Development and User Satisfaction Assessment of the VJR RTtech Mobile Application in Patient Positioning for Radiological Technology Students
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Abstract
Objectives: Mastering radiographic positioning to produce high-quality diagnostic images requires comprehensive spatial awareness, anatomical knowledge, and technical precision. Radiological technology students encounter major challenges in learning various positioning protocols across different anatomical regions. This present study developed a mobile-based instructional application called VJR RTtech to facilitate radiographic positioning instruction organized by anatomical regions and evaluated user satisfaction.
Materials and Methods: VJR RTtech was developed using the Thunkable platform, which incorporated routine and specialized positioning techniques by anatomical regions. Each technique included positioning protocols, visual demonstrations, central ray angulation, source-to-image distance, and collimation procedures. A total of 52 third- and fourth-year radiological technology students from the Faculty of Medicine Vajira Hospital, Navamindradhiraj University, who completed their clinical practicum, tested the application for 15 days. Satisfaction across three dimensions (interface design, content quality, and system usability) was assessed using a validated 11-item questionnaire using a five-point Likert scale. Content validity was confirmed by three experts using the item-objective congruence index (IOC > 0.5). Descriptive statistics were used to analyze satisfaction levels. Internal consistency reliability was evaluated using Cronbach’s alpha, and inferential comparisons between student subgroups were conducted with independentsamples t-tests or Mann–Whitney U tests.
Results: The response rate was 85.2%. Out of 61 students who were invited, 52 completed the questionnaire. The overall satisfaction score was 4.54 ± 0.62 (90.8%), indicating very high satisfaction. All three dimensions reached very high satisfaction levels. The dimension scores were as follows: interface design 4.61 ± 0.58 (92.2%), content quality 4.68 ± 0.53 (93.6%), and system usability 4.24 ± 0.78 (84.8%).
Conclusion: VJR RTtech demonstrated exceptionally high user satisfaction across all dimensions assessed, especially in content quality. These results confirm its effectiveness as a supplemental instructional resource for radiographic positioning in radiological technology programs.
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References
Kjelle E, Chilanga C. The assessment of image quality and diagnostic value in X-ray images: a survey on radiographers’ reasons for rejecting images. Insights Imaging 2022;13:36. doi: 10.1186/s13244-022-01169-9.
Kim MS, Aro MR, Lage KJ, Ingalls KL, Sindhwani V, Markey MK. Exploring the usability of mobile apps supporting radiologists' training in diagnostic decision making. J Am Coll Radiol 2016;13(3):33543. doi: 10.1016/j.jacr.2015.07.021.
Atkinson S, Neep M, Starkey D. Reject rate analysis in digital radiography: an Australian emergency imaging department case study. J Med Radiat Sci 2020;67(1):72-9. doi: 10.1002/jmrs.343.
Tafti A, Byerly DW. X-ray radiographic patient positioning [internet]. 2022 [cited 2025 Jan 4]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK565865/
Bontrager KL, Lampignano JP. Textbook of radiographic positioning and related anatomy. 11th ed. Philadelphia: Elsevier; 2021.
American Registry of Radiologic Technologists. Radiography didactic and clinical competency requirements [internet]. 2022 [cited 2025 Jan 4]. Available from: https://www.arrt.org/pages/arrt-reference-documents/by-document-type/didacticand-clinical-competency-requirements
Rawle M, Pighills A, Mendez D, Dobeli K. Radiographic technique modification and evidence-based practice: a qualitative study. J Med Radiat Sci 2022;70(1):56-63. doi: 10.1002/jmrs.616.
Lundvall LL, Dahlström N, Dahlgren MA. Radiography students’ learning during clinical placements: developing professional knowing in practice. Vocations Learn 2021;14(3):1-19. doi: 10.1007/s12186-021-09269-1.
Shafuda S, Daniels E, Karera A. Bridging theory and practice: experiences of diagnostic radiography students during clinical training in resource-constrained settings. J Med Radiat Sci 2025;72:225-33. doi: 10.1002/jmrs.854.
Kumsa MJ, Lemu BN, Nguse TM, Omiyi DO, Akudjedu TN. Clinical placement challenges associated with radiography education in a low-resource setting: a qualitative exploration of the Ethiopian landscape. Radiography (Lond) 2022;28(3): 634-40. doi: 10.1016/j.radi.2022.04.014.
Sujar A, Kelly G, García M, Vidal FP. Interactive teaching environment for diagnostic radiography with real-time X-ray simulation and patient positioning. Int J Comput Assist Radiol Surg 2022;17(1):85-95. doi: 10.1007/s11548-021-02499-7.
Miller EM, Schmid KK, Abbey BM. The effect of non-immersive virtual reality radiographic positioning simulation on first-year radiography students’ image evaluation performance. Radiography (Lond) 2024;30(4):1180-6. doi: 10.1016/j.radi.2024.05.011.
Sapkaroski D, Baird M, Mundy M, Dimmock MR. Quantification of student radiographic patient positioning using an immersive virtual reality simulation. Simul Healthc 2019;14(4):258-63. doi: 10.1097/SIH.0000000000000380.
Hazell L, Lawrence H, Friedrich-Nel H. Simulation based learning to facilitate clinical readiness in diagnostic radiography: a meta-synthesis. Radiography (Lond) 2020;26(4):e238-45. doi: 10.1016/j.radi.2020.03.006.
Intharaksa R, Dathananurak P, Lakkathum J. Instruction media using the Thunkable program [vocational certificate project]. Information Technology Program, Attawit Commercial Technology College; 2019. [cited 2023 Feb 6]. Available from: https://online.fliphtml5.com/ezqiy/zyzu/#p=1
Yousef MO, Omer A, Abdullah R, Alharbi M, Aljehani B, Felemban Z, et al. From awareness to integration: mobile applications as tools in radiology education. J Radiat Res Appl Sci 2025;18(2):101353. doi: 10.1016/j.jrras.2025.101353.
Lewis TL, Aungst TD, Hutchinson C. Radiology education, mobile technology and medical apps. BMJ Simul Technol Enhanc Learn 2015;1(2):45-8. doi: 10.1136/bmjstel-2014-000009.
Lozano-Lozano M, Galiano-Castillo N, Fernández-Lao C, Postigo-Martin P, Álvarez-Salvago F, Arroyo-Morales M, et al. The Ecofisio mobile app for assessment and diagnosis using ultrasound imaging for undergraduate health science students: multicenter randomized controlled trial. J Med Internet Res 2020;22(3):e16258. doi: 10.2196/16258.
Gali RL, Smith E. RadTechPro app review. J Digit Imaging 2016;29(4):403-5. doi: 10.1007/s10278-016-9886-9.
Nittayasupaporn B, Tohsen F, Poungpum T, Apipunyasopon L. Development and assessment of CUFastTech mobile application for plain radiograph. Thai J Rad Tech 2021;45(1):1-7.
Pairodsantikul P, Phlangrit L, Wiwatthananon N, Kawvised S, Wongsa P, Pamarapa C. The development of application for general radiography in skull. Thai J Rad Tech 2023;48(1):60-70.
Phonphotthanamat W. A comparative study of verifying the content validity of a research instrument with the IOC, CVR and CVI. RSU Libr J 2022;28(1):169-92. doi: 10.14456/rilj.2022.8
Likert R. The method of constructing an attitude scale. In: Fishbein M, editor. Readings in attitude theory and measurement. New York: John Wiley & Sons; 1967. p. 90-5.
Kang H. Sample size determination and power analysis using the G*Power software. J Educ Eval Health Prof 2021;18:17. doi: 10.3352/jeehp.2021.18.17.
Tavakol M, Dennick R. Making sense of Cronbach’s alpha. Int J Med Educ 2011;2:53-5. doi: 10.5116/ijme.4dfb.8dfd.
Alkharusi H. A descriptive analysis and interpretation of data from Likert scales in educational and psychological research. Indian Journal of Psychology and Education 2022;12(2):13-6.
