‘This is the last episode’: the association between problematic binge-watching and loneliness,emotion regulation,and sleep-related factors in poor sleepers

Evidence on the relation between binge-watching and sleep quality is still scarce and inconsistent and none has taken into account both the healthy and pathological dimensions of the phenomenon. This study aimed at filling this gap by investigating both aspects in healthy participants with high and low sleep quality. Further, we aimed at identifying sociodemographic, psychological and sleep-related determinants of problematic binge-watching in poor sleepers. We first conducted independent comparisons between good (n = 253) and poor sleepers (n = 209) on different binge-watching symptoms and motives, assessed through ‘Binge-watching Engagement and Symptoms’ and ‘Watching TV Series Motives’ questionnaires, respectively. Then, we focused on the problematic aspects of binge-watching in poor sleepers, investigating the role of emotion regulation, loneliness, and sleep-related factors using hierarchical multiple regressions. Comparisons between the two groups revealed a greater extent of binge-watching behaviour (t = −2.80, p = 0.005) and greater use of this practise to cope with negative emotions (t = −4.17, p < 0.001) in poor sleepers. In addition, hierarchical multiple regressions showed that gender (β = −0.166, p = 0.008), alcohol consumption (β = −0.135, p = 0.035), emotional dysregulation (β = 0.260, p = 0.001; β = 0.298, p < 0.001), feelings of loneliness (β = 0.159, p = 0.029; β = 0.199, p = 0.003), and daytime sleepiness (β = 0.149, p = 0.016) are significant determinants of problematic binge-watching in this population. In addition to showing for the first time the relationship between sleep quality and different aspects of binge-watching, our findings indicate that emotional dysregulation, feelings of loneliness, and daytime sleepiness play a key role in determining problematic binge-watching in poor sleepers, possibly due to the existence of a pathological vicious circle between these factors in poor sleepers.     

In search of a cut-off apnea–hypopnea index in type 3 home portable monitors to diagnose and treat obstructive sleep apnea: a mathematical simulation

The American Academy of Sleep Medicine (AASM) uses similar apnea–hypopnea index (AHI) cut-off values to diagnose and define severity of sleep apnea independent of the technique used: in-hospital polysomnography (PSG) or type 3 portable monitoring (PM). Taking into account that PM theoretically might underestimate the AHI, we explored whether a lower cut-off would be more appropriate. We performed mathematical re-calculations on the diagnostic PSG-AHI (scored using AASM 1999 rules) of 865 consecutive patients with an AHI of ≥20 events/h who started continuous positive airway pressure (CPAP). For a PSG-AHI of ≥15 events/h re-scored using AASM 2012 rules (PSG-AHI^AASM2012), a PM-respiratory event index (REI)^AASM2012 cut-off point of ≥15 events/h resulted in a post-test probability of 100% of having the disease, but with negative tests in 57.1%. A PM-REI^AASM2012 cut-off of 8 events/h, still resulted in a positive post-test probability of 100% but with negative tests in only 34.3%. Combination of the cut-off values with clinical estimation of being ‘at high risk’ based on Epworth Sleepiness Scale (ESS) and Berlin Questionnaire scores only resulted in a small reduction in the percentage of negative tests (respectively 52.7% and 32.7%). After 6 months, CPAP adherence was not lower using the PM-REI^{AASM 2012} cut-off ≥8 events/h in comparison to ≥15 events/h (median 5.7 vs. 5.8 h/night, p = 0.368) and the reduction in ESS was similar too (median –4 and –5 points, p = 0.083). Consequently, using a lower PM-REI^AASM2012 cut-off could result in cost savings because of less negative studies and lesser need for a confirmatory PSG or a performance of a CPAP trial.     

Warm ears,a red flag for sleepiness?

Core body and skin temperatures are intimately linked to sleep and alertness. The distal-to-proximal skin temperature gradient has been described as a good physiological predictor for sleep onset. Increased ear skin temperature is often caused by increased blood flow reflected in redness, which is commonly noticed in people who are sleepy, especially anecdotally in children. Nonetheless, no prior study investigated the possible relation between sleepiness and ear skin temperature as a separate measurement. We assessed the relation between ear skin temperature and sleepiness in patients undergoing regular electroencephalographic examinations, because of suspicion of epilepsy, both without and after sleep deprivation. Subjective sleepiness was measured using the Stanford Sleepiness Scale, and objective sleepiness by determining sleep onset with electroencephalography. Distal, proximal and ear skin temperature were measured repeatedly using wireless measurement devices (iButtons). Forty-four adult patients were included. Ear skin temperature correlates weakly with distal skin temperature (r = 0.174, p < 0.001) and distal-to-proximal gradient (r = 0.160, p < 0.001), but not with proximal skin temperature (r = −0.001, p = 0.975). Ear skin temperature increased significantly in a subgroup of 13 patients, between 5 and 1 min before sleep onset (p = 0.002; η² = 0.059), even though this increase was also associated with supine posture. iButtons is a valid method to measure ear skin temperature, which appears to function partly like a distal and partly like a proximal skin temperature measurement. Change in ear skin temperature is associated with sleep onset and supine posture.     

Sleep symptoms are essential features of long-COVID – Comparing healthy controls with COVID-19 cases of different severity in the international COVID sleep study (ICOSS-II)

Many people report suffering from post-acute sequelae of COVID-19 or “long-COVID”, but there are still open questions on what actually constitutes long-COVID and how prevalent it is. The current definition of post-acute sequelae of COVID-19 is based on voting using the Delphi-method by the WHO post-COVID-19 working group. It emphasizes long-lasting fatigue, shortness of breath and cognitive dysfunction as the core symptoms of post-acute sequelae of COVID-19. In this international survey study consisting of 13,628 subjects aged 18–99 years from 16 countries of Asia, Europe, North America and South America (May–Dec 2021), we show that post-acute sequelae of COVID-19 symptoms were more prevalent amongst the more severe COVID-19 cases, i.e. those requiring hospitalisation for COVID-19. We also found that long-lasting sleep symptoms are at the core of post-acute sequelae of COVID-19 and associate with the COVID-19 severity when COVID-19 cases are compared with COVID-negative cases. Specifically, fatigue (61.3%), insomnia symptoms (49.6%) and excessive daytime sleepiness (35.8%) were highly prevalent amongst respondents reporting long-lasting symptoms after hospitalisation for COVID-19. Understanding the importance of sleep-related symptoms in post-acute sequelae of COVID-19 has a clinical relevance when diagnosing and treating long-COVID.     

Bidirectional associations of sleep and discretionary screen time in adults: Longitudinal analysis of the UK biobank

The direction of the association between discretionary screen time (DST) and sleep in the adult population is largely unknown. We examined the bidirectional associations of DST and sleep patterns in a longitudinal sample of adults in the general population. A total of 31,361 UK Biobank study participants (52% female, 56.1 ± 7.5 years) had two repeated measurements of discretionary screen time (TV viewing and leisure-time computer use) and self-reported sleep patterns (five sleep health characteristics) between 2012 and 2018 (follow-up period of 6.9 ± 2.2 years). We categorised daily DST into three groups (low, <3 h/day; medium, 3–4 h/day; and high, >4 h/day), and calculated a sleep pattern composite score comprising morning chronotype, adequate sleep duration (7–8 h/day), never or rare insomnia, never or rare snoring, and infrequent daytime sleepiness. The overall sleep pattern was categorised into three groups (healthy: ≥ 4; intermediate: 2–3; and poor: ≤ 1 healthy sleep characteristic). Multiple logistic regression analyses were applied to assess associations between DST and sleep with adjustments for potential confounders. Participants with either an intermediate (OR: 1.40; 95% CI: 1.15, 1.71) or a poor (OR: 1.16; 95% CI: 1.10, 1.24) sleep pattern at baseline showed higher odds for high DST at follow-up, compared with those with a healthy baseline sleep pattern. Participants with medium (OR: 1.40; 95% CI: 1.14, 1.71) or high DST (OR: 1.62; 95% CI: 1.30, 2.00) at baseline showed higher odds for poor sleep at follow-up, compared with participants with a low DST. In conclusion, our findings provide consistent evidence that a high DST at baseline is associated with poor sleep over a nearly 7 year follow-up period, and vice versa.