Sleep duration, timing and quality: How smartphone data predict labor productivity

Researchers at University of Tsukuba examined the association between sleep characteristics and workplace productivity using real-world sleep data from approximately 80,000 users (spanning more than 2 million nights) of sleep-tracking smartphone applications. Their findings suggest that individuals classified as “social jet lag” and “insomnia-prone” types experience significantly reduced productivity.

This article was originally published on MedicalXpress.com

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