Together with (physical and mental) exercise, diet, and social activities, sleep is a key health behavior that occupies one third of our lives, yet remains neglected. In the first part of this review, we present the current knowledge on how sleep promotes body, brain, mental, occupational, and social health as well as creativity, productivity, and well-being. In the second part, we discuss how good sleep and screening for sleep–wake disorders may improve health and reduce the burden of brain, mental, cardiovascular, metabolic disorders and cancer. We also review the literature on measurements of sleep health and present the Bernese Sleep Health Questionnaire, a new and simple tool to assess sleep health and screen for sleep–wake circadian disorders in clinical practice.

For athletes, sleep is essential for recovery and performance. Yet, up to two-thirds of athletes report poor sleep quality. Comprehensive data across all sports disciplines on the underlying causes of sleep problems are missing. We reanalyzed a data set of N = 1004 Swiss top athletes across an extensive array of 88 sports to gain knowledge on the specific deficits in sleep health with respect to gender, sport classes, sport-related factors, and well-being. We found that 18% of athletes were affected by at least two out of five high-risk sleep factors: 9% of athletes slept less than 6 h per day, 30% were dissatisfied with their sleep, 17% showed problems falling asleep within 30 min, 18% of athletes reported difficulty maintaining sleep more than three times a week, and 6% of athletes used sleeping pills more than once a week. We found sleep health strongly linked to overall well-being and mental health (22% showed at least moderate symptoms of either depression or anxiety). Therefore, screening and treating sleep disorders might effectively improve mental health and general well-being as well as performance among athletes around the globe.

Generally, sleep is thought of as a state of rest that helps to recover the body and brain from the physical and cognitive activities during wakefulness. The main characteristics of sleep in contrast to wakefulness support this idea: a barely present motor activity and a very low reactivity to both internal and external stimuli. The long-term atonic state of skeletal muscles is taken as an indication that important restorative processes on the musculoskeletal system take place during sleep – and the state of unconsciousness as well as inadequate responsiveness suggests that the central nervous system pauses to engage in important synaptic plasticity processes. About 40 years ago, therefore, in sleep research, the idea was that especially NREM sleep fosters synthetic processes of growth and repair in the body, and REM sleep was believed to be directed towards increases in synthetic processes within the brain, including the consolidation of memory (Horne, 1979). The opinion that SWS is mainly for body restitution was encouraged by the observation that after falling asleep during the early night period, human growth hormone (hGH) is present in relatively large amounts in the plasma (Born et al., 1988). Additionally, it was shown that after high loads of physical activity during the day, in the following night the percentage of SWS increased (Shapiro et al., 1981). Moreover, sleep deprivation seems to weaken muscle recovery by increasing protein breakdown, which adversely affects protein synthesis and promotes muscle atrophy (Dattilo et al., 2011, 2012). Muscle recovery would potentially be impaired because this process is strongly regulated by the anabolic and catabolic hormones mentioned above, which are strongly influenced by sleep. On the other hand, the heart muscle and the diaphragm (the main muscle for respiratory activity) prove that the vital contractile elements of a muscle maintain their function without rest over the lifespan. And if they did, it seems more likely to be the motor unit of the supporting and target muscles as a whole (including the reflex pathways) that needs rest (Fitts, 2008). Furthermore, the muscle protein synthetic response following resistance exercise seems rather time-dependent than state-dependent, e.g. amino acids are taken up in skeletal muscle tissue within hours independent of being awake or asleep (McGlory et al., 2017). However, the aforementioned release of hGH during the early hours of sleep and the results from sleep deprivation studies point in the direction that some regeneration processes are dependent on sleep, and most likely on SWS (Dattilo et al., 2011). The proposed hypothesis that bodily recovery and regeneration are sleep-dependent is widely used, but often lacks extensive supportive experimental evidence. In this presentation we will discuss the current concepts of muscle recovery during sleep and review the studies in that field. References Born, J., Muth, S., & Fehm, H. L. (1988). The significance of sleep onset and slow wave sleep for nocturnal release of growth hormone (GH) and cortisol. Psychoneuroendocrinology, 13(3), 233–243. https://doi.org/10.1016/0306-4530(88)90021-2 Dattilo, M., Antunes, H. K., Medeiros, A., Mônico-Neto, M., Souza, H. de S. Á., Lee, K. S., Tufik, S., & de Mello, M. T. (2012). Paradoxical sleep deprivation induces muscle atrophy. Muscle & Nerve, 45(3), 431–433. https://doi.org/10.1002/mus.22322 Dattilo, M., Antunes, H. K., Medeiros, A., Mônico Neto, M., Souza, H. S., Tufik, S., & de Mello, M. T. (2011). Sleep and muscle recovery: endocrinological and molecular basis for a new and promising hypothesis. Medical Hypotheses, 77(2), 220–222. https://doi.org/10.1016/j.mehy.2011.04.017 Fitts, R. H. (2008). The cross-bridge cycle and skeletal muscle fatigue. Journal of Applied Physiology, 104(2), 551–558. https://doi.org/10.1152/japplphysiol.01200.2007 Horne, J. A. (1979). Restitution and human sleep: A critical review. Physiological Psychology, 7(2), 115–125. McGlory, C., Devries, M. C., & Phillips, S. M. (2017). Skeletal muscle and resistance exercise training; the role of protein synthesis in recovery and remodeling. Journal of Applied Physiology, 122(3), 541–548. https://doi.org/10.1152/japplphysiol.00613.2016 Shapiro, C. M., Bortz, R., Mitchell, D., Bartel, P., & Jooste, P. (1981). Slow-wave sleep: A recovery period after exercise. Science 214(4526), 1253–1254. https://doi.org/10.1126/science.7302594

Problems with initiating and maintaining sleep are among the most common health complaints, with prevalence rates exceeding 50% depending on the survey. Preventing the progression to chronic insomnia may reduce public healthcare costs and prevent secondary illnesses. This study examined the effectiveness of a novel app‐based digital course using cognitive behavioural therapy for insomnia (CBT‐I) in preventing the manifestation of insomnia among individuals with sub‐threshold to moderate symptoms. Participants were assigned to an intervention group ( N = 191, ages 20–75) or a waitlist control group ( N = 72, ages 22–77) and assessed at three time points: Pre‐intervention (T0), Post‐intervention (T1, after 7‐week course) and Follow‐up (T2, 3 months after course initiation) using the Insomnia Severity Index (ISI), Sleep Hygiene Index (SHI) and sleep diary entries. Results showed a significant reduction in insomnia severity (−4.8 ± 3.7 ISI points) and improved sleep hygiene (−3.5 ± 4.5 SHI points) from T0 to T1 ( d = 1.35, and d = 0.69, respectively), with stable effects maintained at the 3‐month follow‐up. Remission was achieved by 48% of the intervention group compared to 18% of the control group. Improvements were also observed in sleep latency, sleep efficiency and reductions in nocturnal awakenings and wake time after sleep onset ( d = 0.25–0.71). Activating evening activates, napping, irregular bedtimes, uncomfortable sleep environment, perceived stress and rumination significantly reduced ( d = 0.16–0.59). Notably, 68% of users reported sustained improvements in their sleep. The findings indicate that various sleep hygiene behaviours can be effectively modified through an app‐based CBT ‐I intervention. Trial Registration: This study was pre‐registered at Open Science Framework https://osf.io/yj2va

Mobile health (mHealth) interventions can transform health care delivery and improve public health. At the same time, the evidence on lifestyle interventions continues to grow. They show promising results in preventing and treating noncommunicable diseases and enhancing health-related quality of life. These factors highlight the potential of multidomain mHealth interventions for lifestyle management. This viewpoint paper focuses on drawing valuable lessons from past experiences and providing guidance to developers of mHealth interventions for lifestyle management. We underscore the critical role of sharing practical insights to advance innovation in the field of mHealth interventions. We used an iterative consensus process to derive lessons learned, identify challenges, and reflect on possible actions. Our insights are based on our experience in developing 2 smartphone-based lifestyle interventions. Challenges and corresponding options in the following areas are presented: target population (preferences, personalization, and delivery), user involvement and testing, human support, and multidomain interventions (interdisciplinarity, flexibility, and core team). The development of multidomain mHealth interventions for lifestyle management requires a participatory and iterative approach involving relevant stakeholders (including end users) so that the right people get the right content at the right time. Additionally, it is crucial to consider established frameworks, guidelines, and regulations; allocate appropriate resources; and form a core team committed to the project’s aims and open to working in an interdisciplinary team.

Insomnia is characterized by frequent and persistent difficulties initiating and maintaining sleep, along with impaired daytime functioning. Blended treatments are increasingly popular for treating psychological disorders such as depression. Blended treatments combine elements of face-to-face therapy and online interventions. A single-arm pre-post study investigated the feasibility of a blended treatment combining face-to-face cognitive behavioral therapy for insomnia and internet-based cognitive behavioral therapy for insomnia (SLEEPexpert+). The findings show that the therapists have a positive attitude toward blended CBT-I (b-CBT-I) and that they feel supported by the online components of the treatment. Possible barriers to implementing blended treatments are integrating the online materials into the face-to-face sessions and adapting one’s therapeutic style to the blended treatment approach. No definitive statements about the effectiveness of the b-CBT-I treatment can be made. However, of the six presented cases, five patients showed notably higher sleep efficiency and fewer insomnia symptoms at the end of the therapy. Program usage data indicate that participants mainly used the online components at the beginning of their treatment. Future studies should investigate the effectiveness of b-CBT-I with a sufficiently powered randomized controlled trial comparing b-CBT-I with an adequate control group in routine care.