Behavioral Sleep Medicine最新文献

Objectives: Nightmares affect up to 12% of the population and are often comorbid with psychiatric disorders like anxiety and depression. Limited research has examined their influence on nightmare frequency. This study investigates the relationship between depression and trait-anxiety symptoms on incident nightmare frequency at follow-up.

Method: Cross-sectional and longitudinal analyses were conducted on 758 Wisconsin Sleep Cohort participants. Trait anxiety and depression symptom severity were measured using the State Trait Anxiety Inventory and Zung Depression Scale. Ordinal regression determined nightmare frequency cutoffs based on anxiety and depression severity. Cross-sectional associations were assessed with Spearman and Kruskal-Wallis tests. Longitudinal associations were analyzed using adjusted binomial regression of binary nightmare frequency (low: <4/month, high: >5/month) against clinical cutoffs of trait anxiety and depression.

Results: Adjusted models indicated a small correlation between baseline nightmare frequency and trait anxiety (β = 0.01, p = .010) and depression symptoms (β = 0.01, p = .005). High baseline trait-anxiety symptoms were associated with frequent nightmares at follow-up (OR = 3.75, CI95% [1.306,10.793], p < .014), but depression symptoms were not (OR = 1.35, CI95%[0.399, 4.587], p = .627).

Conclusions: Our findings suggest that high trait-anxiety symptoms are associated with increased incident nightmare frequency, when adjusted for depression. However, high depression symptoms were not associated with an increase in nightmare frequency when adjusted for trait-anxiety.

Objectives: A multitude of physical and mental challenges are being faced in the population with Co-morbid Insomnia and Sleep Apnea (COMISA). Unfortunately, research about clinical characteristics and management of COMISA based on quantitative evidence is lacking.

Method: Standard procedures for literature retrieval, selection and quality assessment, data extraction, analysis, and interpretation were conducted step by step. For studying the sleep characteristics, common complications and widely recognized treatment options for COMISA, Weighted Mean Difference (WMD) and Odds Ratio (OR) were applied to assess the mean and risk differences between compared groups. Outcomes included sleep health parameters and secondary impairments in physical and mental well-being.

Results: COMISA showed worse sleep quality than OSA only by PSQI (WMD = 3.38 point) and heavier sleep fragmentation (WMD = 11.46 min) than insomnia only. Besides, COMISA patients showed a higher risk for depression (OR [95%CI] = 5.03[2.31, 10.93]) and PTSD (OR [95%CI] = 3.96[1.85, 8.46]) in comparison with OSA alone. Compared to insomnia alone, COMISA patients suffered from more than two times higher risk of cardiovascular diseases, hypertension, and diabetes. In treating COMISA patients, combining CBTI with PAP treatment can enhance the improvement of insomnia severity (ISI, WMD [95%CI] =-3.26[-4.51, -2.00] point) and sleep efficiency (WMD [95%CI] = 6.39[1.97, 10.81] %) compared to PAP alone.

Conclusions: Impaired sleep domains in COMISA cover sleep quality and sleep structure. Also, COMISA has a higher risk for cardiometabolic diseases and mental disorders. Combining CBTI with PAP can be a recommended treatment to relieve sleep impairments for COMISA.

Objectives: Examine psychometric properties of the Insomnia Severity Index (ISI) in a sample of nurses.

Method: In a sample of day shift nurses (N = 289), a confirmatory factor analysis (CFA), convergent and discriminant validity analyses, and a test-retest reliability analysis were performed.

Results: CFA showed that a two-factor model provided the best fit. The ISI had moderate to poor convergent validity with sleep diary parameters, and moderate convergent validity with the Sleep Condition Indicator (r = -.66), Pittsburgh Sleep Quality Index (r = .66), and PROMIS Sleep-Related Impairment measure (r = .67). The ISI demonstrated good discriminant validity with the measures Composite Scale of Morningness (r = -.27), Nightmares Disorder Index (r = .25), PTSD Checklist for DSM-5 (sleep items removed; r = .32), and Perceived Stress Scale (r = .43). The ISI had weaker discriminant validity with the PHQ-9 (r = .69) and Generalized Anxiety Disorder Screener (r = .51). The ISI demonstrated a good test-retest reliability (ICCs = .74-.88).

Conclusions: The ISI is a psychometrically strong measure for the assessment of insomnia severity in day shift nurses. Overlap with psychological symptoms, primarily anxiety and depression, suggests caution while interpreting these constructs.

Objectives: Discrepancies between sleep diaries and sensor-based sleep parameters are widely recognized. This study examined the effect of showing sensor-based sleep parameters while completing a daily diary. The provision of sensor-based data was expected to reduce variance but not change the mean of self-reported sleep parameters, which would in turn align better with sensor-based data compared to a control diary.

Method: In a crossover study, 24 volunteers completed week-long periods of control diary (digital sleep diary without sensor-based data feedback) or integrated diary (diary with device feedback), washout, and then the other diary condition.

Results: The integrated diary reduced self-reported total sleep time (TST) by <10 minutes and reduced variance in TST. The integrated diary did not impact mean sleep onset latency (SOL) and, unexpectedly, the variance in SOL increased. The integrated diary improved both bias and limits of agreement for SOL and TST.

Conclusions: Integration of wearable, sensor-based device data in a sleep diary has little impact on means, mixed evidence for less variance, and better agreement with sensor-based data than a traditional diary. How the diary impacts reporting and sensor-based sleep measurements should be explored.

Objectives: Poor sleep is a common side effect of cancer. Cannabis is increasingly used to manage cancer treatment-related symptoms, including sleep. This study investigated factors related to cannabis use for sleep among Canadian cancer survivors.

Method: Adult Canadian cancer survivors (N = 940) were recruited via the Angus Reid Institute and completed an online, cross-sectional survey. Univariate and multiple binomial logistic regression models identified factors associated with cannabis use for sleep.

Results: Of the participants (M_age = 64.5 yrs; Women = 51.1%; White = 92.9%), 25.1% (n = 236) currently use cannabis for sleep. Participants were at greater odds of using cannabis for sleep if they identified as a gender other than man or woman (AOR = 11.132), were diagnosed with multiple medical conditions (2:AOR = 1.988; 3+:AOR = 1.902), two psychological conditions (AOR = 2.171), multiple sleep disorders (AOR = 2.338), insomnia (AOR = 1.942), bone (AOR = 6.535), gastrointestinal (AOR = 4.307), genitourinary (AOR = 2.586), hematological (AOR = 4.739), or an unlisted cancer (AOR = 3.470), received hormone therapy only (AOR = 3.054), drink heavily (AOR = 2.748), or had mild insomnia (AOR = 1.828). Older participants (AOR=.972) and those with sleep apnea were less likely to use cannabis for sleep (AOR=.560).

Conclusion: Given its prevalence, research is needed to understand how factors associated with cannabis use as a sleep aid among Canadian cancer survivors may influence its use and effectiveness and whether these factors are barriers to accessing evidence-based treatments.

Objectives: The main objectives of the current paper were to examine the feasibility, acceptability, and adherence of a remotely delivered intervention consisting of mindfulness-based stress reduction plus prenatal sleep classes (MBSR+PS) compared with treatment as usual (TAU).

Method: In this pilot randomized controlled trial, 52 pregnant women with poor sleep quality were randomized to MBSR+PS or TAU. MBSR was delivered through eight weekly 2.5-hour sessions, and PS was delivered through eight weekly 30-minute sessions. PS content drew material from cognitive behavioral therapy for insomnia tailored for the perinatal period and from a mindfulness- and acceptance-based lens. Participants completed endpoint measures 10-12 weeks after randomization.

Results: We surpassed all acceptability targets, including the percentage of eligible participants willing to be randomized (96%), percentage of participants who initiated treatment (88%), and satisfaction scores (Client Satisfaction Questionnaire-8 score M = 28.04, SD = 3.6). We surpassed all feasibility targets, including our enrollment target, retention rate (92%), and measure completion (96%). Finally, we surpassed adherence targets, including MBSR and PS session attendance (≥80%). Though sleep outcomes were exploratory, increases in sleep efficiency were greater in the MBSR+PS group relative to TAU (SMD=.68).

Conclusions: Patient-reported poor sleep quality during pregnancy has high public health significance because it is common, consequential, and under-treated. The current feasibility and acceptability data for using remotely delivered MBSR and PS to improve prenatal sleep quality are encouraging and warranting future research that is sufficiently powered and designed to provide efficacy data. In addition, exploratory sleep outcomes offer preliminary evidence that this sleep program may improve sleep efficiency during pregnancy.

Objectives: This study examined the associations among maternal sleep quality, executive function, and perceptions of infant sleep in a sample of families recruited from human service and public health systems.

Methods: Seventy-three mothers of infants 5-14 months old were included in the study. Mothers racially and ethnically identified as American Indian/Alaskan Native (4.1%), Asian (4.1%), Black/African American (12.3%), Latina (23.3%), more than one race (12.3%), Pacific Islander (1.4%), and White (42.5%). Mothers completed questionnaires assessing their own sleep (Pittsburgh Sleep Quality Index) and executive function (Behavior Rating Inventory of Executive Function) as well as their perceptions about their infant's sleep (Brief Infant Sleep Questionnaire).

Results: Results of the path analysis indicated significant direct effects among maternal sleep quality, executive function, and perceptions of infant sleep. Significant indirect effects were found such that poor maternal sleep quality was linked to poorer perceptions of infant sleep through maternal executive dysfunction, adjusting for infant sleep patterns, infant age, and maternal race and ethnicity.

Conclusions: The current study highlights the potential role of maternal behavioral and cognitive factors in shaping mothers' perceptions about infant sleep. These findings support the need for health professionals and researchers to consider maternal sleep quality and executive function when addressing mothers' concerns about infant sleep.

Study objectives: To construct and evaluate the inter-rater reliability of the Structured Clinical Interview for DSM-5-TR Sleep Disorders - Kid (SCISD-Kid).

Method: The SCISD-Kid was modeled on the adult SCISD-R and accounted for pediatric developmental and sociocultural factors. Fifty sleep-disturbed children (M_age = 11.9, SD = 2.9) and 50 caregivers responded to the final SCISD-Kid. Video recordings were double-scored to evaluate inter-rater reliability.

Results: The final SCISD-Kid contained approximately 90 questions. Eight of the nine covered disorders had prevalence rates sufficient for analyses for both samples (i.e., k > 2). Inter-rater reliability was examined using Cohen kappa coefficients (κ); reliability estimates ranged from excellent to good. For youth, restless legs syndrome yielded the lowest reliability (.48), while nightmare disorder, narcolepsy, and NREM sleep arousal disorder - sleepwalking type showed the highest reliability (1.00). Across caregivers, NREM sleep arousal disorder - sleep terror type (.49) and hypersomnolence (.54) had the lowest reliability. In contrast, circadian rhythm - delayed sleep phase type, nightmare disorder, and NREM sleep arousal disorder - sleepwalking type showed the highest reliability (1.00).

Conclusions: The SCISD-Kid is a promising tool for screening sleep disorders. It showed good to excellent reliability across both samples. Next steps for validation will be discussed.