Search results for: sleep hygiene index

Authors: Kriti Singh, Saurabh Tripathi, Pankaj Chaudhary, Abid Ali Ansari, Seema Nigam

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Introduction: The introduction of android and iOS has changed our lives dramatically over the past few years. The new generation is more dependent on their mobile phones for carrying out their daily pursuits. Smartphones have revolutionized our lives. The cutdown in rates of mobile network services has been affecting us drastically. A new type of dependence is seen among the people for Smartphones. A cross-sectional study was conducted to determine the state of addiction among the group of medical students, along with its association with sleep hygiene and anxiety. Material and Method: Study included 50 individuals in the age group of 18-35 years. Smartphone Addiction Scale Short Version, Sleep Hygiene Index, and Perceived Stress Scales were used conducting the study. Results: Mean age of 22 years (12%). The majority of subjects were 20-year olds (15 out of 50), the majority were males with few females. Mean Smartphone addiction score 39 (very severe), Mean Sleep Hygiene Index score 26.76 (moderate maladaptive hygiene and Mean Perceived Stress score of 19.92 (moderate stress). Conclusion: In majority students were found to have a very severe Smartphone Addiction with moderate sleep hygiene and a moderate level of perceived stress. The Smartphone was being used was for surfing social media applications.

Keywords: addiction perceived stress, sleep hygiene index, smartphone

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Authors: Dongjoo Kim, Chang-Sik Son, Won-Seok Kang

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Adequate sleep affects various parts of one’s overall physical and mental life. As one of the methods in determining the appropriate amount of sleep, this research presents a heart rate based sleep quality index. In order to evaluate sleep quality using the heart rate, sleep data from 280 subjects taken over one month are used. Their sleep data are categorized by a three-part heart rate range. After categorizing, some features are extracted, and the statistical significances are verified for these features. The results show that some features of this sleep quality index model have statistical significance. Thus, this heart rate based sleep quality index may be a useful discriminator of sleep.

Keywords: sleep, sleep quality, heart rate, statistical analysis

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Authors: Ika Wulansari, Yati Afiyanti, Indang Trihandini

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Sleeping disorder experienced by patients with breast cancer can affect the physical, mental, health, and well-being. This study examines the effect of progressive muscle relaxation training and sleep hygiene education to change sleep quality scores of the patient with breast cancer. The study design using quasi-experiment with pre-post test within the control group, involving 62 breast cancer patients using consecutive sampling method in Jakarta. Statistical test results with independent t-test showed a significant difference in score of sleep quality between in intervention group and the control group (6,66±3,815; 9,30±3,334, p-value = 0,005). Progressive muscle relaxation exercise and sleep hygiene education proven to be affective to change the patients sleeping quality, so that it can be an alternative therapeutic option to overcome sleeping disorders.

Keywords: sleeping disorders, breast cancer, progressive muscle relaxation, sleep hygiene education

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Authors: Sataroopa Mishra, Mona Basker, Sneha Varkki, Ram Kumar Pandian, Grace Rebekah

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Background: Sleep deprivation is a matter of public health importance among adolescents. We used adolescent sleep wake scale and adolescent sleep hygiene scale to determine the sleep quality and sleep hygiene respectively of school going adolescents in Vellore city of India. The objective of the study was to do factorial analysis of the scales and validate it for use in local population. Methods: Observational questionnaire based cross sectional study. Setting: Community based school survey in a semi-urban setting in three schools in Vellore city. Data collection: Non probability sample was collected form students studying in standard 9 and 11. Students filled Adolescent Sleep Wake scale (ASWS) and Adolescent Sleep Hygiene Scale (ASHS) translated into vernacular language. Data Analysis: Exploratory Factorial Analysis was used to see the factor loading of various components of the two scales. Confirmatory factorial analysis is subsequently planned for assessing the internal validity of the scales.Results: 557 adolescents were included in the study of 12 – 17 years old. Exploratory factorial analysis of adolescent sleep hygiene scale indicated significant factor loading for 18 items from 28 items originally devised by the authors and has been reconstructed to four domains instead of 9 domains in the original scale namely sleep stability, cognitive – emotional, Physiological - bed time routine - behavioural arousal factor (activites before bedtime and during bed time), Sleep environment (lighting and bed sharing). Factorial analysis of Adolescent sleep wake scale showed factor loading of 18 items out of 28 items in original scale reconstructed into 5 aspects of sleep quality. Conclusions: The factorial analysis gives a reconstructed scale useful for the local population. Further a confirmatory factorial analysis has been subsequently planned to determine the internal consistency of the scale for local population.

Keywords: factorial analysis, sleep hygiene, sleep quality, adolescent sleep scale

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Authors: Sadie Khorramnia, Asha Bonney, Kate Galloway, Andrew Kyoong

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Sleep plays a pivotal role in the registration and consolidation of memory. Multiple observational studies have demonstrated that self-reported sleep duration and sleep quality are associated with cognitive performance. Montreal Cognitive Assessment questionnaire is a screening tool to assess mild cognitive (MCI) impairment with a 90% diagnostic sensitivity. In our current study, we used MOCA to identify MCI in patients who underwent sleep study in our sleep department. We then looked at the clinical risk factors and sleep-related parameters in subjects found to have mild cognitive impairment but without a diagnosis of sleep-disordered breathing. Clinical risk factors, including physician, diagnosed hypertension, diabetes, and depression and sleep-related parameters, measured during sleep study, including percentage time of each sleep stage, total sleep time, awakenings, sleep efficiency, apnoea hypopnoea index, and oxygen saturation, were evaluated. A total of 90 subjects who underwent sleep study between March 2019 and October 2019 were included. Currently, there is no pharmacotherapy available for MCI; therefore, identifying the risk factors and attempting to reverse or mitigate their effect is pivotal in slowing down the rate of cognitive deterioration. Further characterization of sleep parameters in this group of patients could open up opportunities for potentially beneficial interventions.

Keywords: apnoea hypopnea index, mild cognitive impairment, sleep architecture, sleep study

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Authors: Chen-Yu Tsai, Wen-Te Liu, Chen-Chen Lo, Kang Lo, Yin-Tzu Lin

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Background: Driving drowsiness related to insufficient or disordered sleep accounts for a major percentage of vehicular accidents. Sleep deprivation is the primary reason related to low sleep efficiency. Nevertheless, the mechanism of sleep deprivation induces driving fatigue to remain unclear. Objective: The objective of this study is to associate the relationship between insufficient sleep efficiency and driving fatigue. Methodologies: The physical condition while driving was obtained from the questionnaires to classify the state of driving fatigue. Sleep efficiency was quantified as the polysomnography (PSG), and the sleep stages were sentenced by the reregistered Technologist during examination in a hospital in New Taipei City (Taiwan). The independent T-test was used to investigate the correlation between sleep efficiency, sleep stages ratio, and driving drowsiness. Results: There were 880 subjects recruited in this study, who had been done polysomnography for evaluating severity for obstructive sleep apnea syndrome (OSAS) as well as completed the driver condition questionnaire. Four-hundred-eighty-four subjects (55%) were classified as fatigue group, and 396 subjects (45%) were served as the control group. The ratio of stage three sleep (N3) (0.032 ± 0.056) in fatigue group were significantly lower than the control group (p < 0.01). The significantly higher value of snoring index (242.14 ± 205.51 /hours) was observed in the fatigue group (p < 0.01). Conclusion: We observe the considerable correlation between deep sleep reduce and driving drowsiness. To avoid drowsy driving, the sleep deprivation, and the snoring events during the sleeping time should be monitored and alleviated.

Keywords: driving drowsiness, sleep deprivation, stage three sleep, snoring index

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Authors: E. Botchway, C. Godfrey, V. Anderson, C. Catroppa

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Introduction: Sleep disturbances are common after childhood traumatic brain injury (TBI). This systematic review aimed to assess the prevalence, types, and predictors of sleep disturbances in childhood TBI. Methods: Medline, Pubmed, PsychInfo, Web of Science, and EMBASE databases were searched. Out of the 547 articles assessed, 15 met selection criteria for this review. Results: Sleep disturbances were common in children and adolescents with TBI, irrespective of injury severity. Excessive daytime sleepiness and insomnia were the most common sleep disturbances reported. Sleep disturbance was predicted by sex, injury severity, pre-existing sleep disturbances, younger age, pain, and high body mass index. Conclusions: Sleep disturbances are highly prevalent in childhood TBI, regardless of the injury severity. Routine assessment of sleep in survivors of childhood TBI is recommended.

Keywords: traumatic brain injury, sleep diatiurbances, childhood, systematic review

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Authors: L. Korpinen, T. Kava, I. Salmi

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This study aimed to describe the operating model of obstructive sleep apnea. Due to the large number of patients, the role of nurses in the diagnosis and treatment of sleep apnea was important. Pulmonary physicians met only a minority of the patients. The sleep apnea study in 2018 included about 800 patients, of which about 28% were normal and 180 patients were classified as severe (apnea-hypopnea index [AHI] over 30). The operating model has proven to be workable and appropriate. The patients understand well that they may not be referred to a pulmonary doctor. However, specialized medical follow-up on professional drivers continues every year.

Keywords: sleep, apnea patient, operating model, hospital

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Authors: Jiajia Peng

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Tinnitus is one of the common symptoms of ear diseases and is characterized by an abnormal perception of sound without external stimulation. Tinnitus is agony and seriously affects the life of the general population by approximately 1%. Sleep disturbance is a common problem in patients with tinnitus. Lack of sleep will lead to the accumulation of metabolites in the brain and cannot be cleared in time. These substances enhance sympathetic nerve reactivity in the auditory system, resulting in tinnitus occurrence or aggravation. Then, tinnitus may aggravate sleep disturbance, thus forming a vicious circle. Through a systematic review of the relevant literature, we summarize the research on tinnitus and sleep. Although the results suggest that tinnitus is often accompanied by sleep disturbance, the impact of unfavorable sleep habits on tinnitus is not clear. In particular, the relationships between sleep behaviors and other chronic diseases have been revealed. To reduce the incidence rate of tinnitus, clinicians should pay attention to the relevance between different sleep behaviors and tinnitus.

Keywords: tinnitus, sleep, sleep factor, sleep behavior

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Authors: Cheng-Yu Tsai, Wen-Te Liu, Yin-Tzu Lin, Chen-Chen Lo, Kang Lo

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Background: Driving drowsiness related to inadequate or disordered sleep accounts for a major percentage of traffic accidents. Sleep-disordered breathing (SDB) syndrome is a common respiratory disorder during sleep. However, the effects of SDB syndrome on driving fatigue remain unclear. Objective: This study aims to investigate the relationship between SDB pattern and driving drowsiness. Methodologies: The physical condition while driving was obtained from the questionnaires to classify the state of driving fatigue. SDB syndrome was quantified as the polysomnography, and the air flow pattern was collected by the thermistor and nasal pressure cannula. To evaluate the desaturation, the mean hourly number of greater than 3% dips in oxygen saturation was sentenced by reregistered technologist during examination in a hospital in New Taipei City (Taiwan). The independent T-test was used to investigate the correlations between sleep disorders related index and driving drowsiness. Results: There were 880 subjects recruited in this study, who had been done polysomnography for evaluating severity for obstructive sleep apnea syndrome (OSAS) as well as completed the driver condition questionnaire. Four-hundred-eighty-four subjects (55%) were classified as fatigue group, and 396 subjects (45%) were served as the control group. Significantly higher values of snoring index (242.14 ± 205.51 /hours) were observed in the fatigue group (p < 0.01). The value of respiratory disturbance index (RDI) (31.82 ± 19.34 /hours) in fatigue group were significantly higher than the control group (p < 0.01). Conclusion: We observe the considerable association between SDB syndrome and driving drowsiness. To promote traffic safety, SDB syndrome should be controlled and alleviated.

Keywords: driving drowsiness, sleep-disordered breathing syndrome, snoring index, respiratory disturbance index.

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Authors: Sumaiya Amir Khan, Shayma Al-Sharif, Samiha Mazher, Neha Intikhab Khan

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This research paper aims to evaluate the effectiveness of sleep-tracking AI applications in smart-watches. It focuses on comparing the sleep analyses of two different smartwatch brands, Samsung and Fitbit, and measuring sleep at three different stages – REM (Rapid-Eye-Movement), NREM (Non-Rapid-Eye-Movement), and deep sleep. The methodology involves the participation of different users and analyzing their sleep data. The results reveal that although light sleep is the longest stage, deep sleep is higher than average in the participants. The study also suggests that light sleep is not uniform, and getting higher levels of deep sleep can prevent debilitating health conditions. Based on the findings, it is recommended that individuals should aim to achieve higher levels of deep sleep to maintain good health. Overall, this research contributes to the growing literature on the effectiveness of sleep-tracking AI applications and their potential to improve sleep quality.

Keywords: sleep tracking, lifestyle, accuracy, health, AI, AI features, ML

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Authors: Sabrina Servot, Annick St-Amand, Michel Rousseau, Valerie Simard, Evelyne Touchette

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Child maltreatment has a profound impact on children’s development. In its victims, internalizing and externalizing problems are highly prevalent, and sleep problems are common. Furthermore, the environment they live in is often disorganized, lacking routine and consistency. In non-maltreated children, several studies documented the important role of sleep regulation and sleep ecology. A poor sleep ecology (e.g., lack of sleep hygiene and bedtime routine, inappropriate sleeping location) may lead to sleep regulation problems (e.g., short sleep duration, nocturnal awakenings), and sleep regulation problems may increase the risk of behavior problems. Therefore, this scoping review aims to map evidence about sleep ecology and sleep regulation and the associations between sleep ecology, sleep regulation, and behavior problems in maltreated preschoolers. Literature from 1993 was searched in PsycInfo, Pubmed, Medline, Eric, and Proquest Dissertations and Theses. Articles and thesis were comprehensively reviewed based upon inclusion/exclusion criteria: 1) it concerns maltreated children aged 1-5 years, and 2) it addresses at least one of the following: sleep ecology, sleep regulation, and/or their associations with behavior problems in maltreated preschoolers. From the 650 studies screened, nine of them were included. Data were charted according to study characteristics, nature of variable documented, measures, analyses performed, and results of each study, then synthesized in a narrative summary. The main results show all included articles were quantitative. Foster children samples were used in four studies, children experienced different types of maltreatment in six studies, while one was specifically about sexually abused children. Regarding sleep ecology, only one study describing maltreated preschoolers’ sleep ecology was found, while seven studies documented sleep regulation. Among these seven studies, 17 different sleep variables (e.g., parasomnia, dyssomnia, total 24-h sleep duration) were used, each study documenting from one to nine of them. Actigraphic measures were employed in three studies, the others used parent-reported questionnaires or sleep diaries. Maltreated children’s sleep was described and/or compared to non-maltreated children’s sleep, or an intervention group, showing mild differences. As for associations between sleep regulation and behavior problems, five studies investigated it and performed correlational or linear regression analyses between sleep and behavior problems, revealing some significant associations. No study was found about associations between sleep ecology and sleep regulation, between sleep ecology and behavior problems, or between these three variables. In conclusion, literature about sleep ecology, sleep regulation, and their associations with behavior problems are far more scarce in maltreated preschoolers than in non-maltreated ones. At present, there is especially a paucity of research about sleep ecology and the association between sleep ecology and sleep regulation in maltreated preschoolers, while studies on non-maltreated children showed sleep ecology plays a major role in sleep regulation. In addition, as sleep regulation is measured in many different ways among the studies, it is difficult to compare their findings. Finally, it seems necessary that research fill these gaps, as recommendations could be made to clinicians working with maltreated preschoolers regarding the use of sleep ecology and sleep regulation as intervention tools.

Keywords: maltreated preschoolers, sleep ecology, sleep regulation, behavior problems

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Authors: Gabriela Kloudova, Miloslav Stehlik, Peter Sos

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The quality of sleep can affect combat performance where the vigilance, accuracy and reaction time are a decisive factor. In the present study, airborne and special units are measured on duty using actigraphy fingerprint scoring algorithm and QEEG (quantitative EEG). Actigraphic variables of interest will be: mean nightly sleep duration, mean napping duration, mean 24-h sleep duration, mean sleep latency, mean sleep maintenance efficiency, mean sleep fragmentation index, mean sleep onset time, mean sleep offset time and mean midpoint time. In an attempt to determine the individual somnotype of each subject, the data like sleep pattern, chronotype (morning and evening lateness), biological need for sleep (daytime and anytime sleepability) and trototype (daytime and anytime wakeability) will be extracted. Subsequently, a series of recommendations will be included in the training plan based on daily routine, timing of the day and night activities, duration of sleep and the number of sleeping blocks in a defined time. The aim of these modifications in the training plan is to reduce day-time sleepiness, improve vigilance, attention, accuracy, speed of the conducted tasks and to optimize energy supplies. Regular improvement of the training supposed to have long-term neurobiological consequences including neuronal activity changes measured by QEEG. Subsequently, that should enhance cognitive functioning in subjects assessed by the digital cognitive test batteries and improve their overall performance.

Keywords: sleep quality, combat performance, actigraph, somnotype

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Authors: Amina Aquil, Abdeljalil El Got

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Background: Sleep quality is one of the most important indicators related to the quality of life of patients suffering from cancer. Many factors could affect this quality of sleep and then be considered as associated predictors. Methods: The aim of this study was to assess the prevalence of sleep disorders and the associated factors with impaired sleep quality in Moroccan women with gynecological cancer. A cross-sectional study was carried out within the oncology department of the Ibn Rochd University Hospital, Casablanca, on Moroccan women who had undergone radical surgery for gynecological cancer (n=100). Translated and validated Arabic versions of the following international scales were used: Pittsburgh sleep quality index (PSQI), Hospital Anxiety and Depression Scale (HADS), Rosenberg's self-esteem scale (RSES), and Body image scale (BIS). Results: 78% of participants were considered poor sleepers. Most of the patients exhibited very poor subjective quality, low sleep latency, a short period of sleep, and a low rate of usual sleep efficiency. The vast majority of these patients were in poor shape during the day and did not use sleep medication. Waking up in the middle of the night or early in the morning and getting up to use the bathroom were the main reasons for poor sleep quality. PSQI scores were positively correlated with anxiety, depression, body image dissatisfaction, and lower self-esteem (p < 0.001). Conclusion: Sleep quality and its predictors require a systematic evaluation and adequate management to prevent sleep disturbances and mental distress as well as to improve the quality of life of these patients.

Keywords: body image, gynecological cancer, self esteem, sleep quality

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Authors: Cheng-Yu Tsai, Wen-Te Liu, Chen-Chen Lo, Yin-Tzu Lin, Kang Lo

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Background: Driving fatigue related to inadequate or disordered sleep accounts for a major percentage of traffic accidents. Obstructive sleep apnea syndrome (OSAS) is a common respiratory disorder during sleep. However, the effects of OSAS severity on driving drowsiness remain unclear. Objective: The aim of this study is to investigate the relationship between OSAS severity and driving fatigue. Methodologies: The physical condition while driving was obtained from the questionnaires to classify the state of driving fatigue. OSAS severity was quantified as the polysomnography, and the mean hourly number of greater than 3% dips in oxygen saturation during examination in a hospital in New Taipei City (Taiwan). The severity of OSAS was diagnosed by the apnea and hypopnea index (AHI) with the American Academy of Sleep Medicine (AASM) guideline. The logistic regression model was used to examine the associations after adjusted age, gender, neck circumstance, waist circumstance, and body mass index (BMI). Results: There were 880 subjects recruited in this study, who had been done polysomnography for evaluating severity for OSAS as well as completed the driver condition questionnaire. 752 subjects were diagnosed with OSA, and 484 subjects had fatigue driving behavior in the past week. Patients diagnosed with OSAS had a 9.42-fold higher odds ratio (p < 0.01, 95% CI = 5.41 – 16.42) of driving drowsiness for cohorts with a normal degree. Conclusion: We observe the considerable correlation between OSAS and driving fatigue. For the purpose of promoting traffic safety, OSAS should be monitored and treated.

Keywords: obstructive sleep apnea syndrome, driving fatigue, polysomnography, apnea and hypopnea index

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Authors: Mohamed Boubekri, Kristen Bub, Jaewook Lee, Kate Kurry

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In this study, we explored the impact of light, particularly daylight on sleep time and quality of elementary school children. Sleep actigraphy was used to measure objectively sleep time and sleep efficiency. Our data show a good correlation between light levels and sleep. In some cases, differences of up to 36 minutes were found between students in low light levels and those in high light level classrooms. We recommend, therefore, that classroom design need to pay attention to the daily daylight exposures elementary school children are receiving.

Keywords: light, daylight, actigraphy, sleep, circadian rhythm, sustainable architecture, elementary school, children

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Authors: Chi-Feng Lai, Wen-Chun Liao Liao

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Many people are bothered by sleep difficulties in Taiwan’s society. However, majority of patients get medical treatments without a comprehensive sleep assessment. It is still a big challenge to formulate a comprehensive assessment of sleep difficulties in clinical settings, even though many assessment tools have existed in literature. This study tries to implement reliable and effective ‘comprehensive sleep assessment scales’ in a medical center and to explore differences in sleep-related factors between clinic clients with or without sleep difficulty complaints. The comprehensive sleep assessment (CSA) scales were composed of 5 dimensions: ‘personal factors’, ‘physiological factors’, ‘psychological factors’, ‘social factors’ and ‘environmental factors, and were first evaluated by expert validity and 20 participants with test-retest reliability. The Content Validity Index (CVI) of the CSA was 0.94 and the alpha of the consistency reliability ranged 0.996-1.000. Clients who visited sleep clinic due to sleep difficulties (n=32, 16 males and 16 females, ages 43.66 ±14.214) and gender-and age- matched healthy subjects without sleep difficulties (n=96, 47 males and 49 females, ages 41.99 ±13.69) were randomly recruited at a ratio of 1:3 (with sleep difficulties vs. without sleep difficulties) to compare their sleep and the CSA factors. Results show that all clinic clients with sleep difficulties did have poor sleep quality (PSQI>5) and mild to moderate daytime sleepiness (ESS >11). Personal factors of long working hours (χ2= 10.315, p=0.001), shift workers (χ2= 8.964, p=0.003), night shift (χ2=9.395, p=0.004) and perceived stress (χ2=9.503, p=0.002) were disruptors of sleep difficulties. Physiological factors from physical examination including breathing by mouth, low soft palate, high narrow palate, Edward Angle, tongue hypertrophy, and occlusion of the worn surface were observed in clinic clients. Psychological factors including higher perceived stress (χ2=32.542, p=0.000), anxiety and depression (χ2=32.868, p=0.000); social factors including lack of leisure activities (χ2=39.857, p=0.000), more drinking habits (χ2=1.798, p=0.018), irregular amount and frequency in meals (χ2=5.086, p=0.024), excessive dinner (χ2=21.511, p=0.000), being incapable of getting up on time due to previous poor night sleep (χ2=4.444, p=0.035); and environmental factors including lights (χ2=7.683, p=0.006), noise (χ2=5.086, p=0.024), low or high bedroom temperature (χ2=4.595, p=0.032) were existed in clients. In conclusion, the CSA scales can work as valid and reliable instruments for evaluating sleep-related factors. Findings of this study provide important reference for assessing clinic clients with sleep difficulties.

Keywords: comprehensive sleep assessment, sleep-related factors, sleep difficulties

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Authors: Somaye Ghafarpour, Kamran Yazdanbakhsh, Mohamad Reza Zarbakhsh, Simin Hosseinian, Samira Ghafarpour

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Unsatisfactory sleep quality is one of the most common complications of pregnancy, which can predispose mothers to postpartum depression, requiring implementing effective psychological interventions to prevent and modify behaviors accentuating sleep problems. This study was a randomized clinical controlled trial with a pre-test/post-test design aiming to investigate the effectiveness of sleep behavioral interventions during the third trimester of pregnancy on sleep quality and postpartum depression. A total of 50 pregnant mothers in the 26-30 weeks of pregnancy suffering from sleep problems (based on the score obtained from the Pittsburgh Sleep Questionnaire) were randomized into two groups (control and intervention, n= 25 per group). The data were collected using interviews, the Pittsburgh Sleep Quality Index (PSQI), and the Edinburgh Postnatal Depression Scale (EPDS) were used. The participants in the intervention group received eight 60-minute sessions of combinational training for behavioral therapy techniques. At the end of the intervention and four weeks after delivery, sleep quality and postpartum depression were evaluated. Considering that the Kolmogorov Smirnov test confirmed the normal distribution of the data, the independent t-test and analysis of covariance were used to analyze the data, showing that the behavioral interventions were effective on the overall sleep quality after delivery (p=0.001); however, no statistically significant effects were observed on postpartum depression, the sub-scales of sleep disorders, and daily functioning (p>0.05). Considering the potential effectiveness of behavioral interventions in improving sleep quality and alleviating insomnia symptoms, it is recommended to implement such measures as an effective intervention to prevent or treat these problems during prenatal and postnatal periods.

Keywords: behavioral interventions, sleep quality, postpartum depression, pregnancy, delivery

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Authors: Seyed Ahmad Hosseini, Makan Cheraghpour, Saeed Shirali, Roya Rafie, Matin Ghanavati, Arezoo Amjadi, Meysam Alipour

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Background: There is a mutual relationship between sleep duration and obesity. We studied the relationship between sleep duration with obesity and dietary Intake. Methods: This cross-sectional study was conducted on 444 male students in Ahvaz Jundishapur University of Medical Science. Dietary intake was analyzed by food frequency questionnaire (FFQ). Anthropometric indices were analyzed. Participants were being asked about their sleep duration and they were categorized into three groups according to their responses (less than six hours, between six and eight hours, and more than eight hours). Results: Macronutrient, micronutrient, and antioxidant intake did not show significant difference between three groups. Moreover, we did not observe any significant difference between anthropometric indices (weight, body mass index, waist circumference, and percentage body fat). Conclusions: Our study results show no significant relationship between sleep duration, nutrition pattern, and obesity. Further study is recommended.

Keywords: sleep duration, obesity, dietary intake, cross-sectional

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Authors: David Parmenter, Brian Millar

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Obstructive sleep apnoea is a common condition which is generally under-diagnosed. Poorly managed obstructive sleep apnoea carries serious health risks and can greatly impact on the sufferer's quality of life. This publication covers the aetiology, symptoms, and treatment of sleep apnoea. The treatment of Obstructive Sleep Apnoea is an emerging field, and the useful role of the Dental Team is relatively unknown, therefor this paper will highlight the role of the dental team in its treatment. The concept of mandibular advancement appliances, along with the clinical and laboratory stages for constructing them, are documented. It is the hope of the author that this publication will educate healthcare professionals on the role of dental practitioners in the multidisciplinary team for treating sleep apnoea. Objective: Individuals should be more aware of the demographic of patients at risk of sleep apnoea, how it is diagnosed and which group of sleep apnoea patients are suitable to refer for mandibular appliance therapy. Individuals should also be aware of what a mandibular advancement appliance is and how it helps treat obstructive sleep apnoea.

Keywords: sleep apnoea, snoring, sleep appliances, mandibular advancement appliance

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Authors: Hae Dun Kim, Joo Hyun Jang, Geu Rim Seo, Kyung Soo Ra, Hyung Joo Suh

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Lactuca sativa (lettuce) has been known for its medical property to relieve anxiety and nervous. This study was implemented to investigate sleep-promoting effects of the lettuce alcohol extract (LAE). Caffeine is widely used psychoactive substance known to induced wakefulness and insomnia to its consumers. In the present study, the sedative-hypnotic activity of the LAE was studied using the method of pentobarbital-induced sleep in the mouse model. The LAE was administrated to mice 30 min before the pentobarbital injection. The LAE prolonged the pentobarbital-induced sleep duration and decreased sleep latency. The effects of LAE were comparable to those of induced by diazepam. Another study was performed to examine whether LAE ameliorates caffeine-induced sleep disturbance in mice. Additionally, caffeine (10 mg/kg, p.o) delayed sleep onset and reduced sleep duration of mice. Conversely, LAE treatment (80 or 160 mg/kg, p.o), especially at 160 mg/kg, normalized the sleep disturbance induced by caffeine. LAE supplementation can counter the sleep disturbance induced by caffeine. These results suggest that LAE possess significant sedative-hypnotic activity, which supports the popular use of lettuce for treatment of insomnia and provide the basis for new drug discovery. Furthermore, these results demonstrate that the lettuce extract may be preferable for the treatment of insomnia.

Keywords: caffeine, Lactuca sativa, sleep duration, sleep latency

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Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

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Authors: Gabriella Tjondro, Julita Dortua Laurentina Nainggolan

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Introduction: There are several things affecting menstrual cycle, namely, nutritional status, diet, financial status of one’s household and exercises. The most commonly used parameter to calculate the fat in a human body is body mass index. Therefore, it is necessary to do research to prevent complications caused by menstrual disorder in the future. Design Study: This research is an observational analytical study with the cross-sectional-case control approach. Participants (n = 124; median age = 19.5 years ± SD 3.5) were classified into 2 groups: normal, NM (n = 62; BMI = 18-23 kg/m²) and obese, OB (n = 62; BMI = > 25 kg/m²). BMI was calculated from the equation; BMI = weight, kg/height, m². Results: There were 79.10% from obese group who experienced menstrual cycle disorders (n=53, 79.10%; p value 0.00; OR 5.25) and 20.90% from normal BMI group with menstrual cycle disorders. There were several factors in this research that also influence the menstrual cycle disorders such as stress (44.78%; p value 0.00; OR 1.85), sleep disorders (25.37%; p value 0.00; OR 1.01), physical activities (25.37%; p value 0.00; OR 1.24) and diet (10.45%; p value 0.00; OR 1.07). Conclusion: There is a significant relation between body mass index (obese) and menstrual cycle disorders. However, BMI is not the only factor that affects the menstrual cycle disorders. There are several factors that also can affect menstrual cycle disorders, in this study we use stress, sleep disorders, physical activities and diet, in which none of them are dominant.

Keywords: menstrual disorders, menstrual cycle, obesity, body mass index, stress, sleep disorders, physical activities, diet

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Authors: Yi-Fung Lin, Pei-Chen Tsai

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Background: The hospital healthcare team provides 24-hour patient care, and therefore shift-work is inevitable in the nursing field. There is an increased awareness that shift-work affecting circadian rhythms may cause various health problems, especially in poor sleep quality, which may harm the quality of life. Purposes: The purpose of this study was to investigate the influences of demographic characteristics on nurses’ sleep quality and quality of life and the relationship between these predictors of nurses’ quality of life. Methods: A cross-sectional, descriptive correlational study was conducted with purposive sampling of 520 female nurses in a medical center in north Taiwan from July to September 2014. Data were collected with structured questionnaires using Psychometric Evaluation of the Chinese version of the Pittsburgh Sleep Quality Index (PSQI) and the World Health Organization Quality of Life (WHOQOL-BREF). Outcomes: The main results include: 1) Irregular menstruation, non-regular exercisers, and more daily caffeine consumption have negative impacts on sleep quality. 2) Younger age, fewer children, low education level, low annual income, irregular menstruation, pain during menstrual cycles, non-regular exercisers, constipation, and poor sleep quality all contribute negative impacts on the quality of life. 3) The odds ratio of sleep disturbance between 12-hour shifts and 8-hour shifts was 2.26, but there was no significant difference regarding their quality of life scores. Conclusion: This study showed that there is a strong correlation between oncology nurses’ sleep quality and quality of life. Sleep quality is a significant predictor of quality of life in oncology nurses.

Keywords: oncology nurses, sleep quality, quality of life, shift-work

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Authors: Cheng-Yu Tsai, Wen-Te Liu, Shin-Mei Hsu, Yin-Tzu Lin, Chi Wu

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Background: Obstructive Sleep apnea syndrome (OSAS) is a common respiratory disorder during sleep. In addition, Body parameters were identified high predictive importance for OSAS severity. However, the effects of body parameters on OSAS severity remain unclear. Objective: In this study, the objective is to establish a prediction model for OSAS by using body parameters and investigate the effects of body parameters in OSAS. Methodologies: Severity was quantified as the polysomnography and the mean hourly number of greater than 3% dips in oxygen saturation during examination in a hospital in New Taipei City (Taiwan). Four levels of OSAS severity were classified by the apnea and hypopnea index (AHI) with American Academy of Sleep Medicine (AASM) guideline. Body parameters, including neck circumference, waist size, and body mass index (BMI) were obtained from questionnaire. Next, dividing the collecting subjects into two groups: training and testing groups. The training group was used to establish the random forest (RF) to predicting, and test group was used to evaluated the accuracy of classification. Results: There were 3330 subjects recruited in this study, whom had been done polysomnography for evaluating severity for OSAS. A RF of 1000 trees achieved correctly classified 79.94 % of test cases. When further evaluated on the test cohort, RF showed the waist and BMI as the high import factors in OSAS. Conclusion It is possible to provide patient with prescreening by body parameters which can pre-evaluate the health risks.

Keywords: apnea and hypopnea index, Body parameters, obstructive sleep apnea syndrome, Random Forest

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Authors: Ziyu Zhang, Xuanyu Ren, Fei Wu, Qinfei Lu, Yongmei Li, Xinyue Zhi

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Introduction: Adolescents experience a critical period of physical and psychological growth. Few studies focus on the influence of sleep hygiene on psychological health from the high school period to freshmen year. Also, the influence of the COVID-19 pandemic has public health significance. Methods: Totally 698 students from high school and college were included in the manuscript, and a cross-sectional procedure was conducted; the objective was to make the epidemiological comparison of the social phobia/depression prevalence and discuss the effects of potential determinants. Results: Psychological problems, including social phobia and depression, are prevalent, especially among high school students, with gender differences. The current results indicated that the association between sleep status and social phobia is most obvious among high school students, while the higher MMR risk was found both for high school social phobia students and college depressive freshmen. Moreover, the interaction between social phobia and depression was also obvious for both populations. Conclusions: Psychological problems, including social phobia and depression, are more prevalent among high school girls when compared with their male and freshmen peers. Important influenced factors for the risk of psychological problems among the two populations were different, but media multitasking status should be paid attention to for both.

Keywords: adolescence, psychological health, epidemiology, social culture

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Authors: Jiajia Peng, Jianqing Qiu, Jianjun Ren, Yu Zhao

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Background: Insufficient sleep has been focused on as a public health epidemic. However, a comprehensive analysis of disease trajectory associated with unhealthy sleep habits is still unclear currently. Objective: This study sought to comprehensively clarify the disease's trajectory in relation to the overall poor sleep pattern and unhealthy sleep behaviors separately. Methods: 410,682 participants with available information on sleep behaviors were collected from the UK Biobank at the baseline visit (2006-2010). These participants were classified as having high- and low risk of each sleep behavior and were followed from 2006 to 2020 to identify the increased risks of diseases. We used Cox regression to estimate the associations of high-risk sleep behaviors with the elevated risks of diseases, and further established diseases trajectory using significant diseases. The low-risk unhealthy sleep behaviors were defined as the reference. Thereafter, we also examined the trajectory of diseases linked with the overall poor sleep pattern by combining all of these unhealthy sleep behaviors. To visualize the disease's trajectory, network analysis was used for presenting these trajectories. Results: During a median follow-up of 12.2 years, we noted 12 medical conditions in relation to unhealthy sleep behaviors and the overall poor sleep pattern among 410,682 participants with a median age of 58.0 years. The majority of participants had unhealthy sleep behaviors; in particular, 75.62% with frequent sleeplessness, and 72.12% had abnormal sleep durations. Besides, a total of 16,032 individuals with an overall poor sleep pattern were identified. In general, three major disease clusters were associated with overall poor sleep status and unhealthy sleep behaviors according to the disease trajectory and network analysis, mainly in the digestive, musculoskeletal and connective tissue, and cardiometabolic systems. Of note, two circularity disease pairs (I25→I20 and I48→I50) showed the highest risks following these unhealthy sleep habits. Additionally, significant differences in disease trajectories were observed in relation to sex and sleep medication among individuals with poor sleep status. Conclusions: We identified the major disease clusters and high-risk diseases following participants with overall poor sleep health and unhealthy sleep behaviors, respectively. It may suggest the need to investigate the potential interventions targeting these key pathways.

Keywords: sleep, poor sleep, unhealthy sleep behaviors, disease trajectory, UK Biobank

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Authors: Andrew Anis Fakhrey Mosaad

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Introduction: There are many different types of sleep disorders, each with serious implications for a person's health and a large financial burden on society. Method: This review offers a framework based on the International Classification of Sleep Disorders to aid in the diagnosis and treatment of sleep disorders. Differentiating between primary and secondary insomnia is covered, along with pharmacological and nonpharmacological therapy options. Common abnormalities of the circadian rhythm are mentioned along with their therapies, such as light therapy and chronotherapy. This article discusses the identification and management of periodic limb movement disorder and restless legs syndrome. The therapy of upper airway resistance syndrome and obstructive sleep apnea are the main topics of discussion. Conclusion: The range of narcolepsy symptoms and results, as well as diagnostic procedures and treatment, are discussed. The causes, outcomes, and treatments of many types of insomnias, such as sleep terrors, somnambulism, and rapid eye movement (REM) behavior sleep disorders, are discussed.

Keywords: diagnosis, treatment, sleep disorders, insomnia

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Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

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Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

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Authors: Fagner Luiz P. Salles, Janaina C. Oliveira, Ivair P. Cesar

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Statement of the Problem: Auriculotherapy (AT) is a TCM technique, which uses seeds instead of needles, based physiologically on the mechanical stimulation of the cranial nerves. In the context of understanding the new concept of health of the WHO, the AT is an integrative approach for achieving Global Health Care so as to achieve the global health care concerns. This study aimed to evaluate the effect of auriculotherapy on pain and sleep quality in patients with chronic pain. Methodology and Theoretical Orientation: This study was performed between February and March 2017 at the Faculdade Estácio de Sá de Vitória, Brazil. The pain evaluation was through VAS in 4 periods: maximum, minimum, average and at the time of evaluation; the evaluation of sleep quality was used the Pittsburgh Sleep Quality Index. Socio-demographic data included: gender, age, use of medication and BMI. All data are presented as mean (standard deviation), Teste Mann-Whitney and T-student with P-values < 0.05 were regarded as significant. Findings: Participated in this study thirty-two individuals with age (M = 43.18, SD = 17.86), the time with pain in years (M = 3.67, SD = 3.68), 81.7% were female, 75% of the individuals used medication and BMI (M = 26.67; SD = 6.20). The pain presented improvement in the maximum level and the average of the pain and sleep quality before did not have statistically significant results. Conclusion and Significance: This study showed that TA is efficacy for reduction levels of pain. However, AT was not effective in improving sleep quality.

Keywords: auriculotherapy, chronic pain, sleep quality, integrative approach

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