scholarly journals SleepOMICS: How Big Data Can Revolutionize Sleep Science

Author(s):  
Nicola Luigi Bragazzi ◽  
Ottavia Guglielmi ◽  
and Sergio Garbarino

Sleep disorders have reached epidemic proportions worldwide, affecting the youth as well as the elderly, crossing the entire lifespan in both developed and developing countries. “Real-life” behavioral (sensor-based), molecular, digital, and epidemiological big data represent a source of an impressive wealth of information that can be exploited in order to advance the field of sleep research. It can be anticipated that big data will have a profound impact, potentially enabling the dissection of differences and oscillations in sleep dynamics and architecture at the individual level (“sleepOMICS”), thus paving the way for a targeted, “one-size-does-not-fit-all” management of sleep disorders (“precision sleep medicine”).

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Katarzyna Klasa ◽  
Stephanie Galaitsi ◽  
Andrew Wister ◽  
Igor Linkov

AbstractThe care needs for aging adults are increasing burdens on health systems around the world. Efforts minimizing risk to improve quality of life and aging have proven moderately successful, but acute shocks and chronic stressors to an individual’s systemic physical and cognitive functions may accelerate their inevitable degradations. A framework for resilience to the challenges associated with aging is required to complement on-going risk reduction policies, programs and interventions. Studies measuring resilience among the elderly at the individual level have not produced a standard methodology. Moreover, resilience measurements need to incorporate external structural and system-level factors that determine the resources that adults can access while recovering from aging-related adversities. We use the National Academies of Science conceptualization of resilience for natural disasters to frame resilience for aging adults. This enables development of a generalized theory of resilience for different individual and structural contexts and populations, including a specific application to the COVID-19 pandemic.


Author(s):  
Yan Wang ◽  
Feng Hao ◽  
Yunxia Liu

Population change and environmental degradation have become two of the most pressing issues for sustainable development in the contemporary world, while the effect of population aging on pro-environmental behavior remains controversial. In this paper, we examine the effects of individual and population aging on pro-environmental behavior through multilevel analyses of cross-national data from 31 countries. Hierarchical linear models with random intercepts are employed to analyze the data. The findings reveal a positive relationship between aging and pro-environmental behavior. At the individual level, older people are more likely to participate in environmental behavior (b = 0.052, p < 0.001), and at the national level, living in a country with a greater share of older persons encourages individuals to behave sustainably (b = 0.023, p < 0.01). We also found that the elderly are more environmentally active in an aging society. The findings imply that the longevity of human beings may offer opportunities for the improvement of the natural environment.


2017 ◽  
Vol 8 (7) ◽  
pp. 816-826 ◽  
Author(s):  
Gilad Feldman ◽  
Huiwen Lian ◽  
Michal Kosinski ◽  
David Stillwell

There are two conflicting perspectives regarding the relationship between profanity and dishonesty. These two forms of norm-violating behavior share common causes and are often considered to be positively related. On the other hand, however, profanity is often used to express one’s genuine feelings and could therefore be negatively related to dishonesty. In three studies, we explored the relationship between profanity and honesty. We examined profanity and honesty first with profanity behavior and lying on a scale in the lab (Study 1; N = 276), then with a linguistic analysis of real-life social interactions on Facebook (Study 2; N = 73,789), and finally with profanity and integrity indexes for the aggregate level of U.S. states (Study 3; N = 50 states). We found a consistent positive relationship between profanity and honesty; profanity was associated with less lying and deception at the individual level and with higher integrity at the society level.


Author(s):  
S. G. Khachatryan ◽  
M. A. Isayan ◽  
H. A. Hovakimyan

This article represents a brief overview and summary of the main ideas, suggestions, agreements, and conclusions reached during a special round-table discussion held on Oct 10, 2019, at the Armenian National Institute of Health, with the participation of representatives from the Armenian Sleep Disorders Association and the Executive Committee of the Assembly of National Sleep Societies (ANSS) of the European Sleep Research Society. As the pilot activity of the ANSS "Beyond Boundaries" project, it aimed to identify the current needs in the field of sleep medicine in Armenia and to summarize the recommendations to help improving the future multidisciplinary development of this important field in Armenia. The article aims to serve as a guiding point for further collaborations regarding sleep medicine in Armenia. Based on the evaluation of this pilot project, the ANSS will further shape and improve the "Beyond Boundaries" project for further implementation in other European countries that wish to develop knowledge and skills in the field of sleep medicine and research and broaden their international network.


Author(s):  
Rebecca L. Monk ◽  
Lauren Colbert ◽  
Gemma Darker ◽  
Jade Cowling ◽  
Bethany Jones ◽  
...  

Abstract Background Theory of mind (ToM), the ability to understand that others have different knowledge and beliefs to ourselves, has been the subject of extensive research which suggests that we are not always efficient at taking another’s perspective, known as visual perspective taking (VPT). This has been studied extensively and a growing literature has explored the individual-level factors that may affect perspective taking (e.g. empathy and group membership). However, while emotion and (dis)liking are key aspects within everyday social interaction, research has not hitherto explored how these factors may impact ToM. Method A total of 164 participants took part in a modified director task (31 males (19%), M age = 20.65, SD age = 5.34), exploring how correct object selection may be impacted by another’s emotion (director facial emotion; neutral × happy × sad) and knowledge of their (dis)likes (i.e. director likes specific objects). Result When the director liked the target object or disliked the competitor object, accuracy rates were increased relative to when he disliked the target object or liked the competitor object. When the emotion shown by the director was incongruent with their stated (dis)liking of an object (e.g. happy when he disliked an object), accuracy rates were also increased. None of these effects were significant in the analysis of response time. These findings suggest that knowledge of liking may impact ToM use, as can emotional incongruency, perhaps by increasing the saliency of perspective differences between participant and director. Conclusion As well as contributing further to our understanding of real-life social interactions, these findings may have implications for ToM research, where it appears that more consideration of the target/director’s characteristics may be prudent.


2020 ◽  
Vol 7 (1) ◽  
pp. 205395172093514 ◽  
Author(s):  
Laurence Barry ◽  
Arthur Charpentier

The aim of this article is to assess the impact of Big Data technologies for insurance ratemaking, with a special focus on motor products.The first part shows how statistics and insurance mechanisms adopted the same aggregate viewpoint. It made visible regularities that were invisible at the individual level, further supporting the classificatory approach of insurance and the assumption that all members of a class are identical risks. The second part focuses on the reversal of perspective currently occurring in data analysis with predictive analytics, and how this conceptually contradicts the collective basis of insurance. The tremendous volume of data and the personalization promise through accurate individual prediction indeed deeply shakes the homogeneity hypothesis behind pooling. The third part attempts to assess the extent of this shift in motor insurance. Onboard devices that collect continuous driving behavioural data could import this new paradigm into these products. An examination of the current state of research on models with telematics data shows however that the epistemological leap, for now, has not happened.


First Monday ◽  
2017 ◽  
Author(s):  
Benny Bornfeld ◽  
Sheizaf Rafaeli

Badges are a common gamification mechanism used by many crowd-sourced online systems. This study provides evidence to their effectiveness and measures their effect size using a big data natural experiment in three large Stack Exchange online Q&A sites. We analyze the introduction of 22 different badge-launch events and the resulting changes in user behavior. Consistent with earlier studies, we report that most badge introductions have the desired effect. Going beyond traditional findings on the individual level, this study measures overall badge effect size on the service.


Author(s):  
Nuno M. Garcia ◽  
Nuno Pombo ◽  
Torsten Braun ◽  
Francisco Flórez-Revuelta ◽  
Ivan Chorbev ◽  
...  

UNSTRUCTURED The increased availability of devices that can record every aspect of a person’s life will allow the recording of a large amount of data that will be primarily useful for that particular user. These devices and their data will place each and every one of us at the doorstep of the era of personal big data. Using this data, in a not so distant future, we will be able to set a personal digital life coach, a digital platform that will act at an individual level, but also considering a global interaction, not only as a social networking tool, but as a platform that will profit from the individual experiences of its users. This position paper focuses on the identification of the milestones that will mark the creation of such a software and hardware platform, by exploring the opportunities and challenges that it poses to the computer science researchers, and how such a solution can be designed to be a user-adoptable lifestyles monitoring and training tool.


2018 ◽  
Vol 115 (8) ◽  
pp. E1740-E1748 ◽  
Author(s):  
Robert Thorstad ◽  
Phillip Wolff

We use big data methods to investigate how decision-making might depend on future sightedness (that is, on how far into the future people’s thoughts about the future extend). In study 1, we establish a link between future thinking and decision-making at the population level in showing that US states with citizens having relatively far future sightedness, as reflected in their tweets, take fewer risks than citizens in states having relatively near future sightedness. In study 2, we analyze people’s tweets to confirm a connection between future sightedness and decision-making at the individual level in showing that people with long future sightedness are more likely to choose larger future rewards over smaller immediate rewards. In study 3, we show that risk taking decreases with increases in future sightedness as reflected in people’s tweets. The ability of future sightedness to predict decisions suggests that future sightedness is a relatively stable cognitive characteristic. This implication was supported in an analysis of tweets by over 38,000 people that showed that future sightedness has both state and trait characteristics (study 4). In study 5, we provide evidence for a potential mechanism by which future sightedness can affect decisions in showing that far future sightedness can make the future seem more connected to the present, as reflected in how people refer to the present, past, and future in their tweets over the course of several minutes. Our studies show how big data methods can be applied to naturalistic data to reveal underlying psychological properties and processes.


SIMULATION ◽  
2018 ◽  
Vol 95 (9) ◽  
pp. 823-843
Author(s):  
Ahmed Abdelghany ◽  
Hani Mahmassani ◽  
Khaled Abdelghany ◽  
Hasan Al-Ahmadi ◽  
Wael Alhalabi

This paper presents the main findings of a simulation-based study to evaluate incidents in pedestrian/crowd tunnels and similar elongated confined facilities, with high-volume heterogeneous traffic. These incidents, when occur, imposes hazardous conditions that always result in significant number of fatalities. The aim of this study is to understand how these facilities perform under different irregular scenarios and possibly identify potential causes of accidents. The problem of studying incidents in large-scale high-volume pedestrian facilities is that these incidents are difficult to expect or replicate. Thus, studying these facilities through real-life scenarios is almost impossible. Accordingly, a micro-simulation assignment model for multidirectional pedestrian movement is used for this purpose. The model adopts a Cellular Automata (CA) discrete system, which allows detailed representation of the pedestrians’ walkways in the tunnel. The modeling approach captures crowd dynamics through representation of behavioral decisions of heterogeneous pedestrians at the individual level. Several experiments are conducted to study the pedestrian flow in the proposed tunnel considering different operational scenarios including demand levels, heterogeneous traffic, evacuation scenario, and tunnel blockage. Results show that flow of large pedestrian volumes through a long confined linear structure, such as a tunnel, are subject to the same flow dynamics as we observe with vehicular traffic. In particular, they are subject to the formation of “clumps” and shock waves that can rapidly propagate and lead to inefficient operation, including flow breakdown with stop-and-go waves.


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