Among The Sleep Free Download Mac
Dayna Delabarre
Later that night, Teddy is taken away from David by an unseen force. David goes after it and finds Teddy inside a washing machine. He unplugs it and takes him out. Teddy realizes that something is not right and that they must find Zoey. Along the way, they encounter a shadowy figure called Harald. The search leads them to discover a slide that takes them to a small playhouse within a cavern that is presumably under the house, and the door found inside it leads them into a journey through several surreal environments, consisting of an underground playground, a dilapidated mansion that has merged with a marshy forest, and a bizarre series of corridors created by hundreds of closets. Teddy instructs David to find four memories he shared with Zoey that will lead them to her. The memories take the forms of four objects: Her pendant from her necklace shown at the start of the game, the music box she plays to put him to sleep at night, the storybook, and the pink elephant. Throughout the search, David is pursued by a large, feminine, troll-like monster named Hydra and a creature with glowing white eyes named Heap, who has a coat as a body like the ones in David's closet earlier.
Introduction: Individuals report using cannabis for the promotion of sleep, and the effects of cannabis on sleep may vary by cannabis species. Little research has documented preferences for particular cannabis types or cannabinoid concentrations as a function of use for sleep disturbances.
Methods: 163 adults purchasing medical cannabis for a physical or mental health condition at a cannabis dispensary were recruited. They provided self-report of (a) whether cannabis use was intended to help with sleep problems (e.g. insomnia, nightmares), (b) sleep quality (PSQI), (c) cannabis use (including preferred type), and (d) symptoms of DSM-5 cannabis dependence.
Results: 81 participants reported using cannabis for the management of insomnia and 14 participants reported using cannabis to reduce nightmares. Individuals using cannabis to manage nightmares preferred sativa to indica strains (Fisher's exact test (2) = 6.83, p < 0.05), and sativa users were less likely to endorse DSM-5 cannabis dependence compared with those who preferred indica strains (χ(2)(2) = 4.09, p < 0.05). Individuals with current insomnia (t(9) = 3.30, p < 0.01) and greater sleep latency (F(3,6) = 46.7, p < 0.001) were more likely to report using strains of cannabis with significantly higher concentrations of CBD. Individuals who reported at least weekly use of hypnotic medications used cannabis with lower THC concentrations compared to those who used sleep medications less frequently than weekly (t(17) = 2.40, p < 0.05).
Conclusions: Associations between sleep characteristics and the type of cannabis used were observed in this convenience sample of individuals using cannabis for the management of sleep disturbances. Controlled prospective studies are needed to better characterize the impact that specific components of cannabis have on sleep.
Background: Poor sleep quality and depressive symptoms are common among college nursing students, and may be associated with each other. However, the mechanism for this association has not been well understood.
Methods: 242 undergraduate nursing students at a public university in the northeast United States completed an online survey delivered through SurveyMonkey with self-reports of sleep quality, coping styles, and depressive symptoms from October to November 2015.
Conclusions: In addition to sleep promotion, effective interventions to facilitate the development of appropriate coping strategies among nursing students are needed to enhance their mental health and well-being.
Correlations, means, and standard deviations for depression severity, self-reported sleep difficulty, cognitive control of emotion stimuli, objective sleep measures, and the clock circadian locomotor output cycles kaput gene, CLOCK, single nucleotide polymorphisms.
There are a few studies of the association of sleep quality and obesity.8,11,12 In the WSCS, polysomnographic measures of sleep quality were associated with ghrelin levels.9 Jennings and colleagues8 reported an association between poor global sleep quality, measured through the Pittsburgh Sleep Quality Index (PSQI) and increased BMI and the metabolic syndrome. The associations among sleep duration, sleep quality, and obesity are bidirectional. Once obesity occurs, sleep is likely to be disturbed and weight loss has been observed to reduce sleep disturbance and obesity associated sleep disordered breathing.13
A series of multiple linear regression analyses was performed in order to evaluate the associations among levels of anxiety and depression symptoms with components and total score of PSQI and ESS; they are summarized in Table 3 and Table 4. Our analyses demonstrated that HADS-Anxiety and HADS-Depression scores (outcome variables) were significantly associated with all the components of PSQI except sleep disturbance, use of sleeping medication, and daytime dysfunction. The PSQI global score had a positive significant association with anxiety (β = 0.29; P = 0.01) and depression (β = 0.31; P < 0.01) components of HADS (Table 3).
The current study found that poor sleep quality, anxiety and depression symptoms, and reduced quality of life were highly prevalent among patients with severe obesity. More than two-thirds of patients with severe obesity reported poor sleep quality and the mean (standard deviation) self-reported sleep duration was 6 h and 20 min (1 h and 30 min). We also found that poor sleep quality and excessive daytime sleepiness were strongly associated with mood disturbance and poorer quality of life. After controlling for age, sex, hypertension, diabetes, and OSA, sleep quality and daytime sleepiness were significantly associated with mood disturbance and quality of life impairment.30
A growing body of epidemiological evidence indicates that both sleep quantity and quality are associated with increased risk of obesity.4 Several potential mechanisms have been proposed for the sleep-obesity relationship, including alterations in metabolic hormones.31 Once severe obesity occurs, the management of obesity through lifestyle change and medical approaches becomes more difficult; thus, bariatric surgery is recommended by several international guidelines for this patient population.32 Despite the success of bariatric surgery in weight loss, significant psychological morbidity may still remain. To improve success with interventions, including bariatric surgery, to treat severe obesity, a greater understanding of factors that maintain obesity and its comorbidities is necessary.
The severely obese individuals in our study also reported high anxiety and depressive symptoms and low quality of life. The results from a cross-sectional study of McDonough and colleagues36 demonstrated that compared to individuals with normal weight, over-weight, and obese individuals reported lower health-related quality of life (HRQoL). There is a close link between obesity and depression. Algul and colleagues37 postulated that compared to healthy controls, the obese group are more depressed, had lower quality of life, and higher sleep disturbance.
We investigated the potential link between PSQI and ESS with HADS-Anxiety, HADS-Depression scores, and IWQOLLite via the utilization of linear regression models. The data are cross sectional and causal pathways among these variables cannot be inferred. We used SEM analysis to test whether poor sleep factors negatively influence mood or vice versa. Interestingly, our hypothesized SEM model that was presented earlier supported our prior linear model findings. We hypothesized that sleep can be influenced by obesity-related conditions, and both poor sleep factors and obesity-related conditions may influence quality of life and mood of the participants.
Our study has merit in sample size and a detailed statistical analysis. Our study has also has several limitations. The main limitation is the cross-sectional design, so direct causal relationship between sleep disturbances and anxiety and depressive symptoms cannot be inferred. Another limitation is using self-report questionnaires. PSQI is a reliable and validate instrument; however, it cannot be used as an accurate diagnostic tool.
Sleep and physical activity are both associated with multiple behavioral and metabolic health outcomes, and both behaviors have been linked to the development of weight status. Recent estimates suggest that many children are not meeting sleep recommendations or participating in adequate levels of physical activity, which may be related to the high prevalence of childhood overweight and obesity. Much of the research assessing these relationships has focused on adults and older children, and has relied on parent- or child-reported, cross-sectional research in predominantly White samples. Little work has focused on these relationships in very young children. Although more research has been conducted in adolescent samples, these studies rarely consider the effect of weeknights vs. weekend nights or physical activity intensity in their analyses. Therefore, the overall purpose of this dissertation was to examine the longitudinal relationships between sleep, physical activity, and weight status in both very young children and adolescents.
This dissertation was comprised of three studies. The first study used data from the Linking Activity, Nutrition and Child Health (LAUNCH) observational study to evaluate longitudinal associations between sleep and physical activity in 6-24 month-old children. Device-based measures were used to assess daytime, nighttime, and 24 hour sleep durations, nighttime sleep awakenings, and daytime total physical activity. Linear mixed models assessed whether the within- and between-person effects of physical activity were associated with sleep. Children with higher total physical activity levels slept less during the day compared to children with lower total physical activity levels, and when children were more physically active compared to their own average physical activity levels, their 24-hour sleep duration was lower. Differences in nighttime sleep duration were seen based on race/ethnicity and SES. The findings indicate that mechanisms underlying the sleep and physical activity relationship in young children vary from those that have been suggested in older children and adults.
aa06259810