published openly for public use in an online repository. In general, at the end of the program, learners reported considerable improvements in CMR knowledge and skills. All respondents to the program evaluation survey agreed to recommend the program to their colleagues, while 87% indicated interest in returning to help train others. CONCLUSIONS: The SWiM program is the first master class in MRI acquisition for practicing imaging technologists in LMICs. The program holds the potential to help reduce disparities in MRI expertise and access. The support of the MRI community, imaging societies, and funding agencies will increase its reach and further its impact in democratizing MRI.

Radiography students' perceptions of artificial intelligence in medical imaging.

INTRODUCTION: Education relating to Artificial Intelligence (AI) is becoming critical to developing contemporary radiographers. This study sought to investigate the perceptions of a sample of Australian radiography students regarding AI within the context of medical imaging. METHODS: Radiography students completed a cross-sectional online questionnaire which obtained quantitative and qualitative data relating to their perceptions and attitudes of AI within the radiographic context. Descriptive and inferential statistics were utilised, and thematic analysis was undertaken for open-text responses. RESULTS: Responses were gathered from twenty-five participants, in their second, third and fourth year of study. Most participants demonstrated a positive attitude towards AI. Most students view AI to be an assistive tool, though the cohort was less convinced AI would increase future employment in the industry. Females were more likely to disagree that AI will increase work opportunities for the radiographer (p = 0.021), as well as those in their final year of study (p = 0.011). Perceived benefits of AI related to improved work efficiency and image quality. Negative perceptions of AI involved reduced job security, and potential impact on patient care and safety. DISCUSSION: Students presented a multitude of positive and negative perceptions towards the role that AI may play in their future careers. Education pertaining to AI is central to transforming future clinical practice, and it is encouraging that undergraduate students are intrigued and willing to learn about AI in the radiographic context. CONCLUSION: This study offers insight into the current perspectives of Australian radiography students on AI within medical imaging, to assist in implementation of future AI-related education in the undergraduate setting.

[Clinical Validation of Chest X-ray Educational Content for Radiography Students Using Gaze Information].

PURPOSE: Radiography training for students in colleges of radiology should be based on real clinical situations. The purpose of this study was to verify the clinical validity of our originally developed scenarios for chest X-ray training and the instructional contents using gaze information of experienced radiology technologists (RTs). METHODS: We divided 8 RTs with different experiences into an evaluator group (3 RTs) and a subject group (5 RTs). The evaluator group created a validation model consisting of 31 items, a chest X-ray scenario, instructional contents, and gaze attention objects during the scenario. The subject group simulated chest X-ray wearing an eye tracker. The evaluator group evaluated fit rates of the validation model to subjects' procedures based on gaze information to verify the clinical validity of the validation model. RESULTS: The subject group procedures did not deviate from the scenario. We obtained a fit rate of 91.6±6.70%. CONCLUSION: Our validation model showed more than 90% fitting with the chest X-ray techniques of five RTs with different backgrounds. This result suggested that the scenario and instructional contents in this study had clinical validity.

Virtual Technology in Radiologic Technology Classrooms: Educational Effect of the COVID-19 Pandemic.

PURPOSE: To investigate the educational effect of the COVID-19 pandemic on virtual technology use in the radiologic technology classroom by comparing virtual technology use and perceived barriers for use from before the COVID-19 pandemic through the spring 2021 semester. METHODS: An explanatory mixed-method, cross-sectional survey design was used to evaluate radiologic technology educators' integration of virtual technology and continuance intention to use (CITU) virtual technology in the radiologic technology classroom. A pseudoqualitative component also was used to add meaning to the quantitative data. RESULTS: A total of 255 educators completed the survey. Educators with associate degrees scored significantly lower in CITU compared with participants with master's degrees (P = .04) and doctoral or professional degrees (P = .01). Virtual technology use significantly increased from before COVID-19 to spring 2021 (P < .001). Educators' perceptions of barriers to technology integration significantly decreased from before COVID-19 to spring 2021 (P < .001). In this report, radiologic technology educators indicated intentions for increased virtual technology use in the future compared with their use during the spring 2021 semester (P = .001). DISCUSSION: Virtual technology use was low before COVID-19, and although it increased during the spring 2021 semester, it remained relatively low. Future intentions for virtual technology use indicate an increase from spring 2021, suggesting a change in future delivery of radiologic science education. Instructors' levels of education had a significant effect on CITU scores. Cost and funding was consistently the highest reported barrier to virtual technology use, whereas student resistance to technology was consistently the lowest reported barrier. Narratives of participants' challenges, current and future use, and rewards related to virtual technology also added pseudoqualitative meaning to the quantitative findings. CONCLUSION: The educators in this study demonstrated low virtual technology use before the COVID-19 pandemic, increased virtual technology use because of the pandemic, and significantly positive CITU scores. Radiologic science educators' responses regarding their challenges, current and future use, and rewards might be helpful in facilitating more effective technology integration.

Evaluating Current Tuition Trends in Radiography Programs.

PURPOSE: To identify current tuition trends among types of radiography programs; compare tuition rates; and provide prospective students, educators, and professionals with a comprehensive cost analysis for postsecondary education planning, recruitment, and retention. METHODS: Radiography program tuition data were collected from the Joint Review Committee on Education in Radiologic Technology (JRCERT) website. National tuition rates were obtained from the National Center for Education Statistics website. Tuition fees for JRCERT-accredited programs were sorted by degree level and state. The data were evaluated for each pathway to determine tuition range, median cost, cost effectiveness, and comparison with national rates. RESULTS: The range of annual tuition costs for JRCERT-accredited radiography programs was $750 to $51 769. Results were not normally distributed, and the median annual tuition rate for all programs was $5005. Broken down by program type, the median tuition rate was $4861 for a certificate, $4556 for an applied associate of science degree, $5959 for an associate of science degree, and $10 075 for a bachelor of science degree. The overall mean for radiography tuition was $7875, compared with the national average of $13 016 for all undergraduate institutions nationally. DISCUSSION: Radiography program tuition rates vary widely. Prospective students' use of research and financial strategies to determine the best value is recommended. The applied associate of science degree in radiography was found to be the most cost-effective type of program. Bachelor's degrees in radiography were the most expensive option, but according to the literature, a bachelor's degree could yield additional benefits such as increased employment, advanced career opportunities, and higher return on investment. CONCLUSION: An education in radiography is a competitive option compared with the national average for undergraduate programs. To achieve a favorable outcome, prospective students should evaluate educational costs, educational value, and informed decision-making strategies when investing in their postsecondary education.