Stopping too soon: Search termination and subsequent search misses in diagnostic radiography

Diagnostic radiography requires balancing image evaluation, dose optimisation, and workflow efficiency within time-constrained clinical environments. Image acceptance depends on detecting technical issues and determining when further inspection is unnecessary and when an image is sufficient for clinical purposes. Visual search theory suggests that observers rely on internal stopping rules to guide termination decisions, yet their role in radiographic image adequacy remains underexplored. This paper develops a model of radiographic search termination.

A conceptual model was developed through narrative synthesis of literature from cognitive psychology, medical image perception and radiology. Relevant studies were selected to identify key constructs, including quitting rules, subsequent search misses, inattentional blindness and confidence during incomplete search. These constructs were integrated to generate a radiography-specific framework explaining search termination.

A model is presented in which radiographic image evaluation is considered a multiple-target visual search task governed by an internal stopping threshold. This threshold reflects when the expected benefit of continued inspection falls below its perceived cost. It may be shaped by perceptual evidence, time pressure, workload, interruptions, target prevalence, patient presentation, observer confidence, experience and departmental norms. The model proposes three candidate termination patterns: global-impression termination, target-substitution termination and constraint-driven termination. It also identifies structured second-pass inspection, confidence calibration and feedback on missed secondary inadequacies as theoretically informed strategies requiring empirical investigation.

Framing image acceptance as a stopping-policy decision provides a cognitive explanation for variability in adequacy assessment and repeat imaging. Search termination reflects a dynamic balance between thoroughness and efficiency under uncertainty.

Integrating visual search theory into education and workflow design may support better calibration of stopping thresholds, improving image quality, reducing unnecessary repeats, and supporting clinically meaningful decision-making.