Background and Objective The ovulatory menstrual cycle is characterized by hormonal fluctuations that influence physiological systems and functioning. Multi-sensor wearable devices can be sensitive tools capturing cycle-related physiological features pertinent to women’s health research. This study used the Oura ring to track changes in sleep and related physiological features, and also tracked self-reported daily functioning and symptoms across the regular, healthy menstrual cycle. Methods Twenty-six healthy women (age, mean (SD): 24.4 (1.1 years)) with regular, ovulatory cycles (length, mean (SD): 28.57 (3.8 days)) were monitored across a complete menstrual cycle. Four menstrual cycle phases, reflecting different hormone milieus, were selected for analysis: menses, ovulation, mid-luteal, and late-luteal. Objective measures of sleep, sleep distal skin temperature, heart rate (HR) and vagal-mediated heart rate variability (HRV, rMSSD), derived from the Oura ring, and subjective daily diary measures (eg sleep quality, readiness) were compared across phases. Results Wearable-based measures of sleep continuity and sleep stages did not vary across the menstrual cycle. Women reported no menstrual cycle-related changes in perceived sleep quality or readiness and only marginally poorer mood in the midluteal phase. However, they reported moderately more physical symptoms during menses (p < 0.001). Distal skin temperature and HR, measured during sleep, showed a biphasic pattern across the menstrual cycle, with increased HR (p < 0.03) and body temperature (p < 0.001) in the mid- and late-luteal phases relative to menses and ovulation. Correspondingly, rMSSD HRV tended to be lower in the luteal phase. Further, distal skin temperature was lower during ovulation relative to menses (p = 0.05). Conclusion The menstrual cycle was not accompanied by significant fluctuations in objective and perceived measures of sleep or in mood, in healthy women with regular, ovulatory menstrual cycles. However, other physiological changes in skin temperature and HR were evident and may be longitudinally tracked with the Oura ring in women over multiple cycles in a natural setting.

Despite the increasing interest in sleep and dream-related processes of emotion regulation, their reflection into wake and dream emotional experience remains unclear. Here, we aimed to assess dream emotions and their relationships with wake emotions through the modified Differential Emotions Scale (Fredrickson, 2003), which includes a broad array of both positive and negative emotions. The scale has been first validated on 212 healthy Italian participants, in two versions: a WAKE-2wks form, assessing the frequency of 22 emotions over the past 2 weeks, and a WAKE-24hr form, assessing their intensity over the past 24 h. Fifty volunteers from the wider sample completed the WAKE-24hr mDES for several days until a dream was recalled, and dream emotions were self-reported using the same scale. A bifactorial structure was confirmed for both mDES forms, which also showed good validity and reliability. Though Positive and Negative Affect (average intensity of positive and negative items, PA, and NA, respectively) were balanced in dreams, specific negative emotions prevailed; rmANOVA showed a different pattern (prevalence of PA and positive emotions) in wake (both WAKE-2wks and WAKE-24hr), with a decrease of PA and an increase of NA in the dream compared to previous wake. No significant regression model emerged between waking and dream affect, and exploratory analyses revealed a stable proportion of PA and NA (with prevailing PA) over the 3 days preceding the dream. Our findings highlight a discontinuity between wake and dream affect and suggest that positive and negative emotions experienced during wake may undertake distinct sleep-related regulation pathways.

Our results indicate that presleep learning favors sleep propensity and maintenance, offering the possibility to explore planned cognitive training as a low-cost treatment for sleep impairments.

Although the issue has been repeatedly explored, data on the impact of the COVID-19 pandemic on children’s sleep quality are inconsistent. To clarify these discrepancies, here we investigate possible age-related differences. During the lockdown, 112 parents of toddlers (0–3 years, N = 61) and pre-schoolers (4–5 years, n = 51) completed an online survey including the Children’s Sleep Habits Questionnaire (CSHQ). Sleep-related items required an additional retrospective judgment, referring to the pre-pandemic period. During the lockdown, sleep schedules were delayed in both age groups whereas sleep quality (CSHQ total scores) improved in pre-schoolers but not in toddlers. Between-groups comparisons revealed that, prior to the lockdown, pre-schoolers showed worse sleep quality than toddlers, whereas this difference disappeared during home confinement. Also, pre-schoolers’ sleep timing was advanced before the lockdown and delayed during the lockdown relative to toddlers’. Our data highlight a significant modulation of age on the impact of the pandemic crisis on sleep, with pre-schoolers experiencing greater effects than toddlers. This profile suggests that factors affecting sleep features have different weights at different ages: sleep patterns would be mainly determined by developmental factors (i.e., biological drive) in younger children, whereas environmental factors (e.g., major lifestyle changes) would have a stronger effect on older ones.

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