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See detailThe influence of well-being, social support, media use and sociodemographic factors on problematic social media sue among Luxembourgish adolescents
van Duin, Claire UL; Heinz, Andreas UL; Willems, Helmut Erich UL

in Cogent Medicine (2020), 7(1),

Background: Adolescents spend an increasing amount of time communicating online. Previous research has indicated that electronic media communication has been associated with positive outcomes on ... [more ▼]

Background: Adolescents spend an increasing amount of time communicating online. Previous research has indicated that electronic media communication has been associated with positive outcomes on adolescent well-being and development, however, problematic social media use is on the rise. This study investigates factors that influence problematic social media use (PSMU), based on previous empirical research and the Differential Susceptibility to Media Effects Model by Valkenburg and Peter (2013). Methods: The data used in this study stems from the 2018 Health Behaviour for School-aged Children (HBSC) study in Luxembourg. Data from elementary and secondary school students aged 11 to 18 was used (N = 6164), which was collected through a written survey. A four-stage hierarchical multiple regression analysis was conducted using SPSS, with problematic social media use as the dependent variable. 14 independent variables were included in the model, added in four blocks: sociodemographic factors, social support factors, well-being factors and media use factors.Results: The results indicate that in stage one of the hierarchical regression, the sociodemographic predictors accounted for 3% of the variation in problematic social media use. The addition of the social support factors to the model in stage two explained an additional 7% of the variation in problematic social media use, and the addition of the well-being factors in stage three an additional 5.3%. In stage four of the hierarchical regression media use factors were added to the model, and the four blocks of predictors accounted for 22.2% of the variation in problematic social media use (Adjusted R2 = 0.222). The most important predictors for problematic social media use were preference for online social interaction (β = 0.205, p < .001), the intensity of electronic media communication (β = 0.155, p < .001), psychosomatic complaints (β = 0.136, p < .001), perceived stress (β = 0.122, p < .001) and cyberbullying perpetration (β = 0.117, p < .001). Conclusions: The block of sociodemographic factors contributed minimally to the explanation of the variance in problematic social media use in the model. The most important predictors for problematic social media use were preference for online social interaction, the intensity of electronic media communication, psychosomatic complaints, perceived stress and cyberbullying perpetration. This suggests that there are several starting points for the prevention of problematic social media use among adolescents. [less ▲]

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See detailPrévention primaire
Barré, Jessica; Bejko, Dritan; Bendiane, Marc-Karim et al

in RAPPORT NATIONAL DU CANCER au Grand-Duché de Luxembourg 2020 (2020)

Le chapitre prévention primaire se concentre sur les facteurs de risques externes établis comme principaux, liés au mode de vie des personnes, à savoir le tabac, l’alcool, l’alimentation, l’activité ... [more ▼]

Le chapitre prévention primaire se concentre sur les facteurs de risques externes établis comme principaux, liés au mode de vie des personnes, à savoir le tabac, l’alcool, l’alimentation, l’activité physique et la surcharge pondérale et l’obésité, susceptibles d’engendrer un cancer. L’éducation à la santé joue un rôle important, afin d’amener les individus à adopter des comportements préventifs, dans l’objectif de prévenir une maladie ou de la détecter à un stade asymptomatique. Les données des enquêtes European Health Interview Survey (EHIS, étude pilotée par le Ministère de la Santé et le Luxembourg Institute of Health) et Health Behaviour in School-Aged Children (HBSC, enquête coordonnée au Luxembourg par le Ministère de la Santé, le Ministère de l’Education nationale, de l’Enfance et de la Jeunesse, et l’Université de Luxembourg) ont été utilisées dans ce chapitre, pour compiler les données statistiques liées aux facteurs de risques. L’ensemble des comparaisons européennes est réalisé par Eurostat, (https://ec.europa.eu/), par l’étude internationale HBSC (http://www.hbsc.org/) et par le réseau international de chercheurs HBSC. Le chapitre se poursuit sur un descriptif des démarches de prévention mises en place sur le territoire national, au regard des facteurs de risques exposés au paragraphe 1, par exemple pour : Le tabac : Plan National de Lutte contre le Tabagisme (PNLT) 2016-2020, programme de sevrage tabagique (Ministère de la Santé/ Caisse Nationale de Santé), loi du 13 juin 2017 transposant la directive européenne 2014/40/UE sur les produits tabac ; L’alcool : Loi du 22 décembre 2006 portant interdiction de la vente de boissons alcoolisées à des mineurs de moins de seize ans, Plan d’Action Luxembourgeois de réduction du Mésusage de l’Alcool (PALMA) 2020-2024 ; L’alimentation et l’activité physique : Plan Cadre National « Gesond Iessen, Mei Bewegen » (PCN GIMB) 2018-2025. D’autres facteurs de risques additionnels ont par ailleurs été identifiés et font l’objet d’une prise en charge spécifique (ex : exposition au radon, recommandations de prescriptions en imagerie médicale, exposition aux UV, vaccination contre le HPV et l’hépatite B, exposition professionnelle à des agents cancérigènes…). Le rôle et les actions de la Direction de la Médecine Préventive de la Direction de la Santé, et de la Fondation Cancer, sont rappelés, dans ce cadre. [less ▲]

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See detail“What's a normal weight?” – Origin and receiving country influences on weight-status assessment among 1.5 and 2nd generation immigrant adolescents in Europe
Kern, Matthias Robert UL; Heinz, Andreas UL; Stevens, Gonneke W.J.M. et al

in Social Science and Medicine (2020)

Many adolescents struggle with adequately assessing their weight-status, often leading to unnecessary weight-related interventions or preventing necessary ones. The prevalence of weight-status over- and ... [more ▼]

Many adolescents struggle with adequately assessing their weight-status, often leading to unnecessary weight-related interventions or preventing necessary ones. The prevalence of weight-status over- and underestimation differs considerably cross-nationally, suggesting that individual weight-status assessment is informed by cross-nationally differing standards of evaluation. For adolescents with a migration background, this brings up the possibility of a simultaneous influence of origin- and receiving country standards. The current study examines the magnitude of both influences using data from the 2014 Health Behaviour in School-Aged Children study. The cross-national design of the study enabled us to aggregate weight-evaluation standards for 41, primarily European, countries. Subsequently, we identified a sample of 8 124 adolescents with a migration background whose origin as well as receiving country participated in the study. Among those adolescents, we assessed the effects of origin and receiving country weight-evaluation standards using cross-classified multilevel regression analyses. Descriptive analyses revealed considerable differences in weight-evaluation standards between the countries. Regression analyses showed that both origin- and receiving country weight-evaluation standards were significantly associated cross-sectionally with weight-status assessment among the immigrant adolescents, with a stronger impact of receiving country standards. Results illustrate the context-sensitivity of adolescent weight-status assessment and reinforce the theoretical notion that immigrant adolescent development is not only informed by factors pertaining to their receiving country but also, albeit to a lesser extent, by those pertaining to their origin country. [less ▲]

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See detailPatterns of health related gender inequalities – a cluster analysis of 45 countries
Heinz, Andreas UL; Catunda, Carolina UL; van Duin, Claire UL et al

in Journal of Adolescent Health (2020), 66(6S), 29-39

Purpose: The paper explores gender inequalities between 45 countries across 10 health indicators among adolescents and whether those differences in health correlate with gender inequality in general ... [more ▼]

Purpose: The paper explores gender inequalities between 45 countries across 10 health indicators among adolescents and whether those differences in health correlate with gender inequality in general. Methods: Data from 71,942 students aged 15 years from 45 countries who participated in the 2018 Health Behaviour in School-aged Children survey were analyzed. For this purpose, 10 indicators were selected, representing a broad spectrum of health outcomes. The gender differences in the countries were first presented using odds ratios. Countries with similar risk profiles were grouped together using cluster analyses. For each of the 10 indicators, the correlation with the Gender Inequality Index was examined. Results: The cluster analysis reveals systematic gender inequalities, as the countries can be divided into seven distinct groups with similar gender inequality patterns. For eight of the 10 health indicators, there is a negative correlation with the Gender Inequality Index: the greater the gender equality in a country, the higher the odds that girls feel fat, have low support from families, have low life satisfaction, have multiple health complaints, smoke, drink alcohol, feel school pressure, and are overweight compared with boys. Four indicators show a divergence: the higher the gender equality in a country in general, the larger the differences between boys and girls regarding life satisfaction, school pressure, multiple health complaints, and feeling fat. Conclusions: Countries that are geographically and historically linked are similar in terms of the health risks for boys and girls. The results challenge the assumption that greater gender equality is always associated with greater health equality. [less ▲]

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