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Measures technology overload in a German sample, suggesting factors influencing overload experiences.
In today’s digital environment, individuals frequently engage with multiple information sources and communication streams across social media and web platforms, often leading to a feeling of overload. Web browsing, a central activity that integrates tasks such as email, social media, and content consumption, has become a prominent setting for experiencing such information overload. Despite its relevance, research investigating overload has primarily focused on isolated platforms, and little is known about how overload manifests and evolves over time. While the Technology Overload Scale is widely used to measure aspects of overload—namely, information, communication, and system feature overload—its psychometric properties and longitudinal invariance remain underexplored. Addressing these gaps, this study investigates the scale’s reliability and longitudinal invariance using four waves of survey data from a German sample over a three month period. Our findings reveal that while the information overload subscale demonstrates good psychometric quality and stability over time, the full three-factor model lacks empirical support. We also identify patterns of intraindividual changes in overload experiences over time, and show that gender, income, profession, negative affect, and coping strategies have an effect in information overload. This work advances the conceptual and methodological foundations for studying information overload in everyday technology use by validating a reliable measurement tool for longitudinal research.
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Lassila et al. (2026) studied this question.
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