The majority of American adolescents experience insufficient quality and quantity of sleep due to various biological and sociocultural factors, including very early high school start times. Additionally, many high schools begin their school day before the recommended 8:30 am, making it difficult to compensate for changing adolescent sleep needs. Adolescents who do not obtain enough quality sleep are at risk for physical and mental health concerns, such as daytime sleepiness and impaired ability to handle stress, as well as impaired occupational participation in roles such as being a student, an athlete, and a worker. This program contains a presentation to educate school district administrators on adolescent sleep factors and needs. The presentation additionally educates administrators about strategies for delaying high school start times to better support adolescent sleep. The program also gives an optional framework for school districts to trial modestly delayed start times for one school quarter as a way of gauging long-term feasibility of permanently adopting healthier secondary school start times.

Sleep is a critical occupation that supports and promotes participation in occupational performance in all individuals (AOTA, 2014). It builds the foundation for cognitive development and supports learning in children (Ashworth et al., 2014; Schlieber & Han, 2018; Kurz et al., 2019). Children with poor sleep habits may exhibit dysregulation in their daytime activity level (Foitzik & Brown, 2018; Johnson et al., 2017). Consequently, sleep difficulties affect their academic performance and social participation at school (Taylor et al., 2012; Deliens & Peigneux, 2019). Sleep problems in autistic children are two to three times greater than in neurotypical children (Moore et al., 2017; Souders et al., 2017). Of further concern is that a significant increase in sleep problems in autistic children has been associated with the Covid-19 pandemic (Bruni et al., 2022). Occupational therapy practitioners (OTPs) in schools recognize the importance of sleep as an essential building block for learning (Beisbier & Cahill, 2021; Gronski & Doherty, 2020) and specialize in assessing sensory behaviors using evidence-based assessments (Kirby et al., 2019; Schoen et al., 2018). However, due to a lack of sleep knowledge and resources, many school-based OTPs do not address sleep problems during the assessment and intervention process (Gentry & Loveland, 2013). Sensory assessments can help to detect atypical sleep patterns and inform a proactive approach to nurturing a healthy lifestyle (Tauman et al., 2017; Reynolds et al., 2012). OTPs are encouraged to provide sensory-informed sleep health education and consultation to support autistic children in school-based practice. A literature review was completed based on current occupational therapy (OT) practice in sleep care. Several key findings suggested that (a) the teaching and clinical training in sleep health are lacking in formal OT educational programs, (b) teachers are unaware of OT scope of practice, and (c) most OTPs in school experience heavy caseloads and have time constraints which may hinder interdisciplinary collaboration and family partnership. Furthermore, research studies from OT, psychology, neuroscience, and education were identified and carefully reviewed to determine effective therapies that fall within the scope of OT practice. Through this doctoral work, an evidence-based educational program was developed for OTPs to fill this practice gap and address sleep difficulties in autistic children within the school setting. Sleep Practice in Occupational Therapy (SPOT) is a research-informed program for OTPs who provide school-based services to autistic children in Hong Kong. The main objective of this program is to extend OT school-based practice in areas of sleep assessment, intervention, interprofessional collaboration, and family partnership within this student population. This four-week online educational course consists of mini-lectures on the neurobiological evidence in sleep in autistic children, multiple group discussions regarding sleep health education, and individual work projects to build competence in sleep assessment and intervention. Upon completion, OTP participants will be equipped with evidence-based sleep hygiene resources and sleep health educational presentation materials generated by the program author. Qualitative and quantitative data will be collected for program evaluation and to inform the efficacy of this OT-led sleep health education program in school settings. It is anticipated that the SPOT program will advance our professional service delivery and advocacy within schools and, ultimately, improve the academic learning and quality of life of autistic children. Furthermore, this training program is applicable to school-based OT practice in other geographic regions of the world that advocate for an inclusive approach to serving children with diverse sensory needs.

<p> The study of the different sleep stages of a patient using his/her recorded EEG signals falls in the area of signal classification. In general, this involves extracting from the EEG signals, a signal feature on which the classification is performed. In this thesis, we apply the techniques of signal classification to the analysis of the sleep of a patient. The feature we use is the power spectral density (PSD) matrices of a multi-channel EEG signal. This not only allows us to examine the power spectrum contents of each signal which complies with what clinical experts use in their visual judgement of EEG signals, but also allows the correlation between the multi-channel signals to be studied. To establish a metric facilitating the classification, we analyze the structure as well as exploit the specific geometric properties of the space of PSD matrices. Specifically, we study this space from the viewpoint of Riemannian manifolds. We apply a Riemannian metric and, with the aid of fibre bundle theory, develop intrinsic (geodesic) distance measures for the PSD matrix manifold. To utilize such new distance measures effectively for EEG signal classification, we need to find a suitable weighting matrix for the PSD matrices so that the distances between similar features are minimized while those between dissimilar features are maximized. A closed form expression for this weighting matrix is obtained by solving an equivalent convex optimization problem. The effectiveness of using these novel weighted distance measures is verified by applying them to the sleep pattern classification of a collection of recorded EEG signals using the k-nearest neighbor decision algorithm with excellent results. </p> / Thesis / Doctor of Philosophy (PhD)

This thesis explores the interaction between sleep and burnout in the treatment of poor sleep. Sleep isvital for overall health and recovery from daily life demands, while stress is closely related to sleepdisruptions. Chronic insomnia can develop from sleep disturbances caused by stress. Burnout,characterized by emotional exhaustion, physical fatigue, and cognitive weariness, is a prevalentconsequence of chronic stress. Sleep quality is greatly influenced by various factors and has a significantimpact on overall well-being. This study investigates how sleep quality and burnout at baseline of ashort, student-led, group treatment, affect sleep quality as a treatment outcome. It hypothesizes thathigher stress and poorer sleep at baseline would predict unchanged or impaired sleep qualityimmediately after treatment, and that poor sleep and burnout would individually have a positiverelationship with sleep as a treatment outcome. The data for this study is obtained from a sleepintervention program conducted by students from the Master's Program in Clinical Psychology at UmeåUniversity in collaboration with Region Västerbotten. The participants completed questionnairesassessing their background information, stress levels, burnout, and sleep quality at baseline and aftertreatment. The findings showed no interaction effects between sleep and burnout but indicate thatpatients with poorer sleep at intake may not benefit from the treatment program whereas high burnoutdoes not affect the treatment outcome. The short, student-led, group treatment does not seem tobenefit people with severe sleep problems.

Indiana University-Purdue University Indianapolis (IUPUI) / The study evaluated the effects of a mandibular repositioning appliance (MRA) in patients with obstructive sleep apnea. The MRA was designed to hold the mandible anteriorly in an attempt to maintain a patent airway. Eleven subjects completed a full-night polysomnogram wherein their normal sleep was recorded half the night without the appliance (control) and the other half with the appliance (test). The sequencing of test and control halves was randomly assigned to avoid bias. After seven subjects were tested with the MRA, the MRA was modified for four additional patients by placing anterior vertical elastics (MRA*) to minimize the opening of the mandible. The skeletal and soft tissue changes with both appliances were analyzed using lateral cephalometric radiographs. The MRA was found to have no significant effect on the obstructive sleep apnea patients as a group. Individual response to the appliance varied from noticeably worse to marked improvement. Subject #2A exhibited the reduction of a moderate-to-severe apnea (Apnea-hypopnea index 55.92) to a clinically acceptable level (Apnea-hypopnea index 9.57) with appliance wear. The treatment was considered successful. Significant cephalometric changes with appliance wear were increased lower facial height, a superiorly positioned hyoid bone relative to the mandibular plane, and a decreased posterior airway space. No cephalometric measurement could accurately predict the outcome of the treatment, and posterior airway space, commonly measured in sleep research, was not reliable. The mandibular repositioning appliance was effective in treating a small percentage of individuals with obstructive sleep apnea. A polysomnogram was needed to quantitatively measure the effectiveness of treatment. Under no circumstance should a subjective evaluation by the patient or the clinician be used to assess treatment results. Further investigation is required to evaluate the long-term effectiveness of this treatment. Periodic follow-up sleep studies are required for any patient treated with this appliance until more long term studies are completed.

BACKGROUND: Prior to now, sleep has been particularly difficult to accurately measure in a home setting. The acceptability of wearable devices that allow for the collection of not only sleep data, but heart rate, activity, and other variables allows for the expansion of research from the lab into a patient’s daily life. METHODS: Data from three studies was evaluated to determine acceptability of Fitbit wearable devices as well as the utility of sleep data the devices could collect to characterize sleep disturbances. The populations included two post-surgical groups experiencing acute pain (orthopedic surgery, n = 7; cardiac surgery n = 14) and one group of children and adolescents receiving intensive treatment for chronic pain (n = 14). RESULTS: Both the composition of the studies and the Fitbit devices were well tolerated by all three groups, as measured by an acceptability survey. For utility, significant differences were found in step counts, number of nightly awakenings, and pain ratings. Correlations were also found between pain and sleepiness, step counts, and sleep efficiency. CONCLUSION: The future is bright for the integration of wearable devices and other smart technology into clinical settings. For the populations studied here, this could mean fewer hospital visits and increased quality of life by being able to provide feedback to providers via validated, non-invasive methods.

Adolescent prevalence of obesity and at-risk WC has continued to rise worldwide. Sleep duration, sleep quality, and physical activity have been hypothesized as contributing factors to this increase. PURPOSE: This study aimed to examine the sleep–obesity relation in adolescents. METHODS: Using data from the 2015-2016 NHANES(n=454; ages 16-18 years), the effect of sleep duration, sleep quality, and MVPA on BMI and WC by gender was analyzed using appropriate sampling weights. RESULTS: Longer sleep duration was associated with increased BMI (β=0.07; 0.065, p<0.05) and WC (β=0.069; 0.13, p<0.05) among males and females. Poor sleep quality was associated with increased BMI among males and females (β= 0.04; 0.08, p< 0.05). A significant main effect was observed across sleep duration, sleep quality and MVPA via multiple regression for both BMI and WC. CONCLUSIONS: For both males and females, BMI and WC were impacted by excessive sleep, poor sleep quality, and low MVPA, with greater associations among males.

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