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How do scientists differentiate between healthy and unhealthy smartphone habits based on specific metrics? 


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Scientists differentiate between healthy and unhealthy smartphone habits by utilizing various metrics. One approach involves measuring biometric data like blood pressure, pulse, blood glucose, and brain waves (θ, α1, α2, α3, and β waves) to detect smartphone addiction. Additionally, the use of problematic smartphone use (PSU) scales, subjective estimates, or objective logs helps in assessing the impact of smartphone interactions on mental and physical health. Studies show that measuring smartphone addiction through PSU scales yields larger associations with mental health compared to subjective estimates or objective logs. Furthermore, analyzing physiological, psychological, and behavioral habits through smartphone sensors and external biodevices aids in evaluating adherence to healthy lifestyles. By combining these approaches, researchers can effectively distinguish between healthy and unhealthy smartphone habits based on specific metrics.

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Scientists differentiate healthy and unhealthy smartphone habits by analyzing app repertoire, habitual use, and fragmentation patterns using data-driven features from smartphone log data.
Scientists differentiate healthy and unhealthy smartphone habits by measuring smartphone use through problematic use scales, subjective estimates, or objective logs, with problematic use scales showing stronger associations with mental health.
Scientists differentiate healthy and unhealthy smartphone habits by analyzing physiological (activity, respiration), psychological (mood), and behavioral (social interaction) data collected via smartphone-based biodevices and external sensors.
Scientists differentiate healthy and unhealthy smartphone habits by analyzing biometric data like blood glucose, pulse, and brain waves, showing distinct patterns based on smartphone use and addiction levels.
Scientists differentiate healthy and unhealthy smartphone habits by analyzing biometric data like blood glucose, blood pressure, pulse, and brain waves, correlating them with smartphone addiction levels.

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