Sleep Disturbance Factors Research Articles

Construction and verification of the prediction model for risk of sleep disturbance in elderly patients with hypertension: a cross-sectional survey based on NHANES database from 2005 to 2018

ObjectiveTo construct and verify a risk prediction model for sleep disturbance in elderly patients with hypertension, aiming to offer guidance for sleep management in this demographic.MethodsA cohort of 6,708 elderly hypertensive patients from the NHANES database, spanning 2005 to 2018, met the inclusion criteria and were selected for this study. Participants were randomly assigned to a development group (n = 4,696) and a verification group (n = 2,012) in a 7:3 ratio. The occurrence of sleep disturbance was assessed across the subjects. Independent risk factors for sleep disturbance were analyzed using weighted multivariate logistic regression within the development group. A predictive model for sleep disturbance risk in elderly hypertensive patients was developed and verified using Stata 17.0. The model's predictive accuracy and stability were evaluated using the verification group's data.ResultsOf the 6,708 subjects, 2,014 (30.02%) were identified with sleep disturbance, and the weighted prevalence of sleep disturbance among elderly hypertensive patients was 33.283%. Weighted multivariate logistic regression analysis in the development group revealed that six factors were independently associated with sleep disturbance: higher total depression scores, higher education level, asthma, overweight, arthritis, and work restriction (OR > 1 and P < 0.05). The area under the receiver operating characteristic (ROC) curve (AUC) for the nomogram prediction model was 0.709 in the development group and 0.707 in the verification group, indicating good discrimination ability. Brier scores for the nomogram model were 0.185 in the development group and 0.189 in the verification group, both below 0.25, suggesting good calibration. Decision Curve Analysis (DCA) determined that the nomogram's clinical net benefit was maximized when the threshold probability for sleep disturbance in elderly hypertensive patients was 0.13–0.67 in the development group and 0.14–0.61 in the verification group, highlighting the model's clinical utility.LimitationsThis study is not without its limitations, including issues with data collection, the absence of external validation, and the non-extrapolation of results.ConclusionThe prevalence of sleep disturbance among elderly hypertensive patients stands at 33.283%. The nomogram model, based on identified risk factors for sleep disturbance in this population, has demonstrated good predictive efficiency and clinical relevance. It serves as a valuable tool to assist healthcare providers in identifying elderly hypertensive patients at high risk for sleep disturbance.

A Meta-Regression of psychosocial factors associated with sleep outcomes in mindfulness-based intervention trials.

In this meta-regression, we aimed to explore associations between changes in psychosocial factors and changes in sleep disturbance during mindfulness-based interventions (MBIs). We also investigated participant-specific and methodological factors associated with sleep disturbance during MBIs. We utilized data from a published meta-analysis of 40 randomized controlled trials of MBIs (published from inception to 2020) with a sleep disturbance outcome measure in healthy and clinical adult populations. We conducted meta-regressions to test associations between sleep improvements following MBIs and psychosocial factors, as well as demographic and methodological factors. MBIs were associated with significant reductions in sleep disturbance (SMD = -0.523; 95% CI = -0.678 to -0.368) and psychosocial factors (SMD = -0.213 - -0.894). Reductions in sleep disturbance were associated with reductions in stress (r = 0.74, p = .02) and depression (r = 0.90, p < .001). MBIs improve sleep disturbance across a wide range of healthy and clinical populations. Stress and depression may be important psychosocial factors associated with sleep disturbance. Future RCTs should include measures of additional factors and should investigate longitudinal associations between psychosocial, demographic, and methodological factors with changes in sleep disturbance to test mechanisms and to identify "active ingredients" of MBIs.

Evolution and characteristics of nocturnal knee pain after knee arthroplasty.

Nocturnal knee pain and sleep disorders are two common but poorly studied issues contributing to dissatisfaction following knee arthroplasty. This study aims to evaluate the prevalence and associated factors of nocturnal pain and sleep disturbance in a population undergoing knee arthroplasty. We included in this prospective observational study 111 patients undergoing knee athroplasty (79 TKA and 32 UKA). Sleep quality, nocturnal knee pain (preoperatively, at day 3, at 3 and 6 weeks, at 3 months and one year after surgery), pain during mobilization and neuropathic pain were evaluated by scores. Painkillers and sleeping pills intake were recorded. Potentially predictive factors for postoperative nocturnal pain evolution were studied. Poor sleeping quality rate was 54% for the pre-operative patients and was still 53% at one year after surgery. The prevalence of nocturnal knee pain was 38,74% before surgery and 2,9% at one year after arthroplasty. This study has been performed at the University Hospital Saint Luc Brussels. Evolution and Characteristics of nocturnal knee pain after knee arthroplasty. Nocturnal pain after knee surgery was significantly associated with higher pain scores at rest during activity and at night. Nocturnal pain was significantly associated with a higher PSQI and DN4 scores and a higher consumption of painkillers or sleeping pills at W6. The multiple variable regression showed a statistically significant correlation between preoperative and postoperative nocturnal pain at D3 and W3. Compared to TKA, UKA patients reported significantly less nocturnal pain at W3 and W6. Bad sleeping quality is present in 54% of knee arthroplasty patients before and after surgery. Nocturnal pain is present in 39% of knee arthroplasty patients before surgery and this drops to 3% after one year. Nocturnal pain is associated with higher pain intensity, neuropathic symptoms, increased medication consumption and poor sleeping quality. Night pain disappeared faster after UKA than TKA, with a tipping point around 6 weeks postoperatively.

Concurrent and longitudinal associations of dissatisfaction with height and weight, body mass index with sleep disturbance among adolescents in China.

Sleep disturbance in adolescents is a significant global public health issue that can result in various physical and mental disorders. Height and weight dissatisfaction, as subjective perceptions of body shape, are common in adolescence and may affect individuals' sleep situations. However, the association of them is unclear. This study aimed to examine the cross-sectional and longitudinal associations among height dissatisfaction, weight dissatisfaction, body mass index (BMI), and sleep disturbance in adolescents. A total of 27,260 participants completed measures of sleep disturbance, height and weight satisfaction, and BMI. The cross-sectional and longitudinal effects of height satisfaction, weight satisfaction, and BMI as well as their changes in sleep disturbance over time were tested. Height satisfaction (ps < 0.001) and weight satisfaction (ps < 0.001) were negatively associated with concurrent sleep disturbance after adjusting for socio-demographic covariates and previous sleep disturbance. Height satisfaction (ps < 0.001) and weight satisfaction (ps < 0.001) at T1 as well as their increases (ps < 0.001) over 6 months predicted decreases in sleep disturbance over time. The cross-sectional and longitudinal associations between BMI and sleep disturbance were not significant (ps > 0.42). Moreover, height dissatisfaction (ORs = 1.06 to 1.34) and weight dissatisfaction (ORs = 1.21 to 1.36) were risk factors for concurrent and long-term sleep disturbance while adjusting socio-demographic covariates and previous sleep disturbance. Greater attention to subjective perception of height satisfaction and weight satisfaction, instead of BMI is needed.

Sleep disturbances in hospitalized children: a wake-up call

Although sleep is essential for (recovery of) health, it is adversely affected by hospitalization, due to disease discomfort, environmental noise, and care routines, causing reduced sleep and increased disturbances. This study evaluates factors affecting sleep quality and quantity in hospitalized children and compares inpatient sleep with sleep at home. Using an observational, prospective study design, we assessed sleep in hospitalized children aged 1–12 years, admitted to a tertiary center, and compared this with home 6–8 weeks after discharge. We measured total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), sleep efficiency, awakenings, and subjective sleep quality, using actigraphy, sleep diaries, and PROMIS questionnaires. We explored an array of sleep-disturbing factors. Regression analyses identified key determinants affecting sleep patterns, while mixed linear models compared sleep in hospital to sleep at home. Out of 621 eligible patients, 467 were invited, and 272 (58%) consented to participate. Key determinants of sleep included pain, number of previous admissions, (underlying) chronic illness, and environment-, staff-, and disease-related factors. Parents reported lower perceived sleep quality in the hospital compared to at home, 97-min (SE 9) lower TST, 100-min (5) longer WASO, more difficulties with falling asleep, lower sleep satisfaction, and more awakenings. Actigraphy outcomes revealed shorter TST (20 min (6)), but better sleep efficiency and fewer awakenings in the hospital.Conclusion: Sleep in hospital was compromised in comparison to sleep at home, primarily due to disturbances related to treatment, environment, and staff. These findings underscore the necessity and potential of relative simple interventions to improve sleep quality and minimize sleep disturbances in hospitalized children.

The prevalence and moderating factors of sleep disturbances in people living with HIV: a systematic review and meta-analysis

This systematic review and meta-analysis aimed to investigate the prevalence of self-reported sleep disturbances in people living with HIV considering the effects of age, depression, anxiety, CD4 cell counts, time since HIV diagnosis, study region, and the instruments used to measure sleep disturbances. We searched PubMed, PsycINFO, and EMBASE to include eligible articles. In this meta-analysis of 43 studies, the pooled prevalence of self-reported sleep disturbances was 52.29% (95% confidence interval 47.69–56.87). The subgroup analyses revealed that variations in the sleep measurements and study region significantly contributed to the observed heterogeneity. In the meta-regression analyses, higher proportions of participants with depression or anxiety and longer times since HIV diagnosis were significantly associated with a higher prevalence of self-reported sleep disturbances after adjusting for mean age. Our findings emphasise the substantial burden of sleep disturbances in people living with HIV and identified comorbid depression and anxiety and the time since HIV diagnosis as significant moderators. These results underscore the importance of considering these factors when designing tailored screening programmes for high-risk patients and implementing early interventions to prevent and mitigate sleep disturbances in people living with HIV.

Novel electrical therapy to improve sleep disturbance in patients with autoimmune rheumatic diseases.

Sleep disturbance is common in autoimmune rheumatism diseases (ARD) and it plays an important role in activating disease and affects the quality of life. This study aims to evaluate the efficacy and acceptability of the novel electrical therapy on sleep disturbance in ARD patients and its effect on immunologic factors. A total of 51 ARD patients (26 treatment group and 25 control group) with sleep disturbance were enrolled in this study. Sleep parameters and immunological indicators (serum level of 12 cytokines and immune function) were collected. The novel electrical therapy was prescribed for 15-30 min 3-6 times a day. The Pittsburg Sleep Index (PSQI) was assessed before and after 3 months' treatment by Mi Energy equipment. Immune function and serum levels of cytokines of all participants at baseline and after treatment were tested with flow cytometry and flow immunofluorescence, respectively. Correlation analysis was used to analyze the relationship between sleep disturbance and immunologic factors. Multiple linear regression analysis was employed to investigate the risk of sleep disturbance in ARD. The global score of PSQI (Baseline: 12.81 ± 4.07, After novel electrical therapy: 4.88 ± 2.76) was effectively improved after 3 months of adjuvant therapy by electrical therapy. We also found that serum levels of IL-8 and IL-1β statistically significantly decreased after novel electrical therapy. This adjuvant therapy can also significantly decrease the percentage of CD4 + CD8 + T cell, effector memory CD8 + T cell, Memory CD8 + T cell, Th17 cell, and plasma cell and significantly can increase the percentage of naïve CD8 + T cell, Th2 cell, and Tfh2 cell. Nevertheless, all serum level of 12 cytokines and the percentage of immune cells did not correlate with the PSQI global score except the Tc17 cell. Furthermore, age is an independent risk factor influencing PSQI scores (OR = 1.15, p < 0.05) in patients with autoimmune diseases through multiple linear regression analysis. Novel electrical therapy can effectively improve sleep disturbance in patients with ARD. It can also change the serum level of some cytokines (IL-8 and IL-1β) and percentage of immune cells (CD4 + CD8 + T cell, effector memory CD8 + T cell, Memory CD8 + T cell, Th17 cell, naïve CD8 + T cell, Th2 cell, Tfh2 cell, and plasma cell).

Sleep disturbance and internalizing symptoms in adolescents: a moderated mediation model of self-control and mindfulness

ObjectivesDespite accumulating evidence regarding the impact of sleep disturbance on internalizing symptoms among adolescents, the underlying psychological mechanisms remain inadequately explored. This study aimed to investigate a conceptual framework elucidating how sleep disturbance influences internalizing symptoms in adolescents through the mediating role of self-control, with mindfulness as a moderator.MethodsIn this cross-sectional study, 1876 Chinese adolescents (Mage = 14.88 years, SD = 1.47 years, range = 12–19 years, 44.7% boys) completed the Youth Self-Rating Insomnia Scale (YSIS), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Brief Self-control Scale (BSCS), and Mindful Attention Awareness Scale-Children (MAAS-C) to provide data on sleep-related variables, internalizing symptoms (anxiety and depression), self-control, and mindfulness, respectively. The PROCESS macro for SPSS was applied to perform moderated mediation analysis.ResultsSleep disturbance demonstrated a significant positive correlation with internalizing symptoms in adolescents, including anxiety (β = 0.481, p < 0.001) and depression (β = 0.543, p < 0.001). Self-control served as a mediator between sleep disturbance and two forms of internalizing symptoms. Moreover, mindfulness moderated the pathways from self-control to internalizing symptoms (for anxiety symptoms: β = 0.007, p < 0.001; for depression symptoms: β = 0.006, p < 0.001), and the mediating relationships were weaker for adolescents exhibiting higher levels of mindfulness.ConclusionsOur findings enhance understanding of the impact, pathways, and influencing factors of sleep disturbance on adolescent internalizing symptoms, suggesting the importance of enhancing mindfulness levels in addressing self-control deficits and subsequently reducing internalizing symptoms among adolescents.

Prevalence and influencing factors of sleep disturbance among medical students under the COVID-19 pandemic.

Medical students may feel severe psychological stress during COVID-19, which might impair their ability to sleep. This research aimed to look at the risk factors for sleep disturbance and the prevalence of sleep disturbance among medical students. 538 medical students in total were recruited for this research. Anxiety, depression, and sleep disturbance were assessed using the Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS), and Pittsburgh Sleep Quality Index (PSQI). To evaluate the possible risk variables, we computed descriptive statistics for each assessment item and ran univariate and logistic regression analyses. Medical students had a 63.6% prevalence of sleep disturbance (n = 342). According to logistic regression, introverted students are 1.77 times more likely than extroverted students to have sleep disturbance (OR = 1.77, 95% CI 1.08-2.91). Medical students with depression had a 5.6-times higher risk of sleep disturbance than those without depression (OR = 5.60, 95% CI 3.43-9.15). Additionally, medical students with anxiety were 3.95 times more likely than those without anxiety to have sleep disturbance (OR = 3.95, 95% CI 2.04-7.64). According to this research, the COVID-19 pandemic caused significant sleep disturbance among medical students. Additionally, among medical students, introversion, anxiety, and depression were risk factors for sleep disturbance.

Depression and active disease are the major risk factors for fatigue and sleep disturbance in inflammatory bowel disease with consequent poor quality of life: Analysis of the interplay between psychosocial factors from the developing world.

The prevalence and risk factors of fatigue and sleep disturbances in inflammatory bowel disease (IBD) patients and their impact on the quality of life (QOL) are largely underreported in the developing world, where IBD is on the rise. Consecutive patients attending the IBD clinic were interviewed between November 2021 and March 2022 using an assisted questionnaire (English, Hindi and Telugu versions)(including demographics, disease activity, QOL, IBD fatigue score [IBD-F], Hospital anxiety and depression score: [HADS], Pittsburg Sleep Quality Index: [PSQI]). Logistic regression was used to identify risk factors of fatigue and sleep disturbance. A correlational analysis between mental health factors and QOL was performed. AS many as 202 IBD patients (age 18-78 [median 31] years, 65.8% male) completed the questionnaires. Fatigue and sleep disturbances were highly prevalent (55.9% and 53.4%, respectively). On multi-variate analysis, depression (p = 0.008, odds ratio [OR] -1.38, 95% confidence interval [CI]-1.09-1.75), active disease (p = 0.001,OR-8.81,95% CI- 2.49-31.23) and poor sleep (p = 0.009, OR-1.17, 95% CI:1.04-1.31) were predictive of fatigue, whereas depression (p < 0.001,OR-1.32,95% CI-1.19-1.46) and active disease (p < 0.001,OR-6.77, 95% CI-2.67-17.17) were predictive of sleep disturbance. On sub-group analysis, poor sleep quality and lack of renumeration predicted fatigue, whereas old age and female gender predicted poor sleep quality in Crohn's disease (CD). QOL (Short IBD questionnaire: [SIBDQ]) scores had a strong and moderate negative correlation with IBD-F (r = -0.735, p < 0.0001) and PSQI (r = -0.682, p < 0.001) scores, respectively. The results should be interpreted in the context of lack of validated translated questionnaires in all native languages in a multilingual country. Translational assistance was provided to overcome the limitation. Fatigue and sleep disturbances are highly prevalent in Indian IBD patients. Apart from modulation of disease activity, screening those with mental health illness may help improve fatigue/sleep quality and overall QOL.

Changes in sleep disturbance among Chinese adolescents: A population-based online survey

ObjectiveSleep disturbance is prevalent among adolescents but little is known about the short-term changes among Chinese adolescents. The study aimed to explore the prevalence and change patterns of sleep disturbance and identify its risk and protective factors. MethodsData were collected online from April 21st to May 12th, 2021 (Time 1, T1) and December 17th to 26th, 2021 (Time 2, T2). The final sample comprised 34,260 adolescents. Self-administrated questionnaires were used to assess socio-demographic variables, sleep disturbance, depression, anxiety, life events, family function, and resilience. ResultsThe prevalence of sleep disturbance was 12.0% at T1 and 11.8% at T2, with higher rates in females than males. Four groups of sleep disturbance change patterns were identified: non-sleep disturbance group (80.4%), persistent group (4.2%), new-onset group (7.6%), and remission group (7.8%). Risk factors for new-onset sleep disturbance included being in junior high school (AOR = 1.26, 95%CI = 1.15–1.38), family history of mental disorders (AOR = 1.49, 95%CI = 1.03–2.15), and moderate (AOR = 1.24, 95%CI = 1.13–1.36) and severe (AOR = 1.48, 95%CI = 1.27–1.72) family dysfunction. Risk factors for persistent sleep disturbance included being in junior (AOR = 1.25, 95%CI = 1.08–1.45) and senior (AOR = 1.53, 95%CI = 1.15–2.03) high school, parental currently unmarried status (AOR = 1.34, 95%CI = 1.05–1.73), moderate (AOR = 1.19, 95%CI = 1.02–1.39) and severe (AOR = 1.28, 95%CI = 1.06–1.55) family dysfunction. Medium (AOR = 0.48, 95%CI = 0.43–0.53) and high (AOR = 0.34, 95%CI = 0.29–0.40) levels of resilience were protective factors against new-onset sleep disturbance, as well as against persistent sleep disturbance (medium level: AOR = 0.51, 95%CI = 0.43–0.60; high level: AOR = 0.32, 95%CI = 0.25–0.43). ConclusionsInterventions aimed at promoting family functions and enhancing resilience may improve sleep disturbance among adolescents.

The Effect of Serotonin Transmission on Depressive and Insomnia Symptoms in Inflammatory Bowel Diseases.

The serotonergic pathway may impact the pathogenesis and the course of inflammatory bowel diseases (IBDs). The aim of this study was to investigate the relationship between 5-HT, the serotonin transporter (SERT), and the clinical course of the disease with the occurrence of sleep and mood disorders. Participants completed sleep questionnaires and the Beck Depression Inventory (BDI). Serum 5-HT, SERT protein expression, and mRNA levels were quantified. Additionally, patients treated with anti-TNF therapy were examined before and after treatment. In this study, 77 patients with IBD and 41 healthy controls (HCs) were enrolled and 24 of them were treated with anti-TNF therapy. Patients with IBD had higher 5-HT levels and SERT protein expression than the HCs, but not mRNA SERT levels (p = 0.015, p = 0.001, p = 0.069, respectively). Similar results were obtained for patients in the active state of the disease compared to the non-active state. There was a positive relationship between insomnia severity and SERT protein expression. BDI did not correlate with serotonin or SERT. After anti-TNF therapy, only 5-HT levels were decreased. 5-HT and SERT protein are overexpressed in active IBD and may represent a candidate for novel disease activity biomarkers. The correlation between the SERT protein level and the severity of insomnia symptoms might be among the underlying biochemical factors of sleep disturbances. Anti-TNF treatment might contribute to the reduction in 5-HT levels.

Multidimensionality of the PROMIS sleep disturbance 8b short form in working adult populations

ObjectivesThe Patient-Reported Outcomes Measurement Information System sleep disturbance measures were developed using item response theory assumptions of unidimensionality and local independence. Given that sleep health is multidimensional, we evaluate the factor structure of the Patient-Reported Outcomes Measurement Information System sleep disturbance 8b short form to examine whether it reflects a unidimensional or multidimensional construct. MethodsSix full-time working adult samples were collected from civilian and military populations. Exploratory and confirmatory factor analyses were conducted. Single-factor and two-factor models were performed to evaluate the dimensionality of sleep disturbance using the 8b short form. Sleep duration and subjective health were examined as correlates of the sleep disturbance dimensions. ResultsAcross six working adult samples, single-factor models consistently demonstrated poor fit, whereas the two-factor models, with insomnia symptoms (ie, trouble sleeping) and dissatisfaction with sleep (ie, subjective quality of sleep) dimensions demonstrated sufficient fit that was significantly better than the single-factor models. Across each sample, dissatisfaction with sleep was more strongly correlated with sleep duration and subjective health than insomnia symptoms, providing additional evidence for distinguishability between the two sleep disturbance factors. ConclusionsIn working adult populations, the Patient-Reported Outcomes Measurement Information System sleep disturbance 8b short form is best modeled as two distinguishable factors capturing insomnia symptoms and dissatisfaction with sleep, rather than as a unidimensional sleep disturbance construct.

Risk prediction of sleep disturbance in clinical nurses: a nomogram and artificial neural network model

BackgroundSleep disturbance occur among nurses at a high incidence.AimTo develop a Nomogram and a Artificial Neural Network (ANN) model to predict sleep disturbance in clinical nurses.MethodsA total of 434 clinical nurses participated in the questionnaire, a cross-sectional study conducted from August 2021 to June 2022.They were randomly distributed in a 7:3 ratio between training and validation cohorts.Nomogram and ANN model were developed using predictors of sleep disturbance identified by univariate and multivariate analyses in the training cohort; The 1000 bootstrap resampling and receiver operating characteristic curve (ROC) were used to evaluate the predictive accuracy in the training and validation cohorts.ResultsSleep disturbance was found in 180 of 304 nurses(59.2%) in the training cohort and 80 of 130 nurses (61.5%) in the validation cohort.Age, chronic diseases, anxiety, depression, burnout, and fatigue were identified as risk factors for sleep disturbance. The calibration curves of the two models are well-fitted. The sensitivity and specificity (95% CI) of the models were calculated, resulting in sensitivity of 83.9%(77.5–88.8%)and 88.8% (79.2–94.4%) and specificity of83.1% (75.0–89.0%) and 74.0% (59.4–84.9%) for the training and validation cohorts, respectively.ConclusionsThe sleep disturbance risk prediction models constructed in this study have good consistency and prediction efficiency, and can effectively predict the occurrence of sleep disturbance in clinical nurses.

Prediction of risk factors of sleep disturbance in patients undergoing total hip arthroplasty.

The purpose of this study was to assess sleep quality in patients undergoing total hip arthroplasty (THA) from preoperatively to 12weeks postoperatively and to establish a risk predictor for postoperative sleep disturbance to enable early care and intervention. A self-designed data collection form was used. Patients were assessed preoperatively and at 5 postoperative time points using visual analog scale (VAS) for pain, sleep quality and neuropsychological status with the following assessment tools: the Chinese versions of the Pittsburgh Sleep Quality Index (CPSQI), the Epworth Sleepiness Scale (CESS), the Zung Self-Rating Anxiety Scale (ZSAS) and the Epidemiological Studies Depression Scale (CESD). Univariate and multivariate logistic regression analysis was used for the identification of risk factors for postoperative sleep disturbance. The receiver operating characteristic (ROC) curve was plotted to evaluate the regression model. Of the 290 eligible patients, 193 (133 women) were included in the study. There was a 60.6% prevalence of preoperative sleep disturbance. The CPSQI score increased significantly at 2weeks postoperatively compared to preoperative baseline, but appeared to decrease at 4weeks postoperatively. Multivariate logistic regression analysis showed that pain (VAS score: OR = 1.202 [95% CI = 1.002-1.446, P < 0.05]), daytime sleepiness (CESS score: OR = 1.134 [95% CI = 1.015-1.267, P < 0.05]) and anxiety (ZSAS score: OR = 1.396 [95% CI = 1.184-1.645, P < 0.001]) were risk factors associated with postoperative sleep disturbance at 2weeks. The ROC curve showed that the AUC was 0.762, the sensitivity was 83.19% and the specificity was 64.86%. Postoperative sleep disturbance is highly prevalent in the first 2weeks after THA. The risk prediction model constructed according to the above factors has good discriminant ability for the risk prediction of sleep disturbance after THA. The use of this risk prediction model can improve the recognition of patients and medical providers and has good ability to guide clinical nursing observation and early screening of sleep disturbance after THA.

Influencing factors for Sleep Disturbance in the Intensive Care Unit Patients: A Systematic Review

Purpose : Sleep disturbances in patients in the intensive care unit (ICU) are related to health problems after discharge. Therefore, active prevention and management are required. Hence, identification of the factors that affect sleep in patients who are critically ill is necessary.Methods : The PubMed, Cochrane Library, CINAHL, EMBASE, and Web of Science databases were searched. Selection criteria were observational and experimental studies that assessed sleep as an outcome, included adult patients admitted to the ICU, and published between November 2015 and April 2022.Results : A total of 21,136 articles were identified through search engines and manual searches, and 42 articles were selected. From these, 22 influencing factors and 11 interventions were identified. Individual factors included disease severity, age, pain, delirium, comorbidities, alcohol consumption, sex, sleep disturbance before hospitalization, chronic obstructive pulmonary disease (COPD), cardiovascular disease, and high diastolic blood pressure (DBP), low hemoglobin (Hb), and low respiratory rate (RR). Environmental factors included light level, noise level, and temperature. Furthermore, treatment-related factors included use of sedatives, melatonin administration, sleep management guidelines, ventilator application, nursing treatment, and length of ICU stay. Regarding sleep interventions, massage, eye mask and earplugs, quiet time and multicomponent protocols, aromatherapy, acupressure, sounds of the sea, adaptive intervention, circulation lighting, and single occupation in a room were identified.Conclusion : Based on these results, we propose the development and application of various interventions to improve sleep quality in patients who are critically ill.

Sleep during and following critical illness: A narrative review.

Sleep is a complex process influenced by biological and environmental factors. Disturbances of sleep quantity and quality occur frequently in the critically ill and remain prevalent in survivors for at least 12 mo. Sleep disturbances are associated with adverse outcomes across multiple organ systems but are most strongly linked to delirium and cognitive impairment. This review will outline the predisposing and precipitating factors for sleep disturbance, categorised into patient, environmental and treatment-related factors. The objective and subjective methodologies used to quantify sleep during critical illness will be reviewed. While polysomnography remains the gold-standard, its use in the critical care setting still presents many barriers. Other methodologies are needed to better understand the pathophysiology, epidemiology and treatment of sleep disturbance in this population. Subjective outcome measures, including the Richards-Campbell Sleep Questionnaire, are still required for trials involving a greater number of patients and provide valuable insight into patients' experiences of disturbed sleep. Finally, sleep optimisation strategies are reviewed, including intervention bundles, ambient noise and light reduction, quiet time, and the use of ear plugs and eye masks. While drugs to improve sleep are frequently prescribed to patients in the ICU, evidence supporting their effectiveness is lacking.

0164 Move Your Feet and Sleep: A Longitudinal Dynamic Analysis of Physical Activity, Sedentary Behavior, and Insomnia Symptoms

Abstract Introduction Insomnia symptoms, which include sleep disturbances and daytime dysfunction, are associated with poor physical and mental health. Physical activity has been associated with good sleep while sedentary behavior has been associated with poor sleep. This study investigated whether physical activity and sedentary behavior are associated with insomnia symptoms both generally (i.e., between-persons, mean-level) and dynamically (i.e., within-persons, person-centered). Methods Participants (N=775) included adults (Mage=47.3 years,54.6% female) who completed an online longitudinal study investigating sleep and health across the lifespan at three time points (approximately 17-weeks apart). Participants reported: (a) their duration of moderate-to-vigorous physical activity per week (in minutes), (b) the percentage of their day spent sedentary, and (c) their insomnia symptoms via the Insomnia Severity Index which was scored according to traditional standards (i.e., total score) as well as proposed two factor scores: (1) Sleep Disturbance (items 1,2,3) and (2) Daytime Dysfunction (items 4,5,6,7). Multilevel modeling was used to examine the associations among physical activity, sedentary behavior, and insomnia symptoms at both between- and within-persons levels. Results No significant associations were observed among total ISI score or the factor scores, and minutes spent in moderate-to-vigorous physical activity (all p’s&amp;gt;.05). Sedentary behavior, however, was significantly associated with total ISI score at both the between-person and within-person levels (β=.02, t=2.71, p=.007; β=0.03, t=2.62, p=.009, respectively). For the Sleep Disturbance factor, between-person sedentary behavior was not a significant predictor while within-person sedentary behavior was associated with higher sleep disturbance scores (β=0.01, t=1.16, p=.245; β=.01, t=2.06, p=.039, respectively). For the Daytime Dysfunction factor, both between-persons and within-person levels of sedentary behavior were associated with increased daytime dysfunction (β=.02, t=3.30, p=.001; β=.01, t=2.53, p=.012). Conclusion Sedentary behavior appears to be a more robust predictor of insomnia symptoms than physical activity. Further, the association between sedentary behavior and insomnia symptoms was observed to be dynamic in that when an individual reported being more sedentary than customary, they also reported more insomnia symptoms. Future analyses should consider demographic variables and comorbid conditions to identify subgroups in which these associations are most pronounced. Support (if any) National Institute on Aging of the National Institutes of Health under Award Number K23AG049955 (PI: Dzierzewski).

Роль родительских представлений о своем сне и сне ребенка в регуляции сна и бодрствования у детей 5—13 лет: культурно-исторический подход в психосоматике

&lt;p&gt;From perspective of cultural-historical approach in psychosomatics, the psychological regulation of a child's sleep and wakefulness is developed in children in interaction with significant adults. The aim was to reveal the relationship between dysfunctional beliefs of parents about their own sleep and its vulnerability as well as their violations of sleep hygiene and parental beliefs about the sleep of their children aged 5-13, the beliefs of the children about their sleep and their quality of sleep and wakefulness. 147 pairs of "parent-child 5-13 years old without diagnosed sleep disorders" participated (47 pairs with a child 5-6 years old, 49 pairs with a child 7-9 years old, 51 pairs with a child 10-13 years old). Parents answered questions about their child's sleep pattern, filled children's sleep habits questionnaire, dysfunctional beliefs about sleep and sleep vulnerability scales about their own and their child's sleep, insomnia severity index, and a scale of behavioral factors of sleep disturbances about their own sleep. Children answered the questions of children's self-report about their sleep, dysfunctional beliefs about and vulnerability of their sleep scales, pediatric sleepiness scale. According to the analysis of mediation, dysfunctional perceptions of parents about their own sleep are indirectly associated with sleepiness and sleep difficulties in children, since they increase the likelihood of the same perceptions of parents about their children's sleep. Sleepiness, according to the children appraisals, is additionally indirectly related to the dysfunctional beliefs of parents about their sleep through the mediation of the child's beliefs about their sleep. Parents' beliefs about their sleep vulnerability are associated with children's poorer sleep and sleepiness, as they increase the likelihood of the child's sleep vulnerability beliefs, which, in turn, increase the likelihood of the child's own perceptions of the vulnerability of his sleep. The data are consistent with the perspective of the psychology of physicality about the development of the psychological regulation of sleep and wakefulness of the child in interaction with significant adults.&lt;/p&gt;

Alterations in Sleep Cycle among Nonhospitalized COVID-19-Affected Population during the Pandemic in Karnataka State—A Web-Based Study

Abstract Objectives The psychological and physiological distress and social isolation could adversely affect sleep. As sleep disturbances may persist and deteriorate health, it is important to assess prevalence and related factors of sleep disturbances among the residents of Karnataka state during the coronavirus disease 2019 (COVID-19) infection. Methods In this study, 250 responders across the state of Karnataka accessed the survey voluntarily during September 2021 and January 2022. Pittsburgh Sleep Quality Index, Insomnia Severity Index scales, features that are related to sleep quality, and some hypothesized risk factors of sleep disturbances in context of COVID-19 infection are employed to format a self-reported questionnaire. Results In this study, females 27(19.1%) experienced more sleep disturbances than males 9 (8.3%). The study revealed the participants who received both the doses of vaccination (126; 54.3%) had better sleep. The participants who reported themselves to be stressed (182; 72.8%) had more disturbances in sleep. A total number of 45 participants (18.4%) experienced difficulty in breathing and out of all the responders 11 (47.8%) were actually worried about their current sleep problem. Conclusion COVID-19 infection and changes imposed during the pandemic have led to a surge in individuals reporting sleep problems across the globe. The findings raise the need to screen for worsening sleep patterns to create more awareness about the secondary consequences of COVID-19 infection.