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health technology teams

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Cast framework measures social media use across multiple levels

The CAST-framework: Measure and model social media use as a multi-level phenomenon through real-world applications

Abstract: Designing social media experiences that support well-being requires understanding when, how, and for whom use matters. Screen-time totals omit content and context, and connecting these with behavior and experience requires coordinating measurements across timescales. We introduce the CAST framework to connect measurement choices with person-specific models of exposure, behavior, physiology, and experience. Its dimensions specify where observations occur, how they are obtained, what they measure, and at what temporal resolution. Responses to interventions, such as whether to proceed after an app-opening pause, enter as behavioral measurements. We propose four synchronized measurement modules linking mobile and wearable data with self-reports and intervention responses. A synthetic demonstration with 120 simulated participants over 28 days illustrates how daily aggregation can obscure opposing effects of different activities under specified generating assumptions. The framework guides selection of measures and outcomes for evaluating social media interfaces and interventions.

Mon 14 SeptHuman-Computer InteractionComputers and SocietySocial and Information Networks
The gist
Measuring how people use social media just by total screen time misses important details about what they see, do, and feel. The authors created the CAST framework to track social media use by combining data from phones, wearables, surveys, and user reactions in real time. This approach captures behaviors and experiences at different times and places, helping understand how social media affects well-being more precisely. They showed that simple daily summaries can hide opposite effects of different activities, highlighting why detailed, synchronized measurements matter.
Open 2609.15978v1