Consumer sleep trackers (e.g., Oura Ring, Whoop, Apple Watch) now claim medical-grade accuracy in measuring sleep stages, REM cycles, and recovery scores. Millions use this data to adjust bedtime routines, caffeine intake, or stress practices. However, a March 2025 meta-analysis in *Sleep Medicine Reviews* concluded that while total sleep time estimates are reasonably accurate, stage detection (especially REM vs. deep sleep) has error rates exceeding 30% compared to polysomnography. Despite this, apps increasingly prescribe personalized interventions—like delaying alarms or suggesting naps—based on these flawed metrics. This raises concerns: are users making suboptimal or even harmful decisions based on inaccurate biofeedback? The dilemma centers on whether the motivational benefits of self-monitoring outweigh the risks of acting on misleading data.

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