To sum upIn summary, this study was aimed to investigate the effects of a smartphone-based slow paced breathing intervention (6 cpm) performed for a duration of 15 minutes before sleeping during across 30 days, compared to a control condition with participants using social media on their smartphone. Results showed that in the experimental group subjectivesleepquality was improved and CVA night was increased, while a marginal increase was also found in CVA morning .
PSQI consisted of 19 items to evaluate quality of nocturnal sleep in hemodialysis patients within the past month. This questionnaire is composed of seven components, as follows: subjectivesleepquality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, daytime dysfunction and use of sleeping medications. Total scores of these indices are calculated within a score range of 0-21, and scores of ≤5 are defined as adequate sleepquality, while scores of >5 are defined as inadequate sleepquality. Reliability of PSQI has been confirmed using Cronbach’s alpha (0.8) (28, 29), and in this study, reliability of the questionnaire was confirmed at Cronbach’s alpha of 0.72.
The first hypothesis was that self categorised good sleepers would have better overall sleepquality than self categorised poor sleepers, but no significant difference in overall sleepquality in poor sleepers taking and not benzodiazepines. This was supported by the data of the present study. The mean values for the Global PSQI scores indicated that older adults who categorised themselves as good sleepers had better global sleepquality than those who categorised themselves as poor sleepers. However, as expected, due to the possibility of tolerance effects, there was no difference in global sleepquality between the poor sleepers that were taking benzodiazepine hypnotics and older adults not using these medications to improve their sleep. Previous research with older adults in residential care has proposed that self-classified good and poor sleepers categorise themselves in that manner due to the way that they thought about their own sleepquality, in the wider context of their construction of normal sleep, which was based on their cognitive comparison strategies, rather than their classification being grounded on their actual experience of sleep (Davis, Hood, & Bruck, 2007). The process of downward social comparison, whereby people search for comparison with others worse off than themselves, is suggested to improve personal satisfaction, while upward social comparison may contribute to the individual feeling more disappointed with their experiences. For older people downward social comparison is believed to lend a degree of protection against the loss of control that is often an adjunct to aging (Heckhausen & Brim, 1997; Frieswijk et al., 2004). Davis, Hood, and Bruck (2007) found that those categorising themselves as good sleepers utilised downward social comparison, while those classifying themselves as poor sleepers tended towards upward social comparisons. This occurrence might also, at least in part, account for mixed results as to whether subjective and objective sleepquality and sleep parameters concur in older people (Chong, Fujun, & Chunying, 2000; Riedel & Lichstein, 1998; Vitiello, Larsen & Moe, 2004).
Limited availability of the data regarding the “ Prevalence of mobile use and its association with sleepquality in the Saudi population ” compelled us to design this project. To our knowledge, the current study recruited the largest number of samples of young Saudi population for investigating the link between mobile phone use and sleepquality. We hypothesize that a positive association exists between mobile use and poor sleepquality. We also aimed to ﬁ nd out the prevalence of mobile-related sleep risk factors (MRSRF) in mobile users and their effects on sleep, ie, using mobile before sleeping after the lights have been turned off, not enabling airplane mode on mobiles, putting the mobiles near or below the pillows and bedside while sleeping. As no previous studies are available to highlight these important ﬁ ndings.
High-resolution magnetic resonance imaging by voxel- based morphometry shows gray matter loss in the frontal, temporal, and parietal lobes, the anterior cingulate gyrus, the hippocampus, and the cerebellum in patients with OSA . Functional magnetic resonance imaging dem- onstrates decreased brain activation in the frontal and par- ietal lobes, insula, and cingulate gyrus , while single photon emission computerized tomography shows signifi- cantly reduced regional cerebral blood flow in the bilateral para-hippocampal gyri, right lingual gyrus, peri-central gyrus, and cuneus in OSA patients . Taken together, these findings suggest that dysfunction in these areas can account not only for cognitive deficits, but also for the misperception of sleepquality in OSA patients.
Ages of the participants ranged from 37-69 (mean=53.4). Of the 80 subjects participating in the study, 38 (47.5%) were females and 42 (52.5%) were males. As shown in table-1, no significant between group differences were reported as regards age or sex. Similarly, no significant differences were reported between patients and controls regarding socioeconomic status (p values ≥ 0.05; table-1 and figure 1). Patients with hepatic cirrhosis showed significantly higher scores (indicating more problems) in most of the subscores of Pittsburgh sleepquality index, namely subjectivesleepquality, sleep latency, sleep disturbances, use of sleep medications, and total score of PSQI. These differences are all highly significant (p values ≤ 0.01; table-2 and figure 2). Patients also showed significantly later usual bedtimes and wake up times in weekends but not in week days. They also reported significantly longer time lost before falling asleep and time lost due to waking up during night. Finally, patients with hepatic cirrhosis reported significantly higher tendency towards evening circadian preference as compared to healthy controls (table 3, figure 3 and 4).
Main calculations: first, correlations were computed between sleep patterns (PSQI: subjectivesleepquality, sleep duration, sleep latency, sleep efficacy, sleep disturbances, sleep medication, daytime dysfunction; overall score), driv- ing behavior (MDBQ: overall score), general health (GHQ:2 overall score), aggression (overall score), and reaction times (auditory, visual, and visual–auditory stimuli). Second, t-tests for unrelated samples were carried out with the PSQI cutoff score of less than five points (no sleep disturbances) or five and higher points (sleep disturbances) as independent variables and driving behavior, general health, aggression, and reaction time as dependent variables. Third, a multiple regression analysis (stepwise; backward) was performed with the MDBQ total score as a dependent variable, and subjectivesleep, general health, and aggression as predictors. Fourth, a path analysis was executed, again with the MDBQ total score as a dependent variable; we tested the direct effects of sleep on driving behavior and indirect effects via general health. The nominal level of statistical significance was set at alpha < 0.05. Statistical computations were performed with SPSS ®
In the present study, the baseline sleepquality was not significantly different in the two groups. However, the intervention could significantly improve the overall PSQI score and all dimensions of sleep except for the use of sleep medications and daytime dysfunction. In addition, although the median score of the daytime dysfunction was not significantly different between the two groups, however, in comparison with the baseline, a significant reduction in daytime dysfunction was occurred in the in- tervention group. According to the patients in this study, the intervention did not affect their use of sleep medica- tions. This finding might be attributed to the fact that most patients in the CCU have doctor’s orders of sleep- ing medication at night and the orders are routinely ex- ecuted by nurses. Moreover, most patients are trusting in their physician’s instructions such as sleep medica- tions and do not change or discontinue their medica- tions without the physician’s authorization (20). Saeedi et al. also noted that complementary therapies had no significant effect on use of sleep medications in hospital- ized patients (6). For instance, Neyse et al. found that ear- plug can significantly improve the majority of domains of sleepquality except for subjectivesleep domain (21). Daneshmandi et al. (10) also found that eye mask signifi- cantly improved the mean scores of the sleep latency, the sleep duration, the habitual sleep efficiency, the daytime dysfunction and the use of sleep medications, but had no significant effect on subjectivesleepquality domain. The contradiction between the results of Neyse et al. (21) and Daneshmandi et al. (10) with the results of the cur- rent study might be attributed to the differences in the interventions used. For example, in the study conducted by Neyse et al. (21) instead of eye mask, earplugs have been used. On the other hand, in the study conducted by Daneshmandi et al. (10) the duration of intervention was longer than this study. The duration of intervention in the study conducted by Daneshmandi et al. was at least four nights while our intervention lasted only for three nights (10).
The authors analyzed quality of sleep according to the time of the experiment and the type of refuge space using the OSA sleep inventory and calculating the average score of the two subjects. Subjectivesleepquality by type of refuge space for the summer experiment is summarized in Figure 6. As for the “refreshing” and “initiation and maintenance of sleep” factors, which are important in maintaining strength and stamina for day-to-day living, the score for the corrugated cardboard temporary shelter and subjects’ homes reached fifty points, showing that quality of sleep was maintained in these environments. Although the “frequent dreaming and anxiety” factor was rated low for subjects’ homes, it is possible that the subjects were affected because the evaluation was made one day before the experiment commenced. As for the tent, the score was around forty points for most factors. The rating for
Fifth, no data were gathered as regards subjectivesleepquality and daytime sleepiness or fatigue. These limitations hold particularly true in that no item canvassed respiratory issues such as obstructive sleep apnea or snoring, which, by definition, impair sleep. Sixth, we observed that the mean reported subjectivesleep duration of about 8.5 hours matched the recommended sleep duration for young adults. Accord- ingly, we might question to what extent the present sample of university students reflects young adults as a whole. In this regard, we also note that some participants completed the survey during the summer break, when a more individual and self-paced wake-sleep pattern is more likely. Last, given the cross-sectional nature of the survey, no conclusion can be drawn as to the direction of influence between sleep duration, gender, BMI, and feeling of being restored. A longitudinal study design, like that reported by Nishiura and Hashimoto 66
Chinese version of the Pittsburgh SleepQuality Index (C-PSQI): We used the translated (Chinese) version of the Pittsburgh SleepQuality Index of Chiang , originally developed by Buysse, Reynolds III, Monk et al. . This is a self-rated questionnaire which assesses sleepquality and disturbances over a 1-month time inter- val. Nineteen individual items generated seven “component” scores: subjectivesleepquality, sleep latency, sleep duration, habitual sleep efficient, sleep disturbances, use of sleeping medication, and daytime dysfunction. The seven components were scored from 0 to 3 points, with each component weighted equally. A score of “0” indicated no difficulty, while a score of “3” represented severe difficulty. The possible total scores of the seven components ranged from 0 to 21. A higher score signified worse sleepquality. “Poor sleep” was defined as a PSQI score of greater than 5 . The Cronbach’s α value for this study was 0.83.
A trend towards significance was observable for the association between affiliation and disorders in initiating or maintaining sleep. A possible explanation might be that oxytocin is an important factor in the association between affiliation and sleep (Blagrove et al., 2012). Oxytocin has anxiolytic (anxiety reducing) and sedating effects and is secreted in the paraventricular nucleus of the hypothalamus, the part of the brain that is involved in regulating sleep and arousal, so it may play an important role in sleep-wake behavior. Furthermore, oxytocin is also involved in affiliative behaviors, which might explain the link between sleep and affiliation. Moore et al. (2010) also found that affiliation/sociability was an important factor in predicting sleep in (pre)adolescents. The authors argued that due to the developmental importance of social relationships during (pre)adolescence and the availability of cell phones and social media, it is not surprising that socially active (pre)adolescents have more sleep problems than those who have a less vivacious social life.. Affiliation did turn out to also be a moderately strong predictor of the mean hours of sleep a child gets each night during the week and subjectivesleepquality. So, more affiliation was related to less sleep problems.
Nearly 16% of the students in our sample classified their sleepquality bad, however Corrêa et al found that 40% of the study subjects reported their life. 26 Poor sleepquality is associated with excessive daytime sleepiness. 27,28 In the present study, daytime dysfunction was reported by 70% of the participants, who had difficulty staying awake during the day at least once a week. This is consistent with the literature, although there are variations across studies in the proportion of medical students reporting daytime sleepiness: 31%; 42.1% ; and 63%. 27,29,30 Therefore, medical students experienced greater deleterious effects on subjectivesleepquality and daytime dysfunction than non-medical students. This can be explained by the fact that attending a medical course requires a high level of dedication and selflessness, signifying harmful lifestyle changes, such as sleep deprivation and poor sleep hygiene habits. 31-34
Although no differences in sleep patterns could be found when only nights with nightmares and compar- able nights of control participants with neutral dreams were analyzed, some results have to be discussed more detailed. Highest effect sizes (small-medium to medium) were found for sleep onset latency (NM longer), arousal index (NM higher), percentage of stage N1 (NM more) and percentage of stage REM (NM less). All differences point in the expected direction which suggests that nightmare sufferers may potentially differ in sleep archi- tecture. Overall, we found almost exclusively high effects on self reported sleepquality with significant differences between both groups and some small to medium effects for objective sleepquality that were not significantly dif- ferent. Nightmares seem to influence subjectivesleepquality more severely than physiological sleep pattern. Future ambulatory studies should include more NM subjects to unveil possible sleep pattern differences.
Sleep disturbances were measured with the Polish version of the Pittsburgh SleepQuality Questionnaire (PSQI). The PSQI has internal consistency and a reliability coefficient (Cronbach’s alpha) of 0.83 for its 7 components. The PSQI is a 19-item self-rated questionnaire used for evaluating subjectivesleepquality during the previous month. The PSQI is a questionnaire designed to evaluate the following: overall sleepquality, sleepquality, sleep latency, sleep dura- tion, sleep efficiency, sleep disturbance, medication use, and daytime dysfunction. 12 Each answer was scored on a scale
Background: Medical residency programs are traditionally supposed to be having long working hours, which can be associated with a poor quality of sleep and resultant daytime sleepiness. This poses threat to both physician and patient. This study has an alarming importance in recent scenario, where India is witnessing growing incidents of assaults against resident doctors. We evaluated the subjectivesleepquality, day time sleepiness, satisfaction with life, stress, anxiety and depression and their association with subjectivesleepquality amongst the residents on their off- duty days and also compared these findings amongst various departments of our institution.
This study aims to determine the relationship between Post Traumatic Stress Disorder (PTSD) and current circadian typology and sleep habits of adults who experienced the Great Hanshin-Awaji Earthquake (on 17th January 1995) after becoming adults. An integrated questionnaire was administered in August, 2011 to 467 people aged 38 - 92 (mean age: 64.8 years) in Hyogo Prefecture, Japan, with responses received from 223 people (females: 142, males: 78, unknown: 3). The questionnaire consisted of basic questions about attributes such as age and sex, questions on sleep habits and sleepquality (SubjectiveSleepQuality Scale), the Torsvall-Åkerstedt Diurnal Type Scale and the Impact of Event Scale-Revised (IES-R) which dealt with PTSD scores. The participants were divided into a High Damage Group (HDG) and Low Damage Group (LDG) based on public statistical information on the extent of damage to buildings and number of casualties in the smaller districts of Kobe City in which participants experienced the disaster. HDG participants exhibited significantly higher IES-R scores than LDG participants (p = .002). Only in HDG participants, there was significantly negative correlation between Diurnal-Type scale scores and IES-R scores (high PTSD scores correlated with greater evening type [low scores of Diurnal-Type scale]) (p = .001) (p = .920 in LDG participants). In both the HDG and LDG, there was a significant positive correlation between the SubjectiveSleepQuality Scale (higher score meaning lower sleepquality) and IES-R score (high PTSD scores correlated with low quality of sleep) (p < .001 in HDG; p = .001 in LDG). These results suggest that people who suffered severe damage from a disaster and who currently show severe PTSD symptoms are more evening-typed and have a lower quality of sleep. Intervention to im- prove their quality of sleep and promote a morning-typed lifestyle may be an effective way to reduce PTSD symptoms.
Whole-night polygraphy is a method which is widely used in sleep laboratories for diagnostic purposes. The evalua- tion of the recordings is based on definitions of sleep stages well established since fifties . The technique, scoring and terminology, as well as a set of sleep indica- tors, are standardised . Besides the proportion of the individual sleep stages, several other measures such as sleep latency and sleep efficacy are used (see Methods). The sleep indicators were originally developed for diag- nostic purposes, in patients with narcolepsy and apnoic syndrome. It was considered of interest to judge the use- fulness of the individual indicators in psychiatric disor- ders. Some information on that can be obtained from the number of significant correlations in Tables II and IV. As it will be seen, the sleep efficacy, or its modification (SPT/ TIB), seem to be more informative than the other polys- omnographic indicators.
Results: A total of 188 patients with migraine, aged 38.1 ± 9.9 years, were enrolled. The mean SCD-Q score was 6.5 ± 5.5, and 44.7% of participants were identified as SCD. Migraineurs with SCD reported higher headache pain intensity and headache impact, as well as greater prevalence of anxiety, depression, reduced quality of sleep, and shorter sleep duration during weekdays compared to migraineurs without SCD. There were no significant differences in terms of age, sex, migraine type (chronic/episodic), medication, or sleep duration during weekends between the two groups. Upon multivariate logistic analysis adjusted for age, sex, headache characteristics, and psychological variables, depression was associated with increased risk of SCD (Odds ratio 1.31, 95% confidence interval 1.16 – 1.49) and sleep duration during weekdays was associated with decreased risk of SCD (Odds ratio 0.66, 95% confidence interval 0.44 – 0.97).