Preventing postpartum insomnia: findings from a three-arm randomised controlled trial of Cognitive Behavioural Therapy for Insomnia, a responsive bassinet, and sleep hygiene.

STUDY OBJECTIVES: Insomnia symptoms are common during the perinatal period and are linked to adverse outcomes. This single-blind 3-arm randomised controlled trial examined whether two interventions targeting different mechanisms prevent postpartum insomnia. METHODS: Participants were nulliparous females 26-32 weeks gestation with Insomnia Severity Index (ISI) scores≥8, recruited in Australia and randomised 1:1:1 to: (a) a responsive bassinet designed to support infant sleep and reduce maternal sleep disruption until 6 months postpartum (RB), (b) therapist-assisted cognitive behavioural therapy for insomnia (CBT-I) delivered during pregnancy and postpartum, or (c) a sleep hygiene booklet (control; CTRL). Outcomes were assessed at baseline (T1), 35-36 weeks gestation (T2), and 2, 6, and 12 months postpartum (T3-T5). The primary outcome was ISI scores averaged T3-T5. Primary analyses were regressions controlling for baseline outcomes. RESULTS: 127 participants (age M±SD=32.62±3.49) were randomised (RB=44, CBT-I=42, CTRL= 41). Both interventions were feasible and well-accepted, with few related adverse events reported. Compared to CTRL, the average ISI across T3-T5 was lower for CBT-I (p=.014, effect size [ES]=0.56, medium) but not RB (p=.270, ES=0.25, small). Exploratory findings on maternal insomnia diagnosis, sleep disturbance, sleep-related impairment, beliefs and attitudes about sleep, depression, anxiety, as well as infant sleep outcomes were also presented. CONCLUSIONS: CBT-I but not RB reduced prenatal insomnia (very large effect) and prevented postpartum insomnia (medium effect). Further research is needed to examine the effects of both CBT-I and RB on other outcomes such as sleep-related wellbeing, postpartum depression, and maternal postpartum sleep duration.

Cognitive behavioural therapy for insomnia reduces actigraphy and diary measured sleep discrepancy for individuals with comorbid insomnia and major depressive disorder: A report from the TRIAD study.

OBJECTIVE/BACKGROUND: Discrepancies between sleep diaries and actigraphy occur among individuals with insomnia. Cognitive behavioural therapy for insomnia (CBT-I) improves insomnia but the impact on discrepancy is unclear. This study examined CBT-I's effects on actigraphy-diary discrepancy and explored sleep-related beliefs and attitudes as a mediator. PATIENTS/METHODS: Participants were 108 (age M±SD = 47.23 ± 12.42, 67.60 % female) adults with insomnia and major depressive disorder from the Treatment of Insomnia and Depression study. They were randomized to 7 sessions of CBT-I or sham Quasi-Desensitization Therapy for Insomnia (DTI), plus 16 weeks of antidepressants. Two weeks of actigraphy and sleep diary were collected at baseline, mid-treatment, end-treatment. Differences between sleep diary and actigraphy total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE) were calculated. Participants completed Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS) at baseline and mid-treatment. RESULTS: At baseline, diary (versus actigraphy) TST was shorter (1.1 ± 1.41h), whilst SOL (21.64 ± 41.25min) and WASO (17.45 ± 61.99min) were longer. Mixed effects models using daily data showed that after adjusting for age and sex, participants in the CBT-I group (versus DTI) showed greater reduction in all actigraphy-diary discrepancy domains (all p-values<.01), reductions evident from mid-treatment. Group differences on actigraphy-diary discrepancy reductions in TST, SOL, and SE (not WASO) were mediated by changes in DBAS from baseline to mid-treatment (all p-values<.05). Changes in discrepancy did not mediate insomnia symptom changes (p-values>.39). CONCLUSIONS: CBT-I reduced actigraphy-diary discrepancy in individuals with comorbid insomnia and depression; this reduction was associated with improved sleep-related attitudes, a therapeutic target of CBT-I. CLINICAL TRIAL REGISTRATION: TRIAD (Treatment of Insomnia and Depression): Improving Depression Outcome by Adding Insomnia Therapy to Antidepressants. Prospectively registered with Clinical Trials (NCT00767624). SUPPORT (IF ANY): MH078924, MH078961, MH079256.

Does providing feedback and guidance on sleep perceptions using sleep wearables improve insomnia? Findings from "Novel Insomnia Treatment Experiment": a randomized controlled trial.

STUDY OBJECTIVES: Insomnia is a disorder diagnosed based on self-reported sleep complaints. Differences between self-reported and sensor-based sleep parameters (sleep-wake state discrepancy) are common but not well-understood in individuals with insomnia. This two-arm, parallel-group, single-blind, superiority randomized-controlled trial examined whether monitoring sleep using wearable devices and providing support for interpretation of sensor-based sleep data improved insomnia symptoms or impacted sleep-wake state discrepancy. METHODS: A total of 113 (age M = 47.53; SD = 14.37, 64.9% female) individuals with significant insomnia symptoms (Insomnia Severity Index(ISI) ≥10) from the community were randomized 1:1 (permuted block randomization) to receive 5 weeks (1) Intervention (n = 57): feedback about sensor-based sleep (Fitbit and EEG headband) with guidance for data interpretation and ongoing monitoring, and (2) Control (n = 56): sleep education and hygiene. Both groups received one individual session and two check-in calls. The ISI (primary outcome), sleep disturbance (SDis), sleep-related impairment (SRI), depression, and anxiety were assessed at baseline and post-intervention. RESULTS: In total, 103 (91.2%) participants completed the study. Intention-to-treat multiple regression with multiple imputations showed that after controlling for baseline values, compared to the Control group (n = 51), the Intervention group (n = 52) had lower ISI (p = .011, d = 0.51) and SDis (p = .036, d = 0.42) post-intervention, but differences in SRI, depression, anxiety, and sleep-wake state discrepancy parameters (total sleep time, sleep onset latency, and wake after sleep onset) were not meaningful (P-values >.40). CONCLUSIONS: Providing feedback and guidance about sensor-based sleep parameters reduced insomnia severity and sleep disturbance but did not alter sleep-wake state discrepancy in individuals with insomnia more than sleep hygiene and education. The role of sleep wearable devices among individuals with insomnia requires further research. CLINICAL TRIAL REGISTRATION: The Novel Insomnia Treatment Experiment (NITE): the effectiveness of incorporating appropriate guidance for sleep wearables in users with insomnia. https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378452, Australia New Zealand Clinical Trials Registry: ACTRN12619001636145.

Does changing perceptions of sleep by incorporating sleep wearables improve insomnia? Protocol for a randomized study (the Novel Insomnia Treatment Experiment).

Study Objectives: Insomnia is common in the general population and is diagnosed based on self-reported sleep complaints. There is a frequent discrepancy between objectively recorded and self-reported sleep (sleep-wake state discrepancy), especially in individuals with insomnia. Although sleep-wake state discrepancy is well-documented in the literature, it is not well understood. This protocol describes the methodology of a randomized control study, which will examine whether providing monitoring and feedback about objectively recorded sleep with support for interpretation of sleep-wake state discrepancy improves insomnia symptoms and will explore the potential mechanisms of change. Methods: Participants are 90 individuals with insomnia symptoms (Insomnia Severity Index [ISI] ≥10). Participants will be randomized to one of two conditions: (1) Intervention: feedback about objectively recorded sleep (actigraph and optional electroencephalogram headband) with guidance for data interpretation, (2) Control: sleep hygiene session. Both conditions will involve individual sessions and two check-in calls. The primary outcome is ISI score. Secondary outcomes include sleep-related impairment, symptoms of anxiety and depression, and other sleep and quality of life measures. Outcomes will be assessed using validated instruments at baseline and post-intervention. Discussion: With increasing number of wearable devices that measure sleep, there is a need to understand how sleep data provided by these devices could be utilized in the treatment of insomnia. Findings from this study have the potential to better understand sleep-wake state discrepancy in insomnia and uncover new approaches to supplement current insomnia treatment.

A pre-drive ocular assessment predicts alertness and driving impairment: A naturalistic driving study in shift workers.

Sleepiness is a major contributor to motor vehicle crashes and shift workers are particularly vulnerable. There is currently no validated objective field-based measure of sleep-related impairment prior to driving. Ocular parameters are promising markers of continuous driver alertness in laboratory and track studies, however their ability to determine fitness-to-drive in naturalistic driving is unknown. This study assessed the efficacy of a pre-drive ocular assessment for predicting sleep-related impairment in naturalistic driving, in rotating shift workers. Fifteen healthcare workers drove an instrumented vehicle for 2 weeks, while working a combination of day, evening and night shifts. The vehicle monitored lane departures and behavioural microsleeps (blinks >500 ms) during the drive. Immediately prior to driving, ocular parameters were assessed with a 4-min test. Lane departures and behavioural microsleeps occurred on 17.5 % and 10 % of drives that had pre-drive assessments, respectively. Pre-drive blink duration significantly predicted behavioural microsleeps and showed promise for predicting lane departures (AUC = 0.79 and 0.74). Pre-drive percentage of time with eyes closed had high accuracy for predicting lane departures and behavioural microsleeps (AUC = 0.73 and 0.96), although was not statistically significant. Pre-drive psychomotor vigilance task variables were not statistically significant predictors of lane departures. Self-reported sleep-related and hazardous driving events were significantly predicted by mean blink duration (AUC = 0.65 and 0.69). Measurement of ocular parameters pre-drive predict drowsy driving during naturalistic driving, demonstrating potential for fitness-to-drive assessment in operational environments.