Identifying Features of Scanxiety Among People With Cancer: A Nominal Group Technique Method.

Authors

Nian D F Kemme, Linda Kwakkenbos, Judith B Prins, Evelien J M Kuip, José A E Custers

Published in

Psycho-oncology. Volume 35. Issue 8. Pages e70560.

Abstract

Patients undergoing cancer-related scans often experience scan-associated anxiety, which can significantly impact their mental well-being. So far, this so-called scanxiety has not been clearly defined, even though it has gained more attention. This study investigated features of scanxiety in cancer patients.
Two nominal group technique (NGT) sessions were conducted with curatively treated and advanced cancer patients. In the first round, participants took turns sharing features of scanxiety, followed by a group discussion to clarify unclear or overlapping features. Finally, participants rated the extent to which they thought features applied to scanxiety. Additional to the NGT sessions, interviews were conducted with patients and healthcare professionals to provide further insights. Findings from the NGT sessions and interviews were collated and reviewed by the research team using a qualitative content analysis.
A total of 16 patients (9 men and 7 women) participated in the NGT sessions and an additional 14 people were interviewed (3 patients and 11 healthcare professionals). The NGT sessions and interviews initially generated 72 and 67 features, respectively. After merging and removing duplicates, the final list of features included 63 features. Following discussions in the multidisciplinary research team informed by predefined decision rules, 23 features were identified as unique to scanxiety. These features reflect emotional, cognitive, behavioural, physiological and physical reactions, social and interpersonal characteristics, and care- and process-related characteristics associated with scanxiety.
This study provides a first comprehensive characterisation of scanxiety by identifying features that are unique to anxiety associated with cancer-related scans and lays the groundwork for improved assessment and targeted support in cancer care.

PMID:
42531600
Bibliographic data and abstract were imported from PubMed on 31 Jul 2026.

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