Enhancing validity through cognitive interviewing: A methodological example using the registered nursing forecasting nurse survey

Systemic anti-cancer therapy (SACT) nurses are facing increasing workload challenges against the backdrop of increased treatment complexity and patient caseload, coupled with a lack of policy guidance or research about the required composition of SACT workforce to ensure optimal care and outcomes. The Registered Nursing Forecasting (RN4CAST) study is an international research initiative designed to model what happens to the quality of patient care and care outcomes when components of the workforce change in acute and geriatric inpatient units. The insights from the RN4CAST have not been applied to the oncology setting. Therefore, the purpose of the study is to amend and test the RN4CAST nurse survey to ensure draft Registered Nursing Forecasting SACT day unit (RN4CAST-SACT-D) survey items are relevant, unambiguous/straightforward and the design/format is usable. This study adopted cognitive interviewing (CI), it combed two analytical approaches (reparative approach and descriptive approach) while Question Appraisal System (QAS) and cognitive theory were adopted. Totally, 12 interviews were conducted within two rounds, 48 items remained unchanged, 20 items underwent rephrasing for enhanced clarity, 20 new items were incorporated to address test content gaps, and adjustments were made to the provided answers to 5 questions. This study refined the RN4CAST survey for SACT day units through cognitive interviewing, addressing comprehension, retrieval, judgment, and response.issues. Adjustments in wording improved clarity and relevance, aligning the survey with nurses' experiences. • This paper presents a detailed exemplar of applying cognitive interviewing to design and improve survey content validity. • This study underscores the advantages of cognitive interviews in survey development. • It highlighted how itergrating analytical approaches improves data comprehension and strengthens face and content validity.