Abstract

Sleep misperception – the discrepancy between objective and subjective measures of sleep – has been shown to be prevalent among patients with insomnia and may be a promising target for sleep intervention. This study examined sleep misperception in a diverse outpatient medical sample using consumer-grade wearable actigraphs (i.e., Fitbit Charge HR™). Forty-four self-identified problem sleepers aged 20 to 79 participated in the study. Participants completed sleep diaries for one week while also tracking their sleep using the Fitbit Charge HR™. After receiving a personalized sleep report based on these data, participants repeated another week of sleep assessment. Sleep misperception was observed for both total sleep time and sleep onset latency during the first week, such that participants underestimated their total amount of sleep per night and overestimated the amount of time it took them to fall asleep. Pre-post changes in self-reported sleep, mood, and health were examined as a secondary aim in this study. Objectively measured sleep remained relatively unchanged from baseline to follow-up. Despite this lack of change in actual sleep, participants perceived themselves to be sleeping more hours per night, falling asleep more quickly, and sleeping better overall at one-week follow-up. Statistically significant improvements in depression, anxiety, mental health functioning, and insomnia symptom severity were also observed at follow-up. Overall, findings showed that sleep misperception is prevalent among problem sleepers and that sleep discrepancy can be reduced through the use of corrective sleep feedback.

Notes

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Graduation Date

2018

Semester

Spring

Advisor

Cassisi, Jeffrey

Degree

Doctor of Philosophy (Ph.D.)

College

College of Sciences

Department

Psychology

Degree Program

Psychology; Clinical Psychology

Format

application/pdf

Identifier

CFE0006976

URL

http://purl.fcla.edu/fcla/etd/CFE0006976

Language

English

Release Date

May 2018

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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