The internet information overload scale: development and initial validation in Chinese adults

Abstract This study developed and initially validated the Internet Information Overload Scale (IIOS), assessing emotional, cognitive-evaluative, information-sharing, and avoidance responses to perceived internet information overload. Semistructured interviews with 18 participants informed item generation. Item analysis and exploratory factor analysis were conducted in 511 Chinese adults. Confirmatory factor analysis, reliability and validity testing, measurement invariance across sex, and nomological validity analyses were conducted in an independent sample of 935 adults. The model was estimated with maximum likelihood (ML) and the weighted least squares mean- and variance-adjusted estimator (WLSMV) for ordered indicators. The 13-item IIOS comprised Emotional Overload, Critical Evaluation, Information Sharing, and Avoidance Response. The ML model yielded χ²(59) = 302.79, CFI=0.973, TLI=0.965, RMSEA=0.067, and SRMR=0.036. WLSMV produced broadly comparable loadings, factor correlations, CFI, TLI, and SRMR, but a higher RMSEA (0.103). Subscale Cronbach’s α values ranged from 0.83 to 0.93. Convergent and discriminant validity and configural, metric, and scalar invariance across sex were supported. IIOS scores correlated positively with fear of COVID-19, anxiety symptoms, and depressive symptoms; associations with general conspiracy belief were weaker. The IIOS showed initial support as a multidimensional measure in Chinese adults, while RMSEA differed across estimators.