Sleep is a topic of scientific and technological relevance, as it is closely related to cognition, emotional well-being, and human health. In addition, health-related geopolitical and social changes have significant implications for sleep research, which in turn is linked to the sustainable development goals (SDGs). An integrative review is conducted to analyze multidisciplinary studies in the field of sleep, considering the socioecological model of sleep health and the SDGs. Sleep was found to play a key role in promoting several SDG: (1) Social and economic inclusion: sleep is linked to poverty eradication, food security, reducing inequalities, and promoting peace and justice; (2) Promoting well-being and quality of life: sleep quality directly affects health, education, gender equality, environmental protection, and combating climate change; (3) Economic and environmental sustainability: Adequate sleep contributes to decent work, innovation, infrastructure, responsible consumption, sustainable communities and collaboration through partnerships. This thematic organization provides an overview of the different aspects of the intersection between sleep health disparities and the SDG.

Sleep health is a multidimensional construct that is essential for general health and well-being. Sleep value, the amount of worth an individual places on their sleep, and sleep resilience, the ability to function emotionally, cognitively, and physically in the presence of sleep disturbances are overlooked dimensions of sleep health. To study these sleep health dimensions, we developed the Sleep Valuation Item Bank 2.0, Values Inventory, Monetary Sleep Value Questionnaire, and Sleep Resilience Questionnaire. This paper describes the methods for the Sleep Resilience and Variance in Sleep Valuation (SRVIV) Study. The SRVIV study was conducted to explore the factor structure of sleep value and sleep resilience and determine how they relate to demographic, sleep, and psychological variables. This study resulted in an analysis sample of 455 participants who were recruited by a Qualtrics team and completed a Qualtrics survey consisting of demographic, anxiety, depression, and sleep-related questionnaires, in addition to sleep value and sleep resilience questionnaires. Adult participants were recruited throughout the continental United States and were predominately female (53%), white (82%), married (50%), and had an average age of 45.4 years. The data resulting from this study can be used to address important questions in the field of sleep psychology.

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.

Clinicians trained in cognitive–behavioural therapy (CBT) are frequently not trained to work with dreams. Given the high prevalence and impact of nightmares and bad dreams, empowering CBT therapists to effectively work with these sleep phenomena is crucial to improve therapeutic outcomes. This article briefly outlines a cognitive–behavioural model of dreams and reviews some clinical guidelines for directly and indirectly addressing nightmares and bad dreams in CBT practice.

Objectives: People living with HIV (PLWH) are more likely to report sleep difficulties and cognitive deficits. While cognitive impairment associated with sleep problems have been found in healthy and medical populations, less is known about the effects of poor sleep health (SH) on cognition among PLWH. This study examined differences in cognitive performance among participants classified based upon their HIV status and reported SH. Methods: One hundred sixteen (N=116) adults recruited from the Greater Los Angeles community were administered a comprehensive cognitive test battery and completed a questionnaire about SH. Participants were classified into the following HIV/SH groups: [HIV+/good sleep health (SH+; n=34); HIV−/SH+ (n=32); HIV−/poor sleep health (SH−; n=18) and HIV+/SH− (n=32)]. Results: For both HIV+ and HIV− individuals, poor SH was associated with lower cognitive performance, with the domains of learning and memory driving the overall relationship. The HIV+/SH− group had poorer scores in domains of learning and memory compared to the SH+ groups. Additionally, the HIV−/SH− group demonstrated poorer learning compared to the HIV−/SH+ group. Conclusions: Our findings suggest that sleep problems within medical populations are relevant to cognitive functioning, highlighting the clinical and scientific importance of monitoring sleep health and cognition to help identify individuals at greatest risk of poor health outcomes. Longitudinal investigations using both objective and subjective measures of sleep are needed to determine the robustness of the current findings and the enduring effects of poor SH in the context of chronic disease. (JINS, 2018, 24, 1038–1046)