Development and Validation of the Content Absorption Overload Scale Among Filipino Young Adult Social Media Users

The widespread use of algorithm-driven social media has intensified concerns regarding the cognitive consequences of prolonged digital engagement. Although existing measures assess either cognitive absorption or information overload, they inadequately capture the simultaneous experience of sustained engagement and cognitive burden characteristic of contemporary social media use. This study aimed to conceptualize the construct of Content Absorption Overload (CAO) and develop and validate the Content Absorption Overload Scale (CAOS) among Filipino young adult social media users. A quantitative psychometric test development design was employed following established procedures for test conceptualization, item construction, pilot testing, item analysis, and scale refinement. Purposive sampling was used to recruit 426 college students aged 18–25 years who actively used social media. The instrument underwent three rounds of pilot testing, supported by expert content validation. Internal consistency was assessed using Cronbach's alpha, construct validity through Confirmatory Factor Analysis (CFA), and convergent validity using Composite Reliability (CR) and Average Variance Extracted (AVE). The final 15-item instrument demonstrated acceptable internal consistency across the three dimensions of Processing Depth (α = .72), Load Capacity (α = .79), and Absorption (α = .82). The three-factor model exhibited a marginally acceptable fit (CFI = .897, SRMR = .076, RMSEA = .074), while convergent validity was supported by satisfactory CR values (.81–.89) despite AVE values slightly below the conventional criterion, consistent with recommendations for newly developed psychometric instruments. The findings provide empirical support for the multidimensional structure of CAO and establish CAOS as a psychometrically sound instrument for assessing cognitive overload arising from sustained social media engagement. The scale offers practical applications for psychological research, digital well-being assessment, and the development of evidence-based interventions promoting healthier technology use.