Reflective analysis in radiography research: Methodological foundations and reporting guidance

The RAD-RA framework supports rigorous, transparent, and ethically accountable reflective research, enabling radiographers to examine professional judgement and practice-based challenges while supporting consistent peer review and qualitative scholarship within the discipline. As artificial intelligence increasingly shapes clinical workflows, decision support, and professional roles in radiography, reflective analysis provides a structured qualitative method for examining how practitioners interpret, negotiate, and respond to AI-supported practice. The RAD-RA framework offers a defensible approach for analysing these emerging interactions, supporting qualitative inquiry into human-AI relationships, professional accountability, and practice implications within radiography.