A structured blended learning approach for medical imaging technology interns: a prospective randomized comparative...

To address radiation safety constraints and equipment shortages in Computed Tomography (CT) training, this study introduces a Structured Blended Learning (SBL) framework integrating Small Private Online Courses (SPOCs), Flipped Classroom (FC), Virtual Simulation (VS), and remote supervision enabled by 5G communication infrastructure. This approach bridges the theory-practice gap by providing a structured progression from knowledge acquisition to simulated and clinical practice.

In a prospective randomized comparative study, 60 medical imaging interns undergoing CT clinical rotations were randomly assigned to either the SBL group (n = 30) or the traditional lecture-based learning (LBL) group (n = 30). Training effectiveness was evaluated using continuous theoretical examination scores (t-tests), ordinal Mini-Clinical Evaluation Exercise (Mini-CEX) practical assessments (Mann-Whitney U tests), and frequency distribution data from Likert-scale surveys (χ² tests) assessing student satisfaction and perceived learning outcomes.

The SBL group consistently outperformed the LBL group across all theoretical assessments, yielding significantly higher mean scores in the pre-class, post-class, and final examinations (t = 2.391-2.779; all P < 0.05; Cohen's d = 0.586-0.717). Mini-CEX assessments revealed superior performance by the SBL group across six domains, including patient positioning and handling, radiation protection and safety, equipment operation and image acquisition, image quality evaluation, organization and efficiency, and overall professional competence (Z = 4.855-5.110; all P < 0.001; r = 0.627-0.660). Furthermore, the SBL group reported significantly higher satisfaction with teaching methods, professional skills development, and overall evaluation (χ² =12.76-37.49; all P < 0.01; Cramér's V=0.231-0.395) and perceived greater effectiveness in professional theoretical knowledge, practical and operational skills, self-directed learning, and overall teaching effectiveness (χ² = 18.27-27.04; all P < 0.01; Cramér's V = 0.276-0.336).

The SBL approach provides an effective, safe, and engaging pedagogical framework for training medical imaging interns in complex CT workflows. By leveraging digital technologies to address physical access and radiation safety constraints, this approach demonstrates potential for broader application in medical imaging technology education, although further multicenter studies are needed to confirm its generalizability.