Behavioral Sleep Medicine最新文献

Objectives: Sleep disorder is a growing public health concern that requires attentive assessment and treatment. However, the length of assessment tools for sleep disorders, including insomnia, hinders their use in both research and clinical settings. Brief assessment measures expedite assessment time, reducing respondent burden, and save resources, especially in resource-limited settings.

Methods: This study investigated the validity and reliability of a short three-item insomnia scale, the Insomnia Severity Index-3 (ISI-3) and established two cutoff scores in a sample of 238 healthcare providers in Oman (45.8% physicians and 54.2% nurses).

Results: The ISI-3 demonstrated good convergent and divergent validity. The receiver operator characteristic recommended two cutoff scores of > 4 (a sensitivity of 0.87.3 and a specificity of 0.96.4) and > 6 (a sensitivity of 0.96.9 and a specificity of 0.97.1).

Conclusions: The ISI-3 is a good assessment index of insomnia, especially when the utilization of the full insomnia index is unfeasible.

Objectives: In this meta-regression, we aimed to explore associations between changes in psychosocial factors and changes in sleep disturbance during mindfulness-based interventions (MBIs). We also investigated participant-specific and methodological factors associated with sleep disturbance during MBIs.

Method: We utilized data from a published meta-analysis of 40 randomized controlled trials of MBIs (published from inception to 2020) with a sleep disturbance outcome measure in healthy and clinical adult populations. We conducted meta-regressions to test associations between sleep improvements following MBIs and psychosocial factors, as well as demographic and methodological factors.

Results: MBIs were associated with significant reductions in sleep disturbance (SMD = -0.523; 95% CI = -0.678 to -0.368) and psychosocial factors (SMD = -0.213 - -0.894). Reductions in sleep disturbance were associated with reductions in stress (r = 0.74, p = .02) and depression (r = 0.90, p < .001).

Conclusions: MBIs improve sleep disturbance across a wide range of healthy and clinical populations. Stress and depression may be important psychosocial factors associated with sleep disturbance. Future RCTs should include measures of additional factors and should investigate longitudinal associations between psychosocial, demographic, and methodological factors with changes in sleep disturbance to test mechanisms and to identify "active ingredients" of MBIs.

Objectives: Sleep and internalizing problems escalate during adolescence and can negatively impact long-term health. However, the directionality of this risk-relationship remains poorly understood within a developmental context. The current study aimed to determine the directionality of this relationship in adolescents with no history of psychiatric disorder and whether sex at birth played a role in this relationship.

Methods: We used data from the Adolescent Brain Cognitive Development, an ongoing multisite longitudinal US study, that covered four waves (W1:9-11 years; W2:10-12 years; W3:11-13 years; W4:12-14 years). Analyses included 3,128 youth (50.99%girls) with no past or current psychiatric disorders at W1. The Sleep Disturbance Scale for Children and the Child Behavior Checklist were used to measure sleep and internalizing problems. Cross-lagged panel models were used to evaluate the cross-lagged relationships across waves.

Results: The sleep-internalizing cross-lagged relationship was unidirectional, with medium-large effect sizes: greater total sleep problems were associated with more severe internalizing problems at later waves (W2➔W3, coefficient = 0.052, p = .021; W3➔W4, coefficient = 0.091, p < .001), with problems in initiating and maintaining sleep predicting internalizing problems early on. Girls showed greater sleep-internalizing risk than boys.

Conclusions: Sleep-internalizing relationships change across adolescence, becoming significant and more specific from early to mid-adolescence. Sleep interventions delivered in early adolescence, to girls in particular, may have a positive short and long-term impact on internalizing outcomes.

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.