0134 The Moderating Role of SSRI Use on the Link Between Undergraduates’ Depressive Symptoms and REM Sleep Duration

Abstract Introduction Introduction: Given that more than 50% of college students report deficient (i.e., short-duration, poor quality) sleep (ACHA, 2023), this population is at significant risk for mental health problems (Gaultney, 2010). Despite robust links between global assessments of sleep (e.g., quality, duration) and psychopathology, recent research has begun to explore more specific sleep indicators (e.g., sleep architecture) and their associations with psychopathology (e.g., depression). Research has focused on links between deficient sleep and negative outcomes via self-report and actigraphy, but these methodologies do not measure the basic properties of sleep characterized through electroencephalography (EEG). Furthermore, sleep EEG measurement has relied on clinic-based polysomnography, which diminishes ecological validity. To extend prior research (e.g., Boon et al., 2025) and address these methodological concerns, this study used ambulatory EEG to examine the dynamic links between undergraduates’ daily reports of depressive symptoms and duration of REM sleep, a form of sleep putatively involved in emotional regulation (e.g., Goldstein & Walker, 2014). Given the impact of SSRI use on REM sleep (Armitage, 2000), we further sought to test if SSRI use moderated this link. Methods Methods: The sample’s (N=156, 77.1% female) mean age was 20.3 years (SD=3.2), and 64.3% of participants were white, with 18.5% Black, 8.3% Hispanic/Latinx, 5.7% Asian/Pacific Islander, and 3.1% multi-racial/“other.” Approximately 20% (n=31) reported daily SSRI usage. Sleep architecture and total sleep time (TST) were assessed with the Muse S (Interaxon, Inc.) across 10 consecutive nights. Depressive symptoms (PHQ-2) were self-reported online each evening, and initial depressive symptom levels (PHQ-9) and SSRI usage were assessed at baseline. Results Results: Dynamic structural equation modeling (i.e., cross-lagged, multilevel modeling) was conducted in Mplus (v. 8.8, Muthen & Muthen, 2022) and demonstrated significant bidirectional relations between REM sleep duration and depressive symptoms for SSRI users. Although depressive symptoms predicted that night’s REM sleep duration across the entire sample, controlling for TST and baseline PHQ-9 levels, decreases in the previous evening’s REM sleep duration predicted increases in the following evening’s depressive symptoms only in SSRI users. Conclusion Conclusion: Our results highlight the transactional associations between mood and REM sleep and underscores the unique process this takes for SSRI users. Support (if any)