Research on screen usage frequently relies on broad measures of “screen time,” which fail to differentiate between various types of activities and their effects. To clarify how digital behavior is defined, we conducted a rapid review and methodological mapping of 36 screen use measurement tools. Three independent coders applied a piloted framework to classify measurement constructs, data collection modality (objective logs, self-, or proxy-report), temporal specificity, framing valence, opportunity cost, dyadic/social context, developmental focus, and evidence of reliability and validity. Interrater agreement was high (Fleiss’ Kappa; Gwet’s AC1). Most instruments used negatively framed item content, emphasizing impairment, dysregulation, or loss of control, focused on adolescents and young adults, and lacked precision in temporal anchoring. Very few assessed opportunity costs, dyadic use, or included validation against device-logged data. No measure emphasized positive or beneficial aspects of screen engagement. These gaps suggest a need for more conceptually balanced tools that integrate objective tracking with context-sensitive self-report items across the lifespan. We propose a blueprint for future development: improve temporal anchoring (e.g., within-day, weekday vs. weekend), broaden age inclusion, assess social and functional context, and report both reliability and validation against behavioral data. Strengthening measurement will advance efforts to identify when, how, and for whom digital behavior supports or undermines well-being.
Shaleha et al. (2026) studied this question.