Sleep Coach Research Articles

Effects and implementation of an intervention to improve sleep, fatigue and recovery among healthcare workers with night shifts: A pre- and post-test study

BackgroundPrevious intervention studies among night workers mainly focused on single interventions and found inconclusive evidence for effectiveness. A comprehensive intervention approach that includes individual and environmental components has been argued as important. Gaining insight into contributing factors for the implementation of interventions for night workers and effectiveness is important to distinguish between theory and programme failure. ObjectivesTo evaluate the effects and implementation of the PerfectFit@Night intervention to improve sleep, fatigue and recovery of night workers in healthcare, using the RE-AIM framework, which assesses reach, effectiveness, adoption, implementation and maintenance of interventions. DesignA prospective pre–post study design, with two measurements before and three and six months after the intervention. SettingTwelve different departments of a university hospital in the Netherlands. ParticipantsHealthcare workers working night shifts (n = 210). MethodsPerfectFit@Night consisted of environmental (provision of a powernap bed and healthy food, and workshop healthy rostering) and individual elements (e-learning and sleep coaching) and was implemented for three months in a phased manner. Questionnaires, logbooks and interview data were used. Effects of the intervention on sleep, fatigue and recovery were evaluated with mixed-effects models, and implementation factors of reach, adoption, implementation and maintenance were evaluated. ResultsNight shift-related insomnia (−11 %-points, 95 % CI: −19 %, −4 % at three months), need for recovery (β: −2.45, 95 % CI: −4.86, −0.03 at six months) and fatigue (OR: 0.46, 95 % CI: 0.25, 0.86 at six months) decreased significantly after the intervention. No changes were found for subjective sleep quality and sleep duration. Barriers and facilitators for implementation were identified for each intervention element at individual (e.g., dietary preferences), organisational (e.g., responsibilities at work) and workplace levels (e.g., location of power nap bed), and for the intervention itself (e.g., useful information in e-learning). Although satisfaction was high and continuation was preferred, embedding of the intervention in the daily routine was limited. Facilitators for future implementation include a positive attitude towards the intervention, clear guidelines regarding intervention elements, appointment of night workers as ambassadors, and suitable conditions in terms of work demands and for the intervention elements. ConclusionsThe multi-faceted PerfectFit@Night intervention reduced insomnia, fatigue and need for recovery in night workers in healthcare. The most important facilitators to improve the implementation of PerfectFit@Night exist at the organisational level (e.g., positive attitude within the culture and suitable work demands). Combining effect and implementation evaluation is crucial to identify barriers and facilitators that hamper or enhance intervention effects. Trial registrationThe study was registered in the Netherlands Trial Register on 17 January 2021 (trial number NL9224).

Federated learning enhanced AR/VR integration in sleep wearable devices

As a crucial aspect of human health, sleep remains a problem to many individuals. Many still struggle with going to sleep or poor sleeping quality. In terms of ways to interfere with this issue, traditional sleep measurement methods, such as polysomnography(PSG), are intrusive, expensive, and inconvenient for long-term monitoring. Wearable devices offer a practical alternative but often face challenges related to accuracy, comfort, and data privacy. Advances in technology present new opportunities to address these issues.This systematic review focuses on examining the drawbacks of current sleeping measurements and wearable devices, and further explores the integration of federated learning (FL) with AR, VR in sleep wearable devices in order to promote sleep facilitation. The study addresses key challenges in sleep research, including accurate and non-intrusive monitoring, data privacy, and personalized sleep coaching. Federated learning enables decentralized data analysis, enhancing model accuracy while preserving user privacy. AR and VR technologies offer immersive environments for sleep facilitation through tailored relaxation techniques. The combination of these technologies provides innovative solutions to improve sleep quality and intervention efficacy. Future research should focus on enhancing device comfort, accuracy, and the integration of FL algorithms for better user experiences.

Factors facilitating and hindering the implementation of digital sleep coaching for bus drivers

Improving fatigue management is critical to the occupational safety of professional drivers. We aimed to identify the factors that facilitated or hindered the implementation of digital sleep coaching in bus companies and to explore bus drivers’ experiences with it. Two bus companies implemented coaching for bus drivers. Using a mixed methods design, we collected data through two workshops (n = 30 and n = 27) attended by key personnel from the organisations and through questionnaires to the drivers (n = 30). Implementation was facilitated by, for example, the flexible participation and multichannel information of coaching, and hindered by restrictions on social support due to the COVID-19 pandemic, and lack of interest and inspiring examples. On average, the drivers rated the appropriateness and the feasibility of coaching as good. However, further development could lead to wider dissemination. It would also be important to involve the key people in the organisations and stakeholders more in supporting the implementation.

Mi Sleep Coach Mobile App to Address Insomnia Symptoms Among Cancer Survivors: Single-Arm Feasibility Study.

Rates of sleep disturbance among survivors of cancer are more than 3 times higher than the general population. Causes of sleep disturbance among survivors are many and multifaceted, including anxiety and fear related to cancer diagnosis and treatments. Cognitive behavioral therapy for insomnia (CBT-I) is considered a first-line treatment for insomnia; However, a lack of access to trained professionals and limited insurance coverage for CBT-I services has limited patient access to these effective treatments. Evidence supports digital delivery of CBT-I (dCBT-I), but there is only limited evidence to support its use among survivors of cancer. Broad adoption of smartphone technology provides a new channel to deliver dCBT-I, but no prior studies have evaluated mobile dCBT-I interventions for survivors. To address the need for accessible and efficacious CBT-I for survivors of cancer, the Mi Sleep Coach program was developed to adapt CBT-I for delivery to survivors of cancer as a self-directed mobile health app. This single-arm feasibility study assessed the adherence, attrition, usefulness, and satisfaction of the Mi Sleep Coach app for insomnia. A 7-week, single-arm study was conducted, enrolling adult survivors of breast, prostate, or colon cancer reporting sleep disturbances. In total, 30 participants were enrolled, with 100% completing the study and providing data through week 7. Further, 9 out of 10 app features were found to be useful by 80% (n=24) to 93% (n=28) of the 30 participants. Furthermore, 27 (90%) participants were satisfied with the Mi Sleep Coach app and 28 (93%) would recommend the use of the Mi Sleep Coach app for those with insomnia. The Insomnia Severity Index showed a decrease from baseline (18.5, SD 4.6) to week 7 (10.4, SD 4.2) of 8.1 (P<.001; Cohen d=1.5). At baseline, 25 (83%) participants scored in the moderate (n=19; 15-21) or severe (n=6; 22-28) insomnia range. At week 7, a total of 4 (13%) patients scored in the moderate (n=4) or severe (n=0) range. The number of patients taking prescription sleep medications decreased from 7 (23%) at baseline to 1 (3%; P<.001) at week 7. The number of patients taking over-the-counter sleep medications decreased from 14 (47%) at baseline to 9 (30%; P=.03) at week 7. The Mi Sleep Coach app demonstrated high levels of program adherence and user satisfaction and had large effects on the severity of insomnia among survivors of cancer. The Mi Sleep Coach app is a promising intervention for cancer-related insomnia, and further clinical trials are warranted. If proven to significantly decrease insomnia in survivors of cancer in future randomized controlled clinical trials, this intervention would provide more survivors of cancer with easy access to evidence-based CBT-I treatment. ClinicalTrials.gov NCT04827459; https://clinicaltrials.gov/study/NCT04827459.

Sleep Technology Intervention to Target Cardiometabolic Health (STITCH): a randomized controlled study of a behavioral sleep extension intervention compared to an education control to improve sleep duration, blood pressure, and cardiometabolic health among adults with elevated blood pressure/hypertension

BackgroundShort sleep duration, defined as < 7 h sleep on weeknights, affects 40% of the US adult population, contributing to the increased risk for cardiometabolic diseases, decreased safety, and poorer mental health. Despite the prevalence of short sleep duration, few studies have tested interventions to extend sleep duration. The objective of this study is to test the effects of a behavioral sleep extension intervention on sleep duration, blood pressure, and other measures of cardiometabolic health among adults with elevated blood pressure or hypertension.MethodsThis is a single-blind, randomized controlled trial to determine the impact of a behavioral sleep extension intervention on sleep duration and cardiometabolic health among individuals with short sleep duration (< 7 h per night) and elevated blood pressure or hypertension (SBP 120–150 mmHg or DBP 80–90 mmHg). After completing the screening, participants will be randomly assigned to either a sleep coaching (intervention) or health education (control) group. The participants will have weekly contact for either coaching or education for 8 weeks (intervention period) followed by monthly coaching or education for the next 2 months (maintenance period). Participants will complete assessment visits, actigraphy, and 24-h ambulatory blood pressure recording at baseline/screening, 8 weeks, and 6 and 12 months. The primary outcome is sleep duration at 8 weeks, and the secondary outcome is blood pressure at 8 weeks.DiscussionThe results of this study will determine the effects of behavioral sleep extension on sleep and cardiometabolic health among adults with short sleep duration and elevated BP/hypertension. The results will inform the feasibility and efficacy of behavioral sleep extension and provide information needed for future multi-site effectiveness studies.Trial registrationClinicalTrials.gov NCT04766424. Registered on 21 February 2021.

App-Supported Sleep Coaching: Implications for Sleep Duration and Sleep Quality.

The present study evaluated whether completers of a 12-week app-based, personalized text supported sleep coaching program demonstrated improvements in sleep continuity, sleep duration, and reduced use of sleep aids. Data were obtained from Sleep Reset, a 12-week consumer product that offers app-based sleep education and monitoring, along with personalized text-based sleep coaching provided by live coaches. 564 completers were included in the study. Pre-post changes for sleep latency (SL), wake after sleep onset (WASO), number of awakenings (NWAK), total sleep time (TST), sleep efficiency (SE%) and use of "sleep aids" were evaluated. To evaluate whether the program produced meaningful results, the proportion of participants who demonstrated reductions in SL, WASO, and NWAK, and increases in TST and SE% were examined. Mean SL was reduced by 11 minutes, mean WASO was reduced by 28 minutes, mean SE% increased by 6.6%, and mean TST increased by about 44 minutes. Of those who reported using "sleep aids" during Week 1, 41% no longer used them by week 12. Those with low SE% at baseline demonstrated greater improvements in SL (16.2 vs 5.7mins), WASO (47.3 vs 7.2mins), SE% (11.2% vs 1.6%), and TST (65.3 vs 31.2mins). Those with ≤6 hours of sleep at baseline demonstrated greater improvements in WASO (36.8 vs 22.3mins), SE% (10.1% vs 4.3%), and TST (85.1 vs 25.5mins). Participants that completed the app-based, personalized text supported coaching intervention reported subjective improvements in sleep duration and quality that suggest more beneficial effects particularly in those with lower sleep efficiency or sleep duration at baseline. An effective sleep coaching program that utilizes trained sleep coaches with access to board-certified providers, may provide a valuable resource for subclinical populations.

0940 Reductions in Use of Sleep Aids Following an App-Based Sleep Coaching Platform

Abstract Introduction Use of sleep supplements and other sleep aids is increasing. Yet, many of these are not supported strategies for ameliorating sleep problems. Providing educational and behavioral strategies may reduce reliance on these substances. Methods Data were obtained from N=93 individuals who participated in the 12-week Sleep Reset program. The Sleep Reset program (Simple Habit, Inc.) includes ongoing text-based communication with coaches trained to support sleep behavior change, and a mobile app that includes a sleep diary, educational modules, mindfulness exercises, and progress tracking. Potential users are screened prior to entry and if they demonstrate a contraindicated medical or psychiatric problem, they were not admitted to the coaching program. If they demonstrate a likely sleep disorder (including insomnia disorder) they are referred for additional support. The coaching communications included information about basic sleep and circadian principles (e.g., sleep hygiene, behavioral scheduling, light exposure, relaxation) and techniques based on CBTI (e.g., stimulus control). Participants were asked if they used any “sleep aids” (which could include medications or melatonin/supplements) daily while in the program. Type of substance was not assessed. Data were binned by week, dichotomized as yes/no regarding any use in that week. Results Of the N=93 participants, N=46 (49%) indicated that they used “sleep aids” at least once in the first week. Among Sleep Reset participants who reported using sleep aids at least once in their first week in the program, use was reduced to N=13 (28.9%) by week 12. This difference was statistically significant (t(44)=10.4, p&amp;lt; 0.0005). Reductions from week 1 were already seen in week 2 (57.8%; t(44)=5.7, p&amp;lt; 0.0005). Another reduction was seen between weeks 3 and 4 (51.1% to 37.8%, t(44)=1.8, p=0.042), and a trend was seen between weeks 9 and 10 (35.6% to 26.7%, t(44)=1.7, p=0.052). Conclusion In an app-led sleep coaching program, those who used sleep aids in week 1 reduced use by 71.1% by the end of the 12-week period, with the largest reductions in the first week. Future controlled studies are needed to validate whether a sleep coaching program can reduce use of sleep aid such as supplements that may not be helpful. Support (if any)

0931 App-Supported Sleep Coaching: Implications for Sleep Duration and Sleep Quality

Abstract Introduction Sleep coaching programs have emerged to address sleep health needs for subclinical populations. Yet, few such programs have been formally evaluated. Methods Data were obtained from N=51 consecutive users who completed the 12-week Sleep Reset program. Sleep Reset (Simple Habit, Inc.) includes ongoing text-based communication with trained coaches and a mobile app that includes a sleep diary, educational modules, mindfulness exercises, and progress-tracking. Potential users with a contraindicated medical/psychiatric problem or a likely sleep disorder (including Insomnia Disorder) are referred for additional care/support. The coaching included information about sleep and circadian principles (e.g., sleep hygiene, behavioral scheduling, light exposure, relaxation) and techniques based on CBTI (e.g., stimulus control). T-tests examined change scores for diary-derived sleep latency (SL), wake after sleep onset (WASO), total sleep time (TST), number of awakenings (NWAK), and sleep efficiency (SE). N=3 had uninterpretable baseline TST. Post-hoc analyses examined those who reported at least one sleep continuity disturbance (SL&amp;gt;=30, WASO&amp;gt;=30, SE&amp;lt; 0.85; N=44) vs none (N=7) and short sleepers (TST&amp;lt; 360 min; N=19) vs 6+ hours (N=32). Results Those who participated in the program saw a mean increase in SE of 6.4% (95%CI [2.7%,10.2%], t(50)=3.4, p=0.001) and TST of 57.8 mins (95%CI [33.8,81.8], t(47)=4.9, p&amp;lt; 0.0005), and a mean decrease in SL of 12.2 mins (95%CI [-20.0,-4.4], t(50)=-3.1, p=0.003), WASO of 32.4 mins (95%CI [-52.7,-12.0]. t(50)=-3.2, p=0.002), and NWAK of 0.3 awakenings (95%CI [-0.7,-0.01], t(50)=-2.1, p=0.046). Those who reported a problem were more likely to show an improvement in SE (+7.9% vs -0.3%, p=0.001), SL (-14.8 vs +4.0 mins, p=0.0008), and WASO (-40.5 vs +15.8 mins, p=0.0001), but groups did not differ in terms of change in NWAK and TST. Short sleepers saw a relative improvement in SE (+12.2% vs +3.0%, p=0.037) and TST (+109.8 vs +23.7 mins, p=0.0001), but no differences in change to SL, WASO, and NWAK. Conclusion The sleep coaching program improved sleep quality and duration for participants without sleep disorders. Those with baseline sleep continuity problems received the most benefit to SL and WASO, and short sleepers saw a nearly 2-hour average increase in TST. Future studies need to extend this work with control groups. Support (if any)

The Indirect Effects of a Mindfulness Mobile App on Productivity Through Changes in Sleep Among Retail Employees: Secondary Analysis.

BackgroundChronic sleep disturbance is prevalent among United States employees and associated with costly productivity impairment. Mindfulness interventions improve sleep (ie, insomnia and daytime sleepiness) and productivity outcomes, and mobile apps provide scalable means of intervention delivery. However, few studies have examined the effects of mindfulness mobile apps on employees, and no research to date has tested the role of sleep improvement as a potential mechanism of action for productivity outcomes.ObjectiveThis study examined the effects of Calm, a consumer-based mindfulness app, and sleep coaching, on productivity impairment among retail employees through the indirect effects of changes in insomnia and daytime sleepiness.MethodsThis study was a secondary analysis of data from a randomized controlled trial (N=1029) comparing the use of Calm (n=585, 56.9%) to a waitlist control (n=444, 43.2%) for 8 weeks among employees of a large retail employer in the United States. A subset of individuals with elevated insomnia symptoms also had access to brief sleep coaching with Calm (n=101, 9.8%). Insomnia symptom severity, daytime sleepiness, and productivity impairment (ie, absenteeism, presenteeism, overall productivity impairment, and non–work activity impairment) were assessed at baseline and weeks 2, 4, 6, and 8. Indirect effects were evaluated with latent growth curve modeling to test whether the Calm intervention (Calm group vs waitlist control) was effective in reducing work productivity impairment through changes in sleep disturbance.ResultsNo significant main effects of Calm intervention on productivity impairment were detected for any outcome at α level of .05, with the exception of non–work activity impairment models, in which Calm intervention reduced non–work activity impairment over time (P=.01 and P=.02 for insomnia and sleepiness models, respectively). Significant indirect effects of insomnia were detected for presenteeism (P=.002), overall work productivity (P=.01), and non–work activity impairment (P=.002); Calm intervention produced significantly greater reductions in insomnia symptoms (relative to waitlist control), and decreases in insomnia were associated with decreases in work productivity impairment. There was no significant indirect effect of change in insomnia on changes in absenteeism (P=.20). Furthermore, we detected no significant indirect effects of daytime sleepiness on productivity impairment.ConclusionsWe found that Calm (plus sleep coaching for a small subset of individuals) had beneficial effects on employee sleep, and these benefits on sleep were related to indirect effects on productivity impairment (ie, presenteeism, overall work productivity impairment, and non–work activity impairment). There were no overall main effects of Calm intervention on productivity impairment; however, insomnia appears to be a mechanism associated with benefits for employee productivity. This is one of the first studies to suggest that sleep benefits of a mindfulness mobile app may also indirectly relate to benefits for workplace productivity.Trial RegistrationClinicalTrials.gov NCT05120310; https://clinicaltrials.gov/ct2/show/NCT05120310

Testing the Pragmatic Effectiveness of a Consumer-Based Mindfulness Mobile App in the Workplace: Randomized Controlled Trial.

BackgroundMental health and sleep problems are prevalent in the workforce, corresponding to costly impairment in productivity and increased health care use. Digital mindfulness interventions are efficacious in improving sleep and mental health in the workplace; however, evidence supporting their pragmatic utility, potential for improving productivity, and ability to reduce employer costs is limited.ObjectiveThis pragmatic, cluster randomized controlled trial aimed to evaluate the experimental effects of implementing a commercially available mindfulness app—Calm—in employees of a large, multisite employer in the United States. Outcomes included mental health (depression, anxiety, and stress), sleep (insomnia and daytime sleepiness), resilience, productivity impairment (absenteeism, presenteeism, overall work impairment, and non–work activity impairment), and health care use (medical visit frequency).MethodsEmployees were randomized at the work site to receive either the Calm app intervention or waitlist control. Participants in the Calm intervention group were instructed to use the Calm app for 10 minutes per day for 8 weeks; individuals with elevated baseline insomnia symptoms could opt-in to 6 weeks of sleep coaching. All outcomes were assessed every 2 weeks, with the exception of medical visits (weeks 4 and 8 only). Effects of the Calm intervention on outcomes were evaluated via mixed effects modeling, controlling for relevant baseline characteristics, with fixed effects of the intervention on outcomes assessed at weeks 2, 4, 6, and 8. Models were analyzed via complete-case and intent-to-treat analyses.ResultsA total of 1029 employees enrolled (n=585 in the Calm intervention group, including 101 who opted-in to sleep coaching, and n=444 in waitlist control). Of them, 192 (n=88 for the Calm intervention group and n=104 for waitlist) completed all 5 assessments. In the complete-case analysis at week 8, employees at sites randomized to the Calm intervention group experienced significant improvements in depression (P=.02), anxiety (P=.01), stress (P<.001), insomnia (P<.001), sleepiness (P<.001), resilience (P=.02), presenteeism (P=.01), overall work impairment (P=.004), and nonwork impairment (P<.001), and reduced medical care visit frequency (P<.001) and productivity impairment costs (P=.01), relative to the waitlist control. In the intent-to-treat analysis at week 8, significant benefits of the intervention were observed for depression (P=.046), anxiety (P=.01), insomnia (P<.001), sleepiness (P<.001), nonwork impairment (P=.04), and medical visit frequency (P<.001).ConclusionsThe results suggest that the Calm app is an effective workplace intervention for improving mental health, sleep, resilience, and productivity and for reducing medical visits and costs owing to work impairment. Future studies should identify optimal implementation strategies that maximize employee uptake and large-scale implementation success across diverse, geographically dispersed employers.Trial RegistrationClinicalTrials.gov NCT05120310; https://clinicaltrials.gov/ct2/show/NCT05120310

Labour, Self -Care and Respite: Neoliberal Rationalities in Sleep Crisis Rhetoric

This article tracks the emergence of sleep discourse in the past ten years in the USA, illustrating a democratisation of this rhetoric insofar as it has begun to interpellate populations beyond midlife women. Despite the sociological and demographic inequities associated with sleep deficits in marginalised populations, the much vaunted 'sleep crisis' is more widely appreciated as a distinct self-care frontier. Such behavioural scripts resonate with exaltations of the self as resilient entrepreneurial problem-solver and are linked to the broader positioning of self-care as salve for the injuries of neoliberalism. Beginning with sleep's ties to women's wellness and consumerist culture writ large, we apprehend sleep as an economy, one with staggering new commercial dimensions. Sleep remedies tend to be focused narrowly on the acquisition of products and technologies (sleep sprays, essential oils and melatonin gummies, blackout curtains, premium bedding, sleep apps, sound machines, adult sleep coaches), all of which come under consideration here. The investigation then turns to the heightened attention paid to the experience of sleep during COVID-19, discusses how sleep discourse articulates to and with a sense of ambivalent dispossession from work regimes and, finally, argues that the sleep crisis has been leveraged to intensify neoliberal brutalities.

Early alert for sleep deprivation using mobile sensor data fusion

In recent years, with the widespread use of digital technology and intelligent gadgets, an enormous amount of data are being generated at an alarmingly rapid rate. The quickly growing technologies and data generated by mobile and Internet of Things devices are tremendous. These data can be used to achieve sleep deprivation in users using machine learning. Multi-modal sensors and technology to detect activity, sleep, and circadian rhythms have become increasingly widespread. For the first time, large-scale sleep tracking is conceivable. In addition to large-scale epidemiological research, multi-sensor data can be used for wellness applications such as sleep coaching for chronic disease patients. Individuals, health, and research must overcome several fundamental obstacles before new technologies may ultimately benefit. We examine existing sleep-monitoring technology from data gathering through mobile data sensors to machine learning mode. We also analyze the current and emerging sensing technologies.

Study design of PerfectFit@Night, a workplace health promotion program to improve sleep, fatigue, and recovery of night shift workers in the healthcare sector

BackgroundHealthcare workers need to be at work 24 h a day to ensure continuity of care in hospitals. However, shift work - particularly night shifts - can have negative acute and long-term effects on health and productivity due to disturbances in the circadian rhythm. Shift work is also associated with unhealthy lifestyle behaviors such as poor sleep hygiene and diet. The PerfectFit@Night intervention aims to improve sleep and recovery, and reduce fatigue, and therewith contribute to sustainable employability of healthcare workers. The current study describes the intervention and the evaluation and implementation.MethodsThe study population will consist of healthcare workers, nurses and physicians, with night shifts in a large Dutch academic hospital. The intervention consists of individual and environmental intervention elements: i) an e-learning for healthcare workers to increase knowledge and awareness on a healthy lifestyle during night shifts, ii) a powernap bed to take powernaps during night shifts, iii) the availability of healthy food at the department during night shifts, iv) a workshop on healthy rostering at the level of the department, and v) individual sleep coaching among the high risk group. In a longitudinal prospective study, data will be collected 1 month before the start of the intervention, in the week before the start of the intervention, and three and 6 months after the start of the intervention. The primary outcomes are sleep, fatigue, and need for recovery. The implementation process will be evaluated using the framework of Steckler and Linnan. Cost-benefit analyses from the employers perspective will be conducted to understand the possible financial consequences or benefits of the implementation of PerfectFit@Night.DiscussionThe feasibility and effectiveness of this workplace health promotion program will be investigated by means of an effect, process and economic evaluation. If proven effective, PerfectFit@Night can be implemented on a larger scale within the healthcare sector.Trial registrationNetherlands Trial Register trial number NL9224. Registered 17 January 2021.

Brainmarker-I Differentially Predicts Remission to Various Attention-Deficit/Hyperactivity Disorder Treatments: A Discovery, Transfer, and Blinded Validation Study

BackgroundAttention-deficit/hyperactivity disorder is characterized by neurobiological heterogeneity, possibly explaining why not all patients benefit from a given treatment. As a means to select the right treatment (stratification), biomarkers may aid in personalizing treatment prescription, thereby increasing remission rates. MethodsThe biomarker in this study was developed in a heterogeneous clinical sample (N = 4249) and first applied to two large transfer datasets, a priori stratifying young males (<18 years) with a higher individual alpha peak frequency (iAPF) to methylphenidate (N = 336) and those with a lower iAPF to multimodal neurofeedback complemented with sleep coaching (N = 136). Blinded, out-of-sample validations were conducted in two independent samples. In addition, the association between iAPF and response to guanfacine and atomoxetine was explored. ResultsRetrospective stratification in the transfer datasets resulted in a predicted gain in normalized remission of 17% to 30%. Blinded out-of-sample validations for methylphenidate (n = 41) and multimodal neurofeedback (n = 71) corroborated these findings, yielding a predicted gain in stratified normalized remission of 36% and 29%, respectively. ConclusionsThis study introduces a clinically interpretable and actionable biomarker based on the iAPF assessed during resting-state electroencephalography. Our findings suggest that acknowledging neurobiological heterogeneity can inform stratification of patients to their individual best treatment and enhance remission rates.

Profile of paediatric sleep patients and polysomnography findings: Experience from an exclusive paediatric sleep clinic in India

Objectives: The objectives of the study were to describe the profile of patients attending an exclusive paediatric sleep clinic in India. Materials and Methods: Children aged 1 month–18 years, attending an exclusive paediatric sleep clinic, were assessed using standardized questionnaires. Children underwent sleep coaching, were treated medically, or underwent polysomnography based on the decision of the paediatric pulmonologist. Level 1 polysomnography was conducted by trained personnel. Results: Of 186 children, 36.5% were for infant sleep issues, 24.7% suspected obstructive sleep apnea (OSA), 18.2% neuromuscular diseases with sleep problems, 15.6% genetic disorders with sleep problems, 4.3% parasomnias, and 0.5% abnormal movements during sleep. Of the 85 paediatric polysomnographies conducted, 9.4% were normal studies, 87% had OSA, 1.1% restless leg syndrome, and 2.3% were inadequate studies. Conclusion: Sleep disorders in children are not uncommon and paediatricians need to be aware and identify them early. More number of exclusive paediatric sleep clinics need to be established in India.

Type 1 Diabetes, Sleep, and Hypoglycemia.

To review the relationship between sleep and hypoglycemia, sleep characteristics, and their associations with glycemic control in persons with type 1 diabetes (T1D). The effects of sleep interventions and diabetes technology on sleep are summarized. Nocturnal hypoglycemia affects objective and subjective sleep quality and is related to behavioral, psychological, and physiological factors. Sleep disturbances are common, including inadequate sleep, impaired sleep efficiency, poor subjective satisfaction, irregular timing, increased daytime sleepiness, and sleep apnea. Some have a bidirectional relationship with glycemic control. Preliminary evidence supports sleep interventions (e.g., sleep extension and sleep coach) in improving sleep and glycemic control, while diabetes technology use could potentially improve sleep. Hypoglycemia and sleep disturbances are common among persons with T1D. There is a need to develop sleep promotion programs and test their effects on sleep, glucose, and related outcomes (e.g., self-care, psychological health).

O007 Sleep health promotion in Aboriginal and Torres Strait Islander communities: untapped potential of Indigenous youth workers as sleep coaches

Abstract Purpose The lack of culturally appropriate sleep health programs and community-led support services are significant barriers to sleep health promotion in Indigenous communities. This project offers Australia’s first-ever training and upskilling program for Indigenous youth workers (IYWs) to work as “Sleep Coaches” in Indigenous communities. Methods Key stakeholders, i.e., community elders, service providers, Indigenous youth and sleep scientists, were consulted to develop a training program for IYWs. Stakeholder consultations ensured community ownership of the program, facilitated co-design of educational and training activities, and integrated traditional and scientific sleep health knowledge for developing sleep health resources. Results Consultations with the advisory group (n=48) identified the need for a multipronged approach for IYWs capacity building. The education and training activities are centred around sleep and include cultural training to cover Indigenous Australians’ understanding and interpretation of sleep health, youth mental health first aid training, and participation in youth alcohol and drug education workshops. For sleep education, two blocks of activities, i.e., foundation and advanced level, are offered to cover triaging, sleep education/support and monitoring. An interactive tool for diabetes education in Indigenous communities (FeltMan/FeltMum) has been adapted to offer culturally appropriate sleep education. Conclusion IYWs’ capacity building as sleep coaches is an innovative way to empower Indigenous communities to embrace sleep health. Going forward, the program will engage with youth mental health services to evaluate the program effectiveness and transferability to other Indigenous communities. There is a need to define the scope of practice and certification to ensure compliance with industry standards.

Feasibility and Acceptability of a Tailored Infant Safe Sleep Coaching Intervention for African American Families.

Background: Approximately 3600 infants die suddenly and unexpectedly annually in the United States. Research suggests limitations of current behavioral interventions to reduce the risk for sleep-related deaths among African American families living in under-resourced neighborhoods. Guided by the theory of planned behavior and the socio-ecological model, the My Baby’s Sleep (MBS) intervention intends to reduce the risk for sleep-related infant deaths while addressing complex needs of African American families living in under-resourced neighborhoods. Objective: To assess feasibility and acceptability of MBS, a 7-month intervention that includes four home visits and multiple check-ins via phone and text message. Methods: This was a single-arm feasibility and acceptability study with quantitative and qualitive measures. African American families were recruited from community agencies that served an under-resourced metropolitan area. Results: Eight families (eight mothers, nine co-caregivers) completed the intervention. Families reported high acceptability of MBS content, process, and format, as evidenced by qualitative data and mean evaluation scores. Conclusion: MBS is feasible and acceptable among African American families living in under-resourced neighborhoods. These results suggest further investigation of MBS intervention efficacy in a large-scale randomized controlled trial.

Paediatric sleep literacy in australian health professionals

ObjectiveThis study aimed to provide the first estimate of sleep knowledge, practices, and attitudes regarding paediatric sleep in Australian health professionals. Methods263 Australian health professionals (medical practitioners, nurses, psychologists, social workers, occupational therapists, pharmacists, dentists and sleep coaches) completed an anonymous survey. ResultsClients with sleep disorders were commonly encountered by health professionals, yet professionals reported little time spent on clinical training in sleep medicine at the undergraduate (∼1–5 hrs) or postgraduate (∼0.5–3.5 hrs) level. Health professionals reported seeking continuing professional development (CPD) in sleep (∼6+ hrs), and CPD had the most influence on health professionals’ practice, relative to other sources of information. Over half of health professionals (∼56–58%) reported that they were not trained in sleep measurement (i.e., sleep diaries and questionnaires), or how to take a sleep history. On average, professionals answered less than half (44.5%) of paediatric sleep knowledge questions correctly (M = 13.35, SD = 6.03). Approximately one third of health professionals reported not routinely screening for sleep disorders in paediatric patients and many did not routinely recommend evidence based treatments. The impact and importance of paediatric sleep was well recognised, but sleep was considered less important than a healthy diet and exercise. ConclusionsResults from the current study highlight key knowledge gaps regarding paediatric sleep across a wide range of Australian health professions, and may inform future efforts to reform clinical sleep medicine training in Australia.

Sleep Coaching for Sleep Inversion in Smith-Magenis Syndrome

Sleep Coaching for Sleep Inversion in Smith-Magenis Syndrome