The Uncertainty in Illness Questionnaire (UIQ): development and validation of a clinically oriented measure for patients and caregivers

Objective The present research aimed to develop and validate the Uncertainty in Illness Questionnaire (UIQ), a self-report tool designed to assess uncertainty in illness (UI) among Italian-speaking patients and caregivers. Across three studies, the psychometric properties of the UIQ were rigorously evaluated in large, diverse samples. Methods & results In Study 1, the novel exploratory graph analysis (EGA) revealed a robust four-factor structure - uncertainty about symptoms, treatments, future change, and relationships (optimal stability > .90, negligible cross-loadings). Such structure was then confirmed in Study 2, in an independent sample, through confirmatory factor analysis (CFA) with a hierarchical model with four first-order factors showing good fit (robust RMSEA = 0.065[90% CI: 0.056-0.075]; robust CFI=0.958; robust TLI=0.949; SRMR=0.043). UIQ demonstrated strong reliability, internal consistency, and both convergent and divergent validity. Measurement invariance analyses reached latent means invariance, revealing that UIQ is interpreted equivalently by patients and caregivers, supporting meaningful group comparisons. Following recent methodological guidelines, Study 3 demonstrated the discriminant validity of the UIQ with the Intolerance of Uncertainty Scale-Revised, measuring dispositional intolerance of uncertainty. Conclusions The tool's brevity and clarity make it suitable for both clinical and research settings, especially where respondent burden must be minimized. The UIQ addresses an important gap in the Italian context, providing a validated, context-specific measure of UI. Convenience sampling, predominantly female participants (> 85%), cross-sectional design, and lack of clinical subgroup analyses limit generalizability. The tool requires cross-cultural validation beyond Italian-speaking populations. UIQ offers clinicians and researchers a reliable means to assess and address UI, ultimately supporting tailored interventions to improve psychological health in medical contexts.