Cross-Cultural Adaptation and Psychometric Validation of the Interview Satisfaction Questionnaire (ISQ) to Assess Unmet Health Communication Needs of Iranian Breast Cancer Patients.

Autonomous and patient-centered health communication (PCHC) between a healthcare provider (HCP) and a client (HCC) is a critical fundament for successful healthcare outcomes. A standard and validated data collection tool for studying the satisfaction of Iranian breast cancer patients (BCPs) with various aspects of their health communication with HCPs does not exist. The current study assessed the application, feasibility, and cultural appropriateness of the Persian-translated version of the interview satisfaction questionnaire (ISQ) in the Iranian context. A standard translation/back-translation procedure was used to prepare a preliminary Persian version of the ISQ (ISQ-P) which was then evaluated for content and face validity by a panel of experts. The study data were collected from 200 breast cancer patients and used to estimate the internal consistency measure of Cronbach's alpha and intra-class correlation coefficient. Confirmatory factor analysis (CFA) was performed to verify the compatibility of the instrument's identified dimensions with the original ISQ's factor structure. The calculated content validity index (CVI = 0.89), content validity ratio (CVR = 0.49), and Cronbach's alpha coefficient (0.79) indicated the appropriateness of the ISQ-P for its intended purpose. The CFA's outputs (root mean square error of approximation (RMSEA) = 0.09, comparative fit index (CFI) = 0.954, Tucker-Lewis index (TLI) = 0.931, standardized root mean square residual (SRMR) = 0.04) affirmed the fitness of the study data to the original 4-factor conceptual model. The study findings supported the suitability of ISQ-P for assessing health communication episodes by Persian-speaking BCPs. However, due to cultural variation, cross-border diversity of health systems, and organizational circumstances, further validity and reliability appraisal of the ISQ-P in distinct sub-samples is recommended.