Psychometric validation of a community healthcare scorecard used for marginalized populations in Bangladesh

Background: Achieving equitable and quality healthcare for marginalized groups remains a critical challenge in Bangladesh. Community perceptions are crucial for assessing healthcare system performance, yet tools like Community Scorecards (CSCs) often lack rigorous psychometric validation, limiting their usefulness for evidence-based policy decisions. Objective: This study aims to psychometrically validate a 14-item CSC for measuring perceived healthcare service quality among marginalized populations in Bangladesh, using both Classical Test Theory (CTT) and the Generalized Partial Credit Model (GPCM) from Item Response Theory. Methods: Data were collected in 2023 from 311 community scoring units across nine marginalized population groups. Each scoring unit represents a Focus Group Discussion (FGD) in which participants reached a group consensus rating on each item using the five-point Likert scale (1 = Very Bad to 5 = Very Good) provided in the questionnaire. We conducted exploratory analysis, factorability checks including the Kaiser-Meyer-Olkin measure and Bartlett’s test of sphericity, exploratory factor analysis (EFA) with oblique (promax) rotation, reliability assessment using both Cronbach’s alpha and McDonald’s omega, and GPCM analysis to evaluate item and scale performance. Results: The Kaiser-Meyer-Olkin measure confirms excellent sampling adequacy (0.83), and Bartlett’s test of sphericity was significant (χ² = 1392.90, df = 91, p