Behavioral Sleep Medicine最新文献

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.

Objectives: Insomnia disorder is co-morbid with and predictive of developing pain conditions and a key factor in pain interference (PI) - the extent to which pain impedes daily living. Emerging literature suggests treating insomnia with cognitive-behavioral therapy for insomnia reduces co-occurring PI. This secondary data analysis tested the extent to which digital CBT-I (dCBT-I) vs. sleep education reduces and prevents significant PI by treating insomnia.

Methods: Insomnia disorder participants were randomized into dCBT-I (n = 697) and sleep education (n = 623) and reported pre- and post-treatment insomnia and PI. Logistic regressions evaluated intervention effects: 1) reduction of insomnia severity changes in PI and 2) prevention of treatment condition on PI.

Results: The reduction model showed that dCBT-I participants with moderate-to-severe pre-treatment PI experienced 17% odds increase in reduced PI for each one-point reduction in insomnia severity compared to control, OR = 1.17, 95% CI [1.01, 1.35]. In the prevention model, dCBT-I participants with little-to-no pre-treatment PI exhibited a 32% odds reduction of post-treatment progression to moderate-to-severe PI compared to control, OR = 0.68, 95% CI [0.51, 0.90].

Conclusion: dCBT-I demonstrated significant and clinically meaningful reduction and prevention effects against PI in a large sample. dCBT-I may help providers address sleep issues to restore pain-related impairments to daytime function, quality of life, and overall sleep.

Objectives: We performed a multidimensional analysis of mood, cognition, sleep and circadian rhythms in patients with post-acute sequelae of SARS-CoV-2 infection (PASC) with the objective of characterizing the phenotype of PASC fatigue.

Methods: We recruited adult patients from a Neuro-COVID-19 Clinic with persistence of disabling symptoms beyond 6 weeks from acute infection. Self-reported symptoms were assessed with Patient-Reported Outcomes Measurement Information System instruments. We evaluated cognitive performance using NIH Toolbox measures and assessed sleep and rest-activity rhythms by 7 days of wrist actigraphy. We performed level 2 polysomnography in a subset of 20 participants.

Results: We studied 58 participants: 83% White, 59% female and 91% not hospitalized for COVID-19. Fatigue severity was significantly correlated with worse self-reported cognitive abilities but not with objectively measured cognitive performance and with greater depression symptoms, several rest-activity rhythm and light exposure disruption measures, and greater actigraphy measured sleep time and time in bed. A multivariable model found significant, independent associations between fatigue severity and subjective cognitive abilities, depression symptoms, and rest-activity rhythm disruption.

Conclusions: Long total sleep times, disruption of light exposure and circadian rest-activity patterns, depression and subjective cognitive impairment are associated with PASC fatigue. Behaviorally influenced sleep and circadian abnormalities may exacerbate fatigue and be targets for therapeutic interventions.

Objectives: The purpose of this randomized controlled trial was to determine whether a cognitive-behavioral sleep health self-management intervention (CB-Sleep Health) would be more effective than a time-balanced attention control (AC) condition in improving multiple dimensions of sleep health (self-reported and objectively derived).

Methods: Young adults with T1D (ages 18-26 years) were randomly assigned to a 12-week CB-Sleep Health (n = 21) or AC condition (n = 18). They wore concurrent continuous glucose monitors and actigraphy devices and completed daily sleep surveys for 14 days at baseline, post-intervention, and 3-month follow-up.

Results: Of the randomized participants, 31 (79.5%) completed the post-intervention, while 33 (84.6%) completed the 3-month follow-up. The CB-Sleep Health intervention had a significant effect on alertness and duration compared to the control group. The changes from baseline were -3.21 s vs. +0.71, p = .005 and +18 min vs. -25.8 min, p = .01, respectively. These effects were sustained at the 3-month follow-up.

Conclusions: Longer sleep duration, higher daytime alertness, and sustained sleep efficiency are possible with this CB-Sleep Health intervention in young adults managing a complex condition.

Objective: To explore the adherence and perceived usefulness of Cognitive Behavioral Therapy for Insomnia (CBT-I) components in the perinatal period and their association with sleep outcomes.

Methods: Seventy-six nulliparous individuals (age M = 33.07 SD ±3.10) from two randomized control trials who received CBT-I at three time points: late pregnancy (35 weeks' gestation), 1.5-3 months postpartum, and 6 months postpartum were analyzed. At each time point, participants self-reported perceived usefulness and adherence for each of the six CBT-I components, and completed the Insomnia Severity Index (ISI), PROMIS Sleep-Related Impairment (PROMIS-SRI), and Dysfunctional Beliefs and Attitudes about Sleep scale (DBAS-16).

Results: All components were perceived as useful by most (74.3-97.1%) participants; adherence varied between components and across time. Cross-sectional multiple regression analyses showed that for "sleep hygiene", higher adherence was associated with lower DBAS-16 at 35 weeks' gestation (small effect). Higher adherence and usefulness to "managing sleep deprivation, sleepiness and fatigue" was associated with lower ISI at 6 months postpartum (small and medium effect size, respectively); higher perceived usefulness was associated with lower PROMIS-SRI at 6 months (small effect; all p-values < .05). There were no significant associations among adherence/usefulness and sleep at 2 months postpartum.

Conclusions: The overall high perceived usefulness of CBT-I components suggests a strong interest in engaging with perinatal sleep health information. Pregnancy may be a crucial time for delivering sleep strategies before facing caregiving duties and heightened postpartum sleep disruptions. These findings provide insights into how CBT-I components are perceived and applied during the perinatal period.