Navigating Acceptability: A Think-Aloud Study of Subjective and Contextual Factors in Radiographic Image Rejection
Robin Decoster1,2, Rachel Toomey1, Michaela Davis1
1School of Medicine, University College Dublin, Dublin 4, Ireland.
Introduction:
Radiographic image quality is evaluated based on technical and anatomical criteria; however, this study investigates how radiographers incorporate contextual factors into their decision-making processes when rejecting images. Using the think-aloud method, it explores radiographers' reasoning across three established phases of image production: planning, execution and evaluation.
Methods:
Nine radiographers from Belgium and Ireland participated in cognitive interviews, simulating four radiographic scenarios involving patient variation and technical challenges. Interviews were recorded, transcribed and analysed thematically.
Results:
Thematic coding revealed five core themes and thirteen subcodes, focusing on aspects such as patient characteristics, workflow, technical parameters and interprofessional dynamics. The findings highlight that image rejection is influenced not only by contrast, resolution or positioning errors but also by patient condition, radiographer experience and departmental culture. Belgian radiographers referenced radiologist preferences more frequently, while Irish participants demonstrated a stronger emphasis on protocol and patient-specific adaptation. Cultural differences, encapsulated knowledge, and terminology ambiguities were noted, suggesting broad variability in image acceptability criteria.
Conclusion:
This study demonstrates that radiographic image quality cannot be fully assessed based on the radiograph alone. Instead, clinical reasoning involves a complex interplay between objective image features and subjective contextual judgements. These findings raise important questions about the role of standardisation versus flexibility in image assessment and have implications for reject analysis, education, and integration of Artificial Intelligence in diagnostic imaging.
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