Suchergebnisse

Introduction: Sleep disturbanceis an important risk factor for the development of depression during adolescence. Excessive electronic media usage at night was a risk factor for adolescents' sleep disturbance. As late sleep onset can reduce sleep, this sleep/circadian rhythm disturbance may cause brain impairment [1]. We planned to identify sleep quality of school going adolescents as well as predictors on disturbed sleep patterns like Television, Mobile. Methods: A community based cross-sectional analytical study compromising of1000 school going adolescents between 8th to 12th standard studying in government and private schools of city of Gwalior for duration 1 year. Questionnaire prepared on Pittsburg Sleep Quality Index guidelines were distributed to them. Results: In our study the most common cause for sleepdisturbancesamong adolescentswere nightmares(15.4%) followed by sleep latency more than 30 minutes. Prevalence of poor sleep quality (PQSI score>5) was more in 15-17 years age adolescents, class standard 11th and 12th and lower economic status. The mean time of sleeping was 7.1±.67 hours on weekdays and 7.42±0.35 hours on weekends. Increasing usage of mobile internate was found to be singnificantly associated with poor sleep quality in comparison to television watching. Poor sleep has direct corelation with scholastic performance. Conclusion: About one third of the adolescent's population was having poor quality sleep. Increasing use of mobile internate was found to be singnificantly associated with poor sleep quality Poor sleep has direct corelation with scolastic performance. Sleep assessment must be included in the overall assessment of child's well-being.

The availability of smartphones and their multi-functionality make them indispensable devices in day-to-day life, especially among students. When smartphone use goes beyond necessity and turns into addiction, the consequences can affect various aspects of life such as mental health, sleep quality, and academic performance. The focus of this research was assessing the presence of smartphone addiction and its association with sleep quality among medical students of the University of Novi Sad. In this cross-sectional study, using the Smartphone Addiction Assessment Scale (SAS-SV) and the Pittsburgh Sleep Quality Index (PSQI), an online survey method, we included 119 medical students, mean age 21.5 (SD±2.8), from of which 75.6% were female students. The obtained results indicate the absence of smartphone addiction (SAS-SV=25.6; SD ±9.1) and the presence of poorer sleep quality (PSQI=5.9; SD±3.3). The prevalence of smartphone addiction was 21%, while the prevalence of poor sleep quality was around 46%. The established moderate positive, statistically significant, correlation between the scores of the questionnaire indicates that increasing the presence of smartphone addiction can worsen the sleep quality in medical students. The need for further research on this subject, on a wider, more representative sample, was recognized. As the complexity of the study program dictates the characteristic lifestyle of students, timely education and raising awareness of the potential risks of behavioral addictions is considered desirable, even necessary.

The aim of the study was to examine the relationship between sleep quality and life satisfaction. The basic hypothesis was that the dimensions of quality and quantity of sleep will be statistically significant predictors of life satisfaction among employees of the Serbian Railways. A total of 126 workers working in different jobs were surveyed: dispatcher, information worker, cashier, train driver, and conductor. Respondents differed according to gender, age, and years of service. The main research variables were operationalized by The Pittsburgh Sleep Quality Index (PSQI; Buysse et al., 1989) and the Satisfaction Life Scale (SWLS; Diener et al.,1985). The results showed that based on the regression model consisting of sleep quality modalities, the criterion variable - life satisfaction (R2 = .40, p <0.01) can be statistically significantly explained. The largest individual contribution to the prediction of the criterion variable has the predictor of dysfunction during the day (b = -. 42, p <0.01), followed by sleep disorders (b = -. 22, p <0.05) and sleep duration (b = -. 22, p < 0.01). Examination of differences with respect to some sociodemographic variables showed that women show poorer quality of sleep, and that the quality of sleep decreases with age, that more sleep disorders occur, which causes dysfunctions during the day and more frequent use of medications.

Abstract. The aim of this article was to review research studies related to the issues of sleep in older adults, examining the relationship between sleep quality and a set of psychological variables of daytime functioning in healthy older adults: quality of life, subjective health, functional ability, cognitive function, and emotional state, in Europe. Combined scoping review search strategies resulted in a total of 84 articles selected for review. We conclude there is a considerable amount of European research on sleep quality and its correlates in older adults' population. Studying these relationships may be the basis for the targeted planning of psychological interventions aiming at raising the quality of life in older adults. The selected domains of older adults' everyday functioning were all well represented in the retrieved research studies.

INTRODUCTION: To mitigate the spread of the pandemic coronavirus infection (COVID-19), governments across the world have adopted "lockdowns" which have confined many individuals to their homes. This disrupts normal life routines, elements of which are important circadian cues. The pandemic is also associated with new stressors, altered roles, and uncertainties about health and economic security, which are also likely to affect sleep. The current study is an online survey of sleep experience, routines, physical activity, and symptoms of anxiety and depression, to study the alterations associated with the lockdown. MATERIALS AND METHODS: The survey was conducted in early May 2020 using a questionnaire circulated through social media platforms. Questions related to demographic characteristics, current and previous sleep schedules, routine, and working patterns. Insomnia (Insomnia Severity Index - 4), Stress (Perceived Stress Scale - 4), anxiety and depressive symptoms (Patient Health Questionnaire - 4) and physical activity (International Physical Activities Questionnaire) were assessed using standardized instruments. RESULTS: A total of 958 valid responses were received. Compared to the prelockdown period, there was a shift to a later bedtime and waking time, with a reduction in night-time sleep and an increase in day-time napping. These effects were visible across occupational groups, but mostly affected working individuals except health professionals. Sleep quality deteriorated across groups. Reductions in sleep duration were associated with depressive symptoms. CONCLUSIONS: The COVID-19 lockdown is associated with changes in sleep schedule and in the quantity and quality of night-time sleep. Although these changes are associated with elevated rates of emotional symptoms, it is unclear from these cross-sectional results, whether sleep deterioration produces psychological distress, or vice versa.

Background: The smart phone contains various mobile applications specifically targeting their contents, such as information, messages, e-mail, education and entertainment towards youths. Problematic and excessive smart phone usage can cause many health problems including anxiety, depression and sleep disorders. Aims: The aim of this study is to analyse the relationship between smart phone usage, sleep quality and depression. Methods: Eight hundred and four students who owned smart phones were given the Information Form, Smart Phone Addiction Scale-Short Version, Pittsburgh Sleep Quality Index (PSQI) and Beck Depression Inventory (BDI). The descriptive statistics, independent sample t-test, one-way ANOVA, correlation analysis and multivariate regression analysis were used for analysis data. Results: The mean age of the students in the sample was 20.93 ± 2.44. It comprised female (65.0%) and male (35.0%) students. All of the students used smart phones. The daily smart phone usage duration was 7.85 ± 4.55 hour. According to the multivariate linear regression analysis results, significant relationships were statistically determined in the positive way between the smart phone addiction and PSQI point ( p  < .01) and BDI point ( p  < .01). Conclusion: Consequently, a relationship exists between smart phone usage, poor sleep quality and depressive symptoms in university students. The university students, whose depression point is high and sleep quality is poor, should be followed up with regarding the smart phone addiction.

The objective was to investigate associations of perceived stress with sleep duration and quality among 430 police officers. Perceived stress was assessed using the Perceived Stress Scale. Sleep duration and quality were assessed using the Pittsburg Sleep Quality Index questionnaire. Mean hours of sleep were determined across quartiles of perceived stress using ANOVA/ANCOVA. Logistic regression was used to obtain odds ratios and 95% confidence intervals for poor sleep quality across perceived stress quartiles. Mean age was 42.1 years. Perceived stress was inversely associated with sleep duration among certain groups: men (p = 0.004), higher-ranked officers (p = 0.002), those with higher depressive symptoms (p = 0.097), no military experience (p = 0.006), and higher workload (p = 0.003). Gender, police rank, depressive symptoms, and workload each significantly modified the association between stress and sleep duration. Prevalence of poor sleep quality increased with higher levels of perceived stress; the trend was significant among men only (p <0.0001), and gender significantly modified this association (interaction p = 0.015). Compared to those in the first quartile of perceived stress, women in the fourth quartile were almost four times and men almost six times more likely to have poor sleep quality. Perceived stress was inversely associated with sleep duration and positively associated with poor sleep quality.

Sleep is an integral human need. A significant public health issue is getting little sleep, which harms health. University students are one of the groups most at risk for poor sleep quality and chronic sleep loss, which could influence both physical and mental health. Students frequently report having persistent sleep issues and may exhibit poor sleep hygiene habits. However, little research has investigated the role of good sleep habits concerning sleep quality and mental health. The present study explores the relationship between sleep hygiene, sleep quality, and mental health among university students. The research design was cross-sectional, and the sample was chosen using a non-probability convenience sampling strategy. Sample comprised of university students (N= 210). The scale of positive mental health, sleep hygiene index, and general sleep scale were used for data collection. Results revealed a significant correlation between sleep quality, sleep hygiene, and mental health among university students. Both sleep hygiene and quality were found to be significant predictors of positive mental health. A significant gender difference was found between sleep quality, sleep hygiene, and positive mental health among male and female university students. These findings can provide information about the link between the study variables and interventions for developing good sleep hygiene habits and quality of sleep amongst university students. It could help improve mental health among this at-risk population.

BACKGROUND: Military police officers are a distinct population group given they deal everyday with violence and crime. For this reason they are more susceptible to develop burnout syndrome, resulting in significant decrease of productivity and changes in the quality of sleep. OBJECTIVE: To analyze the correlation between burnout syndrome and sleep quality relative among military police officers. METHOD: Cross-sectional, descriptive and quantitative study conducted with 32 military police officers of the military police battalion of Teresina, Piaui, Brazil. Data collection was performed through administration of a questionnaire for sociodemographic data, the Masliach Burnout Inventory and the Pittsburgh Sleep Quality Index. Pearson's correlation was used for statistical analysis. RESULTS: The sample comprised 32 male military police officers, with average age 44.35±5.63 years old. Sleep duration exhibited highly significant, inverse and moderate correlation with emotional exhaustion (p=0.0003). Emotional exhaustion exhibited significant moderate correlation with sleep quality (p=0.004). Depersonalization exhibited significant, albeit weak correlation with sleep quality (p=0.03). CONCLUSION: Burnout syndrome domains emotional exhaustion and depersonalization exhibited significant correlation with sleep quality.

Recent scholarship has documented the effects of unstable scheduling practices on worker health and well-being, but there has been less research examining the intergenerational consequences of work schedule instability. This study investigates the relationship between parental exposure to unstable and unpredictable work schedules and child sleep quality. We find evidence of significant and large associations between parental exposure to each of five different types of unstable and unpredictable work scheduling practices and child sleep quality, including sleep duration, variability and daytime sleepiness. We are also able to mediate 35–50% of this relationship with measures of work–life conflict, parental stress and well-being, material hardship, and child behaviour. These findings suggest that the effects of the temporal dimensions of job quality extend beyond workers to their children, with implications for the mechanisms by which social inequality is reproduced and for social policies intended to regulate precarious and unequal employment conditions.