Comparing self reported and physiological sleep quality from consumer devices to depression and neurocognitive performance.

This study examines the relationship between self-reported and physiologically measured sleep quality and their impact on neurocognitive performance in individuals with depression. Using data from 249 participants with medium to severe depression monitored over 13 weeks, sleep quality was assessed via retrospective self-report and physiological measures from consumer smartphones and smartwatches. Correlations between self-reported and physiological sleep measures were generally weak. Machine learning models revealed that self-reported sleep quality could detect all depression symptoms measured using the Patient Health Questionnaire-14, whereas physiological sleep measures detected "sleeping too much" and low libido. Notably, only self-reported sleep disturbances correlated significantly with neurocognitive performance, specifically with processing speed. Physiological sleep was able to detect changes in self-reported sleep, medication use, and sleep latency. These findings emphasize that self-reported and physiological sleep quality are not measuring the same construct, and both are important to monitor when studying sleep quality in relation to depression.
Competing Interests: Competing interests: The authors declare no competing interests.
(© 2025. The Author(s).)