P045 A prospective review of sleep quality in hospitalised respiratory inpatients

Abstract Background and Aim Sleep is an active and restorative state that is vital for maintaining optimal physical and mental health. Hospitalised patients are particularly at risk of poor sleep. We aim to review the sleep quality of respiratory inpatients at a tertiary hospital and to identify modifiable barriers to sleeping well in hospital environments. Methods Prospective data were collected from respiratory ward patients at time of discharge by completion of a medical records review and a Sleep Questionnaire created by Working Group Sleep Health Foundation, including patient rating of sleep quality (very poor, poor, fair, good, very good) and sleep disrupting factors. These data were stratified by pertinent environmental, patient and clinical care factors. Results Data from 6 patients were analysed; median age was 65 years, 3 (50%) were male and median length of hospital stay was 5 days. Four (67%) patients used sedating medications, 1 (17%) used this for treatment of insomnia. Two (33%) of patients characterised their sleep quality as poor or very poor and 3 (50%) patients described their sleep in hospital as slightly worse or much worse than sleeping at home. The main contributing factors to poor sleep quality were noise, checking of vital signs by hospital staff, medical treatments and medical condition relating to admission (eg. pain, dysnpea). Data collection is ongoing. Conclusion A significant proportion of patients experienced poorer sleep quality as a result of their hospital admission, attributable to both extrinsic factors (noise and clinical care) and underlying medical conditions.

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Poor Sleep Quality in Nurses Working or Having Worked Night Shifts: A Cross-Sectional Study

Frontiers in Neuroscience ◽

10.3389/fnins.2021.638973 ◽

2021 ◽

Vol 15 ◽

Author(s):

Qiao Huang ◽

Chong Tian ◽

Xian-Tao Zeng

Keyword(s):

Sleep Quality ◽

Clinical Care ◽

Night Shift ◽

Cross Sectional Study ◽

Poor Sleep ◽

Consecutive Night ◽

Sectional Study ◽

Poor Sleep Quality ◽

Cross Sectional ◽

Night Shifts

Night shifts are part of clinical care. It is unclear whether poor sleep quality of nurses working both consecutive night shifts and day shifts after quitting night shifts is common. In this cross-sectional study, Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality as study outcome. Univariable and multivariable linear and logistic regressions were performed to compare PSQI score and prevalence of poor sleep quality between 512 nurses currently working consecutive night shifts and 174 nurses having worked night shifts in the past. The prevalence of poor sleep quality was 62.11% in nurses working consecutive night shifts and 55.75% in nurses having worked night shifts before. In multivariable regressions with adjustment for potential confounders, compared with nurses working consecutive night shifts, nurses having worked past night shifts reported decreased PSQI score [mean difference: −0.82 (95% CI: −1.27 to −0.38, p < 0.001)] and lower poor sleep quality [odds ratio (OR): 0.49 (95% CI: 0.29 to 0.80, p = 0.005)]. In nurses working consecutive night shifts, a rising curve that plateaued at the end was observed between years of consecutive night shifts and PSQI score, p = 0.004. To explore the change in PSQI score after quitting night shift, we constructed a hypothetical prospective cohort from the cross-sectional data. Here, 98 pairs of nurses with consecutive and past night shifts were matched for the number of night shift years, religion, marital status, living condition, hypertension, and hyperlipidemia. In each pair, a hypothetical change in PSQI score was calculated between the two types of nurses and hypothetical years after quitting night shifts was obtained from the matched nurse with past night shifts. A U-shaped curve between change in PSQI and years after quitting night shifts was observed, p = 0.007. The rising curve and U-shaped curve together formed an S-shaped curve, which mapped the change in sleep quality. These results based on the hypothetical cohort constructed from cross-sectional data suggested the presence of persistent poor sleep quality in night shift nurses. Also, we support early and continuous sleep hygiene education and reflection for an optimal strategy for when to cease working night shifts with regard to sleep-related problems.

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Relationship between Mental Health, the CLOCK Gene, and Sleep Quality in Surgical Nurses: A Cross-Sectional Study

BioMed Research International ◽

10.1155/2020/4795763 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9

Author(s):

Lingyun Shi ◽

Yuanyuan Liu ◽

Ting Jiang ◽

Ping Yan ◽

Fan Cao ◽

...

Keyword(s):

Mental Health ◽

Sleep Quality ◽

Sleep Disorders ◽

Psychological Symptoms ◽

Influential Factors ◽

Poor Sleep ◽

Physical And Mental Health ◽

High Exposure ◽

Surgical Nurses

Nursing is a high-risk occupation with high exposure to stress. The physical and mental health of nurses is directly related to the quality of medical services. Therefore, the sleep quality of nurses should not be ignored. In this study, the method of cluster random sampling was adopted from May to September 2019, and a questionnaire survey was conducted among 521 surgical nurses from five affiliated hospitals of Xinjiang Medical University. The relationship between mental health and sleep quality was analyzed, and 20% of the participants with sleep disorders were randomly selected. The sleep disorders used 1 : 1 matching, finally providing a sample with 60 cases and 60 controls for measurement of the CLOCK gene (rs1801260, rs6850524), to analyze the effect of the interaction between mental health and the CLOCK gene on sleep. The mental health and sleep quality of the surgical nurses were evaluated using the Symptom Checklist 90 (SCL-90) and Pittsburgh Sleep Quality Index (PSQI). The study found that surgical nurses had poor sleep, and there were differences associated with age, years working, frequency of night shifts, and incidence of sleep disorders under marital status (p<0.05). The PSQI scores of the positive psychological symptoms were higher than those of the negative psychological symptoms. The rank sum test was used to compare the sleep quality scores of different genotypes in CLOCK rs1801260 and rs6850524; the results indicated that the PSQI scores were different among different genotypes at the rs1801260 and rs6850524 loci. The logistic regression results suggested that CLOCK gene rs1801260 (TC) and positive psychological symptoms were influential factors for sleep disorders, and the interaction of positive psychological symptoms∗rs1801260 (TT) was a risk factor for sleep disorders (OR=10.833, 95% CI: 2.987–39.288). The sleep quality of nurses is not only affected by demographic characteristics but also affected by mental health status and the CLOCK gene.

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Assessment of the Health Impacts of the 2011 Summer Floods in Brisbane

Disaster Medicine and Public Health Preparedness ◽

10.1017/dmp.2013.42 ◽

2013 ◽

Vol 7 (4) ◽

pp. 380-386 ◽

Cited By ~ 29

Author(s):

Katarzyna Alderman ◽

Lyle R. Turner ◽

Shilu Tong

Keyword(s):

Mental Health ◽

Health Outcome ◽

Psychological Distress ◽

Sleep Quality ◽

Respiratory Health ◽

Psychosocial Health ◽

Sociodemographic Factors ◽

Health Impacts ◽

Poor Sleep ◽

Physical And Mental Health

AbstractObjectiveTo assess the effects of the 2011 floods in Brisbane, Australia, on residents’ physical and mental health.MethodsResidents who had been affected by the floods completed a community-based survey that examined the direct impact of flooding on households and their perceived physical and mental health. Outcome variables included overall and respiratory health and mental health outcomes related to psychological distress, sleep quality, and posttraumatic stress disorder (PTSD). Multivariable logistic regression was used to examine the association between flooding and perceived health outcome variables, adjusted for current health status and sociodemographic factors.ResultsResidents whose households were directly affected by flooding were more likely to report poor overall (Odds Ratio [OR] 5.3; 95% CI, 2.8-10.1) and respiratory (OR 2.3; 95% CI, 1.1-4.6) health, psychological distress (OR 1.9; 95% CI, 1.1-3.5), poor sleep quality (OR 2.3; 95% CI, 1.2-4.4), and probable PTSD (OR 2.3; 95% CI, 1.2-4.5).ConclusionsThe 2011 Brisbane floods had significant impact on the physical and psychosocial health of residents. Improved support strategies may need to be integrated into existing disaster management programs to reduce flood-related health impacts, particularly those related to mental health. (Disaster Med Public Health Preparedness. 2013;0:1–7)

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Severity and Its Contributing Factors in Patients With Vestibular Migraine: A Cohort Study

Frontiers in Neurology ◽

10.3389/fneur.2020.595328 ◽

2020 ◽

Vol 11 ◽

Author(s):

Wei Liu ◽

Hongli Dong ◽

Le Yang ◽

Hongru Zhao ◽

Wanli Dong ◽

...

Keyword(s):

Sleep Quality ◽

Visual Analog Scale ◽

International Headache Society ◽

Vestibular Migraine ◽

Poor Sleep ◽

Contributing Factors ◽

Analog Scale ◽

Duration Of Illness ◽

Adult Participants ◽

Patient Health

Objective: As a recently defined disease entity, vestibular migraine (VM) is a variant of migraine with broad spectrum of manifestations. We evaluated a prospective cohort of patients with VM in two centers to assess severity of VM attacks and investigate its contributing factors in patients with VM.Methods: Adult participants with the diagnosis of VM or probable VM were enrolled according to the 2012 International Headache Society-Bárány Society Criteria. Every outpatient was followed up for 6 months to record the occurrence of VM attacks. Clinical data such as age, sex, number of VM attacks, severity on the visual analog scale, and lipid intake were collected and analyzed. Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, Horne and Ostberg Morningness-Eveningness Questionnaires, and Pittsburgh Sleep Quality Index were also administered to find contributing factors.Results: During a 6-month clinical follow-up, 313 VM attack were reported. According to the Visual Analog Scale, the patients were divided into two groups. Then univariate and multivariable analyses were conducted. Among the risk factors, duration of illness (adjusted OR, 1.041; 95% CI, 1.010–1.073; P = 0.009), time of onset: 00:00:00–12:00:00 (adjusted OR, 3.961; 95% CI, 1.966–7.979; P < 0.001) and PSQI scores (adjusted OR, 1.086; 95% CI, 1.002–1.178; P = 0.046) were significantly associated with the severity of VM attack assessed by VAS.Conclusion: The data suggest that patients tended to experienced more severe VM attacks in early hours of a day, especially for those sufferers with longer duration of illness or poor sleep quality. Targeted management of such factors is required to reduce the severity of attacks.

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Working Mode and Physical Activity as Factors Determining Stress and Sleep Quality during COVID-19 Pandemic Lockdown in Poland

Life ◽

10.3390/life12010028 ◽

2021 ◽

Vol 12 (1) ◽

pp. 28

Author(s):

Anna Lipert ◽

Kamila Musiał ◽

Paweł Rasmus

Keyword(s):

Physical Activity ◽

Sleep Quality ◽

Sleep Disturbances ◽

Online Survey ◽

Short Form ◽

High Stress ◽

Poor Sleep ◽

Physical And Mental Health ◽

Everyday Functioning ◽

High Stress Level

The coronavirus pandemic and related government restrictions have a significant impact on peoples’ everyday functioning and working, which influences their physical and mental health. The aim of the study was to examine the associations between stress and sleep quality of people of different working modes: working in the workplace (WP), working remotely (RW), and nonworking (NW) in relation to their physical activity (PA) during COVID-19 pandemic lockdown in Poland. It was an online survey performed during governmental lockdown in April 2020. The data were collected form 1959 adults using International Physical Activity Questionnaire—Short Form (IPAQ-SF), Pittsburgh Sleep Quality Index (PSQI), and Perceived Stress Scale (PSS). The conducted analysis included t-Student test, analysis of variance (ANOVA), and mediation analysis (MANOVA). A moderate level of stress was reported in 57% of participants, and 34% of them reported a high stress level. Poor sleep quality was reported in 64% of participants. Total PA performed daily was, on average, 184.8 ± 170.5 min/day for WP, 120.6 ± 124.4 min/day for RW, and 124.6 ± 114.7 min/day for NW (p < 0.001). There was a relationship observed between the stress and sleep quality vs. PA habit and working mode, with p < 0.05. Being physically active can be beneficial to perceive less stress and sleep disturbances influencing sleep quality, especially in remotely or nonworking people. Planning future pandemic restrictions, the policymakers should be aware of the appropriate guidelines of work planning and PA recommendations for people of different working modes.

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EVALUATION OF SLEEP QUALITY INDEX IN POSTGRADUATE MEDICAL STUDENTS IN INDIA

10.36106/ijsr/5234798 ◽

2021 ◽

pp. 32-33

Author(s):

Divina Sethi ◽

Namrita Sachdev ◽

Rupali Bhardwaj

Keyword(s):

Medical Students ◽

Sleep Quality ◽

Quality Index ◽

Cross Sectional Study ◽

Poor Sleep ◽

New Delhi ◽

Physical And Mental Health ◽

Cross Sectional ◽

Postgraduate Students ◽

Sleep Quantity

Background: Sleep quality is dened as the satisfaction of the sleep experience, integrating aspects of sleep initiation, sleep maintenance, sleep quantity, and refreshment upon awakening. It is important to measure sleep quality in postgraduate medical students and this study aims to monitor it across the various years of the course. Methodology: A cross-sectional study involving medical postgraduates students at the Postgraduate Institute of Medical Sciences and Research & Dr. Ram Manohar Lohia Hospital, New Delhi was conducted. All rst- to third-year postgraduate students were invited to participate. It was a self rated questionnaire based study using the Pittsburgh Sleep Quality Index (PSQI). Results: Poor sleep quality as observed using raised global PSQI of more than 5 was seen in 104 students (74%). Of this, 39 students belonged to third year (88.6%), 37 students were from second year (74%) and 28 students were from rst year (59.6%). Only 26% of students showed an adequate sleep quality with global PSQI <5.The mean global PSQI scores for students in rst, second and third year were 6.2, 6.6 and 7.8 respectively reecting that third year students were most affected. Conclusion: Postgraduate medical students have more sleep disturbance with impaired sleep quality. Sleep quality has a strong inuence on physical and mental health. Active intervention is required to improve sleep hygiene in these students.

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Descriptive study on sleep quality and its associated factors among elderly in urban population: Chidambaram

International Journal of Community Medicine and Public Health ◽

10.18203/2394-6040.ijcmph20191808 ◽

2019 ◽

Vol 6 (5) ◽

pp. 1999 ◽

Cited By ~ 1

Author(s):

R. Gouthaman ◽

R. Devi

Keyword(s):

Sleep Quality ◽

Elderly People ◽

Population Aging ◽

Depression Scale ◽

Cross Sectional Study ◽

Poor Sleep ◽

Contributing Factors ◽

Cross Sectional ◽

Significance Level ◽

Background Population

Background: Population aging is a major health issue in most countries, sleep is one of the significant factors affecting aging and elderly people’s quality of life. The present study was done to assess sleep quality and its contributing factors among elderly people.Methods: This cross-sectional study was conducted in 2018 on 227 elderly people aged fifty five or more participants were selected from the urban field practice area Chidambaram. Data collection tools were a demographic questionnaire, pittsburg sleep quality index and five point depression scale. The collected data were entered into SPSS software (V-22) and analysed using chi-square test at the significance level of less than 0.5.Results: Among 227 elderly people most of them were between the age group of 55 to 60 years (44.9%) and majority of them were females (59%), literacy (69.6%) married (60.5%), house wives (43.6%). Among the population 34.8% had their PSQI value <5 which suggest good sleep quality and whereas 65.2% had PSQI ≥5 suggesting poor sleep quality.Conclusions: The finding of their study indicates that elderly population in this area, have a fairly good quality. The most important factors contributing to their sleep quality are gender, dependency in doing daily activities, other health problems, marital status and their habitual sleep efficiency.

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A Systematic Review : The Effects Of Pilates Exercise On Sleep Quality In Postpartum Women

Jurnal Kebidanan Midwiferia ◽

10.21070/midwiferia.v7i1.908 ◽

2021 ◽

Vol 7 (1) ◽

pp. 16-26

Author(s):

Niken Bayu Argaheni

Keyword(s):

Systematic Review ◽

Sleep Quality ◽

Poor Quality ◽

Postpartum Women ◽

Poor Sleep ◽

Physical And Mental Health ◽

Quality Sleep ◽

Long Time ◽

Improve Sleep Quality ◽

Postpartum Mothers

Background: Poor sleep quality is associated with old age among the general population, but only a few studies have focused on postpartum women. Poor quality sleep for a long time can reduce a woman's ability to carry out maternal and family duties after childbirth. This study aimed to investigate the effect of Pilates on sleep quality in postpartum women. Method: Systematic review using the database: Google Scholar. The search results that meet the criteria are then analyzed for articles. Results: Pilates exercise was shown to significantly improve sleep quality in postpartum mothers. Conclusion: Therefore, Pilates exercises can be used as an exercise routine for postpartum mothers to improve physical and mental health during the postpartum period.

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Learning Using Concave and Convex Kernels: Applications in Predicting Quality of Sleep and Level of Fatigue in Fibromyalgia

Entropy ◽

10.3390/e21050442 ◽

2019 ◽

Vol 21 (5) ◽

pp. 442 ◽

Cited By ~ 2

Author(s):

Elyas Sabeti ◽

Jonathan Gryak ◽

Harm Derksen ◽

Craig Biwer ◽

Sardar Ansari ◽

...

Keyword(s):

Machine Learning ◽

Sleep Quality ◽

Medical Condition ◽

Electrodermal Activity ◽

Supervised Machine Learning ◽

Poor Sleep ◽

Machine Learning Method ◽

Learning Approaches ◽

Learning Method

Fibromyalgia is a medical condition characterized by widespread muscle pain and tenderness and is often accompanied by fatigue and alteration in sleep, mood, and memory. Poor sleep quality and fatigue, as prominent characteristics of fibromyalgia, have a direct impact on patient behavior and quality of life. As such, the detection of extreme cases of sleep quality and fatigue level is a prerequisite for any intervention that can improve sleep quality and reduce fatigue level for people with fibromyalgia and enhance their daytime functionality. In this study, we propose a new supervised machine learning method called Learning Using Concave and Convex Kernels (LUCCK). This method employs similarity functions whose convexity or concavity can be configured so as to determine a model for each feature separately, and then uses this information to reweight the importance of each feature proportionally during classification. The data used for this study was collected from patients with fibromyalgia and consisted of blood volume pulse (BVP), 3-axis accelerometer, temperature, and electrodermal activity (EDA), recorded by an Empatica E4 wristband over the courses of several days, as well as a self-reported survey. Experiments on this dataset demonstrate that the proposed machine learning method outperforms conventional machine learning approaches in detecting extreme cases of poor sleep and fatigue in people with fibromyalgia.

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Interventions to improve inpatients' sleep quality in intensive care units and acute wards: a literature review

British Journal of Nursing ◽

10.12968/bjon.2020.29.13.770 ◽

2020 ◽

Vol 29 (13) ◽

pp. 770-776 ◽

Cited By ~ 1

Author(s):

Carlos Aparício ◽

Francesca Panin

Keyword(s):

Intensive Care ◽

Literature Review ◽

Sleep Quality ◽

Sleep Disturbances ◽

Clinical Care ◽

Future Research ◽

Poor Sleep ◽

Related Factors ◽

Behavioural Changes ◽

Lack Of Sleep

Background: Sleep is essential for the physical and psychological restoration of inpatients, and lack of sleep results in sleep deprivation and poor sleep quality, with potentially harmful consequences. Aim: To summarise sleep-promoting interventions in the Intensive care unit (ICU) and acute ward setting. Method and results: Six databases were searched to obtain studies for review and eight studies were selected, appraised, analysed and produced two themes: sleep-disturbing factors and sleep-promoting strategies. Sleep-disturbing factors included environmental factors (such as light and noise), illness-related factors (such as pain, anxiety and discomfort), clinical care and diagnostics. Sleep-promoting strategies included using pharmacological aids (medication) and non-pharmacological aids (reducing noise and disturbances, eye masks, earplugs and educational and behavioural changes). Conclusion: The literature review showed that both ICU and acute ward settings affect patients' sleep and both use similar strategies to improve this. Nevertheless, noise and sleep disturbances remain the most critical sleep-inhibiting factors in both settings. The review recommended future research should focus on behavioural changes among health professionals to reduce noise and improve patients' sleep.

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