View clinical trials related to Parasomnias.
Filter by:Assisted living residents who have sleep disturbances are at great risk of developing cognitive impairments. The identification of factors that increase sleep problems in this population is the first step towards improving sleep disorders and reducing and/or delaying the occurrence of cognitive impairments in this population. Physical activity has been proposed to improve sleep quality in older individuals, but there is currently no scientific evidence of how sleep mediates the relationship between physical activity and cognition in assisted living residents. This is a cross-sectional study that investigates the relationship between sleep quality, functional/physical capacity, and cognitive performance. Participants will be recruited through a non-probabilistic sampling method (convenience) as this is a feasibility study that aims to identify, for the first time, sleep disorders in assisted living residents using objective measures of sleep. Sleep quality will be measured with polysomnography, actigraphy, and questionnaire. Functional and physical capacity will be assessed through walking tasks and actigraphy. Cognitive tasks will be used to assess memory. This study will bring new insights into the factors that affect the quality of life and sleep in assisted living residents. The evidence-based knowledge acquired on-site will be translated and shared with the local and global scientific community to raise awareness of the factors that contribute to increasing institutionalization and dependent living. Results obtained from objective and subjective measures of sleep will be of great importance to develop specialized clinical expertise and behavioral interventions that will meet residents' needs.
Sleep deprivation (SD) has a powerful degrading effect on cognitive performance, particularly psychomotor vigilance (PV) and reaction time. Caffeine is well known to be an effective countermeasure to the effects of SD. However, individuals differ in both their response to SD and to the administration of caffeine. This has made it difficult to provide individualized recommendations regarding the use of caffeine to sustain alertness when needed. For the past two decades, the Army's Biotechnology HPC Institute (BHSAI), in collaboration with the Walter Reed Army Institute of Research, have been developing statistical models to predict individual performance during prolonged SD. Recently, this resulted in the publication of the 2B-Alert app, a computer algorithm based on large datasets that can learn an individual's response to SD by combining actigraphic sleep data with simultaneously acquired PV performance data. The 2B-Alert algorithm can predict an individual's sleep need and performance after ~2 weeks of training the model. Recently, the model has been extended to incorporate individualized responses to caffeine. This was recently validated in a retrospective study published by BHSAI in 2019. The present study is designed to test the predictive capacity of the 2B-Alert app in real time. During Phase 1 a total of 21 healthy participants will wear an actigraph & complete multiple daily PV tests on a personal cell phone. After 2 weeks, these individuals will attend Phase 2 involving an in-laboratory stay & SD. Participants will have an 8-hour period of sleep in the laboratory, followed by 62 hours of continuous wakefulness. During these 62 hours, participants will complete PV and mood testing every 3 hours. The 2B-Alert app will be used to predict individual caffeine need to sustain performance at near-baseline levels based on the statistical model. At 44 hours SD, participants will undergo a 6-hour "alertness window" where they may receive individualized doses of caffeine based on the recommendations of the model. After 62 hours of SD, Phase 3 begins, involving a night of monitored recovery sleep and additional sessions of PV and mood testing until release from the study at 6 pm on the final day. It is hypothesized that the 2B-Alert app will be effective at providing caffeine dosing recommendations that return PV and mood performance to normal levels during the alertness window.
This is a novel observational study with the overarching aim of evaluating the association between poor sleep health and poor quality of recovery in a surgical setting. It hopes to assess and optimize the perioperative sleep health of patients so significant improvements in their quality of recovery and health outcomes may be achieved.
Due to the COVID-19 global health pandemic, many people are likely experiencing increased stress. The well-being of physicians in training may be significantly impacted by this pandemic. Meditation is a self-management strategy that can be utilized by anyone to assist with the management of stress. Meditation mobile applications, such as the "Calm" app, can be used to help manage stress, especially during this uncertain time. The investigators propose a prospective evaluation of perceived stress, anxiety, burnout and sleep disturbance in the house staff at Banner University Medical Center Phoenix, with the use of the mobile meditation app, "Calm." The investigatros additionally want to evaluate the feasibility of using the mobile app, including looking at adherence to use of the app and physician satisfaction with use of the app.
The purpose of this study is to determine whether sleep disturbances in children aged 7 to 12 during COVID-19 containment are more prevalent in children who received routine psychiatric care before containment compared to children who don't have any psychiatric care.
The goal of MEM-ASA is to investigate the prevalence of anxiety/depression, sleep disturbances and alcohol use disorder in elderly with cognitive complaints. In memory clinics of Normandy (France), all patients aged over 50 year-old are systematically questioned about anxiety, depression, sleep quality and alcohol use disorder. They also perform a neuropsychological assessment. Questionnaires are given to the patient and his/her caregiver to be filled in at home. Levels of anxiety/depression, sleep quality and alcohol consumption are related to neuropsychological performance, diagnosis and responses to the questionaires.
Perinatal depression and anxiety are common, serious, and frequently overlapping disorders that increase morbidity and mortality in new mothers (including suicide) and result in poor infant/child outcomes. Current therapies often fail to produce recovery or are poorly tolerated, and many pregnant women seek non-pharmacologic therapy or forgo treatment when non-pharmacologic options are not available. Expectant and new mothers who experience circadian rhythm dysregulation are at increased risk for perinatal depression. This Confirmatory Efficacy Clinical Trial of Non-Pharmacological Interventions for Mental Disorders R01 seeks to test whether a Personalized Integrated Chronotherapy (PIC) intervention can improve treatment outcomes for pregnant patients seeking outpatient treatment for depression, with or without anxiety. PIC is a multicomponent treatment consisting of bright light therapy, sleep phase advance, and sleep stabilization/restriction that targets the Research Domain Criteria (RDoC) constructs of circadian rhythms and sleep-wake behavior. To increase sample size and diversity and accelerate recruitment, this study will be performed at 4 sites that differ in clinical structure and that have piloted the PIC intervention. The study will enroll expectant mothers diagnosed with major depressive disorder during 3rd trimester of pregnancy. Participants will be randomized to either: (a) usual care (UC, n = 110) or (b) PIC+UC (n = 110). PIC+UC will have pregnancy and postpartum components and will be administered via a personalized approach tailored to optimize the intervention based on each patient's individual circadian and sleep timing. After a baseline assessment, PIC will be prescribed during 5 dedicated clinical visits: three during 3rd trimester of pregnancy and 2 in the postpartum period. UC will consist of medication and/or psychotherapy. UC will be quantified in both groups to evaluate differences between the PIC+UC and UC groups. Mood will be measured in both groups by blinded clinician interview and patient self-report. The safety profile of the PIC intervention will be assessed by evaluation of side effects/adverse events. Importantly, the study will also examine the target mechanisms by which PIC is hypothesized to work and test the mediation effects of the circadian targets on improvement in mood symptoms. Participants will wear wrist actigraphy/light monitors continuously during weeks 28-40 of pregnancy and postpartum weeks 2-6 to assess light exposure and to estimate sleep timing and duration. Circadian phase (measured with salivary dim light melatonin onset) will be measured at baseline during pregnancy (~30 weeks' gestation), at 36 weeks' gestation, and at postpartum week 6. Exploratory aims will examine associations between infant sleep behavior and maternal circadian rhythms and factors relevant to future dissemination of PIC. If this intervention is effective, perinatal PIC could change clinical practice and have major public health impact due to the high prevalence of perinatal depression and anxiety, the negative effects of mood disorders on mothers and their children, and the need to provide effective, novel, non-pharmacologic therapies for women with perinatal mood disorders.
Cancer and cancer treatment often lead patients and survivors to experience a host of chronic symptoms, of which sleep disturbances are a major concern. Smartphone-based meditation via an already-developed app (i.e., Calm) is a unique and novel way of providing a potentially helpful symptom-management strategy to cancer patients and survivors. Our hypothesis is that cancer patients/survivors using the Calm smartphone app for eight weeks will see improved sleep disturbance (primary outcome) as well as anxiety, depression, pain intensity, global health, quality of life, emotional regulation, and mindfulness when compared to a time and attention-matched health education podcast control group. Cancer patients/survivors (n=300) will be randomly assigned to an intervention or control group for eight weeks, with study outcome measurement occurring at baseline, post-intervention (i.e., week eight), and follow-up (i.e., week 20).
This research study is being conducted to understand if patients benefit from mobile health interventions while waiting for in-clinic mental health treatments, and to understand which patients receive the most benefit.
Bronchial asthma is characterized by the presence of symptoms that vary over time and of severity. Asthma symptoms tend to worsen at night and in the early hours of the morning, and the presence of nocturnal symptoms is an important indicator of therapeutic intervention in order to control the severity of the disease. Aim of the study is to investigate sleep disorders and quality, as well as and depressive and anxiety symptoms in patients affected by severe asthma before and after 6 months of treatment with monoclonal therapy. An observational, cohort, prospective, monocentric study will be conducted to evaluate subjective quality of sleep at baseline and post monoclonal treatment.