Frontiers in sleep最新文献

Introduction: This study evaluated the performance of a wrist-worn wearable, Verily Study Watch (VSW), in detecting key sleep measures against polysomnography (PSG).

Methods: We collected data from 41 adults without obstructive sleep apnea or insomnia during a single overnight laboratory visit. We evaluated epoch-by-epoch performance for sleep vs. wake classification, sleep stage classification and duration, total sleep time (TST), wake after sleep onset (WASO), sleep onset latency (SOL), sleep efficiency (SE), and number of awakenings (NAWK). Performance metrics included sensitivity, specificity, Cohen's kappa, and Bland-Altman analyses.

Results: Sensitivity and specificity (95% CIs) of sleep vs. wake classification were 0.97 (0.96, 0.98) and 0.70 (0.66, 0.74), respectively. Cohen's kappa (95% CI) for 4-class stage detection was 0.64 (0.18, 0.82). Most VSW sleep measures had proportional bias. The mean bias values (95% CI) were 14.0 min (5.55, 23.20) for TST, -13.1 min (-21.33, -6.21) for WASO, 2.97% (1.25, 4.84) for SE, -1.34 min (-7.29, 4.81) for SOL, 1.91 min (-8.28, 11.98) for light sleep duration, 5.24 min (-3.35, 14.13) for deep sleep duration, and 6.39 min (-0.68, 13.18) for REM sleep duration. Mean and median NAWK count differences (95% CI) were 0.05 (-0.42, 0.53) and 0.0 (0.0, 0.0), respectively.

Discussion: Results support applying the VSW to track overnight sleep measures in free-living settings. Registered at clinicaltrials.gov (NCT05276362).

Objectives: To identify factors to optimize long-term non-invasive ventilation (LT-NIV) use by exploring the experience of children using LT-NIV and their parents.

Study design and methods: A qualitative framework analysis method was used. Children aged 8-12 years who used LT-NIV for at least 3-months and their parents/guardians were approached to participate. Thematic analysis of data derived from focus group interviews, conducted separately for children and parents, was performed. Findings were coded and grouped into identified themes.

Results: Data analysis identified four themes: (1) "The double-edged sword," which identified benefits and challenges of LT-NIV use; (2) "Feeling different," where children and parents described fears, frustrations, and concerns including emotional and social implications, and physical changes; (3) "It's not just about the mask," highlighted the influence of equipment issues, including the mask interface, headgear, tubing and humidity, and their impact on tolerance and use of LT-NIV; and (4) "Through the eyes of experience-children and parents as experts for change," which captured ideas for the functional and aesthetic improvement of the equipment including the need for pediatric specific technology.

Conclusions: LT-NIV use has two sides; it helps to improve lives though requires an investment of time and commitment to ensure success. Investing in pediatric-specific equipment needs to be a priority as do alliances between healthcare providers, children who use LT-NIV, and their families. Future technology development and studies of adherence need to consider the experiences of children and their families to reduce the challenges and support optimal use of LT-NIV.

Purpose: Little is known regarding women's lived experiences of how diet impacts sleep. Based on ethnographic interviews among working-class women from Mexico City, our primary aim was to identify themes related to diet and sleep among midlife women. Informed by qualitative analyses, a secondary aim was to examine associations between tea and sleep duration in a broader cohort.

Materials and methods: We conducted a cross-sectional study that entailed in-depth ethnographic interviews about sleep and other behaviors, including diet, with a purposive sample of 30 women from the ELEMENT cohort. Ethnographer field notes and transcripts were analyzed using thematic analysis. Guided by findings from the interviews demonstrating that tea consumption might be associated with sleep, we conducted post-hoc analyses of the relationship between tea and sleep duration using data from food frequency questionnaires and actigraphy, respectively, in the broader cohort (n = 406).

Results: The mean (SD) age of the ethnographic sample was 50.0 (9.0) years. The top noted theme was the use of herbal tea (in Spanish infusion) to improve sleep; most women (29/30) discussed herbal teas, characterizing them as a "natural remedy" to facilitate sleep. The mean (SD) age of the broader sample (N = 406) was 48.4 (6.2) years. Post-hoc analyses revealed positive associations between tea without sugar (though not necessarily herbal tea) and sleep duration. We found that every serving of tea without sugar consumed was associated with an 18.0 min per night [β (SE) = 18.0 (7.8); p = 0.022] and a 13.4 min per night [β (SE) =13.4 (5.6); p = 0.017] increase in weekend and 7-day sleep duration, respectively.

Conclusions: Within a sample of 30 midlife women, dietary practices were described in relation to sleep, specifically the consumption of herbal teas to promote sleep.

Objective: The current study compared self-reported sleep in undergraduate students in Austria and the United States.

Methods: The Pittsburgh Sleep Quality Index responses from 292 Austrian university students (237 females) and 313 U.S. university students (189 females) were analyzed. In addition to the standard scoring procedure for the scale and the individual components of the scale, the data were also evaluated as separate sleep quality and sleep quantity factors using ANOVAs. Sleep timing (bedtime, wake-time, and midpoint) was also examined using independent t-tests.

Results: Austrian students reported better sleep quality and quantity than the U.S. students. In addition, Austrian students had more sleep disturbances and took longer to fall asleep but slept longer and used less sleep medication than U.S. students. Austrian students also went to bed earlier and woke up later than U.S. students.

Conclusions: The current results indicate that sleep in undergraduate students varies across countries. A major difference between the two groups of students was the university setting with the Austrian students living in a large urban area and the U.S. students living in a rural college town, suggesting that the environment could impact student sleep and sleep choices. Finally, the current data indicate that examining sleep quality as a separate factor from sleep quantity provides additional information about sleep in college students. Better documenting sleep and sleep habits in college students across different countries can address important differences that universities and societies can use to help improve sleep and wellbeing in their students.

Here, we aimed to clarify the factors that cause individual differences in manual spindle detection during sleep by comparing it with automatic detection and to show the limitations of manual detection. Polysomnography (PSG) signals were recorded from ten young male participants, and sleep stages were classified based on these signals. Using time-frequency analysis, we detected sleep spindles from the single-channel electroencephalography (EEG) of C4-A1 within the same PSG data. Our results show a detailed accuracy evaluation by comparing the two skilled scorers' outputs of automatic and manual sleep spindle detection and differences between the number of sleep spindle detections and spindle time length. Additionally, based on automatic detection, the distribution of Cohen's kappa for each scorer quantitatively showed that individual scorers had detection thresholds based on EEG amplitude. Conventionally, automatic detection has been validated using manual detection outputs as the criterion. However, using automatic detection as the standard and analyzing the manual detection outputs, we quantitatively showcased the differences in individual scorers. Therefore, our method offers a quantitative approach to examining factors contributing to discrepancies in sleep spindle detection. However, individual differences cannot be avoided when using manual detection, and automatic detection is preferable when analyzing data to a certain standard.

Introduction: Identifying prognostic factors of treatment outcome may assist in customizing an intervention to a patient's needs. Hence, we conducted a secondary analysis of data from a randomized controlled trial to investigate the effectiveness of an internet-based cognitive behavioral therapy for insomnia (iCBT-I) to find patient characteristics that may predict the change of insomnia severity after treatment.

Materials and methods: In this exploratory analysis involving 94 chronic insomnia patients, we examined the predictive value of several self-reported measures, medical history, and sociodemographic variables to psychological distress with separate linear regression models. The main outcome was the Insomnia Severity Index score improvement from pre- to post-treatment.

Results: The study found that duration of insomnia, b (SE) = -0.02 (0.01), p = 0.01, and attitudes about the expected treatment success, b (SE) = 0.80 (0.27), p = 0.004, were predictors of a better outcome. Moreover, a better outcome was associated with a lower level of the following traits: attention seeking, b (SE) = -1.06 (0.51), p = 0.04; grandiosity, b (SE) = -1.50 (0.57), p = 0.01; distractibility, b (SE) = -1.57 (0.75), p = 0.04; and rigid perfectionism, b (SE) = -1.32 (0.65), p = 0.05.

Conclusion: Our results suggest that iCBT-I might be particularly beneficial for patients with higher expectations from the therapy and those who have a shorter duration of insomnia. Some pronounced personality traits, such as attention seeking, grandiosity, distractibility, and rigid perfectionism, may predict worse outcomes. However, because this was a post-hoc analysis, our results must be considered exploratory and verified in further studies.

Clinical trial registration: https://clinicaltrials.gov/study/NCT04300218?cond=NCT04300218&rank=1, Identifier NCT04300218.

Background: It has been suggested that a short nap in the afternoon may improve sleepiness, alertness, and task performance. The present study evaluated the effects of a 30-min rest with a new nap chair on task performance, sleepiness, and neurophysiological measures.

Methods: A randomized controlled crossover trial with a 1-week interval was carried out at the BOOCS Clinic Fukuoka in Japan. The subjects were male workers aged 20 to 64 years with suspected brain fatigue, which was defined by the Profile of Mood Status 2. The intervention was a 30-min rest with an office chair or a nap chair. The primary outcome was the performance in the Uchida-Kraepelin test. The secondary outcomes included the Karolinska Sleepiness Scale and 15-min heart rate variability (HRV). The changes after the nap-chair rest and office-chair rest were compared. Repeated measures analysis of variance with nesting was used in the statistical analysis.

Results: Twenty participants were eligible and entered the crossover trial. The overall 15-min score in the Uchida-Kraepelin test improved after the nap-chair rest and after the office-chair rest to almost the same extent (5.9 vs. 5.5 points, P = 0.68). The Karolinska Sleepiness score significantly decreased after the nap-chair rest, and the between-treatment difference in the decrease was highly significant (P = 0.0004). The average duration of sleep during rest was prominently longer in the nap-chair rest than in the office-chair rest (19.0 vs. 7.6 min, P = 0.002). No participants experienced REM sleep during the rest. LF and HF powers of the HRV were greater during the nap-chair rest than during the office-chair rest, the difference in the HF power being substantial.

Conclusion: A 30-min rest with the nap chair did not appreciably improve the performance in the Uchida-Kraepelin test as compared with the office-chair rest. The nap-chair rest induced a substantially longer sleep accompanied with a parasympathetic activation, thereby resulting in a material improvement in sleepiness after the rest.

Introduction: Children and adolescents treated in specialty mental health services are more likely to have sleep disturbances than those without mental health problems. Few studies have investigated the relationship between sleep and psychopathology in broad clinical samples of children. We examined the relationship between sleep disturbance and age on internalizing and externalizing psychopathology in a sample who sought treatment at children's mental health centers.

Methods: Secondary data analyses were completed on a sample of children (N = 13,472; aged 4 to 18; 55% male) from 39 children's mental health agencies in Ontario, Canada, who completed a semi-structured assessment, the interRAI Children and Youth Mental Health (ChYMH). A split-half sample approach was utilized (S1 n = 6,773, S2 n = 6,699). Hierarchical regressions examined the effects of sleep disturbances (i.e., difficulty falling asleep, staying asleep, night waking, bedtime resistance, falling asleep during the day) on internalizing and externalizing symptoms, above and beyond established child- (i.e., age, sex, sensory sensitivity, pain) and family-level variables (family functioning, caregiver distress, parenting strengths). Age was tested as a moderator for sleep disturbances on both outcome variables.

Results: Overall, 6.7% of children had clinically significant sleep disturbance scores (≥10 out of 16) on the interRAI ChYMH. In both samples, sleep disturbances predicted internalizing (S1 ΔR² = 10%, S2 ΔR² = 10%) and externalizing symptoms (S1 ΔR² = 2%, S2 ΔR² = 1%), above and beyond child and family variables. Age moderated the relationship between sleep disturbances and internalizing symptoms (S1 ß = 0.07; S2 ß = 0.07; ΔR² = 0.004 in both samples), but not externalizing symptoms; sleep disturbance was more strongly related to internalizing symptoms amongst adolescents (ß = 0.98) than children (ß = 0.62).

Discussion: The relationship between sleep and internalizing symptoms appears to change as children move through development. Further, sleep was a stronger predictor of internalizing problems in adolescents than children, suggesting an additional focus of clinician efforts in this age group. These findings strengthen the importance of routine assessment of sleep, as is done with the interRAI ChYMH.

Objective: To evaluate the feasibility of the Sleep Health through University Student Habits (SHUSH) program, a brief sleep improvement intervention based upon principles of cognitive-behavioral therapy for insomnia (CBT-I) developed for Japanese university students.

Methods: Pretest-posttest, single-arm pilot study design with 3-month follow up was used to evaluate the feasibility of SHUSH. We developed then offered a 90-min sleep education class based upon the two-process model of sleep regulation, sleep restriction, stimulus control, and sleep hygiene. We recommended individualized sleep prescriptions (e.g., prescribed time to bed and prescribed time out of bed) from 11 days of daily sleep diary data. We then offered 15 min of individualized follow-up meetings each week for three consecutive weeks in person or online in which we supported adherence to sleep prescriptions. Fifteen university students with self-reported sleep disturbance (Insomnia Severity Index; ISI score ≥ 9) completed the SHUSH program. Participants were on average age 19.7 years old; nine were women, and they were students in occupational therapy and physical therapy. We assessed validated Japanese versions of sleep-related (e.g., ISI, Sleep hygiene practice scale; SHPS), mental health-related (e.g., Generalized Anxiety Disorder Screener) patient-reported outcomes (PROs) and daily sleep diary variables (e.g., sleep onset latency and sleep efficiency).

Results: Comparing baseline and posttest data, a statistically significant difference was observed in insomnia symptom severity, daytime sleepiness, sleep hygiene practices, eveningness to morningness, anxiety, depression, sleep diary improvements (e.g., sleep onset latency, total time in bed, and sleep efficiency). Comparing posttest and 3-mo follow up data (n = 10), a statistically significant difference wasn't observed for most PRO effects. However, there was a statistically significant difference in ineffective sleep behaviors (i.e., SHPS-J). We did observe a rebound effect for some SHPS-J items.

Conclusion: SHUSH was developed as a brief cognitive-behavioral intervention for insomnia. SHUSH participants showed improvements on sleep-related and mental health-related PROs after 4 weeks of intervention. At 3 months follow-up sleep quality and mental health gains were maintained. SHUSH was a feasible program. Randomized controlled trials are needed to test treatment efficacy on sleep related and mental health related PROs in the future.