Development and Validation of the Digital Mentalizing Questionnaire: A Multidimensional Self-Report for Online Social Networks

Digital interactions are increasingly central to human social life, yet existing measures of mentalizing—defined as the capacity to interpret one’s own and others’ mental states—are primarily designed for face-to-face contexts and fail to capture the unique cognitive-affective demands of online social networks. This research introduces the Digital Mentalizing Questionnaire (DMQ), the first multidimensional, theory-driven instrument specifically developed to assess mentalizing processes in digital environments. Across three studies ( N 1 = 278, N 2 = 375, N 3 = 341; participants in Studies 1, 2, and 3 were predominantly female adults with mean ages of 32.95 [ SD = 12.10] and 30.89 [ SD = 10.68] years, respectively, and varied educational backgrounds), the DMQ demonstrated a robust five-factor structure encompassing Digital Self-Mentalizing, Digital Other-Mentalizing, Digital Emotion Regulation, Digital Anticipatory Mentalizing, and Digital Identity Integration. Exploratory factor analysis (Study 1) and confirmatory factor analysis confirmed structural validity, while internal consistency (α = .67–.86), composite reliability, and 1-month test–retest reliability ( r = .58–.79) indicated strong psychometric stability. Measurement invariance across gender further confirmed the scale’s applicability for comparative research (Study 2). Convergent validity was supported through theoretically coherent correlations with established mentalizing measures (Reflective Functioning Questionnaire, Mentalization Questionnaire, Mentalization Emotion Questionnaire, Bergen Social Media Addiction Scale) and negative associations with transdiagnostic psychopathology indicators (Study 3). The DMQ offers a validated, ecologically relevant framework for assessing digital mentalizing, bridging classical theory with contemporary online social cognition. Its application holds promise for advancing cyberpsychology research, informing digital well-being interventions, and understanding the socio-cognitive mechanisms underlying online behavior.