Significant Predictors Of Sleep Quality Research Articles

Factors related to sleep quality in hospitalized antepartum women: A cross-sectional study.

This study investigated the sleep quality and its psychological correlates among hospitalized antepartum women. A cross-sectional correlation study design and convenience sampling were conducted in the gynecological ward of a medical center in northern Taiwan. A total of 101 hospitalized antepartum women were recruited. A self-administered structured questionnaire including demographic profiles, State-Trait Anxiety Inventory (STAI), Antepartum Hospital Stressors Inventory (AHSI), and Pittsburgh Sleep Quality Index (PSQI) was used for the study. Bivariate and multiple linear regressions were used to analyze the data. A majority of the participants had poor sleep quality (82.8%), based on the global PSQI score. Sleep quality correlated with age, marital and employment status, parity, method of conception, multiple gestation, history of pregnant complications, anxiety symptom and hospital stressors which explained 21% of the variance in sleep quality. This study found a high prevalence of poor sleep quality in hospitalized antepartum women. Anxiety symptom was a significant predictor of sleep quality. Healthcare providers should be encouraged to assess sleep and emotional status in antepartum women during hospitalization and provide them appropriate interventions to improve sleep and reduce anxiety symptoms and hospital stressors.

Factors associated with sleep quality in patients undergoing cardiac surgery: A longitudinal study.

Poor sleep quality is associated with multiple factors in cardiac surgery patients. To examine the trajectory of sleep quality and its associated factors over 3 months in Taiwanese patients undergoing cardiac surgery. A longitudinal study. This study enrolled 95 patients undergoing cardiac surgery in northern Taiwan. Sleep quality was measured using the Pittsburgh Sleep Quality Index and Epworth Sleepiness Scale before surgery, at discharge, and at 1 month and 3 months postsurgery. The majority of participants reported poor sleep quality before cardiac surgery (76.8%) and at discharge (81.6%), and they showed significant improvements in sleep quality at 1 month (B = -0.93, p = .023) and 3 months postsurgery (B = -1.50, p < .001). Significant daytime sleepiness was reported by 25.3% of patients before cardiac surgery, and this proportion significantly decreased at 3 months postsurgery (B = -2.59, p < .001). The significant predictors of sleep quality in cardiac surgery patients were symptom distress, sleep medications, occupation, left ventricular ejection fraction, ACE-I drugs and potassium ions, which explained 53.7% of the total variance in sleep quality. Having a nap habit was an independent predictor of daytime sleepiness in cardiac surgery patients, which could explain 3.7% of the total variation. Poor sleep quality was common in patients undergoing cardiac surgery and was associated with multiple factors, including symptom distress, cardiac function, medications, and psychosocial and environmental factors. Poor sleep quality was observed in cardiac surgical patients before surgery and at discharge postsurgery. Patient education on symptom management, medication adherence and sleep hygiene are suggested to improve sleep quality in patients undergoing cardiac surgery.

Sleep quality and psychological disorders in breast cancer female patients receiving radiotherapy at a tertiary oncology center in West Saudi Arabia.

Breast cancer is the most prevalent type of cancer among women worldwide. Many recently diagnosed and treated breast cancer patients complain about sleep disorders, depression, anxiety, stress, and fatigue. This study aimed to evaluate sleep quality among breast cancer patients and to assess its association with psychological disorders, and socio-demographic and clinical characteristics of patients. This cross-sectional study was conducted among women who received radiotherapy for breast cancer (stage 1-3) at King Abdul-Aziz Medical City-Jeddah from January to August 2021. Each participant completed a personal information form, the Pittsburgh Sleep Quality Index (PSQI), the Depression, Anxiety, and Stress Scale-21 (DASS-21), and the International Physical Activity Questionnaire (IPAQ). Clinical data were collected from the medical records to evaluate certain risk factors. Descriptive statistics were used for participant characteristics, and analyses of variance were used to assess associations between the qualitative variables. Fifty-six women with a mean age of 50.1years and an average of 10months after cancer diagnosis were included. Poor sleep quality was present in 58% of respondents. Symptomatic depression, anxiety, and stress were found in 34%, 32%, and 30% of women, respectively. Poor sleep quality was associated with depression (p = 0.031), anxiety (p = 0.03), and stress (p = 0.024) and was independently associated with hot flashes. In multivariate analysis, patients with depression or withcancer for more than 6months were less likely to have good sleep after controlling other variables (21.74 and 14.71 times, respectively). Poor sleep quality was present in 58% of women with breast cancer receiving radiotherapy and was significantly associated with depression, anxiety, stress, and hot flashes. Depression level and cancer duration were significant predictors of sleep quality. Early identification and proper management of psychological and sleep disorders are necessary to improve the quality of life and survival of breast cancer patients.

Is There a Link Between Sleep Quality and a Tendency for Eating Disorders?

Aim: Poor sleep quality has been associated with an increased risk of developing eating disorders, and unhealthy eating behaviours. The aim of the study was to explore the potential link between sleep quality and eating disorders. Subjects and Method: This descriptive, observational, and cross-sectional study was conducted with 357 (84 male; 273 female) university students between the ages of 18-25 years. Exclusion criteria included being diagnosed with chronic disease and psychiatric disorders, being pregnant and lactating, using drugs that affect sleep patterns, being shift workers, and participants who did not complete the questionnaire. The questionnaire consisted of six parts including Pittsburgh Sleep Quality Index (PSQI), Three-Factor Eating Questionnaire (TFEQ-21), SCOFF (REZZY) Eating Disorders Scale, anthropometric measurements, demographic properties, and nutritional habits. Results: The prevalence of poor sleep quality was found to be 63% and there was no significant difference between gender in terms of sleep quality (p=0.769). There was significant relationship between total TFEQ 21 (p=0.02), SCORF (REZZY) (p&lt;0.001) scores and sleep quality. Uncontrolled eating behaviours was found higher in students with poor sleep quality (p&lt;0.05). Age, body mass index (kg/m2), and smoking were not significant predictors of sleep quality. However, participants with a tendency towards eating disorders behaviour were found to have a significantly higher risk of poor sleep quality (odds ratio [OR]: 2.338, 95% confidence interval [CI]: 1.444-3.785, p=0.001), as were those with a tendency towards emotional eating behaviour (OR: 1.575, 95% CI: 1.022-2.427, p=0.040). Conclusion: Students with poor sleep quality had higher levels of uncontrolled eating behaviour and a tendency towards unhealthy eating attitudes than those with good sleep quality.

뇌졸중 집중치료실에 입원한 환자의 환경적 스트레스와 수면의 질의 관계

Purpose : The aim of this research was to identify the mediating effect of sleep disturbance on the relationship between environmental stress and sleep quality in stroke patients admitted to the stroke intensive care unit.&#x0D; Method : The participants in the study were 99 patients, the analysis was based on Baron and Kenny’s model to examine the mediating effects of sleep disturbance on the relationship between environmental stress and sleep quality of stroke patients.&#x0D; Result : In the first and second step, environmental stress was identified as a significant predictor of sleep disturbance (β＝.45, p＜.001) and sleep quality (β＝-.32, p＝.001). In the third step, sleep disturbance (β＝-.23, p＝.001) was observed as a significants predictor of sleep quality, and the direct relationship between environmental stress and sleep quality was significant (β＝-.22, p＝.001). Sleep disturbance was found to exhibit a complete mediating effect on the relationship between environmental stress and sleep quality.&#x0D; Conclusion : The result of this study suggests that strategies for managing the sleep quality of stroke patients should include effective ways to manage environmental stress and sleep disturbance.

The Role of Physical Activity on the Relationships Between Pain, Anxiety, and Sleep Quality in Older Age.

Sleep quality is associated with a range of negative outcomes in older adults, including a higher risk for cognitive decline, greater disability, and poorer quality of life. Pain and anxiety are both important factors associated with poor sleep quality. Physical activity (PA) is frequently recommended to enhance sleep quality and may have additional benefits for pain and anxiety symptoms. However, current models have not examined the interplay among these factors in relation to sleep quality in older adults. We examined survey data from a community sample of 281 older adults (aged 55-98years). Bootstrapped mediation and moderated mediation models using the PROCESS macro in SPSS were used to analyze indirect pathways from pain and anxiety to sleep quality and the conditional effects of exercise. Higher levels of pain and anxiety were significantly and independently associated with poorer sleep quality in older adults. The effect of pain on sleep quality was partially mediated by anxiety symptoms. PA significantly moderated the effects of anxiety on sleep quality, while it did not significantly impact the relationship between pain and sleep quality. The overall indirect effect was not moderated byPA. Pain and anxiety are both significant predictors of sleep quality in older adults, and pain influences sleep quality in older adults partially through its influence on anxiety symptoms. PA may be beneficial for sleep quality for individuals with high anxiety, but patients may see fewer benefits from PA if sleep problems are primarily related to pain.

Habilitation of sleep problems among mothers and their children with autism spectrum disorder: Insights from multi-level exploratory dyadic analyses.

Few habilitation strategies for children with autism spectrum disorder (ASD) consider their sleep-related problems. Together with the fact that caregivers of children with ASD also face issues with sleep, there may be yet-to-be uncovered relationships between caregiver-child sleep patterns and sleep quality, offering a key opportunity for clinicians to consider the needs of both child and caregiver in terms of sleep. 29 dyads of mothers and their children with ASD were recruited for this cohort study and both subjective (self-report questionnaires and sleep diaries) and objective (cortisol samples and actigraphy) measures of sleep were collected to investigate significant predictors of sleep quality. Comparative, correlational, and hierarchical analyses were conducted. Findings indicated that both mother and child experience sleep deprivation in terms of shorter sleep duration and poor sleep quality in terms of longer sleep onset latencies and a higher frequency of wake bouts. Exploratory hierarchical analyses also found that child-related sleep difficulties such as sleep disordered breathing and night waking significantly predict mothers’ sleep quality, which may point to the bi-directional influence of mother-child sleep. Based on these findings, it is recommended that clinicians adopt a family systems perspective and consider the sleep environment of the household, particularly that of the caregiver and child, when designing interventions for sleep-related problems in ASD. Finally, there is a need for additional support to promote good quality sleep among caregivers of children with ASD to bolster out-of-clinic care.

Social support predicts sleep quality in people with multiple sclerosis during the COVID-19 pandemic

BackgroundPoor sleep quality is one of the most prominent patient-reported problems in people with multiple sclerosis (PwMS). The COVID-19 pandemic resulted in PwMS having less contact with physicians, therapists, support groups, and family, which led to decreased access to typical supports. The purpose of this study was to assess how social support impacted sleep quality during the COVID-19 pandemic in PwMS within the United States. MethodsAnonymous surveys were utilized to gather data from February – May 2021 from 209 PwMS during their return appointments (face-to-face and virtual) at the University of Kansas Medical Center (KUMC)’s MS Clinic in the United States. SPSS 27 was used to run four regressions in order to determine if social support predicted sleep quality with and without the inclusion of covariates (age, education, disability, anxiety/depression). ResultsThe results indicate that overall feelings of being socially supported predict sleep quality. Additionally, various facets of social support predict sleep quality, even when controlling for covariates. Interestingly, while depression and anxiety were significant predictors of sleep quality, those constructs do not attenuate the social support—sleep relationship. ConclusionThese findings will provide key information pertaining to the association between social support and sleep in PwMS during COVID-19 where typical supports were limited. Understanding the challenges facing those living with chronic illnesses, specifically PwMS, will help researchers and clinicians alike create interventions to promote social support in the midst of a global pandemic.

Frontal white matter association with sleep quality and the role of stress.

An important measure of brain health is the integrity of white matter connectivity structures that link brain regions. Studies have found an association between poorer sleep quality and decreased white matter integrity. Stress is among the strongest predictors of sleep quality. This study aimed to evaluate the association between sleep quality and white matter and to test if the relationship persisted after accounting for stress. White matter microstructures were measured by diffusion tensor imaging in a population of Old Order Amish/Mennonite (N=240). Sleep quality was determined by the Pittsburgh Sleep Quality Index. Current stress levels were measured by the perceived stress scale. Exposure to lifetime stress was measured by the lifetime stressor inventory. Microstructures of four white matter tracts: left and right anterior limbs of internal capsule, left anterior corona radiata, and genu of corpus callosum were significantly correlated with sleep quality (all p ≤ 0.001). The current stress level was a significant predictor of sleep quality (p ≤ 0.001) while lifetime stress was not. PSQI remained significantly associated with white matter integrity in these frontal tracts (all p < 0.01) after accounting for current stress and lifetime stress, while current and lifetime stress were not significant predictors of white matter in any of the four models. Sleep quality did not have any substantial mediation role between stress and white matter integrity. Sleep quality was significantly associated with several frontal white matter tracts that connect brain structures important for sleep regulation regardless of current or past stress levels.

Prevalence and Predictors of Restless Leg Syndrome in Adolescents and Young Adults of Bengaluru City, India: A Cross-Sectional Study

Introduction: Restless leg syndrome (RLS) is a sensorimotor disease characterized by an urge to move the legs, often caused by uncomfortable and unpleasant sensations in the legs. It affects the quality of sleep which in turn affects scholastic performance in children and predisposes them to cardiovascular diseases in the long run. Hence, the primary aim of this study was to assess the prevalence and predictors of RLS, poor sleep quality, and excessive daytime sleepiness (EDS). Methods: This was a cross-sectional observational study conducted between September 2017 and March 2020 in Bengaluru, India, including all consenting PreUniversity College, Degree College, and Higher Secondary school students. After parental consent and assent (if applicable) was obtained, a semi-structured standardized pilot-tested questionnaire consisting of the RLS diagnostic criteria, Pittsburgh Sleep Quality Index (PSQI), Epworth sleepiness scale, and questions on sleep hygiene was administered. The prevalence was expressed as proportions and 95% confidence intervals (95% CI). Regression analysis was done to determine the predictors. Results: The overall prevalence (95% CI; frequency) of students with RLS, poor sleep quality, and EDS in our study population was 8.36% (7.54, 9.24; n = 1,544/4,211), 36.67% (35.21, 38.14; n = 1,544/4,211), and 39.87% (38.39, 41.37; n = 1,679/4,211), respectively. PSQI and Epworth score were the significant predictors of RLS. Age, Epworth score, knowledge score, and the number of unacceptable sleep habits were the significant predictors of sleep quality. Female gender, PSQI, RLS, knowledge score, and the number of unacceptable sleep habits were the significant predictors of EDS. Conclusions: The prevalence of RLS, those with poor sleep quality and EDS among adolescents and young adults was higher when compared to the historical data of general population in the same city.

Relationship between Walking Activity and Sleep Quality among Community-Dwelling Older Adults

Purpose To explore the relationship between walking activity and sleep quality among elderly. Design A cross-sectional, correlation study with purposive sampling was conducted on participants with a walking habit but not regular moderate-intensity exercise. Methods Data were collected by structured questionnaires, including the Walking Activity Questionnaire and the Pittsburgh Sleep Quality Index. Findings The total walking time per week and frequency of walking per day were significant predictors of sleep quality. Conclusions Walking can help older community-dwelling adults improve their sleep quality. Clinical evidence Walking more than once per day and total walking time per week ≥210 minutes were associated with good sleep quality.

The Relationship Between Resilience and Sleep Quality During the Second Wave of the COVID-19 Pandemic: A Longitudinal Study.

PurposePrevious studies showed poor sleep quality during the first Italian lockdown consequent to the quick spread of the virus. Poor sleep quality remained stable during the so-called “second wave”, which started in Autumn 2020. This study aimed to compare sleep quality between the two waves of contagions and to examine the effect of resilience, together with sociodemographic and COVID-related variables, on sleep quality during the second wave.Patients and MethodsA total of 648 participated in this longitudinal study through an online survey during the first lockdown consequent to the COVID-19 and during the second wave. The Medical Outcomes Study—Sleep Scale (MOS-SS) and the Resilience Scale (RS) were administered. Sociodemographic and COVID-related information were also collected.ResultsThe results showed sleep quality slightly increased in the second wave, even though with a small effect size. Correlational analysis showed that resilience is inversely correlated with sleep quality measured in the two waves. Sleep quality during the second wave was positively correlated with sleep quality in the first lockdown. Likewise, the results of multiple regression revealed that the sleep quality in the first lockdown and resilience were significant predictors of sleep quality during the second wave.ConclusionThese findings highlighted that the prevalence of poor sleepers remained high during the second wave. Together with the sleep quality in the first lockdown, resilience represents an important factor related to sleep quality during the second wave. Interventions to improve sleep quality among the general population should take into account these findings.

The Impact of COVID-19 on Sleep Quality in People Living With Disabilities

Background: Research exploring the impact of the COVID-19 pandemic on sleep in people with disabilities has been scarce. This study provides a preliminary assessment of sleep in people with disabilities, across two timepoints during the pandemic, with a focus on those with visual impairment (VI).Methods: Two online surveys were conducted between April 2020 and March 2021 to explore sleep quality using the Pittsburgh Sleep Quality Index (PSQI). A convenience sample of 602 participants completed the first survey and 160 completed the follow-up survey.Results: Across both timepoints, participants with disabilities reported significantly poorer global sleep quality and higher levels of sleep disturbance, use of sleep medication and daytime dysfunction than those with no disabilities. Participants with VI reported significantly higher levels of sleep disturbance and use of sleep medication at both timepoints, poorer global sleep quality, sleep duration and latency at time 1, and daytime dysfunction at time 2, than those with no disabilities. Global sleep quality, sleep duration, sleep efficiency, and self-rated sleep quality deteriorated significantly in participants with no disabilities, but daytime dysfunction increased in all three groups. Disability and state anxiety were significant predictors of sleep quality across both surveys.Conclusion: While sleep was consistently poorer in people with disabilities such as VI, it appears that the COVID-19 pandemic has had a greater impact on sleep in people with no disabilities. State anxiety and, to a lesser extent, disability, were significant predictors of sleep across both surveys, suggesting the need to address anxiety in interventions targeted toward improving sleep.

Relationship between Personality and Sleep Quality of Young Adults: A Correlational Study

The purpose of the present study was to determine the relationship between the big five factors of personality and the domains of sleep quality, and to assess the difference, if any, in the personality factors and sleep quality of male and female young adults. Convenient sampling and snowball sampling techniques were used to gather a sample of 565 young adults (Females: 293; Males: 270; Prefer not to say: 2), aged between 18 to 25 years, all of whom were residents of West Bengal. The Big Five Inventory (BFI) and the Pittsburgh Sleep Quality Index (PSQI) were employed to collect data and measure the variables under study. The obtained data was analyzed using Pearson’s Product Moment Correlation (r), Independent sample t test, Mann-Whitney U test and Multiple Regression Analysis. The results imply that all the personality factors (i.e., Extraversion, Agreeableness, Conscientiousness and Neuroticism), except that of Openness to experience, are significantly correlated with sleep quality. The same four personality factors (i.e., Extraversion, Agreeableness, Conscientiousness and Neuroticism) are also found to be significant predictors of sleep quality. Component 1 (Subjective sleep quality), component 5 (Sleep disturbances) and component 7 (Daytime Dysfunction) were found to bear a correlation with all the mentioned four factors of personality, thereby, contributing majorly to the significant relationship between personality and sleep quality. Hence, personality of an individual plays a considerable role in determining one’s sleeping patterns and quality of sleep. The gender difference is prevalent in sleep quality as female young adults are found to have poorer sleep quality than their male counterparts. However, it has little impact on personality as only Neuroticism is found to be considerably higher in females than in males.

Psychological Distress Prospectively Predicts Later Sleep Quality in a Sample of Black American Postpartum Mothers

ABSTRACT Objective: Previous longitudinal studies have demonstrated prospective relationships between maternal sleep quality and subsequent psychological distress in the postpartum period. Despite evidence for prospective relationships between mood and subsequent sleep quality in adult populations, this direction has not been examined in postpartum women. We aimed to test prospective relationships between sleep quality and subsequent psychological distress, as well as the plausible reverse possibility, in a sample of Black American postpartum mothers (n = 146). Participants: Mothers were recruited prenatally from two hospitals in a Southeastern city of the United States. Eligible and interested mothers enrolled in a follow-up study on infant development. Data from the current study were obtained during the follow-up study. Method: Mothers reported on their psychological distress (i.e., anxiety, depression, stress) and sleep quality at 3- and 6-months postpartum. We performed hierarchical linear regressions to explore whether 1) maternal sleep quality at 3-months postpartum would predict maternal psychological distress at 6-months postpartum, after adjustment for mothers’ earlier psychological distress, and 2) whether psychological distress at 3-months postpartum would predict maternal sleep quality at 6-months postpartum, after adjustment for mothers’ earlier sleep quality. Results: Maternal sleep quality at 3-months postpartum was not a significant predictor of psychological distress at 6-months postpartum. However, maternal psychological distress at 3-months postpartum was a significant predictor of sleep quality at 6-months postpartum. Conclusions: Mothers’ psychological distress earlier in the postpartum was a significant predictor of their later sleep quality. Replication is needed in large, prospective studies, with results stratified by race/ethnicity.

Prevalence and Correlates of Sleep Quality Among Jordanian University Students: A Cross-Sectional National Study.

Poor sleep quality affects university students' life and increases their risk of long-term health consequences. This study aimed to describe the quality of sleep among Jordanian university students, examine differences in sleep quality according to selected variables, and identify predictors of sleep quality. A cross-sectional correlational design and a multi-strategic sampling technique were used to select a sample of 1,308 university students. The Pittsburgh Sleep Quality Index, the Perceived Stress Scale, and the Sleep Hygiene Instrument were administered to the subjects. T-test, ANOVA, and multiple regressions were used to analyze the data. The results showed that most students were classified as poor sleepers (87.1%), and only (12.8%) reported having a good sleep quality. Among the components of sleep quality, subjective sleep quality (m = 1.90, SD = 0.89) and daytime dysfunction (m = 1.72, SD = 0.67) had the highest mean scores, while sleep efficiency (m = 0.50, SD = 0.91) and the use of sleep medications (m = 0.23, SD = 0.73) had the lowest mean scores. There were statistically significant differences in sleep quality in relation to residency, academic level, academic achievement, and family income. Significant predictors of sleep quality were gender, marital status, employment status, sleep hygiene, and stress.

0239 Mindfulness Moderates the Relationship Between Lucid Dreaming, Nightmare Distress, and Sleep Quality

Abstract Introduction Nightmares can cause poorer sleep quality. Various mechanisms have been explored as potential treatments for nightmares, including mindfulness practices and lucid dreaming. Presently, little literature has looked at the interaction effects between mindfulness and lucid dreaming to reduce nightmare distress. Methods A sample of 275 individuals was recruited from both the United States and Thailand via social media and a student pool of research subjects at UNC Charlotte. Data were recorded on participants’ demographic information, lucid dreaming from the Lucidity and Consciousness in Dreams Scale (Voss et al., 2013), Mindfulness using the Five Facet Mindfulness Questionaire (Baer et al., 2006), Nighmares via the Nightmare Distress Questionaire (Belicki, 1992), and sleep quality using the Pittsburgh Sleep Quality Index (PSQI; Buysse et al., 1989). Higher scores on each measure were associated with more lucid dreaming, more mindful behaviors, more severe nightmares, and poorer sleep quality. PROCESS model 8 was run to conduct a moderated mediation analysis (Hayes, 2018). Lucid dreaming was used as the predictor; sleep quality as the outcome variable, nightmare distress as the mediator and mindfulness acted as a moderator on both the direct and indirect pathway of lucid dreaming onto the mediator and outcome. Results Mindfulness was a significant predictor at both the mediator and outcome variables. Nightmare distress was a significant predictor of sleep quality. A statistical trend (p=.054) suggests lucid dreaming may have a positive effect on nightmare distress. In the indirect path, lucid dreaming had a positive effect on PSQI scores only for individuals with low mindfulness. Conclusion The moderated mediation suggests that individuals with low mindfulness may see a decrease in sleep quality from lucid dreaming. This could be due to lucid dreaming being associated with more severe nightmares. A zero-effect size could not be ruled out of the confidence intervals for individuals of average or high mindfulness, but the data suggest that lucid dreaming alone may not help treat nightmares, but the combination of lucid dreaming and mindfulness therapies could promote lower distress and better sleep quality. Support Psychological Sciences departmental funding

Vitamin D Deficiency and Sleep Quality in Minority Pregnant Women.

To examine if vitamin D deficiency was associated with poor sleep quality in a sample of African American and Hispanic pregnant women. We also examined if race moderates the relationship between serum 25(OH)D levels and sleep quality among participants in this sample. Using a cross-sectional design, a sample of 115 African American and Hispanic pregnant women were enrolled from a federally qualified health center in the Midwest. Women completed questionnaires and had blood drawn for serum 25(OH)D levels between 24- and 32 weeks gestation. The questionnaires included demographic characteristics, the Pittsburgh Sleep Quality Index, and dietary vitamin D and calcium intake. The overall regression model indicated that the predictors explained 17% of variance in sleep quality (F(5, 103) = 4.10, p = .002, R = 0.17). Serum 25(OH)D levels were significant predictors of sleep quality after controlling for covariates (i.e., race, maternal age, prepregnancy body mass index, gestational age at data collection). Race did not moderate the association between serum 25(OH)D levels and sleep quality among women in this sample. Pregnant women should be screened for vitamin D deficiency. Women who have vitamin D deficiency should be provided vitamin D supplementation. Vitamin D supplementation may be a simple solution to enhance sleep quality at this critical time in a woman's life.

The music that helps people sleep and the reasons they believe it works: A mixed methods analysis of online survey reports.

Sleep loss is a widespread problem with serious physical and economic consequences. Music can impact upon physical, psychological and emotional states, which may explain anecdotal reports of its success as an everyday sleep aid. However, there is a lack of systematic data on how widely it is used, why people opt for music as a sleep aid, or what music works; hence the underlying drivers to music-sleep effects remain unclear. We investigated music as a sleep aid within the general public via a mixed methods data online survey (n = 651) that scored musicality, sleep habits, and open text responses on what music helps sleep and why. In total, 62% of respondents stated that they used music to help them sleep. They reported fourteen musical genres comprising 545 artists. Linear modelling found stress, age, and music use as significant predictors of sleep quality (PSQI) scores. Regression tree modelling revealed that younger people with higher musical engagement were significantly more likely to use music to aid sleep. Thematic analysis of the open text responses generated four themes that described why people believe music helps sleep: music offers unique properties that stimulate sleep (Provide), music is part of a normal sleep routine (Habit), music induces a physical or mental state conducive to sleep (State), and music blocks an internal or external stimulus that would otherwise disrupt sleep (Distract). This survey provides new evidence into the relationship between music and sleep in a population that ranged widely in age, musicality, sleep habits and stress levels. In particular, the results highlight the varied pathways of effect between music and sleep. Diversity was observed both in music choices, which reflected idiosyncratic preferences rather than any consistent musical structure, and in the reasons why music supports good sleep, which went far beyond simple physical/mental relaxation.

Effect of deployment related experiences on sleep quality of German soldiers after return from an International Security Assistance Force (ISAF) mission to Afghanistan

The aim of the present study was to investigate the effect of experiencing potentially traumatic events during deployment on post-deployment sleep quality as measured by the Pittsburgh Sleep Quality Index (PSQI) and the Addendum for Post-Traumatic Stress Disorder (PTSD) of the Pittsburgh Sleep Quality Index (PSQI-A). Deployment related experiences were quantified on a standardised list of the Mental Health Advisory Team of the U.S. armed forces. The original sample consisted of 118 soldiers of the German armed forces who were deployed to Afghanistan for six months. The present analyses focused on data assessed after deployment (n = 70) and in a three-month follow-up (n = 51). Results indicate that immediately after return experiences during deployment had an independent significant effect on sleep quality but not three months later. Immediately after return depressive and stress symptoms significantly affected sleep quality while three months later somatic symptoms were significant. At both time points sleep prior to deployment was a significant predictor of sleep quality following deployment. Given the importance of sleep quality prior to deployment as a known independent risk factor for newly occurring mental disorders after deployment, these results underline the need to improve sleep quality already at an early stage.