Assessing the neuroanatomy knowledge and spatial ability of radiotherapy technologist undergraduates using an interactive volumetric simulation tool-the RadioLOG project.

OBJECTIVE: To assess the use of a volumetric image display simulation tool (VDST) for the evaluation of applied radiological neuroanatomy knowledge and spatial understanding of radiotherapy technologist (RTT) undergraduates. METHODS: Ninety-two third-year RTT students from three French RTT schools took an examination using software that allows visualization of multiple volumetric image series. To serve as a reference, 77 first- and second-year undergraduates, as well as ten senior neuroradiologists, took the same examination. The test included 13 very-short-answer questions (VSAQ) and 21 exercises in which examinees positioned markers onto preloaded brain MR images from a healthy volunteer. The response time was limited. Each correct answer scored 100 points, with a maximum possible test score of 3,400 (VSAQ = 1,300; marker exercise = 2,100). Answers were marked automatically for the marker positioning exercise and semi-automatically for the VSAQs against prerecorded expected answers. RESULTS: Overall, the mean test score was 1,787 (150-3,300) and the standard deviation was 781. Scores were highly significantly different between all evaluated groups (p < 0.001). The interoperator reproducibility was 0.90. All the evaluated groups could be discriminated by VSAQ, marker, and overall total scores independently (p ≤ 0.0001 to 0.001). The test was able to discriminate between the three schools either by VSAQ scores (p < 0.001 to 0.02) or by overall total score (p < 0.001 to 0.05). CONCLUSION: This software is a high-quality evaluation tool for the assessment of radiological neuroanatomy knowledge and spatial understanding in RTT undergraduates. KEY POINTS: • This VDST allows volumetric image analysis of MR studies. • A high reliability test could be created with this tool. • Test scores were strongly associated with the examinee expertise level.

Comment les MERM travaillant en radiothérapie perçoivent-ils leurs compétences dites "soft"?

OBJECTIVES: Research in the last decade shows growing interest for soft skills in healthcare, due to awareness of the influence of adverse events in healthcare. However, there was no specific study about non-technical skills used by therapists in the French radiation oncology departments. What are these behavioral competencies that medical radiation technologists (MRT) use in their work to deliver safe and efficient healthcare? METHOD: We built a self-assessment grid of 40 non classified soft skills for the active MRT to fulfill. This tool was sent to a total of 8 private and public radiation oncology department's head therapists. First, the 42 sampled MRTs had to choose how much they felt reflected in each of the listed soft skills. Second, they were asked to select 5 skills that they felt were the most important for a radiation therapist from the 40 soft skills in the initial grid. RESULTS: The 5 soft skills MRTs think they have include the following: conscientiousness, working autonomously, listening, diligence, and working in a multidisciplinary team. The three they think they have the least are: being creative, managing conflicts, and being bold. For the skills that they felt were the most important , MRT selected: being conscientious, listening, working in a multidisciplinary team, showing empathy, and anticipating. CONCLUSION: These results show that the skills known in the Big Five personality traits model as "conscientiousness" and "agreeableness" come first. Conscientiousness and listening skills are the biggest skills for the radiation therapists, because these are the skills they think they have the most, and also because they consider these skills as the most useful for an MRT. The radiation therapists surveyed did not think they were bold, nor creative, nor able to manage conflicts. The way the MRT perceives themselves is as a conscientious technician and a nice caregiver, compliant with what is expected from them professionally and in the society.

Building and Exploitation of Learning Curves to Train Radiographer Students in X-Ray CT Image Postprocessing.

INTRODUCTION: This study aims to construct learning curves related to the realization of standardized postprocessing by radiographer students and to discuss their exploitation and interest. MATERIALS AND METHODS: This study was carried out in 21 French students in their 3rd year of training. Two postprocessing protocols in CT (#1 traumatic shoulder; #2 petrous bone) were repeated 15 times by each student. Each achievement was timed to obtain overall learning curves. The realization accuracy was also assessed for each student at each repetition. RESULTS: The learning rates for the two protocols are 63% and 56%, respectively. The number of repetitions to reach the reference time for each protocol is 11 and 12, respectively. In both protocols, the standard deviations are significantly reduced and stabilized during repetitions. The mean accuracy progresses more quickly in protocol #1. DISCUSSION: The measured learning rates reflect a rapid learning process for each protocol. The analysis of the standard deviations shows that students have reached a homogeneous level. The average times and accuracies measured during the last repetitions show that the group has reached a high level of performance. Building learning curves helps students measure their progress and motivates them. CONCLUSION: Obtaining learning curves allows trainers/supervisors to qualify the learning difficulty of a task while motivating students/radiographers. The use of learning curves is inline with the competency-based training paradigm.