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Measuring "Scanxiety": A Systematic Review and Symptom Coverage Analysis of Commonly Used Measures
K Bullock1, G H Rawlings2, G Lee1
1University of Staffordshire, Staffordshire, UK.
Introduction:
"Scanxiety" refers to the anxiety and/or distress that an individual experiences before, during, or after a medical scan (e.g., MRI, ultrasound, CT, etc). Symptoms characterising scanxiety remain poorly defined and are inconsistently measured. This systematic review aimed to synthesise symptoms reported in relation to scanxiety among adult populations, and to evaluate patient reported outcome measures commonly used to measure scanxiety focusing on how well these measures capture its symptoms.
Methods:
A best fit framework synthesis approach was applied to explore scanxiety symptoms using the five areas model (emotional, cognitive, behavioural, physiological and environmental domains). Symptoms identified were then mapped against nine measures commonly used to assess scanxiety. The quality of studies included was appraised using the Mixed Methods Appraisal Tool.
Results:
Across 23 studies, 159 symptoms were identified in studies exploring experiences of scanxiety. Symptoms were synthesised into 18 conceptual clusters spanning all domains of the five areas model. Existing measures predominantly assessed emotional and physical symptoms, while behavioural and cognitive symptoms were inconsistently represented. Environmental symptoms were not captured by any measure reviewed.
Conclusion:
Scanxiety is a multi-dimensional and contextually influenced experience, the symptoms of which are not adequately captured by the assessment tools included in this review. The findings have implications for clinicians working with this group, particularly how best to assess symptoms and identify scanxiety in advance to inform appropriate intervention.
Implications For Practice:
Assessment of scan-related distress extends beyond emotional and physical symptoms to include behavioural and environmental factors. Developing scanxiety-specific tools grounded in lived experience may improve identification and support across a wider range of imaging contexts.
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