Insomnia Severity Index Scores Research Articles

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

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. 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. 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. 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.

The predictive value of supervised machine learning models for insomnia symptoms through smartphone usage behavior

IntroductionDigital phenotyping can be an innovative and unobtrusive way to improve the detection of insomnia. This study explores the correlations between smartphone usage features (SUF) and insomnia symptoms and their predictive value for detecting insomnia symptoms. MethodsIn an observational study of a German convenience sample, the Insomnia Severity Index (ISI) and smartphone usage data (e.g., time the screen was active, longest time the screen was inactive in the night) for the previous 7 days were obtained. SUF (e.g., min, mean) were calculated from the smartphone usage data. Correlation analyses between the ISI and SUF were conducted. For the specification of the machine learning models (ML), 80 % of the data was allocated to training, 20 % to testing, and five-fold cross-validation was used. Six algorithms (support vector machine, XGBoost, Random Forest, k-Nearest-Neighbor, Naive Bayes, and Logistic Regressions) were specified to predict ISI scores ≥15. Results752 participants (51.1 % female, mean ISI = 10.23, mean age = 41.92) were included in the analyses. Small correlations between some of the SUF and insomnia symptoms were found. In the ML models, sensitivity was low, ranging from 0.05 to 0.27 in the testing subsample. Random Forest and Naive Bayes were the best-performing algorithms. Yet, their AUCs (0.57, 0.58 respectively) in the testing subsample indicated a low discrimination capacity. ConclusionsGiven the small magnitude of the correlations and low discrimination capacity of the ML models, SUFs, as measured in this study, do not appear to be sufficient for detecting insomnia symptoms. Further research is necessary to explore whether examining intra-individual variations and subpopulations or employing alternative smartphone sensors yields more promising outcomes.

Insomnia severity among caregivers of children with type 1 diabetes: A mixed method study

AimThis research was conducted to assess the severity of insomnia experienced by caregivers of children with type 1 diabetes. MethodIn this study, a mixed-method descriptive sequential pattern design was employed, incorporating both qualitative and quantitative research methods. In the study, 152 caregivers were surveyed for quantitative data on survey form and insomnia severity. Additionally, 9 mothers underwent semi-structured interviews for qualitative insights. ResultsOf caregivers, 13.8% were identified to experience clinical insomnia. There were statistically significant differences in insomnia severity index scores in terms of experiencing sleep problems after the child's type 1 diabetes diagnosis, caregivers having adequate sleep duration at night, how they felt on waking in the morning, difficulty managing their child's diabetes the next day due to lack of sleep, difficulty getting to sleep at night, sleeping more than one hour during the day, lack of sleep due to caring and treatment, lack of sleep due to not meeting the desired targets for blood glucose values and receiving support for type 1 diabetes management due to lack of sleep (p < 0.05). Three themes were identified as a result of qualitative analysis: Sleep status of caregivers, effect of sleep problems on daily life and solving sleep problems. ConclusionsCaregivers experience insomnia during the process of type 1 diabetes management and this situation affects their daytime care duties. Practical implicationsResearch shows caregivers of children with type 1 diabetes often face insomnia, highlighting the need for solutions.

DOES A SINGLE DAY OF EXERCISE SNACKING IMPROVE INSOMNIA SEVERITY AND SLEEP ARCHITECTURE IN INDIVIDUALS WITH SELF-REPORTED INSOMNIA?

INTRODUCTION &amp; AIMS Regular exercise may reduce an individual’s insomnia severity, but time constraints remain a significant barrier to participation. Exercise snacking, defined as short bouts of moderate-to-vigorous physical activity performed periodically during the day, shows potential to address time pressures for other chronic conditions. However, its effects on insomnia severity and sleep architecture are unknown. The aim of this study was to explore the impact of a single day of exercise snacking on insomnia severity and sleep architecture in individuals with self-reported insomnia symptoms. METHODS Adults self-reporting insomnia symptoms were recruited to participate in a single-arm study. Participants completed a single-day exercise snacking protocol that included three sessions of 3 x 20 second ‘all out’ stair climbing efforts, separated by 1-4 hours. Self-reported insomnia severity was assessed at baseline and at 24-hours using the Insomnia Severity Index (ISI). Sleep architecture (sleep stages, time, and efficiency) was quantified during the night before, and immediately after the exercise protocol, via the Withings Sleep Analyzer. RESULTS Fourteen adults aged (median [range]) 23 [19-34] years at baseline, including 64% females, with a body mass index of (mean ± SD) 24.4 ± 5.0 kg/m2, and an ISI score of 15.4 ± 3.2, were recruited. Twelve participants completed all testing timepoints. Adherence to the protocol was 93%. Compared to baseline, there was a significant reduction in the ISI at 24-hours (baseline mean: 15.2, 95% CI 12.8-17.7; 24-hours: 11.4, 95% CI 9.0-13.8; p = 0.001, Cohen’s d = -1.21). No significant changes were found for sleep architecture outcomes including sleep stages, time, or efficiency. CONCLUSION A single day of exercise snacking improves acute insomnia severity symptoms, but not objectively measured sleep architecture, in adults with self-reported insomnia symptoms. A randomised controlled trial with an extended follow-up period and wider age range of participants is required.

Data-driven shortened Insomnia Severity Index(ISI): a machine learning approach.

The Insomnia Severity Index (ISI) is a widely used questionnaire with seven items for identifying the risk of insomnia disorder. Although the ISI is still short, more shortened versions are emerging for repeated monitoring in routine clinical settings. In this study, we aimed to develop a data-driven shortened version of the ISI that accurately predicts the severity level of insomnia disorder. We collected a sample of 800 responses from the EMBRAIN survey system. Based on the responses, seven items were grouped based on the similarity of their response using exploratory factor analysis (EFA). The most representative item within each group was selected by using eXtreme Gradient Boosting (XGBoost). Based on the selected three key items, maintenance of sleep, interference with daily function, and concerns about sleep problems, we developed a data-driven shortened questionnaire of ISI, ISI-3m (machine learning). ISI-3m achieved the highest coefficient of determination ( ) for the ISI score prediction task and the accuracy of 0.965, precision of 0.841, and recall of 0.838 for the multiclass-classification task, outperforming four previous versions of the shortened ISI. As ISI-3m is a highly accurate shortened version of the ISI, it allows clinicians to efficiently screen for insomnia and observe variations in the condition throughout the treatment process. Furthermore, the framework based on the combination of EFA and XGBoost developed in this study can be utilized to develop data-driven shortened versions of the other questionnaires.

Evaluation of Sleep in Pregnant Inpatients Compared With Outpatients.

To evaluate whether antepartum hospitalization was associated with differences in sleep duration or disrupted sleep patterns. This was a prospective cohort study with enrollment of pregnant people aged 18-55 years with singleton gestations at 16 weeks of gestation or more between 2021 and 2022. Each enrolled antepartum patient was matched by gestational age to outpatients recruited from obstetric clinics at the same institution. Participants responded to the ISI (Insomnia Severity Index) and wore actigraph accelerometer watches for up to 7 days. The primary outcome was total sleep duration per 24 hours. Secondary outcomes included sleep efficiency (time asleep/time in bed), ISI score, clinical insomnia (ISI score higher than 15), short sleep duration (less than 300 minutes/24 hours), wakefulness after sleep onset, number of awakenings, and sleep fragmentation index. Outcomes were evaluated with multivariable generalized estimating equations adjusted for body mass index (BMI), sleep aid use, and insurance type, accounting for gestational age correlations. An interaction term assessed the joint effects of time and inpatient status. Overall 58 participants were included: 18 inpatients and 40 outpatients. Inpatients had significantly lower total sleep duration than outpatients (mean 4.4 hours [SD 1.6 hours] inpatient vs 5.2 hours [SD 1.5 hours] outpatient, adjusted β=-1.1, 95% CI, -1.8 to -0.3, P=.01). Awakenings (10.1 inpatient vs 13.8, P=.01) and wakefulness after sleep onset (28.3 inpatient vs 35.5 outpatient, P=.03) were lower among inpatients. There were no differences in the other sleep outcomes, and no interaction was detected for time in the study and inpatient status. Inpatients were more likely to use sleep aids (39.9% vs 12.5%, P=.03). Hospitalized pregnant patients slept about 1 hour/day less than outpatients. Fewer awakenings and reduced wakefulness after sleep onset among inpatients may reflect increased use of sleep aids in hospitalized patients.

Actigraphy measures show sleep improvement after parathyroidectomy for primary hyperparathyroidism

ImportanceThe symptoms of primary hyperparathyroidism are often subtle, such as fatigue, mood changes, and sleep disturbances. After parathyroidectomy, patients often report improvement in sleep and mood; however, objective data supporting these improvements is lacking. ObjectiveThis prospective study uses standard measures to objectively and subjectively assess sleep in patients with primary hyperparathyroidism before and after parathyroidectomy. DesignA longitudinal prospective study was conducted over three one-week-long periods: pre-parathyroidectomy, 1-week post-parathyroidectomy, and three months post-parathyroidectomy. During each time point, patients wore an actigraphy device, recorded a sleep diary, and completed the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Depression Anxiety Stress Scale (DASS). Statistical analysis was performed using repeated measures models to compare the average measures among the three time points and test for trends over time. SettingSingle institution, tertiary care center. ParticipantsPatients with primary hyperparathyroidism from ages 18 to 89 years old. ExposureParathyroidectomy between September 2020 and January 2024. Main outcomes and measuresActigraphy data, consensus sleep diary, Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Depression Anxiety Stress Scales – 21 Items (DASS). ResultsThirty-six patients were enrolled, and 34 patients completed the study. Actigraphy data showed a significant negative trend in average sleep latency (p = 0.045) and average time in bed (p = 0.046). Sleep diary data showed additional differences in the number of awakenings (p = 0.002), wake after sleep onset (p < 0.001), sleep quality (p < 0.001), and sleep efficiency (p = 0.02) among the three time points and/or as a significant negative trend. PSQI and ISI scores were significantly different among the three time points (p = 0.002 and p < 0.001, respectively) and also declined significantly over time (p = 0.008 and p = 0.007, respectively). DASS depression, anxiety, and stress scores were significantly different among the three time points (p < 0.001, p = 0.01, and p < 0.001, respectively), and stress also declined significantly over time (p = 0.005). Conclusion and relevanceThis study represents the most extensive prospective study demonstrating objective and subjective sleep and mood improvement in patients with primary hyperparathyroidism after parathyroidectomy.

Severe Clinical Insomnia Management with Ayurvedic Protocol - A Case Report

Insomnia is characterized by inability to sleep or lack of sleep. Severe clinical insomnia is a highly prevalent health concern faced by a wide majority of people across the globe due to the rise in stressful external environments. Often such cases require long term use of sedative hypnotics or tranquilizers which are habit forming. Ayurveda identifies insomnia as Nidranasa and is a disease which is caused predominantly by Vata Pitta increase and a dip in Kapha levels. Ayurvedic treatment protocol involves internal medication and topical procedures like Shirodhara and Abhyanga. This case report is intended to throw light to a positive outcome of Ayurvedic treatment protocol in severe clinical insomnia. A 34-year-old male presented with symptoms of severe clinical insomnia assessed by Insomnia Severity Index (ISI) associated with obesity and had a history of consuming hypnotics. The treatment protocol included Dhanyamladhara, Udvartana, Takradhara, Abhyanga and Shirodhara along with disease specific internal medicines. The ISI score before treatment of 26 came down to 1 after treatment and was maintained during 3 months follow up. This displays the complete remission of the disease without the use of habit-forming internal medication.

Association of Retinal Neurovascular Impairment with Disease Severity in Patients with Major Depressive Disorder: An Optical Coherence Tomography Angiography Study.

Identifying the fundus objective biomarkers for the major depressive disorders (MDD) may help promote mental health. The aim of this study was to evaluate retinal neurovascular changes and further investigate their association with disease severity in MDD. This cross-sectional study conducted in the hospital enrolled patients with MDD and healthy controls.The retinal neurovascular parameters for all subjects, including vessel density (VD), thickness of ganglion cell complex (GCC) and retinal nerve fiber layer (RNFL), and optic nerve head (ONH) eg are automatically calculated by the software in optical coherence tomography angiography (OCTA). The severity of MDD including depressive symptoms, anxiety, cognition, and insomnia was assessed by Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Scale (HAMA), Montreal Cognitive Assessment (MoCA), and Insomnia Severity Index (ISI) respectively. This study included 74 MDD patients (n=74 eyes) and 60 healthy controls (HCs) (n=60 eyes). MDD patients showed significantly decreased VD of superficial and deep capillary plexus, thickness of GCC and RNFL, and volume of ONH (all p<0.05) and increased vertical cup-to-disc ratio and global loss volume (GLV) (all p<0.05) compared to HCs. Positive associations were found between HAMD scores and cup area (r=0.30, p=0.035), cup volume (r=0.31, p=0.029), and disc area (r=0.33, p=0.020) as well as ISI scores and RNFL thickness (r=0.34, p=0.047). We found the retinal neurovascular impairment and its association with disease severity in MDD patients. OCTA showed promise as a potential complementary assessment tool for MDD.

Relationship of Nocturnal Insomnia Symptoms and Outcomes After Hypoglossal Nerve Stimulation.

In patients undergoing hypoglossal nerve stimulation (HGNS), we examined the Insomnia Severity Index (ISI) to understand how baseline sleep onset insomnia (SOI), sleep maintenance insomnia (SMI), and early morning awakening (EMA) affected postsurgical outcomes. Observational. Multicenter registry. We included patients from the Adherence and Outcomes of Upper Airway Stimulation for Obstructive Sleep Apnea International Registry (ADHERE) with a baseline ISI from 2020 to 2023. Regression analysis examined the association of ISI question scores for SOI, SMI, and EMA and outcomes: Apnea-Hypopnea Index (AHI) reduction, device usage, changes in the Epworth Sleepiness Scale (ESS) and overall ISI score, final visit (FV) completion, and satisfaction. No relationship was noted between insomnia subtypes and AHI reduction or FV completion. In the subgroup of patients with baseline moderate/severe insomnia, patients with major impairment for SOI used their device 64 min/day longer than those with minimal impairment. Amongall patients, those with baseline major impairment for SOI had a 2.3 points greater improvement in ISI from baseline to FV compared to patients with minimal impairment, while patients with baseline major impairment for SMI had a 2.0 and 3.5 points greater improvement in the ESS and ISI than those with minimal impairment. Patients with EMA and moderate/severe baseline insomnia had decreased odds of being satisfied after surgery. In ADHERE, nocturnal symptoms of insomnia did not limit HGNS efficacy or therapy use. Conversely, those with worse insomnia subtype impairments at baseline had improved outcomes related to adherence, sleepiness, and insomnia at the FV.

Harnessing technology to improve sleep in frontline healthcare workers: A pilot study of electronic noise-masking earbuds on subjective and objective sleep measures.

Objective: This pilot study assessed the effects of electronic noise-masking earbuds on subjective sleep perception and objective sleep parameters among healthcare workers (HCWs) reporting sleep difficulties during the COVID-19 pandemic. Methods: Using a pre-post design, 77 HCWs underwent 3 nights of baseline assessment followed by a 7-night intervention period. Participants wore an at-home sleep monitoring headband to assess objective sleep measures and completed subjective self-report assessments. The difference in mean sleep measures from baseline to intervention was estimated in linear mixed models. Results: Compared to baseline assessments, HCWs reported significant improvements in sleep quality as measured by the Insomnia Severity Index (ISI) (Cohen's d = 1.74, p < 0.001) and a significant reduction in perceived sleep onset latency (SOL) during the intervention (M = 17.2 minutes, SD = 7.7) compared to baseline (M = 24.7 minutes, SD = 16.1), (Cohen's d = -0.42, p = 0.001). There were no significant changes in objective SOL (p = 0.703). However, there was a significant interaction between baseline objective SOL (<20 minutes vs >20 minutes) and condition (baseline vs intervention) (p = 0.002), such that individuals with objective SOL >20 minutes experienced a significant decrease in objective SOL during the intervention period compared to baseline (p = 0.015). Conclusions: HCWs experienced a significant improvement in perceived SOL and ISI scores after using the electronic noise-masking earbuds. Our data provide preliminary evidence for a nonpharmacological intervention to improve the sleep quality of HCWs which should be confirmed by future controlled studies.

Sleep health and quality of life in the Detroit Research on Cancer Survivors cohort.

Sleep disturbances represent a modifiable target to improve quality of life and longer-term outcomes in cancer survivors. However, the association between sleep health and overall quality of life in African American cancer survivors has been poorly assessed, a population at increased risk for morbidity and mortality. Seven hundred and eighteen Detroit Research on Cancer Survivors (ROCS) cohort participants completed a supplemental sleep survey at the time of enrollment, which included the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and Insomnia Severity Index (ISI). Linear and logistic regression was used to evaluate the association between sleep and mental health, while block regression models were used to estimate the contribution of clustered factors to Health-Related Quality of Life (HRQOL). Nearly 60% of the cohort reported symptoms indicative of poor sleep quality on the PSQI, 15% reported excessive daytime sleepiness on the ESS, and 12% reported moderate to severe insomnia on the ISI. Survivors with elevated ISI scores reported FACT-G scores that were 17 points lower than those without symptoms of insomnia (95% CI: - 13.1, - 21.2). Poor sleep health accounted for the largest proportion of variability in FACT-G scores (R2 = 0.27) and change in R2 value (0.18) when compared to comorbidities, health behaviors, cancer-related factors, and demographics. Overall sleep health was significantly associated with poorer HRQOL and variability in FACT-G scores. Additional studies investigating a causal relationship between sleep and HRQOL are needed to determine whether sleep quality could affect disparities in cancer outcomes. Addressing sleep quality in cancer survivors may improve long-term health and HRQOL.

An Evaluation of the Relationship between Subjective Tinnitus Perception and COVID-19-Related Psychological Factors

Aim: This study aimed to examine the relationship of tinnitus loudness, annoyance and handicap in tinnitus patients with the level of coronavirus-related anxiety, psychological distress, and fear. It was also aimed to evaluate the effects of insomnia severity and social and emotional loneliness perception on tinnitus in the pandemic period.&#x0D; Materials and Methods: A total of 112 patients over the age of 18 who were followed up in two centers with the diagnosis of chronic subjective tinnitus were included in the study. During the pandemic, the data were collected using the following tools via Google Forms: Demographic Information Form, Visual Analogue Scale (VAS) for tinnitus loudness and annoyance, the Tinnitus Handicap Inventory (THI), Coronavirus Anxiety Scale (CAS), Fear of COVID Scale (FCVS-T), COVID-19 related Psychological Distress Scale (CORPD), Insomnia Severity Index (ISI), and Social and Emotional Loneliness Scale (SELSA-S). &#x0D; Results: A weak positive correlation was found between CAS score and VAS for tinnitus loudness and annoyance, FCVS-T, ISI, Selsa-S total scores; between FCVS-T score and VAS for annoyance, CORPD, ISI scores; and, between CORPD and THI, ISI scores (p

Restless legs syndrome in patients with obstructive sleep apnea: Association between apnea severity and symptoms of depression, insomnia, and daytime sleepiness

ObjectiveTo determine if the prevalence and severity of restless legs syndrome (RLS) varies with apnea severity and analyze differences between the sexes in terms of comorbid RLS with symptoms of depression, insomnia, and daytime sleepiness in patients with obstructive sleep apnea (OSA). MethodsSymptoms of depression, insomnia, and daytime sleepiness were defined as Patient Health Questionnaire–9 score ≥10, Insomnia Severity Index score ≥15, and Epworth Sleepiness Scale score ≥11. Multivariate logistic and linear regression analyses were conducted. ResultsIn 707 adults with OSA (85.1% males), 16.1% (n = 114) had comorbid RLS. The prevalence of RLS was markedly lower in those with moderate and severe OSA than in those with mild OSA. Similarly, the odds of RLS significantly decreased with increasing apnea-hypopnea index. After controlling for age and sex, in patients with comorbid RLS, the International RLS Study Group Rating Scale scores were negatively correlated with apnea-hypopnea index and a nadir peripheral oxygen saturation during sleep. The presence of RLS was more likely to be associated with symptoms of depression, insomnia, and daytime sleepiness after controlling for confounding variables, but only in men. ConclusionsRLS is frequently noted in combination with OSA, with a female preponderance. The severities of OSA and RLS may be negatively associated. In patients with OSA, sex-related differences in terms of comorbid RLS with symptoms of depression, insomnia, and daytime sleepiness warrant further investigations.

Effect of Surgical Masks and N95 Respirators on Anxiety.

Masks are designed to reduce the spread of airborne pathogens, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), although wearing a mask has some adverse effects. The primary objective of this study was to explore the effects of surgical masks and N95 respirators on patients diagnosed with anxiety. Subjects diagnosed with first-episode anxiety disorders were recruited from outpatient departments between February and July, 2023. A self-administered questionnaire was administered at baseline and at follow-up. The questionnaire addressed demographic information, Hamilton Anxiety Rating Scale (HAM-A), Hamilton Depression Rating Scale (HAM-D) and Insomnia Severity Index (ISI). Subjects were divided into three groups (n=30 each): control (no mask); surgical mask; and N95 respirator. The Kruskal-Wallis test and repeated measures analysis of variance were used to examine associations between face mask use and emotion. Ninety subjects completed the study, of whom 51 (56.67%) were male and 39 (43.33%) were female. Time and group effects were observed in HAM-A score among the 3 groups. After 4 weeks, mean (± SD) HAM-A score decreased from 32.63±13.37 to 28.07±9.33 in the control group, increased from 33.67±12.47 to 36.80±10.32 in the surgical mask group, and from 32.33±14.73 to 41.13±8.29 in the N95 respirator group, with no sex differences among the 3 groups. HAM-A score was significantly higher in the mask groups than that in the control group at follow-up. Only N95 respirator group exhibited significant time effects on HAM-D and ISI scores, with a decreasing trend in HAM-D score and an opposite trend in ISI score. Prolonged mask use may exacerbate anxiety, especially among those wearing N95 respirator masks. In a post-pandemic environment, governments should improve public health beliefs regarding coronavirus disease 2019 and promote the safety of face mask use, thus reducing the physiological and psychological effects of improper mask use.

Evaluation of daytime sleepiness and insomnia symptoms in OSA patients with a characterization of symptom-defined phenotypes and their involvement in depression comorbidity-a cross-sectional clinical study.

Recent research highlights the significance of insomnia and sleepiness, shifting from obstructive sleep apnea (OSA) severity and sleep structure, in defining OSA phenotypes. This study aimed to characterize insomnia and sleepiness associated with OSA phenotypes and assess their involvement in depression symptoms (DS) in OSA. This cross-sectional, clinical study included 181 participants who underwent polysomnography (PSG) and filled out questionnaires, including the Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), and Beck Depression Index (BDI). They were categorized into phenotypes: insomnia-sleepiness (I + S; ESS ≥ 11; ISI ≥ 15; n = 20), sleepiness (S; ESS ≥ 11; ISI < 15; n = 22), insomnia (I; ESS < 11; ISI ≥ 15), and asymptomatic (A; ESS < 11; ISI<15; n=55). A linear regression model for the BDI score (R2=0.357, p < 0.001) included ISI score and subjective-to-objective sleep latency ratio. The ISI score was a predictive factor for mild and moderate DS [OR = 1.23 (95% CI: 1.09-1.38), p < 0.001 and OR = 1.39 (95% CI: 1.13-1.72), p = 0.002]. The I and I + S phenotypes are characterized by higher BDI scores (p < 0.001 and p = 0.02), longer subjective sleep latency (p = 0.008 and p = 0.04), and shorter subjective total sleep time (TST; p = 0.049 and p = 0.006) compared to A. Furthermore, the I and I + S groups had shorter subjective TST than S (p = 0.03 and p = 0.047). The I and I + S had higher BDI scores than A (p < 0.001 and p = 0.02, respectively) and S (p < 0.001 and p = 0.02, respectively). The I phenotype was associated with the risk of mild and moderate DS (OR = 5.61 (95% CI: 1.91-16.53), p < 0.001 and OR = 9.55 (95% CI: 1.81-50.48), p = 0.008 respectively). Moreover, the I + S phenotype presented an even greater risk for mild DS (OR = 10.29 (95% CI: 2.95-35.85), p < 0.001). Using clinical features for OSA phenotyping holds promise for finding OSA individuals with increased risk for DS occurrence.

Cross‐sectional analyses of factors associated with the presence and aggravation of chronic insomnia by symptom subtypes

AbstractAimThe aim of this study was to investigate the association of psychological and chronobiological factors with the presence and severity of chronic insomnia by symptom subtypes and their impacts on daytime dysfunctions.MethodsParticipants of the present web‐based epidemiological study were classified as follows: difficulty initiating sleep (DIS) (n = 91); difficulty maintaining sleep (DMS) (n = 13); early morning awakening (EMA) (n = 48); DIS + DMS (n = 67); DIS + EMA (n = 23); DMS + EMA (n = 24); triplet of DIS, DMS, and EMA symptoms (TRP) (n = 69); and normal sleepers (n = 4590). The Insomnia Severity Index (ISI), Hospital Anxiety and Depression Scale (HADS), Munich Chronotype Questionnaire (MCTQ), insomnia‐related psychological measures (including the Ford Insomnia Response to Stress Test [FIRST] and the Dysfunctional Beliefs and Attitudes about Sleep Scale [DBAS]), and the cognitive and somatic domains of the Pre‐Sleep Arousal Scale (PSAS) were evaluated.ResultsThe presence of DIS and DIS + DMS were significantly associated with an evening preference, and EMA and EMA + DMS with a morning preference, while TRP showed no significant association with either chronotype. The increase in DBAS scores was associated with higher ISI scores in all subtypes. Meanwhile, the associations of each psychological measure varied among insomnia subtypes, with the association of PSAS cognitive arousal to DIS and PSAS somatic arousal to both DMS + EMA and TRP. Pathological HADS score was associated with all subtypes.ConclusionChronotypes may be associated with the presence of some insomnia subtypes; however, only psychological factors were speculated to contribute to the aggravation of all subtypes. All insomnia subtypes possibly contribute to the formation of depression.

Effect of Lemiancao on Insomnia in Patients With Depressive Disorder

Objective To investigate the effect of Lemiancao on insomnia in the patients with depressive disorder. Methods Totally 79 patients diagnosed with both insomnia and depressive disorder from February to August in 2022 in Peking University Sixth Hospital were selected and classified into a control group(n=40) and a Lemiancao group(n=39).The Lemiancao group received routine nursing and medical treatment combined with Lemiancao training in the morning and evening every day,while the control group received routine nursing and medical treatment.The sleep status was evaluated based on the Pittsburgh sleep quality index(PSQI),insomnia severity index(ISI),and 36-item short-form health survey(SF-36) before and after treatment. Results The general information of patients showed no significant difference between the two groups(all P>0.05).After a 2-week intervention with Lemiancao training,the Lemiancao group showed lower PSQI and ISI scores and higher SF-36 score than the control group(all P<0.001). Conclusion Lemiancao training has therapeutic effects on insomnia in the patients with depressive disorder.

Sleep Disturbances as a Consequence of Long COVID-19: Insights from Actigraphy and Clinimetric Examinations—An Uncontrolled Prospective Observational Pilot Study

The COVID-19 pandemic represents a global health and social challenge. However, the impact of a SARS-CoV-2 infection itself on mental health and sleep quality remains poorly understood. The purpose of the present uncontrolled prospective observational pilot study was to evaluate the impact of past COVID-19 disease on the incidence of quantitative and qualitative sleep disturbances. A group of 61 subjects (37 female, 24 male) reported sleep disturbances that had lasted for at least one month and had started after recovery from COVID-19. The study used self-reported instruments: the Epworth Sleepiness Scale (ESS) and Insomnia Severity Index (ISI), as well as an objective method—actigraphy—for quantitative analysis of sleep architecture. It was shown that sleep disturbances most commonly started after recovery (68.3%, n = 41) and lasted for more than one month (83.6%, n = 51). ESS scores of 7.8 ± 5.0 points indicate moderate daytime sleepiness, and ISI scores of 16.3 ± 5.8 points denote moderate insomnia. ESS scores were negatively correlated with total time in bed (r = −0.3780, p = 0.003), total sleep time (r = −0.2969, p = 0.020), and wakefulness after sleep onset (r = −0.2654, p = 0.039). In addition, ESS scores were correlated negatively with the respondents’ age (B = −0.17, p = 0.000) and time from COVID-19 onset. A positive correlation was found between wakefulness after sleep onset and ESS scores (B = −0.05, p = 0.039). ISI scores were positively correlated with time in bed (r = 0.3275, p = 0.010). Female gender was found to be a significant predictor of insomnia’s severity (B = 2.159, t = 3.04, p = 0.004). In conclusion, patients with a history of COVID-19 report long-lasting sleep disturbances that do not subside spontaneously. In the patient group studied, moderate levels of daytime sleepiness and insomnia were found. The most frequently reported problems included irregular sleep, frequent awakenings, and difficulty maintaining sleep, while normal sleep duration was preserved. These findings underscore the need for continued attention to the long-term consequences of COVID-19 on sleep health and emphasize the importance of targeted interventions to address these enduring sleep disturbances in affected individuals.

Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia.

The standard of care for military personnel with insomnia is cognitive behavioral therapy for insomnia (CBT-I). However, only a minority seeking insomnia treatment receive CBT-I, and little reliable guidance exists to identify those most likely to respond. As a step toward personalized care, we present results of a machine learning (ML) model to predict CBT-I response. Administrative data were examined for n=1,449 nondeployed US Army soldiers treated for insomnia with CBT-I who had moderate-severe baseline Insomnia Severity Index (ISI) scores and completed one or more follow-up ISIs 6-12 weeks after baseline. An ensemble ML model was developed in a 70% training sample to predict clinically significant ISI improvement (reduction of at least two standard deviations on the baseline ISI distribution). Predictors included a wide range of military administrative and baseline clinical variables. Model accuracy was evaluated in the remaining 30% test sample. 19.8% of patients had clinically significant ISI improvement. Model AU-ROC (SE) was 0.60 (0.03). The 20% of test sample patients with highest probabilities of improvement were twice as likely to have clinically significant improvement as the remaining 80% (36.5% versus 15.7%; χ21=9.2, p=.002). Nearly 85% of prediction accuracy was due to ten variables, the most important of which were baseline insomnia severity and baseline suicidal ideation. Pending replication, the model could be used as part of a patient-centered decision-making process for insomnia treatment. Parallel models will be needed for alternative treatments before such a system is of optimal value.