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While the negative consequences of insomnia are well-documented, a strengths-based understanding of how sleep can increase health promotion is still emerging and much-needed. Correlational evidence has connected sleep and insomnia to resilience; however, this relationship has not yet been experimentally tested. This study examined resilience as a mediator of treatment outcomes in a randomized clinical trial with insomnia patients.
Participants were randomized to either digital cognitive behavioral therapy for insomnia (dCBT-I; n = 358) or sleep education control (n = 300), and assessed at pre-treatment, post-treatment, and 1-year follow-up. A structural equation modeling framework was utilized to test resilience as a mediator of insomnia and depression. Risk for insomnia and depression was also tested in the model, operationalized as a latent factor with sleep reactivity, stress, and rumination as indicators (aligned with the 3-P model). Sensitivity analyses tested the impact of change in resilience on the insomnia relapse and incident depression at 1-year follow-up.
dCBT-I resulted in greater improvements in resilience compared to the sleep education control. Furthermore, improved resilience following dCBT-I lowered latent risk, which was further associated with reduced insomnia and depression at 1-year follow-up. Sensitivity analyses indicated that each point improvement in resilience following treatment reduced the odds of insomnia relapse and incident depression 1 year later by 76% and 65%, respectively.
Improved resilience is likely a contributing mechanism to treatment gains following insomnia therapy, which may then reduce longer-term risk for insomnia relapse and depression.
Insomnia and depression are highly comorbid and mutually exacerbate clinical trajectories and outcomes. Cognitive behavioral therapy for insomnia (CBT-I) effectively reduces both insomnia and depression severity, and can be delivered digitally. This could substantially increase the accessibility to CBT-I, which could reduce the health disparities related to insomnia; however, the efficacy of digital CBT-I (dCBT-I) across a range of demographic groups has not yet been adequately examined. This randomized placebo-controlled trial examined the efficacy of dCBT-I in reducing both insomnia and depression across a wide range of demographic groups.
Of 1358 individuals with insomnia randomized, a final sample of 358 were retained in the dCBT-I condition and 300 in the online sleep education condition. Severity of insomnia and depression was examined as a dependent variable. Race, socioeconomic status (SES; household income and education), gender, and age were also tested as independent moderators of treatment effects.
The dCBT-I condition yielded greater reductions in both insomnia and depression severity than sleep education, with significantly higher rates of remission following treatment. Demographic variables (i.e. income, race, sex, age, education) were not significant moderators of the treatment effects, suggesting that dCBT-I is comparably efficacious across a wide range of demographic groups. Furthermore, while differences in attrition were found based on SES, attrition did not differ between white and black participants.
Results provide evidence that the wide dissemination of dCBT-I may effectively target both insomnia and comorbid depression across a wide spectrum of the population.
This chapter reviews the psychometric properties, validation, and strengths and weaknesses of the most common measurement tools used for the subjective evaluation of sleepiness. Subjective measures of sleepiness described in the chapter include visual analogue scales (VAS), Stanford sleepiness scale (SSS), Karolinska sleepiness scale (KSS), Epworth sleepiness scale (ESS) pediatric sleep questionnaire, sleepiness subscale (PSQ-SS) and pediatric daytime sleepiness scale (PDSS). Children present with a variety of sleep disorders associated with excessive sleepiness. Subjective sleepiness is critical as it is often the initial symptom of underlying sleep pathology, and a major presenting complaint that clinicians must understand and address. More work is needed on potential cultural and racial differences in subjective sleepiness and in relation to specific types of measurement. It has been shown that subjective sleepiness is accompanied by EEG changes including selective slowing of specific frequency bands.
The present study assessed alertness, memory, and performance
following three schedules of ∼8 hr of sleep loss (slow,
intermediate, and rapid accumulation) in comparison to an 8-hr
time in bed (TIB) sleep schedule. Twelve healthy individuals
aged 21–35 completed each of four conditions according
to a Latin Square design: no sleep loss (8-hr TIB for 4 nights;
2300–0700), slow (6-hr TIB for 4 nights; 0100–0700),
intermediate (4-hr TIB for 2 nights; 0300–0700), and rapid
(0-hr TIB for 1 night) sleep loss. On each day, participants
completed a multiple sleep latency test (MSLT), a probed-recall
memory task, a psychomotor vigilance task, a divided attention
task, and the Profile of Mood States. “Rapid” sleep
loss produced significantly more impairment on tests of alertness,
memory, and performance compared to the “slow”
accumulation of a comparable amount of sleep loss. The impairing
effects of sleep loss vary as a function of rate, suggesting
the presence of a compensatory adaptive mechanism operating
in conjunction with the accumulation of a sleep debt.
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