Design and evaluate a mobile app for enhancing patient positioning in radiographic procedures

Thesis Abstract

Effective patient positioning is critical in radiographic procedures to ensure diagnostic image quality, reduce repeat exposures, and minimize patient discomfort. However, inconsistencies in positioning techniques among radiographers often lead to suboptimal imaging outcomes, increased radiation doses, and delays in diagnostic workflows. This study aims to design, develop, and evaluate a mobile application that assists radiographers in enhancing patient positioning accuracy during radiographic procedures. The specific objectives include assessing the usability and acceptability of the app among radiography professionals, determining its impact on positioning accuracy, and evaluating its influence on radiographic image quality and procedure efficiency. Employing a mixed-methods research design, the study adopts a positivist paradigm to quantify improvements in positioning precision while also capturing user perceptions through qualitative feedback. The targeted population comprises registered radiographers working in secondary and tertiary healthcare facilities in a metropolitan region. A sample of 120 radiographers is selected through stratified random sampling to ensure representation across different healthcare settings. The research involves a two-phase process an initial development phase where a user-centered design approach is employed guided by theories such as the Technology Acceptance Model (TAM) and the Cognitive Load Theory to inform app features, followed by an evaluation phase employing a pretest-posttest controlled trial. Data collection instruments include a validated positioning accuracy checklist, a System Usability Scale (SUS) questionnaire, structured interview guides for qualitative insights, and audit data of radiographic images for quality assessment. Instrument validity is established through expert reviews, while reliability is confirmed via Cronbach’s alpha coefficients exceeding 0.8. Quantitative data are analyzed using paired t-tests, chi-square tests, and multiple regression analysis to examine differences pre- and post-intervention and identify predictors of improved outcomes. Qualitative data undergo thematic analysis to elucidate user experiences and perceived barriers or facilitators to app adoption. Expected findings suggest that the mobile app will significantly improve patient positioning accuracy, reflected in a reduction of positioning errors by at least 30%, and enhance image quality scores based on standardized assessment criteria. The usability evaluation is anticipated to yield high SUS scores (above 80), indicating strong acceptance among radiographers. Qualitative insights are projected to reveal increased confidence and efficiency in positioning practices, along with identification of potential challenges such as technology familiarity and workflow integration. This study contributes novel empirical evidence supporting mobile health technology applications in radiography, specifically targeting procedural accuracy and workflow optimization. It extends the theoretical understanding of technology acceptance in medical imaging contexts by integrating TAM with practical usability data. The research provides a replicable framework for developing similar decision-support tools and highlights key factors influencing successful implementation in clinical environments. The main conclusion posits that a well-designed mobile application can serve as an effective adjunct in radiographic positioning, thereby improving image quality, reducing radiation doses, and optimizing operational efficiency. Recommendations include broader deployment of the app across diverse healthcare settings, continuous usability improvement based on user feedback, and development of training modules to facilitate integration. Future research avenues suggested involve longitudinal studies on clinical outcomes and the adaptation of the app for other diagnostic imaging modalities to expand its applicability across radiology practices.