LAUSR

Metacognition, also-known-as subjective cognitive functioning, is an important predictor of cognitive decline and previous work has identified age, education, and mental health symptoms as important predictors. Sleep is essential for optimal neurocognitive functioning; as such, sleep may also play an important role in determining estimates of metacognition. However, it is currently unknown if sleep is associated with metacognition above-and-beyond known predictors. This study aimed to investigate whether sleep characteristics, including insomnia symptoms, global sleep health, and sleep regularity, were associated with metacognitive functioning above-and-beyond know predictors of age, education, and mood. Participants (N=3284) included adults (Mage=42.7 years,48.5% female) who completed an online study investigating sleep and health across the lifespan. Participants self-reported their age and education and completed various questionnaires including the 6-item PROMIS Cognitive Function questionnaire, the Patient Health Questionnaire-4 (PHQ-4), the Insomnia Severity Index (ISI), the RU-SATED sleep health questionnaire, and the Sleep Regularity Questionnaire (SRQ). Stepwise regression models were used to investigate whether ISI, RU-SATED, and SRQ scores predicted PROMIS Cognitive Function scores after accounting for age, education, and PHQ-4 scores. In Step 1 of the model, age and education significantly predicted metacognitive functioning (β=.146, t=8.44, p<.001; β=.086, t=4.97, p<.012). In Step 2, PHQ-4 scores and education were significant while age was no longer significant (β=-.589, t=-40.56, p<.001; β=.03, t=2.10, p=.036). In Step 3, age, education, and RU-SATED scores were not significant predictors while scores on the PHQ-4, ISI, and SRQ were significant predictors of metacognitive functioning (β=-.346, t=-21.93, p<.001; β=-.38, t=-20.20, p<.001; β=.052, t=3.20, p=.001). Step 3 accounted for a significant increase in variance explained (∆R2=.121, F=497.07, p<.001). Sleep characteristics, including insomnia symptoms and sleep regularity, are associated with metacognition above-and-beyond known predictors including age, education, and mood. Sleep characteristics may be an important part of estimates of metacognition. Moreover, because sleep is a modifiable risk factor with effective treatments, it may have potential as a treatment target for cognitive decline. Further research is needed to investigate whether the sleep-metacognitive functioning differs between common demographic groups and whether sleep disturbances predate declines in metacognitive functioning or vice versa. National Institute on Aging: Award K23AG049955 (PI: Dzierzewski).