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©Meritxell Pallejà-Millán, Cristina Rey-Reñones, Maria Luisa Barrera Uriarte, Esther Granado-Font, Josep Basora, Gemma Flores-Mateo, Jordi Duch. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 26.06.2020. BACKGROUND: Mobile apps provide an accessible way to test new health-related methodologies. Tobacco is still the primary preventable cause of death in industrialized countries, constituting an important public health issue. New technologies provide novel opportunities that are effective in the cessation of smoking tobacco. OBJECTIVE: This paper aims to evaluate the efficacy and usage of a mobile app for assisting adult smokers to quit smoking. METHODS: We conducted a cluster randomized clinical trial. We included smokers older than 18 years who were motivated to stop smoking and used a mobile phone compatible with our mobile app. We carried out follow-up visits at 15, 30, and 45 days, and at 2, 3, 6, and 12 months. Participants of the intervention group had access to the Tobbstop mobile app designed by the research team. The primary outcomes were continuous smoking abstinence at 3 and 12 months. RESULTS: A total of 773 participants were included in the trial, of which 602 (77.9%) began the study on their D-Day. Of participants in the intervention group, 34.15% (97/284) did not use the app. The continuous abstention level was significantly larger in the intervention group participants who used the app than in those who did not use the app at both 3 months (72/187, 38.5% vs 13/97, 13.4%; P<.001) and 12 months (39/187, 20.9% vs 8/97, 8.25%; P=.01). Participants in the intervention group who used the app regularly and correctly had a higher probability of not being smokers at 12 months (OR 7.20, 95% CI 2.14-24.20; P=.001) than the participants o

Carbon spheres (CS) are interesting materials for antibacterial applications. Herein, CS are produced by a green process utilizing microwave-assisted hydrothermal treatment of cellulose. The CS are then postmodified in acidic and basic solutions to evaluate the influence of different functionalities on antibacterial properties. CS contain OH/COOH, C Symbol of the Klingon Empire C, and C Symbol of the Klingon Empire O functionalities, while O-CS produced by acid treatment of CS have additional COOH, and NH/NH2 groups, resulting in carbon spheres with negatively and positively charged groups in dispersion. Treatment with base (Na-CS) removes low molecular weight species with oxygen and results in carbon spheres with the highest C/O ratio. CS, O-CS, and Na-CS have nonporous morphology and are in micro/nanometer sizes, although, smaller sized spheres, hollow spheres, and fragments are also attained in the case of O-CS. O-CS show antibacterial activity toward both Gram-positive Staphylococcus aureus (S. aureus) and Gram-negative Pseudomonas aeruginosa (P. aeruginosa). The minimum inhibitory concentration is 200 and 400 mu g mL(-1) for S. aureus and P. aeruginosa, respectively, and is achieved only after 3 h of incubation. Neither CS nor Na-CS exhibit antibacterial activity. The antibacterial activity is suggested to originate from electrostatic interactions between O-CS and the bacteria., QC 20190514

Background: Tobacco use during pregnancy entails a serious risk to the mother and harmful effects on the development of the child. Europe has the highest tobacco smoking prevalence (19.3%) compared with the 6.8% global mean. Between 20% to 30% of pregnant women used tobacco during pregnancy worldwide. These data emphasize the urgent need for community education and implementation of prevention strategies focused on the risks associated with tobacco use during pregnancy.Objective: The aim of this study was to investigate the efficacy of an intervention that incorporates a serious game (Tobbstop) to help pregnant smokers quit smoking.Methods: A two-arm randomized controlled trial enrolled 42 women who visited 2 primary care centers in Catalonia, Spain, between March 2015 and November 2016. All participants were pregnant smokers, above 18 years old, attending consultation with a midwife during the first trimester of pregnancy, and had expressed their desire to stop smoking. Participants were randomized to the intervention (n= 21) or control group (n= 21). The intervention group was instructed to install the game on their mobile phone or tablet and use it for 3 months. Until delivery, all the participants were assessed on their stage of smoking cessation during their follow-up midwife consultations. The primary outcome was continuous tobacco abstinence until delivery confirmed by the amount of carbon monoxide at each visit, measured with a carboxymeter.Results: Continuous abstinence until delivery outcome was 57%(12/21) in the intervention group versus 14%(3/21) in the control group (hazard ratio= 4.31; 95% CI 1 …

Mental disorders have an enormous impact in our society, both in personal terms and in the economic costs associated with their treatment. In order to scale up services and bring down costs, administrations are starting to promote social interactions as key to care provision. We analyze quantitatively the importance of communities for effective mental health care, considering all community members involved. By means of citizen science practices, we have designed a suite of games that allow to probe into different behavioral traits of the role groups of the ecosystem. The evidence reinforces the idea of community social capital, with caregivers and professionals playing a leading role. Yet, the cost of collective action is mainly supported by individuals with a mental condition - which unveils their vulnerability. The results are in general agreement with previous findings but, since we broaden the perspective of previous studies, we are also able to find marked differences in the social behavior of certain groups of mental disorders. We finally point to the conditions under which cooperation among members of the ecosystem is better sustained, suggesting how virtuous cycles of inclusion and participation can be promoted in a 'care in the community' framework.

10.1073/pnas.1309389111, Tens of millions of individuals around the world use decentralized content distribution systems, a fact of growing social, economic, and technological importance. These sharing systems are poorly understood because, unlike in other technosocial systems, it is difficult to gather large-scale data about user behavior. Here, we investigate user activity patterns and the socioeconomic factors that could explain the behavior. Our analysis reveals that (i) the ecosystem is heterogeneous at several levels: content types are heterogeneous, users specialize in a few content types, and countries are heterogeneous in user profiles; and (ii) there is a strong correlation between socioeconomic indicators of a country and users behavior. Our findings open a research area on the dynamics of decentralized sharing ecosystems and the socioeconomic factors affecting them, and may have implications for the design of algorithms and for policymaking.

10.1038/srep00605

Teamwork is a fundamental aspect of many human activities, from business to art and from sports to science. Recent research suggest that team work is of crucial importance to cutting-edge scientific research, but little is known about how teamwork leads to greater creativity. Indeed, for many team activities, it is not even clear how to assign credit to individual team members. Remarkably, at least in the context of sports, there is usually a broad consensus on who are the top performers and on what qualifies as an outstanding performance.In order to determine how individual features can be quantified, and as a test bed for other team-based human activities, we analyze the performance of players in the European Cup 2008 soccer tournament. We develop a network approach that provides a powerful quantification of the contributions of individual players and of overall team performance.We hypothesize that generalizations of our approach could be useful in other contexts where quantification of the contributions of individual team members is important.

The ubiquity of modular structure in real-world complex networks is the focus of attention in many trials to understand the interplay between network topology and functionality. The best approaches to the identification of modular structure are based on the optimization of a quality function known as modularity. However this optimization is a hard task provided that the computational complexity of the problem is in the non-deterministic polynomial time hard (NP-hard) class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining their modularity. This size reduction allows use of heuristic algorithms that optimize modularity for a better exploration of the modularity landscape. We compare the modularity obtained in several real complex-networks by using the extremal optimization algorithm, before and after the size reduction, showing the improvement obtained. We speculate that the proposed analytical size reduction could be extended to an exact coarse graining of the network in the scope of real-space renormalization. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.