(PS10-91) The Use of Wearable Devices in Predicting Affective Switching via Sleep Behavior in Individuals with Premenstrual Dysphoric Disorder

Abstract Text:

Background:
Affective symptoms are contingent on the menstrual cycle in premenstrual dysphoric disorder (PMDD). However, symptom onset can be unpredictable due to irregular cycles and inconsistent symptom severity, making it difficult to identify high-risk periods. This study used continuous remote monitoring to examine the relationship between sleep disturbances and PMDD symptoms. We hypothesized that deep sleep and rapid eye movement (REM) sleep, two sleep factors implicated in PMDD, would fluctuate across menstrual phases and influence irritability and fatigue in those with PMDD.

Methods:
We tracked 25 individuals with confirmed PMDD for three menstrual cycles. Sleep was monitored using the GarminVivoSmart and nightly mood ratings were collected. Three-level multi-level models assessed the relationship between sleep components (REM sleep and deep sleep) and symptoms (fatigue and irritability) across the menstrual cycle, with days nested within cycles and cycles nested within individuals.

Results:
REM sleep decreased in the luteal phase compared with the follicular phase (t=-2.56, p=.014). There was a significant interaction between cycle phase and REM sleep, where decreased REM sleep was associated with increased fatigue, but not irritability, during the luteal phase (t=-2.10, p=.036). Deep sleep did not vary between cycle phases and was not associated with symptom changes.

Conclusions:
REM sleep was decreased in the luteal phase and may impact fatigue levels in PMDD. Remote monitoring of REM sleep holds promise for monitoring affective switching. Future research should explore additional sleep variables and PMDD symptoms in a larger sample of individuals to build within person predictive models of affective switching.