L’utilisation des réseaux sociaux (Snapchat, WhatsApp et Instagram) et le cyberbullying

100% des jeunes possèdent un téléphone portable, 99% ont un ordinateur et 97% ont accès à Internet (Waller et al., 2016). Ces nouveaux moyens technologiques font partie de notre quotidien. Depuis l’apparition de ces réseaux, un nouveau mouvement est né : le cyberbullying. Ce harcèlement par Internet consiste à l’utilisation de technologies modernes de communication afin de nuire aux autres de manière délibérée et agressive. Quand les jeunes arrivent en classe, ils apportent avec eux l’entier de leur vécu quotidien, familial ou encore émotionnel. Les problèmes liés à l’utilisation massive de ces réseaux font partie de notre quotidien d’enseignant. Malheureusement, les études faites jusqu’au jour d’aujourd’hui portent en majeure partie sur les élèves entre 13 ans et plus. Mais qu’en est-il des jeunes âgés entre 9 et 12 ans ? Notre travail de recherche porte donc sur l’utilisation des réseaux sociaux (Snapchat, Instagram et WhatsApp) et le cyberbullying. Deux outils différents ont été utilisés lors de cette recherche : des questionnaires afin d’avoir des résultats quantitatifs et deux entretiens afin d’avoir un point de vue qualitatif. Nos résultats montrent que WhatsApp est le réseau social le plus utilisé, suivi d’Instagram en deuxième position et finalement de Snapchat. Les élèves considèrent le nombre de dangers et de conflits sur les réseaux comme très faibles. Ils avouent tout de même donner plus d’informations personnelles sur WhatsApp que sur les autres réseaux choisis dans l’étude. Concernant leur vision du contrôle des parents, ils l’estiment très faible. Cependant, il s’agit uniquement de leur avis, il serait intéressant de savoir la réalité des faits en interrogeant les parents. Les deux sujets interrogés savent définir le cyberbullying et connaissent les différents acteurs agissant au sein de cette forme de harcèlement. Ils sont également conscients des différents risques, conséquences ou sentiments que peut ressentir une cyber-victime mais n’abordent pas du tout ceux concernant le témoin ou le cyber-harceleur. En conclusion, notre recherche montre que les réseaux sociaux font partie intégrante du quotidien d’un grand nombre d’élèves. Il est donc essentiel que les enseignants s’interrogent sur les moyens de gérer les problèmes que ceux-ci peuvent amener en classe mais également les moyens de les éviter

Additional file 2: of Genetic polymorphism in selenoprotein P modifies the response to selenium-rich foods on blood levels of selenium and selenoprotein P in a randomized dietary intervention study in Danes

Association between mean concentrations of erythrocyte GPX enzyme activity, whole blood selenium and selenoprotein P in relation to the studied polymorphisms, and within-subject effects between genotype and time in the control group. (DOCX 24 kb

Additional file 1: of Genetic polymorphism in selenoprotein P modifies the response to selenium-rich foods on blood levels of selenium and selenoprotein P in a randomized dietary intervention study in Danes

Flow chart of study participants as previously published [28]. (DOCX 37 kb

Knowledge deficit, attitude and behavior scales association to objective measures of sun exposure and sunburn in a Danish population based sample

<div><p>The objective of this study was to develop new scales measuring knowledge and attitude about UVR and sun related behavior, and to examine their association to sun related behavior objectively measured by personal dosimetry. During May-August 2013, 664 Danes wore a personal electronic UV-dosimeter for one week that measured their UVR exposure. Afterwards, they answered a questionnaire on sun-related items. We applied descriptive analysis, linear and logistic regression analysis to evaluate the associations between the questionnaire scales and objective UVR measures. Perceiving protection as routine and important were positively correlated with protective behavior. <i>Knowledge deficit of UV and risk of melanoma</i>, <i>perceived benefits</i> and <i>importance of protection behavior</i> was also correlated with use of protection. ‘<i>Knowledge deficit of UV and risk of melanoma</i> and <i>Perceived barrier towards sun avoidance between 12 and 15’</i> were both associated with increased risk of sunburn. <i>Attitude towards tan</i> was associated to both outdoor time and exposure as well as use of protection, but not to sunburn. The results regarding <i>Knowledge deficit of UV and risk of melanoma</i> associated to UVR exposure and <i>Perceived barrier towards sun avoidance between 12 and 15</i> emphasize the importance of awareness of melanoma risk and the priority of the skin cancer prevention advice. Shifting activities to outside the suns peak-hours could be an approach for structural and campaign preventive measures. Knowledge of items predicting exposure to UVR, use of protection and sunburn are important for planning of preventive interventions and melanoma research.</p></div

In the figure is shown the flow of participants in the project including participation and completion of uv-measurement and questionnaire.

<p>In the figure is shown the flow of participants in the project including participation and completion of uv-measurement and questionnaire.</p

Forecasting Chronic Diseases Using Data Fusion

Data fusion, that is, extracting information through the fusion of complementary data sets, is a topic of great interest in metabolomics because analytical platforms such as liquid chromatography–mass spectrometry (LC–MS) and nuclear magnetic resonance (NMR) spectroscopy commonly used for chemical profiling of biofluids provide complementary information. In this study, with a goal of forecasting acute coronary syndrome (ACS), breast cancer, and colon cancer, we jointly analyzed LC–MS, NMR measurements of plasma samples, and the metadata corresponding to the lifestyle of participants. We used supervised data fusion based on multiple kernel learning and exploited the linearity of the models to identify significant metabolites/features for the separation of healthy referents and the cases developing a disease. We demonstrated that (i) fusing LC–MS, NMR, and metadata provided better separation of ACS cases and referents compared with individual data sets, (ii) NMR data performed the best in terms of forecasting breast cancer, while fusion degraded the performance, and (iii) neither the individual data sets nor their fusion performed well for colon cancer. Furthermore, we showed the strengths and limitations of the fusion models by discussing their performance in terms of capturing known biomarkers for smoking and coffee. While fusion may improve performance in terms of separating certain conditions by jointly analyzing metabolomics and metadata sets, it is not necessarily always the best approach as in the case of breast cancer

Linear regression models of outdoor exposure time, UV-exposure received in SED and the protection scale respectively.

<p>Linear regression models of outdoor exposure time, UV-exposure received in SED and the protection scale respectively.</p

Distribution of demographic characteristics and scale scores in a cross-sectional sample of 664 Danes.

<p>Distribution of demographic characteristics and scale scores in a cross-sectional sample of 664 Danes.</p

Correlation of protection behavior scale and protection attitude and knowledge deficit scales.

<p>Correlation of protection behavior scale and protection attitude and knowledge deficit scales.</p

Logistic regression models of sunburn and background variables, knowledge deficit, attitude and behavior scales.

<p>Logistic regression models of sunburn and background variables, knowledge deficit, attitude and behavior scales.</p