DSM-5 insomnia disorder in pregnancy: associations with depression, suicidal ideation, and cognitive and somatic arousal, and identifying clinical cutoffs for detection

STUDY OBJECTIVES: The study had three primary goals. First, we estimated survey-assessed DSM-5 insomnia disorder rates in pregnancy, and described associated sociodemographics, and sleep-wake and mental health symptoms. Second, we derived cutoffs for detecting DSM-5 insomnia disorder using common self-report measures of sleep symptoms. Third, we identified clinically relevant cut-points on measures of nocturnal cognitive and somatic arousal. METHODS: Ninety-nine women (85.9% in the 2nd trimester) completed online surveys including DSM-5 insomnia disorder criteria, the Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), Presleep Arousal Scale’s Cognitive (PSASC) and Somatic (PSASS) factors, and Edinburgh Postnatal Depression Scale. RESULTS: DSM-5 insomnia disorder rate was 19.2%. Insomnia was associated with depression, suicidality, nocturnal cognitive and somatic arousal, and daytime sleepiness. An ISI scoring method that aligns with DSM-5 criteria yielded excellent metrics for detecting insomnia disorder and good sleep. Regarding quantitative cutoffs, ISI ≥ 10 and ISI ≥ 11 (but not ISI ≥ 15) were supported for detecting DSM-5 insomnia, whereas ISI ≤ 7 and ISI ≤ 9 performed well for detecting good sleep. PSQI cutoff of 5 was supported for detecting insomnia and good sleep. The optimal cutoff for nocturnal cognitive arousal was PSASC ≥ 18, whereas the optimal cutoff for somatic arousal was PSASS ≥ 13. CONCLUSIONS: Insomnia disorder affects a large segment of pregnant women. Empirically derived cutoffs for insomnia, good sleep, cognitive arousal, and somatic arousal may inform case identification and future perinatal sleep research methodology

Risk-taking and circadian misalignment in night shift workers

Introduction: Circadian misalignment is of particular concern for shift workers as it impacts cognitive performance, such as decision making and risk-taking. Research in non-shift workers have demonstrated that sleep loss can lead to increased appetitive and risk-taking behaviors; however, fewer studies have examined this in night shift workers despite the high prevalence of excessive sleepiness and sleep disruption. This study examined the relationship between risk-taking behavior and circadian misalignment in a sample of permanent night shift workers. Methods: Thirty permanent night shift workers participated in a larger study examining the health consequences of circadian misalignment. Circadian phase was evaluated using dim-light salivary melatonin onset (DLMO). Risk-taking behavior was evaluated using a computerized Stop-Light paradigm, which was completed at 7am. This paradigm mimics the context of a traffc light, where a go/no-go decision must be made at onset of the yellow light. Successful go trials were rewarded with 25 points, and a percentage of unsuccessful trials were punished with loss of 25 points. Results: Results revealed that workers with greater circadian misalignment earned less total points (r=.46, p\u3c.05). While participants were more conservative on higher risk trials, this effect was not moderated by degree of circadian misalignment. However, risk-taking behavior did decrease with sleepiness prior to the task (r=-.51, p\u3c.01), perhaps due to increased risk aversion or decreased appetitive drive. Finally, workers with better circadian alignment achieved higher success rates on go trials (r=.42, p\u3c.05), suggesting that circadian alignment is associated with improved ability for decision making in the context of risk. Discussion: Results indicate that greater circadian alignment in shift work may be associated with improved performance in decisions involving risk. This offers further insight into the cognitive vulnerabilities related to circadian misalignment that may impact risk for errors, accidents, and injuries in night shift workers

Predicting circadian phase in night shift workers using actigraphy

Introduction: A major barrier in addressing circadian misalignment in shift work disorder is the lack of feasibility in measuring circadian phase in the clinic, particularly because obtaining dim light melatonin onset (DLMO) is resource intensive. One promising solution is to predict DLMO based on actigraphy (light and movement) using mathematical models; however, these models have only been tested in adults with relatively small variations in daily light-dark schedules, especially compared to night shift workers. This study tested the feasibility of actigraphy in predicting DLMO in a sample of fxed-night shift workers. Methods: A sample of 30 fxed-night shift workers wore wrist actigraphy for 7 to 14 days (mean = 9, SD = 3.4) before completing DLMO in the lab. DLMO was assessed via hourly salivary melatonin samples collected in dim light (\u3c 10 lux) for a period of 24 hours. Light information (i.e., timing and duration) augmented with actigraphy recordings was used in a Kronauer model of the circadian clock to produce a predicted DLMO, which was then compared to in-lab DLMO. Results: Model predictions of DLMO showed high correlation with in-lab DLMO, with an R2 of 0.83. The 95% CI of the model predictions was ± 1.71 hours, which is comparable to studies using non-shift workers in the general population. Follow-up analyses extended the model by including PERIOD3 genotype (variable number tandem repeat) as a proxy for circadian period (tau), which raised the R2 to 0.86. Conclusion: This study is the frst to provide evidence suggesting that actigraphy may be a feasible alternative to in-lab measurement of circadian phase in night shift workers. Future research should explore how inclusion of addition predictors (e.g., biological measurement of tau) may increase accuracy, and further refne the necessary parameters for accurate prediction of circadian phase, such as duration of actigraphy collection

Using mathematical modeling to predict circadian phase in night shift workers

Introduction: A major barrier in addressing circadian misalignment in shift work disorder is the lack of feasibility in measuring circadian phase in the clinic, particularly because obtaining dim light melatonin onset (DLMO) is resource intensive. One promising solution is to use mathematical models to predict DLMO based on actigraphy (light and movement); however, these models have only been tested in adults with relatively small variations in daily light-dark schedules, especially compared to night shift workers. This study tested the feasibility of actigraphy in predicting DLMO in a sample of fixed-night shift workers. Methods: A sample of 10 fixed-night shift workers wore wrist actigraphy for 7 to 14 days (mean = 9, SD = 3.4) before completing DLMO in the lab. DLMO was assessed via hourly salivary melatonin samples collected in dim light (\u3c 10 lux) for a period of 24 hours. Light information (i.e., timing and duration) augmented with actigraphy recordings was used in a Kronauer model of the circadian clock to produce a predicted DLMO, which was then compared to in-lab DLMO. Results: Model predictions of DLMO showed high correlation with in-lab DLMO, with an R2 of 0.83. The 95% CI of the model predictions was ± 1.71 hours, which is comparable to studies using non-shift workers in the general population. Follow-up analyses extended the model by including PERIOD3 genotype (variable number tandem repeat) as a proxy for circadian period (tau), which raised the R2 to 0.86. Conclusion: This study is the first to provide evidence suggesting that actigraphy may be a feasible alternative to in-lab measurement of circadian phase in night shift workers. Future research should explore how inclusion of addition predictors (e.g., biological measurement of tau) may increase accuracy, and further refine the necessary parameters for accurate prediction of circadian phase, such as duration of actigraphy collection

Self-efficacy in Insomnia Symptom Management after Digital CBT-I Mediates Insomnia Severity during the COVID-19 Pandemic

STUDY OBJECTIVES: Digital cognitive behavioral therapy for insomnia (dCBT-I) can reduce acute insomnia and depressive symptoms and prevent symptom recurrence. The current study evaluated self-efficacy in managing insomnia symptoms as a potential mediator of the relationship between prior dCBT-I and subsequent insomnia and depressive symptoms assessed during the coronavirus 2019 (COVID-19) pandemic. METHOD: Participants were 208 adults who completed a randomized controlled trial of dCBT-I versus sleep education in 2016-2017 and also completed self-report assessments of insomnia, depression, and self-efficacy in managing insomnia symptoms. Data were collected in May 2020, five weeks into state-wide COVID-19 stay-at-home orders. Regression and mediation analyses were used to evaluate the extent to which self-efficacy accounted for the relationship between treatment condition and improvement in insomnia and depressive symptoms from pre-treatment to COVID-19 follow-up. RESULTS: Prior dCBT-I predicted greater self-efficacy in managing insomnia symptoms. Self-efficacy accounted for 49% and 67% of the protective effect of dCBT-I against COVID-era insomnia and depressive symptoms, respectively. CONCLUSIONS: This study affirms the importance of self-efficacy as a key intervention outcome and potential mechanism by which dCBT-I predicts future sleep and mental health. Future studies that evaluate the role of self-efficacy in treatment effectiveness and resilience can provide additional clues about how to optimize dCBT-I for maximum benefit to public health

Changes in use of sleep aids following digital cognitive behavioral therapy for insomnia

Introduction: Cognitive behavioral therapy for insomnia is now recommended as first-line treatment for chronic insomnia, and can be delivered digitally (dCBT-I) for increased access. Furthermore, dCBT-I confers an advantage of reduced adverse events relative to pharmacologic interventions (e.g., hypnotics and other sleep aids). This study examined if treatment with dCBT-I can also reduce use of sleep aids compared to an online sleep education control. Methods: 1232 individuals with insomnia (DSM-5 diagnostic criteria) were randomized into two conditions: dCBT-I (N=639), or an online sleep education control (N=593). Use of medications for sleep (prescription and non-prescription) were assessed pre-treatment and post-treatment. Responses were categorized into general classes of medications (i.e. benzodiazepine, hypnotic, antihistamine, etc.), and compared across time points between the two conditions. Results: Results from a repeated-measures mixed-effects logistic regression indicated that the odds of prescription medication was significantly lower following dCBT-I compared to control (OR=0.09, 95%CI[0.02, 0.34]). Specifically, whereas prescription medication use in the control group increased from 16.5% to 18.0% at post-treatment, prescription medication use in the dCBT-I group decreased from 17.8% to 14.6%. Change in prescription medication use was more pronounced for antidepressants, followed by hypnotics. No differences were found in use of non-prescription medications. Conclusion: This study provides preliminary evidence that use of prescription sleep aids may decrease following completion of dCBT-I. Together, this suggests that a minimally resource intensive intervention may have a small effect in reducing reliance on prescription sleep aids

Examining Patient Feedback and the Role of Cognitive Arousal in Treatment Non-response to Digital Cognitive-behavioral Therapy for Insomnia during Pregnancy

Objective: Insomnia affects over half of pregnant and postpartum women. Early evidence indicates that cognitive-behavioral therapy for insomnia (CBTI) improves maternal sleep and mood. However, standard CBTI may be less efficacious in perinatal women than the broader insomnia population. This study sought to identify patient characteristics in a perinatal sample associated with poor response to CBTI, and characterize patient feedback to identify areas of insomnia therapy to tailor for the perinatal experience. Participants: Secondary analysis of 46 pregnant women with insomnia symptoms who were treated with digital CBTI in a randomized controlled trial. Methods: We assessed insomnia, cognitive arousal, and depression before and after prenatal treatment, then 6 weeks postpartum. Patients provided feedback on digital CBTI. Results: Residual cognitive arousal after treatment was the most robust factor associated with treatment non-response. Critically, CBTI responders and non-responders differed on no other sociodemographic or pretreatment metrics. After childbirth, short sleep (\u3c6 hrs/night) was associated with maternal reports of poor infant sleep quality. Patient feedback indicated that most patients preferred online treatment to in-person treatment. Although women described digital CBTI as convenient and helpful, many patients indicated that insomnia therapy would be improved if it addressed sleep challenges unique to pregnancy and postpartum. Patients requested education on maternal and infant sleep, flexibility in behavioral sleep strategies, and guidance to manage infant sleep. Conclusions: Modifying insomnia therapy to better alleviate refractory cognitive arousal and address the changing needs of women as they progress through pregnancy and early parenting may increase efficacy for perinatal insomnia. Name: Insomnia and Rumination in Late Pregnancy and the Risk for Postpartum Depression URL: clinicaltrials.gov Registration: NCT03596879

Digital Cognitive Behavioral Therapy for Insomnia Promotes Later Health Resilience During the Coronavirus Disease 19 (COVID-19) Pandemic

STUDY OBJECTIVES: Stressful life events contribute to insomnia, psychosocial functioning, and illness. Though individuals with a history of insomnia may be especially vulnerable during stressful life events, risk may be mitigated by prior intervention. This study evaluated the effect of prior digital cognitive-behavioral therapy for insomnia (dCBT-I) versus sleep education on health resilience during the COVID-19 pandemic. METHODS: COVID impact, insomnia, general- and COVID-related stress, depression, and global health were assessed in April 2020 in adults with a history of insomnia who completed a randomized controlled trial of dCBT-I (n = 102) versus sleep education control (n = 106) in 2016-2017. Regression analyses were used to evaluate the effect of intervention conditions on subsequent stress and health during the pandemic. RESULTS: Insomnia symptoms were significantly associated with COVID-19 related disruptions, and those previously received dCBT-I reported less insomnia symptoms, less general stress and COVID-related cognitive intrusions, less depression, and better global health than those who received sleep education. Moreover, the odds for resurgent insomnia was 51% lower in the dCBT-I versus control condition. Similarly, odds of moderate to severe depression during COVID-19 was 57% lower in the dCBT-I condition. CONCLUSIONS: Those who received dCBT-I had increased health resilience during the COVID-19 pandemic in adults with a history of insomnia and ongoing mild to moderate mental health symptoms. These data provide evidence that dCBT-I is a powerful tool to promote mental and physical health during stressors, including the COVID-19 pandemic

Improved resilience following digital cognitive behavioral therapy for insomnia protects against insomnia and depression one year later

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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

Risk of excessive sleepiness in sleep restriction therapy and cognitive behavioral therapy for insomnia: a randomized controlled trial.

STUDY OBJECTIVES: Sleep restriction therapy (SRT) has been shown to be comparably effective relative to cognitive behavioral therapy for insomnia (CBT-I), but with lower requirements for patient contact. As such, SRT appears to be a viable alternate treatment for those who cannot complete a full course of CBT-I. However, it is unclear whether SRT-a treatment solely focusing on restricting time in bed-increases risk for sleepiness comparably to CBT-I. The current study tested objective sleepiness as an outcome in a randomized controlled trial comparing SRT, CBT-I, and attention control in a sample of postmenopausal women in whom insomnia was diagnosed according to criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. METHODS: Single-site, randomized controlled trial. A total of 150 postmenopausal women (56.44 ± 5.64 years) with perimenopausal or postmenopausal onset of Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition insomnia disorder were randomized to 3 treatment conditions: sleep education control (6 sessions); SRT (2 sessions with interim phone contact); and CBT-I (6 sessions). Blinded assessments were performed at pretreatment and posttreatment. Risk of excessive sleepiness was evaluated using a symmetry analysis of sleepiness measured through the Multiple Sleep Latency Test (MSLT). RESULTS: The odds ratios (ORs) of being excessively sleepy versus nonsleepy were not different than 1.0 for both SRT (OR = 0.94, 95% confidence interval [0.13-6.96]) and CBT-I (OR = 0.62, 95% confidence interval [0.09-4.46]), indicating that the odds of becoming excessively sleepy following treatment was not different from the odds of being nonsleepy. This suggests that excessive sleepiness is not of unique concern following SRT relative to CBT-I or sleep education. CONCLUSIONS: SRT appears to have a comparable risk profile for excessive sleepiness as CBT-I, and thus may be considered a safe alternative to CBT-I. Future research should characterize objective measures of excessive sleepiness immediately following sleep restriction. CLINICAL TRAIL REGISTRATION: Registry: ClinicalTrials.gov; Name: Behavioral Treatment of Menopausal Insomnia; Sleep and Daytime Outcomes; Identifier: NCT01933295