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BACKGROUND: Sleep and mental health share a bidirectional relationship whereby problems in one exacerbate the other. Accordingly, sleep problems are frequent and severe in serious mental illness (SMI) populations, exacerbating SMI symptoms. This study examined the documentation and treatment of sleep problems within anonymised clinical records of SMI patients, and their association with attendance rates and number of appointments scheduled. METHODS: Patient records between 01.09.2021 and 31.08.2022 were identified and relevant records (n = 229) extracted from an NHS Trust database. Content analysis was used to assess documentation and treatment of sleep problems and Chi-square tests were used to assess demographic differences. Mann-Whitney U tests were used to compare attendance rates and number of appointments scheduled between patients with/without sleep problems. RESULTS: Most (n = 170; 84 %) patients with sleep problems had no or minimal assessment of the sleep problem within their records. Patients were primarily offered no (n = 115; 57 %) or non-recommended (n = 69; 34 %) sleep treatment. More outpatients were offered no sleep treatment (n = 89; 64 %) than inpatients (n = 26; 41 %) (p = .002) whilst more inpatients were offered non-recommended sleep treatments (n = 33; 52 %) than outpatients (n = 36; 26 %) (p < .001). No significant associations were found between sleep and attendance or appointments scheduled. CONCLUSIONS: There is a lack of routine clinical attention to sleep assessment and treatment in SMI groups. Where sleep is addressed, treatment often conflicts with guidelines. Improved sleep assessment and treatment could significantly enhance current SMI patient care.

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BACKGROUND: Disturbed sleep is frequently identified in adult patients with cancer and their caregivers, with detrimental impact on physical health. Less known is the extent to which self-reported and actigraph-measured sleep patterns are similar between patients and their sleep-partner caregivers, and how these different modes of sleep measurements are related to physical health. METHODS: Patients diagnosed with colorectal cancer and their sleep-partner caregivers (81 dyads) completed a questionnaire for physical functioning and collected saliva samples for seven consecutive days, from which cortisol slope was quantified. Additionally, participants completed a daily sleep diary and wore actigraph for 14 consecutive days, from which sleep duration, sleep onset latency (SOL), and duration of wake after sleep onset (WASO) were calculated. RESULTS: Participants reported sleep patterns that fell within or close to the optimal range, which were similar between patients and their caregivers. Self-reported and actigraph-measured sleep duration had moderate levels of agreement (ICC = 0.604), whereas SOL and WASO had poor agreement (ICC = 0.269). Among patients, longer self-reported WASO was associated with poorer physical health and flatter cortisol slope (p ≤ 0.013). Among caregivers, longer self-reported SOL was associated with poorer physical functioning, actigraph-measured WASO was associated with steeper cortisol slope, and longer self-reported sleep markers studied than actigraph-measured were associated with poorer physical functioning (p ≤ 0.042). CONCLUSION: Findings suggest that employing multiple assessment modes for sleep and physical health is vital for comprehensive understanding of sleep health. Furthermore, when addressing patients' sleep health, it may be beneficial to include their sleep-partner caregivers who may experience similar disturbed sleep.

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Sleep holds significant importance for maintaining health and aiding in illness recovery. Its deprivation impacts all human organ systems, from cognitive function, social interaction, and work capacity to cellular regeneration and immune function. Therefore, sleep plays a crucial role in our body and maintaining health and well-being. Given its importance and close relationship with the neurodevelopment and growth of children and adolescents, this topic is highly significant in pediatric and adolescent health consultations. Family physicians, due to their proximity and understanding of the individual within their family, have the prerogative to contribute to family literacy, empower them, and significantly enhance the quality of life and overall health.

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Polysomnography (PSG) is the reference standard of sleep measurement, but is burdensome for the participant and labor intensive. Affordable electroencephalography (EEG)-based wearables are easy to use and are gaining popularity, yet selecting the most suitable device is a challenge for clinicians and researchers. In this systematic review, we aim to provide a comprehensive overview of available EEG-based wearables to measure human sleep. For each wearable, an overview will be provided regarding validated population and reported measurement properties. A systematic search was conducted in the databases OVID MEDLINE, Embase.com and CINAHL. A machine learning algorithm (ASReview) was utilized to screen titles and abstracts for eligibility. In total, 60 papers were selected, covering 34 unique EEG-based wearables. Feasibility studies indicated good tolerance, high compliance, and success rates. The 42 included validation studies were conducted across diverse populations and showed consistently high accuracy in sleep staging detection. Therefore, the recent advancements in EEG-based wearables show great promise as alternative for PSG and for at-home sleep monitoring. Users should consider factors like user-friendliness, comfort, and costs, as these devices vary in features and pricing, impacting their suitability for individual needs.

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Wearable sleep trackers are increasingly used in applied psychology. Particularly, the recent boom in the fitness tracking industry has resulted in a number of relatively inexpensive consumer-oriented devices that further enlarge the potential applications of ambulatory sleep monitoring. While being largely positioned as wellness tools, wearable sleep trackers could be considered useful health devices supported by a growing number of independent peer-reviewed studies evaluating their accuracy. The inclusion of sensors that monitor cardiorespiratory physiology, diurnal activity data, and other environmental signals allows for a comprehensive and multidimensional approach to sleep health and its impact on psychological well-being. Moreover, the increasingly common combination of wearable trackers and experience sampling methods has the potential to uncover within-individual processes linking sleep to daily experiences, behaviors, and other psychosocial factors. Here, we provide a concise overview of the state-of-the-art, challenges, and opportunities of using wearable sleep-tracking technology in applied psychology. Specifically, we review key device profiles, capabilities, and limitations. By providing representative examples, we highlight how scholars and practitioners can fully exploit the potential of wearable sleep trackers while being aware of the most critical pitfalls characterizing these devices. Overall, consumer wearable sleep trackers are increasingly recognized as a valuable method to investigate, assess, and improve sleep health. Incorporating such devices in research and professional practice might significantly improve the quantity and quality of the collected information while opening the possibility of involving large samples over representative time periods. However, a rigorous and informed approach to their use is necessary. (AU)

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Wearable sleep trackers are increasingly used in applied psychology. Particularly, the recent boom in the fitness tracking industry has resulted in a number of relatively inexpensive consumer-oriented devices that further enlarge the potential applications of ambulatory sleep monitoring. While being largely positioned as wellness tools, wearable sleep trackers could be considered useful health devices supported by a growing number of independent peer-reviewed studies evaluating their accuracy. The inclusion of sensors that monitor cardiorespiratory physiology, diurnal activity data, and other environmental signals allows for a comprehensive and multidimensional approach to sleep health and its impact on psychological well-being. Moreover, the increasingly common combination of wearable trackers and experience sampling methods has the potential to uncover within-individual processes linking sleep to daily experiences, behaviors, and other psychosocial factors. Here, we provide a concise overview of the state-of-the-art, challenges, and opportunities of using wearable sleep-tracking technology in applied psychology. Specifically, we review key device profiles, capabilities, and limitations. By providing representative examples, we highlight how scholars and practitioners can fully exploit the potential of wearable sleep trackers while being aware of the most critical pitfalls characterizing these devices. Overall, consumer wearable sleep trackers are increasingly recognized as a valuable method to investigate, assess, and improve sleep health. Incorporating such devices in research and professional practice might significantly improve the quantity and quality of the collected information while opening the possibility of involving large samples over representative time periods. However, a rigorous and informed approach to their use is necessary.

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STUDY OBJECTIVES: To compare the 24-hour sleep assessment capabilities of two contactless sleep technologies (CSTs) to actigraphy in community-dwelling older adults. METHODS: We collected 7-14 days of data at home from 35 older adults (age: 65-83), some with medical conditions, using Withings Sleep Analyser (WSA, n = 29), Emfit QS (Emfit, n = 17), a standard actigraphy device (Actiwatch Spectrum [AWS, n = 34]), and a sleep diary (n = 35). We compared nocturnal and daytime sleep measures estimated by the CSTs and actigraphy without sleep diary information (AWS-A) against sleep-diary-assisted actigraphy (AWS|SD). RESULTS: Compared to sleep diary, both CSTs accurately determined the timing of nocturnal sleep (intraclass correlation [ICC]: going to bed, getting out of bed, time in bed >0.75), whereas the accuracy of AWS-A was much lower. Compared to AWS|SD, the CSTs overestimated nocturnal total sleep time (WSA: +92.71 ± 81.16 minutes; Emfit: +101.47 ± 75.95 minutes) as did AWS-A (+46.95 ± 67.26 minutes). The CSTs overestimated sleep efficiency (WSA: +9.19% ± 14.26%; Emfit: +9.41% ± 11.05%), whereas AWS-A estimate (-2.38% ± 10.06%) was accurate. About 65% (n = 23) of participants reported daytime naps either in bed or elsewhere. About 90% in-bed nap periods were accurately determined by WSA while Emfit was less accurate. All three devices estimated 24-hour sleep duration with an error of ≈10% compared to the sleep diary. CONCLUSIONS: CSTs accurately capture the timing of in-bed nocturnal sleep periods without the need for sleep diary information. However, improvements are needed in assessing parameters such as total sleep time, sleep efficiency, and naps before these CSTs can be fully utilized in field settings.

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The scoring of sleep stages is one of the essential tasks in sleep analysis. Since a manual procedure requires considerable human and financial resources, and incorporates some subjectivity, an automated approach could result in several advantages. There have been many developments in this area, and in order to provide a comprehensive overview, it is essential to review relevant recent works and summarise the characteristics of the approaches, which is the main aim of this article. To achieve it, we examined articles published between 2018 and 2022 that dealt with the automated scoring of sleep stages. In the final selection for in-depth analysis, 125 articles were included after reviewing a total of 515 publications. The results revealed that automatic scoring demonstrates good quality (with Cohen's kappa up to over 0.80 and accuracy up to over 90%) in analysing EEG/EEG + EOG + EMG signals. At the same time, it should be noted that there has been no breakthrough in the quality of results using these signals in recent years. Systems involving other signals that could potentially be acquired more conveniently for the user (e.g. respiratory, cardiac or movement signals) remain more challenging in the implementation with a high level of reliability but have considerable innovation capability. In general, automatic sleep stage scoring has excellent potential to assist medical professionals while providing an objective assessment.

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Background: Diet quality is associated with psychobiological, psychological, biological, and physiological factors of individuals, and in the context of prolonged stress, such as the COVID-19 pandemic, it can lead to a worsening of the quality of food for undergraduates. This study aimed to analyze diet quality and associated factors in Brazilian undergraduates. Methods: Data were collected from 4,799 undergraduate students from all Brazilian regions, from August 2020 to February 2021. The online questionnaire contained socioeconomic variables, the ESQUADA scale to assess diet quality, self-referred changes in weight, the Brazilian food insecurity scale (EBIA), sleep assessment and the perceived stress scale. Unconditional multiple logistic regression analysis was performed to study variables associated with poor and very poor diet quality. Results: Most of participants presented a good diet quality (51.7%), while 9.8% had a poor or very poor diet quality and only 1.1% had an excellent diet quality. 58.2% of undergraduates reported to have an increase in weight during the pandemic and 74.3% of the students presented elevated stress during the pandemic. Logistic regressions showed students who gained weight during the pandemic presented the highest AOR = 1.56 (95% CI = 1.12-2.20) for poor or very poor diet quality. The elevated perceived stress was also associated with a higher AOR = 2.85 (95% CI = 1.71-4.74) for poor or very poor diet quality. Conclusion: Most of the studied undergraduates presented a good diet quality. Nevertheless, poor/very poor diet quality was associated with higher perceived stress and weight gain. Our study indicated that policies should beaimed at the socioeconomically most vulnerable undergraduates, those in a situation of food and nutritional insecurity, high perceived stress, and who gained weight during the pandemic.

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Sleep quality and sleep duration are important for children's physical and mental health. Mental health diagnoses and sleep disturbances may be interlinked. We sought to identify the methods used to assess sleep in paediatric community-based mental health programmes. A systematic review was conducted using an a priori protocol to ascertain the sleep assessment methods used in paediatric community-based mental health programmes. Children for this review were defined as any person under the age of 19. Cochrane Library, CINAHL, Web of Science, ProQuest, APA PsycInfo, and PubMed databases were searched from January 2021 to March 2022. Of the 320 records screened, 314 records were excluded. Six studies were included for analysis. A variety of validated and non-validated sleep instruments were used to measure sleep quality and a range of sleep disturbances in community health programmes for children. There were a limited number of studies associated with sleep assessment in paediatric community-based settings suggesting this is an area of research that may be understudied. Sleep questionnaires were predominately completed by parents or guardians. Further research is required to establish the most effective method for screening sleep behaviour in paediatric community mental health programmes to understand the impact of sleep in the recovery of children and adolescents with mental health disorders.

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A cross-sectional descriptive survey of 105 occupational therapy practitioners examined the practice patterns in sleep management within skilled nursing facilities. All participants viewed sleep as essential to address in their settings, since clients frequently reported inadequate sleep, daytime sleepiness, difficulty staying asleep, and situational interruption. Majority of the practitioners reported not screening, assessing, treating, or documenting sleep issues and lack the use of standardized assessments and evidence-based interventions for sleep. Results suggest that practitioners need more training, education, and advocacy skills to promote the role of occupational therapy in addressing sleep management in skilled nursing facilities.

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Sleep deprivation is expected in the intensive care unit (ICU) and is associated with delirium and increased mortality. Polysomnography (PSG) is the gold standard for sleep assessment, but practical issues limit the method. Hence, many ICUs worldwide use subjective sleep assessment (SSA) for sleep monitoring, but the agreement between SSA and PSG is unknown. The hypothesis was that the level of agreement between SSA and PSG was low and that total sleep time (TST) assessed with SSA would be overestimated compared to PSG in this existing cohort database. In this sub-analysis, 30 consecutive study participants underwent 15-h PSG recordings during two consecutive nights. The attending nurse performed an hourly subjective observer rating of sleep quantity during both nights, and the agreement between SSA and PSG was determined along with mean TST. Primary outcome: The level of agreement between SSA and PSG determined by Bland-Altman analysis. Secondary outcome: (1) The overall mean TST estimated by SSA compared to PSG in all study participants enrolled in the main study during both study nights, (2) TST for all study participants evaluated hourly during both study nights, (3) TST assessed with SSA compared to PSG in study participants sedated with dexmedetomidine during the second night and for study participants treated with placebo or non-sedation the first and second nights. The level of agreement between SSA and PSG was low. Mean TST estimated by SSA during the time interval 4.00 p.m. to 7.00 a.m. was 481 min (428;534, 95% CI) vs. PSG at 437 min (386;488, 95% CI) (p = .05). When sedated with dexmedetomidine, TST estimated using SSA was 650 min (571;729, 95% CI) versus PSG which was 588 min (531;645, 95% CI) (p = 0.56). For participants treated with placebo or non-sedation TST estimated with SSA was 397 min (343;450, 95% CI) versus PSG at 362 min (302;422, 95% CI) versus (p = 0.17). In mechanically ventilated critically ill ICU patients, the level of agreement between SSA and PSG was low, and there was a significant overestimation of mean TST. SSA should only be used under awareness that it is imprecise and overestimates TST.

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OBJECTIVES: Characterizing daily patterns of sleep, stress, presleep worry, and mood in adolescents with and without insomnia symptomatology. DESIGN: Two months of continuous wearable tracking and daily diary ratings. SETTING: Free-living conditions. PARTICIPANTS: Ninety-three adolescents (59 girls; 16-19 years old) with (N = 47; 26 with clinical and 21 with sub-clinical) and without (N = 46; control) DSM-5 insomnia symptomatology. MEASUREMENTS: Fitbit Charge 3 tracked sleep, heart rate, and steps. Evening electronic diaries collected ratings of daily stress, presleep worry, and mood. RESULTS: While sleep duration (control: 6.88 ± 1.41 hours; insomnia: 6.92 ± 1.28 hours), architecture, timing, and night-to-night variability were similar between groups, the insomnia group reported higher levels of stress and worry, being mainly related to "school". At the intraindividual level, stress and worry predicted shorter sleep duration and earlier wake up times, which, in turn, predicted higher stress the following day. Moreover, higher-than-usual stress predicted higher sleep-time heart rate, with a more consistent effect in adolescents with insomnia. Results were overall consistent after controlling for covariates and several robustness checks. CONCLUSIONS: There is a bidirectional relationship between daily stress and sleep, with daily stress negatively impacting sleep, which in turn leads to more stress in adolescents with and without insomnia symptoms. Findings also highlight the complexity of insomnia in adolescence, in which the core clinical features (perceived sleep difficulties) and the critical factors (stress/worry) implicated in the pathophysiology of the disorder are not necessarily reflected in objective sleep indicators.

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Nowadays, self-tracking and optimization are widely spread. As sleep is essential for well-being, health, and peak performance, the number of available consumer technologies to assess individual sleep behavior is increasing rapidly. However, little is known about the consumer wearables' usability and reliability for sleep tracking. Therefore, the aim of the present study was to compare the sleep measures of wearable devices with a standardized sleep diary in young healthy adults in free-living conditions. We tracked night sleep from 30 participants (19 females, 11 males; 24.3 ± 4.2 years old). Each wore three wearables and simultaneously assessed individual sleep patterns for four consecutive nights. Wearables and diaries correlated substantially regarding time in bed (Range CCCLin: 0.74-0.84) and total sleep time (Range CCCLin: 0.76-0.85). There was no sufficient agreement regarding the measures of sleep efficiency (Range CCCLin: 0.05-0.34) and sleep interruptions (Range CCCLin: -0.02-0.10). Finally, these results show wearables to be an easy-to-handle, time- and cost-efficient alternative to tracking sleep in healthy populations. Future research should develop and empirically test the usability of such consumer sleep technologies.

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Objective: Chronic pain can impact on sleep, but the extent and nature of sleep problems in patients with chronic pain are incompletely clear. Several validated tools are available for sleep assessment but they each capture different aspects. We aimed to describe the extent of sleep issues in patients with chronic non-malignant pain using three different validated sleep assessment tools and to determine the relationship of sleep issues with pain severity recorded using the Brief Pain Inventory (BPI), a commonly used self-assessment tool in pain clinics. The BPI has a single question on the interference of pain on sleep and we also compared this with the validated sleep tools. Design: Prospective, cross-sectional study. Setting: Pain management clinic at a large teaching hospital in the United Kingdom. Subjects: Adult patients (with chronic non-malignant pain of at least 3 months' duration) attending clinic during a 2-month period. Methods: Participants completed the Pittsburgh Sleep Quality Index (PSQI), the Pain and Sleep Questionnaire-3 (PSQ-3) and the Verran Snyder-Halpern (VSH) sleep scale, plus the BPI. Duration and type of pain, current medications and demographic data were recorded. Results: We recruited 51 patients and 82% had poor sleep quality as shown by PSQIscores above five. PSQI (p = 0.0002), PSQ-3 (p = 0.0032), VSH sleep efficiency (p = 0.012), sleep disturbance (p = 0.0014) and waking after sleep onset (p = 0.0005) scores were associated with worse BPI pain scores. BPI sleep interference scores concurred broadly with the validated sleep tools. Median [range] sleep duration was 5.5 [3.0-10.0] hours and was also related to pain score (p = 0.0032). Conclusion: Chronic pain has a marked impact on sleep regardless of the assessment tool used. The sleep interference question in the BPI could be used routinely for initial identification of sleep problems in patients with chronic pain.

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Fatal familial insomnia (FFI) is a rare prion disease with autosomal dominant inheritance. Currently, there is only one published case study of FFI in Australia. FFI is universally fatal, with the disease duration ranging from 8 to 72 months. Clinically, it manifests with disordered sleep-wake cycle, dysautonomia, motor disturbances and neuropsychiatric disorders. We describe a case of FFI detailing the investigative process, including the importance of sleep assessment and polysomnography in obtaining a diagnosis.

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Despite many marriage and family therapists (MFTs) utilizing the Biopsychosocial-Spiritual (BPSS) framework in assessment and treatment, there is still a lack of education on sleep and the implications for mental, emotional, and relational health. Newer research within many fields highlights the far-reaching spillover effects of short or poor-quality sleep that can affect our clients. MFTs need to know how to assess, how to provide proper psychoeducation, how to apply this knowledge in clinical settings, and how to collaborate with other healthcare providers. As such, the purpose of this article is threefold: (a) review the biopsychosocial-spiritual importance of sleep; (b) equip MFTs with information on sleep assessment, how to identify situations for referral, and how to provide psychoeducation on sleep hygiene; and (c) review important considerations for research and practice for MFTs.

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Intensive neurological assessments in neurocritical care settings for unduly prolonged period result in profound sleep deprivation in those patients that confounds the true neurological status of these patients, and the mounting apprehension in providers can beget a vicious cycle of even more intensive neurological assessments resulting in further sleep deprivation from being constantly woken up to be "assessed." This iatrogenic state drives these patients into deep sleep stages that impact spontaneous breathing trials, weaken immunity, and lead to unwarranted investigations and interventions. There is dwindling value of prolonged frequent neurochecks beyond the initial 24-48 h of an intracranial event. We insist that sleep must be considered on at least an equal par to other functions that are routinely assessed. We reason that therapeutic sleep must be allowed to these patients in suitable amounts especially beyond the first 36-48 h to achieve ideal and swift recovery. This merits a paradigm shift.

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Sleep affects physiologic and psychological recovery throughout critical illness. Patients often describe poor sleep as a major source of distress while hospitalized in an intensive care unit. The intensive care unit environment poses unique challenges for sleep assessment and monitoring. The purpose of this literature review is to discuss methods of assessment and monitoring of sleep within the intensive care unit setting. The advantages and disadvantages of physiologic monitoring of sleep (eg, polysomnography, bispectral index, and actigraphy) are compared with those of subjective measures of sleep quality (eg, validated patient-oriented sleep questionnaires, and informal nursing assessments).

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Older adults who do not sleep well frequently have difficulty sustaining attention, display slower physical response times, and have memory issues that may contribute to depression or early dementia. The life changes that accompany aging, such as retirement, bereavement, or the onset of chronic illness or disability, can precipitate sleep problems. Insomnia and obstructive sleep apnea are the most common sleep disorders in older adults and can have far-reaching consequences on health and well-being. Nurses should include thorough sleep assessments in any patient interview.

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