Sex differences in response to cognitive behavioural therapy for insomnia: A chart review of 455 patients with chronic insomnia.

BACKGROUND: Insomnia is more prevalent in females, however studies examining sex differences in response to insomnia treatment are scarce. This study assessed sex-specific differences in cognitive behavioural therapy for insomnia (CBT-I)-related changes in insomnia symptoms in a large clinical cohort. METHODS: A chart review was conducted of a clinical cohort (females n = 305, males n = 150) referred to a sleep clinic. Participants had a registered psychologist confirm diagnosis of chronic insomnia according to DSM-IV/V criteria and a Level 1 or 2 sleep study. Daily sleep diaries and questionnaires including the Insomnia Severity Index (ISI), Flinders Fatigue Scale (FFS), the Daytime Feelings and Functioning Scale (DFFS), and the Depression, Anxiety and Stress Scale-21 items (DASS), were administered at baseline, post-treatment, and three-month follow-up. Linear mixed models determined interactions between sex and timepoint on symptoms. RESULTS: Mean (SD) age was 51.7 yrs (15.7, range = 18-90 yrs), and mean BMI was 26.3 kg/m2 (4.9), neither of which differed by sex. At pre-treatment, females demonstrated higher objective total sleep time (min) [343.5 (97.6) vs 323.8 min (92.1), p = 0.044], ISI [19.7 (4.2) vs 18.6 (4.4), p = 0.033], and FFS scores [19.2 (6.0) vs 16.9 (7.2), p = 0.003]. Compared to males, females experienced a greater reduction in FFS and DFFS scores and DASS depressive symptoms (p for interaction: 0.017, 0.043, 0.016 respectively) from baseline to follow-up. The greater reduction in depressive symptoms did not persist after controlling for age, BMI, and sleep apnea severity. Subjective total sleep time similarly increased across treatment for both males [baseline: 335.7 (15.1), post: 357.9 (15.5)] and females [baseline: 318.3 (10.4), post: 354.4 (10.7)], p for interaction: 0.22. CONCLUSION: Females and males experience similar, substantial benefits from CBT-I after accounting for comorbidities, suggesting the same treatment can resolve insomnia in both sexes.

The natural history of insomnia: evaluating illness severity from acute to chronic insomnia; is the first the worst?

STUDY OBJECTIVES: The 3P and 4P models represent illness severity over the course of insomnia disorder. The 3P model suggests that illness severity is worst during acute onset. The 4P model suggests that illness severity crescendos with chronicity. The present analysis from an archival dataset assesses illness severity with new onset illness (i.e. from good sleep [GS] to acute insomnia [AI] to chronic insomnia [CI]). Illness severity is quantified in terms of total wake time (TWT). METHODS: GSs (N = 934) were followed up to 1 year with digital sleep diaries, and classified as GS, AI, or CI. Data for CIs were anchored to the first of 14 days with insomnia so that day-to-day TWT was represented prior to and following AI onset. A similar graphic (+/-acute onset) was constructed for number of days per week with insomnia. GS data were temporally matched to CI data. Segmented linear mixed regression models were applied to examine the change in slopes in the AI-to-CI period compared to GS-to-AI period. RESULTS: Twenty-three individuals transitioned to AI and then CI. Average TWT rose during the first 2 weeks of AI onset (b = 1.8, SE = 0.57, p = 0.001) and was then stable for 3 months (b = -0.02, SE = 0.04, p = 0.53). Average number of affected days was stable from AI to CI (b = 0.0005, SE = 0.002, p = 0.81). That is, while there was week-to-week variability in the number of days affected, no linear trend was evident. CONCLUSIONS: In our sample of CIs, primarily with middle insomnia, the average severity and number of affected days were worst with the onset of AI (worst is first) and stable thereafter.

Comparative short-term safety and efficacy of hypnotics: A quantitative risk-benefit analysis.

Several professional societies have provided recommendations for prescribing medications for insomnia. None has provided an integrative analysis that concurrently quantifies safety and efficacy (e.g., risk-benefit ratios). This represents an important gap for informing clinician decision-making. Accordingly, the aim of the present review is to provide such an analysis for five classes of sleep-promoting medications. Adverse event data values were extracted from the most recent FDA-approved package inserts and converted to an integer before being placebo-adjusted and standardized as a rate per 1000 (AEr). Efficacy data, pre-to-post self-reported data for active and placebo conditions were acquired from pivotal trials identified in "white papers" and systematic reviews/meta-analyses. Weighted effect sizes were calculated for subjective sleep latency, wake time after sleep onset and total sleep time, and then were averaged by medication class for each sleep continuity variable. Overall efficacy was represented by a single variable, SWT (sleep latency + wake time after sleep onset + total sleep time). Risk-benefit was represented using a simple ratio value. For safety, it was found that melatonin receptor agonists had the lowest adverse event rate (AEr = 43.1), and non-benzodiazepine benzodiazepine receptor agonists had the highest rate (AEr = 255.0). For efficacy, it was found that the pre-to-post placebo adjusted effect sizes were largest for benzodiazepines (effect size = 1.94) and smallest for melatonin receptor agonists (effect size = 0.109). For risk-benefit, histamine antagonist had the most favourable profile (risk-benefit = 69.5), while melatonin receptor agonist had the least favourable profile (risk-benefit = 395.7). Overall, the combined metric for risk-benefit suggests that treatment with a histamine antagonist is optimal and potentially represents the best first-line therapy for the medical management of insomnia.

The Assessment of Post-COVID Fatigue and Its Relationship to the Severity and Duration of Acute COVID Illness.

Emerging data suggests that COVID-19 is associated with fatigue well beyond the acute illness period. The present analysis aimed to: (1) characterize the prevalence and incidence of high fatigue at baseline and follow-up; (2) examine the impact of COVID-19 diagnosis on fatigue level following acute illness; and (3) examine the impact of acute COVID-19 symptom severity and duration on fatigue at follow-up. Subjects (n = 1417; 81.0% female; 83.3% White; X¯age = 43.6 years) completed the PROMIS-Fatigue during the initial wave of the pandemic at baseline (April-June 2020) and 9-month follow-up (January-March 2021). A generalized linear model (binomial distribution) was used to examine whether COVID-19 positivity, severity, and duration were associated with higher fatigue level at follow-up. Prevalence of high fatigue at baseline was 21.88% and 22.16% at follow-up, with 8.12% new cases at follow-up. Testing positive for COVID-19 was significantly associated with higher fatigue at follow-up. COVID-19 symptom duration and severity were significantly associated with increased fatigue at follow-up. COVID-19 symptom duration and severity during acute illness may precipitate longer-term fatigue, which could have implications for treatment planning and future research. Future studies should further evaluate the relationship between symptom severity, duration, and fatigue.

Baseline sleep characteristics are associated with gains in sleep duration after cognitive behavioral therapy for insomnia.

OBJECTIVE/BACKGROUND: Cognitive behavioural therapy for insomnia (CBT-I) substantially reduces total wake time (TWT) by the end of treatment. In contrast, total sleep time (TST) does not increase above baseline levels for most patients following 4-8 sessions of treatment. In the 6-12 months following CBT-I, without any further intervention, up to 64% of participants substantially increase their TST (by ≥ 30 min). The current study investigated which baseline characteristics are associated with increases in TST after CBT-I. PATIENTS/METHODS: Data were analysed from a randomised controlled trial assessing acute and maintenance CBT-I (N = 80). Linear mixed models were conducted to assess the effect of baseline characteristics on changes in TST up to 24 months after CBT-I. Baseline characteristics included age, sex, marital status, sleep continuity (derived from sleep diaries and polysomnography studies), and mental health and quality of life questionnaires. RESULTS: At baseline, self-reported sleep latency, wake after sleep onset, early morning awakenings, TWT, TST, and sleep efficiency were associated with the greatest changes in TST (p < .03 for interactions), such that patients who reported more wake/less sleep at baseline also reported the largest increases in TST. No other baseline variables were associated with changes in TST after CBT-I, including age, sex, and polysomnography-derived sleep continuity (p > .07 for interactions). CONCLUSIONS: Patients with more severe self-reported sleep difficulties and lower sleep duration at baseline showed greater improvements in TST after CBT-I. Whether more patients could increase their TST, within the context of acute treatment or following treatment, warrants investigation.

Insomnia symptoms predict longer COVID-19 symptom duration.

OBJECTIVE: /Background: The goal of the present study was to assess the prevalence and incidence of insomnia in the United States during the COVID-19 pandemic, and whether, among those that contracted COVID-19, insomnia predicted worse outcomes (e.g., symptoms of greater frequency, duration, or severity). METHODS: A nationwide sample of 2980 adults living in the United States were surveyed online at two points during the COVID-19 pandemic (T1 = April-June 2020; T2 = January-March 2021). Insomnia symptoms were assessed at both time points using the Insomnia Severity Index (ISI). The T2 survey also asked questions regarding COVID-19 testing and symptoms. RESULTS: The prevalence of insomnia (defined as ISI ≥15) was 15% at T1 and 13% at T2. The incidence rate of insomnia (i.e., new cases from T1 to T2) was 5.6%. Participants with insomnia were not more likely to contract COVID-19 relative to those participants without insomnia. Among those participants in our sample that contracted the virus during the study interval (n = 149), there were no significant group differences in COVID-19 symptom outcomes, with one exception, participants with insomnia were more likely to report a longer symptom duration (insomnia = 24.8 sick days, no insomnia = 16.1 sick days). CONCLUSIONS: The present study suggests the prevalence of insomnia in the U.S. population remained high during the COVID-19 pandemic. The data also support that insomnia may be related to experiencing more chronic COVID-19 symptoms. These findings have more general implications for the role of sleep and insomnia on immune functioning.

Do Placebos Primarily Affect Subjective as Opposed to Objective Measures? A Meta-Analysis of Placebo Responses in Insomnia RCTs.

INTRODUCTION: Little is known about the relative magnitude of placebo responses on objective and subjective measures of sleep continuity. To address this issue, the pre-post effects of placebos on objective and subjective measures (i.e., polysomnography [PSG] and sleep diaries) were evaluated meta-analytically. The guiding hypothesis was that large responses would be observed on sleep diary measures and small responses would be observed on PSG measures. METHODS: PubMed searches, 1967-2016, yielded 329 possible articles, 17 of which met the inclusion and exclusion criteria for the present analysis (including 879 subjects with PSG data, 1,209 subjects with diary data, and six studies with both PSG and sleep diary data). Average change and weighted effect sizes (ESs) were computed via modeling for sleep latency (SL), wake after sleep onset (WASO) and total sleep time (TST). RESULTS: Pre-to-post change on PSG measures were: SL -13.7 min., ES = -0.37; WASO -14.3 min., ES = -0.36; and TST 29.8 min., ES = 0.50. Pre-to-post change on sleep diary measures were: SL -13.5 min., ES = -0.36; WASO -13.3 min., ES = -0.20; and TST 25.5 min., ES = 0.36. The modeled average objective subjective difference per sleep continuity measure was less than 5 minutes. The modeled average objective subjective difference per sleep continuity measure (in effect sizes) was less than 0.17. DISCUSSION: The observed outcomes of this analysis suggest that placebos produce comparable effects on objective and subjective measures of sleep continuity. Thus, objective measures do not appear to protect against placebo responses. This being the case and given the importance of the subjective experience of illness severity and recovery, such data suggests that prospectively sampled sleep continuity data (sleep diaries) may be the optimal data for clinical trials, particularly when only one measure is possible.

The natural history of insomnia: high sleep reactivity interacts with greater life stress to predict the onset of acute insomnia.

STUDY OBJECTIVES: Prior research suggests that some individuals have a predisposition to experience insomnia following acute stressors (i.e. sleep reactivity). The present study was a proof of concept and specifically aimed to provide additional empirical evidence that the link between stressful life events and the onset of acute insomnia is moderated by sleep reactivity. METHODS: About 1,225 adults with a history of good sleep (Mage = 53.2 years, 68% female, 83% white) were recruited nationwide for an online study on sleep health. Participants completed surveys to assess sleep reactivity (baseline), sleep patterns (daily sleep diary), and stressful life events (weekly survey). All daily and weekly measures were completed for a one-year period. Sleep diary data were used to identify sleep initiation/maintenance difficulties, including whether they met criteria for acute insomnia at any point during the one-year interval. RESULTS: Participants with high sleep reactivity compared to low sleep reactivity were at 76% increased odds of developing acute insomnia during the one-year interval. In general, greater weekly stressful life events were associated with greater insomnia during the subsequent week. Those participants with high sleep reactivity demonstrated a stronger relationship between weekly stressful life events and insomnia, such that they reported the greatest levels of insomnia following weeks where they experienced a greater number of stressful life events. CONCLUSIONS: These results further support the sleep reactivity model of insomnia, and specifically, provide evidence that sleep reactivity predicts the incidence of acute insomnia in a sample of participants with no history of insomnia.

Does total sleep time substantially increase after cognitive behavioral therapy for insomnia?

STUDY OBJECTIVES: In most standardized approaches to cognitive behavioral therapy for insomnia, it is commonly the case that total wake time is reduced substantially during sleep restriction, but self-reported total sleep time (TST) is minimally affected. By follow-up, however, TST increases by almost 1 hour on average. A secondary analysis was undertaken to assess what percentage of participants meet or appreciably exceed baseline TST after cognitive behavioral therapy for insomnia. METHODS: Data were drawn from a randomized controlled trial assessing acute and maintenance therapies for chronic insomnia (n = 80). The present analyses assessed the percentage of participants that 1) reached (≥ 0 minute increase) and 2) appreciably exceeded (≥ 30 minutes increase) baseline TST as assessed via daily sleep diaries at posttreatment and 3, 6, 12, and 24 months following treatment. RESULTS: By the end of acute treatment, 45% of participants reached or exceeded baseline TST. By 24 months follow-up, this percentage had increased to 86%. Only 17% of participants achieved a 30-minute increase in TST by the end of acute treatment, and this proportion only increased to 58% over time. CONCLUSIONS: These findings suggest that cognitive behavioral therapy for insomnia in its current form does not appreciably increase self-reported TST in a significant proportion of patients with insomnia. Whether participants would benefit from further increases in TST warrants investigation. The further titration of sleep opportunity may be useful to accelerate increases in TST, to extend the effect to a larger subset of patients, and/or to increase the magnitude of the TST gain. CITATION: Scott H, Cheung JMY, Muench A, et al. Does total sleep time substantially increase after cognitive behavioral therapy for insomnia? J Clin Sleep Med. 2022;18(7):1823-1829.

We know CBT-I works, now what?

Cognitive behavioral therapy for insomnia (CBT-I) has been shown to be efficacious and now is considered the first-line treatment for insomnia for both uncomplicated insomnia and insomnia that occurs comorbidly with other chronic disorders (comorbid insomnia). The purposes of this review are to provide a comprehensive summary of the efficacy data (for example, efficacy overall and by clinical and demographic considerations and by CBT-I formulation) and to discuss the future of CBT-I (for example, what next steps should be taken in terms of research, dissemination, implementation, and practice).

Cognitive Behavioral Therapy for Insomnia (CBT-I): A Primer.

Cognitive Behavioral Therapy for Insomnia (CBT-I) is a multi-component treatment for insomnia that targets difficulties with initiating and/or maintaining sleep and is delivered over the course of six to eight sessions. The primary focus of CBT-I is to address the perpetuating factors (according to the three-factor model of insomnia) that contribute to the development of chronic insomnia. Chronic insomnia is the most prevalent sleep disorder, occurring in approximately 6-10% of the population, and is a risk factor for multiple medical and psychiatric disorders. Despite its prevalence and morbidity, the widespread dissemination of CBT-I is not commensurate with insomnia's overall public health impact. This is particularly surprising given its large evidence base and recent recommendation as the first line intervention for insomnia. The primary goal of this article is to provide a primer or brief introduction to CBT-I that is intended to be accessible to all clinicians and researchers, including non-sleep experts. Core components of CBT-I (i.e., Sleep Restriction Therapy, Stimulus Control Therapy, Sleep Hygiene, and Cognitive Therapy), relapse prevention strategies, multicultural considerations, adjuvants to traditional interventions, treatment adherence issues, efficacy, and further training options are described. A session-by-session outline is also provided.

Measuring the Effects of Social Isolation and Dissatisfaction on Depressive Symptoms during the COVID-19 Pandemic: The Moderating Role of Sleep and Physical Activity.

Social distancing was universally implemented to reduce the spread of the COVID-19 virus. Long-term social distancing can lead to increased feelings of social isolation or dissatisfaction with one's daily interpersonal interactions, which can subsequently result in reduced psychological health (e.g., greater depression). The present study quantified this association, and the extent to which it was moderated by measures of sleep and physical activity, by surveying 3658 adults (mean age = 46.0 years) from across the United States. Participants answered questions related to their social experiences, sleep, physical activity, and depressive symptoms during the early stages of the pandemic (March-June 2020). Results showed that social isolation and social dissatisfaction were associated with greater depressive symptoms. As predicted, self-reported sleep quality and physical activity moderated these associations, such that lower sleep quality and physical activity exacerbated their effect on depressive symptoms.

Durability of treatment response to zolpidem using a partial reinforcement regimen: does this strategy require priming?

BACKGROUND: Previous research has shown that after one month of full dose nightly treatment with zolpidem (priming), subjects with chronic insomnia (CI) switched to intermittent dosing with medication and placebos were able to maintain their treatment responses. This approach to maintenance therapy is referred to as partial reinforcement. The present study sought to assess whether priming is required for partial reinforcement or whether intermittent dosing with placebos (50% placebos and 50% active medication) can, by itself, be used for both acute and extended treatment. METHOD: 55 CI subjects underwent a baseline evaluation (Phase-1) and then were randomized to one of two conditions in Phase-2 of the study: one month of (1) nightly medication use with standard-dose zolpidem (QHS [n = 39]) or (2) intermittent dosing with standard-dose zolpidem and placebos (IDwP [n = 16]). In Phase-3 (three months), the QHS group was re-randomized to either continued QHS full dose treatment (FD/FD) or to IDwP dose treatment (FD/VD). Treatment response rates and Total Wake Time (TWT = [SL + WASO + EMA]) were assessed during each phase of the study. RESULTS: In Phase-2, 77% (QHS) and 50% (IDwP) subjects exhibited treatment responses (p = 0.09) where the average change in TWT was similar. In Phase-3, 73% (FD/FD), 57% (FD/VD), and 88% (VD/VD) of subjects exhibited continued treatment responses (p = 0.22) where the average improvement in TWT continued with FD/FD and remained stable for FD/VD and VD/VD (p < 0.01). CONCLUSION: These results suggest that intermittent dosing with placebos can maintain effects but do not allow for the additional clinical gains afforded by continuous treatment.

The natural history of insomnia: Does sleep extension differentiate between those that do and do not develop chronic insomnia?

According to the "3P model" of insomnia, the variable that mediates the transition from acute insomnia (AI) to chronic insomnia is "sleep extension" (the behavioural tendency to expand sleep opportunity to compensate for sleep loss). In the present analysis, we sought to evaluate how time in bed (TIB) varies relative to the new onset of AI and chronic insomnia. A total of 1,248 subjects were recruited as good sleepers (GS). Subjects were monitored over 1 year with sleep diaries. State transitions were defined, a priori, for AI, recovered from AI (AI-REC), and for chronic insomnia (AI-CI). Two additional groupings were added based on profiles that were unanticipated: subjects that exhibited persistent poor sleep following AI (AI-PPS [those that neither recovered or developed chronic insomnia]) and subjects that recovered from chronic insomnia (CI-REC). All the groups (GS, AI-REC, AI-CI, AI-PPS and CI-REC) were evaluated for TIB differences with longitudinal mixed effects models. Post hoc analyses for the percentage of the groups that were typed as TIB "restrictors, maintainers, and expanders" were conducted using longitudinal mixed effects models and contingency analyses. Significant differences for pre-post AI TIB were not detected for the insomnia groups. Trends were apparent for the AI-CI group, which suggested that minor increases in TIB occurred weeks before the declared onset of AI. Additionally, it was found that a significantly larger percentage of AI-CI subjects engaged in sleep extension (as compared to GS). The present data suggest that transition from AI to chronic insomnia does not appear to be initiated by sleep extension and the transition may occur before the elapse of 3 months of ≥3 nights of sleep continuity disturbance. Given these findings, it may be that the mismatch between sleep ability and sleep opportunity is perpetuated over time given the failure to "naturally" engage in sleep restriction (as opposed to sleep extension).

Acute and Chronic Insomnia: What Has Time and/or Hyperarousal Got to Do with It?

Nearly one-third of the population reports new onset or acute insomnia in a given year. Similarly, it is estimated that approximately 10% of the population endorses sleep initiation and maintenance problems consistent with diagnostic criteria for chronic insomnia. For decades, acute and chronic insomnia have been considered variations of the same condition or disorder, only really differentiated in terms of chronicity of symptoms (days/weeks versus months). Whether or not acute and chronic insomnia are part of the same phenomena is an important question, one that has yet to be empirically evaluated. The goal of the present theoretical review was to summarize the definitions of acute and chronic insomnia and discuss the role that hyperarousal may have in explaining how the pathophysiology of acute and chronic insomnia is likely different (i.e., what biopsychological factors precipitate and/or perpetuate acute insomnia, chronic insomnia, or both?).

Acute sleep deprivation and the selective consolidation of emotional memories.

Research suggests that sleep preferentially consolidates the negative aspects of memories at the expense of the neutral aspects. However, the mechanisms by which sleep facilitates this emotional memory trade-off remain unknown. Although active processes associated with sleep-dependent memory consolidation have been proposed to underlie this effect, this trade-off may also be modulated by non-sleep-related processes, such as the circadian factors, stress-related factors, and/or mood congruent context effects involved in sleep deprivation. We sought to examine the potential role of these factors by randomizing 39 young adults into either a total sleep deprivation condition (26 consecutive hours awake) or a sleep condition (8 h sleep opportunity). Replicating the emotional memory trade-off effect, negative objects were better remembered than neutral objects or background images. However, in spite of generally worse memory performance (for neutral and background information), sleep-deprived participants showed similar recognition rates for negative emotional memories relative to participants who were given a full night of sleep.