Behavioral Sleep Medicine最新文献

Objective: To examine the associations between parent perceived environmental factors, nighttime sleep duration and 24-h sleep duration among an international sample of preschool-aged children.

Methods: Secondary analyses of cross-sectional data from preschoolers across 23 countries (19 LMICs), collected during the third pilot phase (January 2021-August 2024) of the SUNRISE Study. Parents completed a questionnaire which asked about their child's sleep patterns and environmental factors that impacted their child's sleep in the previous 3 days.

Results: Data from 2,219 children were analyzed. A significant difference was observed between nighttime sleep (F = 14.27, p = <0.0001) and nap duration (F = 9.10, p = 0.0004) across country income level. Environmental factors such as heat (-12.87, 95% CI: -11.54, -0.61) and cold (-17.70, 95% CI: -34.53, -0.85) were negatively associated with nighttime sleep duration.

Conclusions: Public health researchers and professionals should prioritize context-specific strategies to minimize the impact of weather conditions on sleep to promote healthy levels of sleep among preschoolers from diverse settings.

Objective: Bedtime procrastination describes going to bed later than intended, leading to insufficient sleep. Although difficulty falling asleep and pre-sleep arousal are assumed to cause bedtime procrastination, the relationship has not been directly examined. In this study, we examined whether difficulty falling asleep and pre-sleep arousal lead to bedtime procrastination.

Methods: We conducted a longitudinal survey, administered three times at 1-month intervals, among participants aged 18-65 years; 1,102 participants were included in the final analysis. Participants were asked to complete questionnaires that included bedtime procrastination, difficulty falling asleep, and pre-sleep arousal (cognitive and somatic) measures. The random intercept cross-lagged panel model was used to test the hypothesis that difficulty falling asleep and pre-sleep arousal increased bedtime procrastination.

Results: No significant cross-lagged path was observed from difficulty falling asleep or pre-sleep cognitive arousal to bedtime procrastination. A significant positive path was observed from pre-sleep somatic arousal to bedtime procrastination between Times 2 and 3, but not Times 1 and 2.

Conclusion: Although difficulty falling asleep did not lead to bedtime procrastination, pre-sleep somatic arousal partially led to bedtime procrastination. These findings suggest that individuals with higher pre-sleep somatic arousal might develop more bedtime procrastination.

Objectives: Insomnia is highly comorbid with mental health conditions, yet graduate psychology students receive limited training in sleep and insomnia management. An online introductory sleep workshop focused on insomnia management with Cognitive Behavioral Therapy for Insomnia (CBT-I) was developed for Australian graduate psychology students to address this training gap. However, some students reported difficulties applying CBT-I knowledge to clinical practice. This study explored the barriers and facilitators to implementing CBT-I knowledge into graduate psychology students' practice post-workshop.

Methods: Semi-structured interviews were conducted with 15 graduate psychology students who attended an online introductory sleep and CBT-I workshop. Data were analyzed using reflexive thematic analysis.

Results: Facilitators of CBT-I implementation included: (1) Helpful workshop resources; (2) Increased awareness of the importance of sleep's role in mental health; (3) Enhanced self-efficacy with introductory sleep skills (e.g. sleep history taking); and (4) Knowing where to access further training. Barriers included: (1) Limited ongoing training and clinical supervision; (2) Accessibility challenges; (3) Clinical implementation challenges; and (4) Constraints of being a graduate student.

Conclusion: The introductory workshop facilitated the development of introductory CBT-I skills among graduate psychology students, but ongoing training and supervision are needed to enhance implementation and expand Australia's CBT-I workforce.

Objective: Research indicates a strong relationship between dietary inflammation and sleep; however, such research is limited among women postpartum. We studied whether prenatal and postnatal pro-inflammatory diets were associated with postpartum sleep quality and duration.

Methods: A secondary data analysis was conducted among 219 women from the Health in Pregnancy and Postpartum randomized controlled trial promoting healthy lifestyles in pregnant women with pre-pregnancy overweight and obesity. Data from ≤16 and 32 weeks gestation, and 6 and 12 months postpartum were used. Sleep was measured using BodyMedia's SenseWear® armband. Energy-adjusted Dietary Inflammatory Index (E-DII^TM) scores were calculated using micro and macronutrients intake collected from 24-hour dietary recalls. Linear mixed-effects models estimated the impact of the E-DII score on postpartum sleep parameters.

Results: Women consuming pro-inflammatory diets, compared to anti-inflammatory diets were more likely to have a later bedtime (p = .04) and a later waketime (p = .03). For every one-unit increase in the prenatal E-DII score, 6-months postpartum sleep latency increased by 0.57 minute (p = .03). Among those receiving the intervention, changes in E-DII scores led to a 7.3-minute earlier bedtime (p = .01), 5.2-minute longer sleep duration (p = .03) and additional 5.7-minute longer time-in-bed (p = .05) compared to controls.

Conclusions: Results suggest anti-inflammatory diets during pregnancy and postpartum may be beneficial for better sleep.

Background: This study employed a multilevel autoregressive mediation model to clarify the longitudinal role of poor sleep quality in the association between mobile-phone addiction and depressive symptoms among Chinese college students.

Methods: 3,662 freshmen (976 Male/2,686 Female) from two Anhui colleges were assessed at T₁ (November 2019, N = 4,211), T₂ (May 2020, N = 4,193) and T₃ (November 2020, N = 3,662) for sleep quality, mobile-phone addiction and depressive symptoms.

Results: Correlation analysis revealed significant associations between smartphone addiction (β = 0.493, 0.391, p <0.001), sleep problems (β = 0.336, 0.318, p <0.001), and depressive symptoms (β = 0.488, 0.431, p <0.001) across T1, T2 and T3 . Positive associations were observed between smartphone addiction and both sleep problems and depressive symptoms (β = 0.343, 0.329 at T1; β = 0.381, 0.402 at T2; β = 0.315, 0.261 at T3; all p < 0.001). A simple mediation model revealed that poor sleep quality partially mediated the association between mobile phone addiction and depressive symptoms among college students (indirect effect β = 0.0505, p < 0.001; total effect β = 0.237, p < 0.001). The multilevel autoregressive mediation model further confirmed that poor sleep quality partially mediated this association (indirect effect β = 0.002, p < 0.05; total effect β = 0.047, p < 0.001).

Conclusion: This study underscores poor sleep quality as a critical mediating factor in the long-term relationship between mobile phone addiction and depressive symptoms among Chinese college students.

Objectives: This case series examined the feasibility and preliminary effects of group-based, videoconference-delivered cognitive-behavioral therapy (CBT) combined with morning light therapy (LT) in adolescents with delayed sleep timing.

Method: Five females aged 14-16 years (M = 15.0, SD = 0.7) completed clinician-administered screening interviews, and baseline and post-treatment assessments, including circadian phase measurement, and validated measures of chronotype, bedtime procrastination, pre-sleep arousal, daytime sleepiness, anxiety, depression, and quality of life. Actigraphy was used for the duration of the study. The intervention included six weekly CBT sessions and short-wavelength wearable LT assigned for 1 hr daily following an advancing wake time schedule.

Results: One participant showed a 94-min circadian phase advance; others showed minimal phase advance, no change, or phase delays (n = 2). All participants reported earlier chronotype by post-treatment. Three advanced either sleep onset or wake time, with one showing both. Two showed increased total sleep time, primarily due to delayed wake time. Other objective sleep outcomes are presented. Bedtime procrastination, pre-sleep arousal, daytime sleepiness, depression, and quality of life improved, with modest reductions in anxiety. Challenges included napping, ADHD and anxiety comorbidity, scheduling barriers (homework, extracurricular activities, screen use), and resistance to earlier bedtimes.

Conclusions: Results suggest heterogeneous circadian and sleep responses but consistent behavioral improvements. Extended LT duration, motivational enhancement, executive function or time management strategies, and behavioral economics-informed interventions may improve engagement and treatment efficacy.

Objectives: 1) Compare the sleep hygiene of our clinical sample to the community-based validation sample and established clinical thresholds and 2) clarify the relationship between sleep hygiene and sleep problems in adolescents referred for Behavioral Sleep Medicine (BSM) treatment.

Methods: Clinical participants included BSM patients aged 11-18 years (n = 354) with insomnia. Adolescents completed the Adolescent Sleep Hygiene Scale (ASHS) and the Pediatric Insomnia Severity Index. Caregivers completed the Sleep Disorders Inventory for Students. Independent samples t-tests compared sleep hygiene between our clinical sample and the community-based ASHS validation sample (572 American adolescents). We report which sleep hygiene subscales fell below thresholds indicating clinically significant problems. Multiple linear regressions determined whether demographics and sleep hygiene subscales predicted sleep problems.

Results: Adolescents referred to our BSM clinic had better overall sleep hygiene than the community-based validation sample, p < .001. They had inadequate sleep hygiene practices related to sleep stability, behavioral arousal, and cognitive/emotional arousal. Demographics and sleep hygiene factors significantly predicted both adolescent-reported insomnia severity and caregiver-reported sleep disturbance, ps < 0.001.

Conclusion: Poor sleep hygiene may result from maladaptive coping and can compound existing sleep problems. It is important to have consistent definitions of sleep hygiene that limit overlap with other key intervention targets.

Objectives: The aim of this systematic review was to synthesize evidence on the impacts of sleep duration and quality in healthcare workers on patient safety and quality of care. A secondary aim was to understand the impact of shiftwork and workload characteristics alongside sleep duration and quality.

Methods: A systematic search of Scopus, PubMed, Embase, APA PsycINFO, and CINAHL databases was completed in May 2023 and updated in December 2024. Only studies published in English from 2013 onwards were considered for inclusion in the review. Quality appraisal of included studies was conducted via the McMaster tools for quantitative and qualitative studies, respectively, and results were synthesized and presented as a narrative summary.

Results: Database searching revealed 7,422 results, with 30 studies eventually included in the review. Studies consistently showed that short sleep duration in healthcare workers was associated with worse patient safety (increased errors and poorer cognitive functioning). There was also a clear link between shiftwork and long shifts with reduced patient safety.

Conclusions: The majority of included studies revealed that patient safety and quality of care are worse where HCWs experience short duration and/or low-quality sleep or are working long and/or irregular shifts.

Objectives: The PANAS is the most widely used measure to detect changes in mood following sleep loss. Although insufficient sleep is associated with enhanced negativity, negative affect items on the PANAS appear unaffected. We examined whether PANAS items were deemed relevant to sleep and subsequently developed a novel tool reflecting changes in negative and positive affect with sleep (NAP-AS).

Methods: Four hundred and forty-nine online respondents (18-79y) indicated the extent to which 100 positive and negative word-items (n = 48 new; n = 52 from any PANAS) were useful in describing the experience of insufficient sleep. Using factor analysis, a new questionnaire to reflect changing mood in relation to insufficient sleep was developed and validated under sleep deprivation conditions (n = 24, 18-34y).

Results: Four out of 10 original negative affect (NA) PANAS items (and 0/10 positive affect (PA) items) were deemed irrelevant to sleep by >50% of respondents ("guilt", "afraid", "scared", "ashamed"). To address this, we developed the NAP-AS using factor analysis (from 100 word items) resulting in 14 items reflecting NA and PA (71.4% new items for PA and NA equally; final fit model: RMSEA = 0.048, CFI = 0.98). In a validation study, this tool was sensitive to sleep deprivation (p < .001), such that NA significantly increased (p = .017, d > 0.47), while PA decreased (p < .001, d > 0.75), relative to when well-rested.

Conclusions: Despite the PANAS being a valid tool assessing changes in affect, several items appear irrelevant to the experience of poor sleep. The NAP-AS was developed to specifically capture changes in positive and negative affect following insufficient sleep. The new tool was sensitive to sleep loss, although further validation for clinical populations is recommended.

Objectives: To examine: 1) cross-sectional associations between past-month use of cannabis for sleep with mental health, substance use, and related factors in adults and 2) the role of genetic and early environmental factors shared by twins (familial confounds) in explaining significant associations.

Methods: In a population-based sample of adult twins (n = 3,165, M_age36.7) we ran regression (phenotypic) and multilevel (co-twin control) models examining associations between past-month use of cannabis for sleep without comes of interest. We controlled for cannabis frequency and sleep quality except when each was the outcome of interest.

Results: Recent use of cannabis for sleep was associated with multiple mental health, substance use, and related factors in phenotypic models. In co-twincontrol models, within-family effects were significant between using cannabis for sleep with more problems from cannabis use, higher cannabis frequency, worse sleep quality, and more frequent use of alcohol and medication for sleep.

Conclusions: Familial confounds may explain many, but not all, associations between recent use of cannabis for sleep and mental health, substance use, and related factors. Longitudinal work is needed to clarify the directionality of associations not explained by familial confounds, and whether they are risks of using cannabis for sleep.