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See detailProblematische Nutzung sozialer Medien von Kindern und Jugendlichen im Schulalter in Luxembourg – Ergebnisse der HBSC Umfrage 2018
Geraets, Anouk UL; van Duin, Claire UL; Catunda, Carolina UL et al

Report (2022)

Insbesondere unter Jugendlichen hat die Nutzung sozialer Medien in den letzten Jahren zugenommen. Wenn die Nutzung Merkmale einer Sucht aufweist (z.B. Gewöhnung und sozialer Rückzug), dann wird von einer ... [more ▼]

Insbesondere unter Jugendlichen hat die Nutzung sozialer Medien in den letzten Jahren zugenommen. Wenn die Nutzung Merkmale einer Sucht aufweist (z.B. Gewöhnung und sozialer Rückzug), dann wird von einer problematischen Nutzung sozialer Medien gesprochen – im Folgenden PSMU genannt. Dieser Kurzbericht gibt einen Überblick darüber, wie häufig PSMU unter luxemburgischen Schülern vorkommt und welche Merkmale mit einem höheren Risiko für PSMU einhergehen. Dazu wurden Daten der luxemburgischen Health Behavior in School-aged Children (HBSC)-Studie 2018 ausgewertet, an der 8 687 Jugendliche im Alter von 11 bis 18 Jahren teilnahmen. Laut dieser Umfrage liegt die Häufigkeit von PSMU in dieser Altersgruppe bei 5,9 %. Eine Reihe von Merkmalen aus den Bereichen Soziodemografie, soziale Unterstützung, Wohlbefinden und Mediennutzung wurden als potenzielle Risikofaktoren untersucht. PSMU tritt häufiger bei Mädchen und jüngeren Schülern sowie bei Schülern mit Migrationshintergrund auf. Bei Schülern, die bei beiden Elternteilen aufwachsen, ist PSMU seltener im Vergleich zu Schülern, die bei Alleinerziehenden oder in anderen Familienkonstellationen aufwachsen. Ein Vergleich der Risikofaktoren hat ergeben, dass das Alter, Cybermobbing, Stress, psychosomatische Beschwerden, eine Vorliebe für Online-Interaktion und die Intensität der Kommunikation über elektronische Medien die wichtigsten Risikofaktoren sind. Das Risiko für einen problematischen Umgang mit sozialen Medien ist somit höher bei jüngeren Schülern; Schülern, die andere online mobben; gestressten Schülern; Schülern mit häufigen psychosomatischen Beschwerden; Schülern, die Online-Kommunikation gegenüber einer Kommunikation in der realen Welt vorziehen sowie Schülern, die elektronische Medien generell häufig nutzen. Speziell zur Prävention von PSMU haben sich noch keine Maßnahmen etabliert, aber es gibt gut erforschte Maßnahmen zur Prävention von Internetsucht, die sich in abgewandelter Form möglicherweise auch bei PSMU eignen. [less ▲]

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See detailDie Bedeutung der Schule für Gesundheit und Wohlbe- finden von Schülerinnen und Schülern: Ergebnisse der HBSC Surveys 2018 in Luxemburg
van Duin, Claire UL; Heinz, Andreas UL; Willems, Helmut Erich UL

Scientific Conference (2022, March 10)

Neben der Familie ist die Schule für Kinder und Jugendliche ein wichtiges Umfeld. Hier verbringen sie einen großen Teil des Tages, hier treffen sie ihre Freunde, und ihre schulischen Leistungen bestimmen ... [more ▼]

Neben der Familie ist die Schule für Kinder und Jugendliche ein wichtiges Umfeld. Hier verbringen sie einen großen Teil des Tages, hier treffen sie ihre Freunde, und ihre schulischen Leistungen bestimmen wesentlich mit, welchen beruflichen Weg sie später einschlagen können. Dementsprechend hat die Schule als sozialer Kontext einen großen Einfluss auch auf das Wohlbefinden und gesundheitliche Befindlichkeiten der Schüler. Positive schulische Erfahrungen können eine Ressource für Wohlbefinden sein, negative Erfahrungen können die psychische und physische Gesundheit beeinträchtigen. Da es sich bei HBSC um eine Befragung handelt, die in der Schule durchgeführt wird und da die Schule ein wichtiges soziales Umfeld ist, werden auch mehrere Fragen zur Schule gestellt. Im Vortrag werden zunächst aktuelle Ergebnisse aus Luxemburg zum schulischen Kontext präsentiert und international eingeordnet. So wird schon seit mehreren Befragungen erhoben, ob die Schüler die Schule mögen, ob sie sich durch die Schularbeit gestresst fühlen und wie sie die Beziehungen zu ihren Klassenkameraden und den Lehrern bewerten und ob sie viel auf der Ebene der Klasse und der Schule mitbestimmen können. In einem zweiten Schritt wird mit Hilfe einer Clusteranalyse untersucht, ob es typische Konstellationen gibt, d. h. Gruppen von Schülern, die sich in ihren Schulerfahrungen möglichst stark ähneln. Aus der HBSC-Studie ist bekannt, dass es zahlreiche Zusammenhänge zwischen diesen Erfahrungen gibt. Wenn solche kohärenten Gruppen identifiziert werden können, dann kann eine darauf basierende Typologie helfen, die komplexen Zusammenhänge zwischen zahlreichen Variablen in komprimierter Form darzustellen. Im konkreten Fall wurden 4 schulbezogene Einstellungen und Bewertungen dazu genutzt, um solche Gruppen zu identifizieren. Diese Gruppen/Cluster werden zunächst anhand der Variablen beschrieben, die zur Gruppenbildung genutzt wurden. Die Analyse zeigt, dass es bezüglich der Schulerfahrungen fünf in sich homogene Cluster gibt. Cluster 1, in dem sich der größte Anteil der Schüler (28.8%) befindet, ist durch allgemein positive Schulerfahrungen gekennzeichnet. Die Schüler in dieser Gruppe mögen die Schule, sie berichten von einem guten Klassenklima und sie geben an, kaum durch die Schularbeit gestresst zu sein. Darüber hinaus berichten diese Schüler über ein gutes Verhältnis zu ihren Lehrern. Cluster 2 ist durch Schüler gekennzeichnet, deren Schulerfahrungen überwiegend positiv sind (sie mögen die Schule und sie haben ein gutes Verhältnis zu den Mitschülern und Lehrern), die sich aber durch die Schularbeit gestresst fühlen, was sich negativ auf ihr allgemeines Wohlbefinden auswirkt. Cluster 3 zeichnet sich durch Schüler aus, die über ein geringes Maß an Stress berichten und insgesamt durchschnittliche Werte für die schulbezogenen Variablen wie Beziehungen zu ihrem Lehrer und das Klassenklima aufweisen. In Cluster 4 befinden sich die Schüler, die viel Schulstress erfahren, relativ schlechte Beziehungen zu ihren Lehrern haben und die Schule im Allgemeinen nicht mögen. Allerdings berichten diese Schüler von einem guten Klassenklima. Dieses Cluster umfasst 14.7% der Schüler und ist damit das kleinste Cluster. Cluster 5 besteht aus Schülern mit durchweg negativen Schulerfahrungen und ist damit das Gegenteil von Cluster 1. Die Schüler in Cluster 5 haben viel Schulstress, sind nicht gerne in der Schule und berichten von schlechteren Beziehungen zu ihren Lehrern und Mitschülern im Vergleich zu den Schülern in den anderen Clustern. Die weitere Beschreibung der Cluster mit Hilfe von soziodemografischen Variablen, anderen schulbezogenen Variablen und gesundheitsbezogenen Ergebnisvariablen wird zeigen, dass die gefundenen Gruppen in sich kohärent sind bezüglich der schulbezogenen Variablen, und dass sie zudem mit gesundheitsbezogenen und mit soziodemografischen Variablen korrelieren. [less ▲]

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See detailTypes of health-related behaviours: a cluster analysis of the Luxembourgish HBSC data
Heinz, Andreas UL; Willems, Helmut Erich UL; van Duin, Claire UL et al

Scientific Conference (2021, June)

Background: Although it is known that health behaviours, socio-demographic variables and outcomes correlate, it is rarely investigated if there are typical patterns of these variables among the research ... [more ▼]

Background: Although it is known that health behaviours, socio-demographic variables and outcomes correlate, it is rarely investigated if there are typical patterns of these variables among the research subjects. Objectives: To find out whether the students can be divided into distinct groups based on their health behaviour and whether these groups differ in other ways (outcomes and socio-demographics). Method: In step 1, a hierarchical cluster analysis was carried out to determine the number of groups and to identify the cluster centres. In step 2, this information was entered as the initial values of a cluster centre analysis. In step 3, the clusters were characterised using additional variables. Results: The 8065 students surveyed could be divided into 5 distinct groups based on their data on smoking, drinking, soft drinks, exercising, fighting and bullying, with cluster 1 and cluster 5 representing the strongest contrast. Cluster 1 comprises students whose health behaviour is generally positive. It is the largest cluster with 49.5% of students. Cluster 5 comprises students whose behaviour is consistently negative. It is the smallest cluster with 7.1% of students. Students in cluster 2 are close to average on many variables, but their dental health is problematic because they frequently consume soft drinks and rarely brush their teeth. Students in cluster 3 are physically inactive, their mental health is poor, but they are also rarely injured. The students in cluster 4 stand out because of their aggressive behaviour. Conclusion: With the help of cluster analysis, it is possible to categorise the students into a small number of groups based on their health behaviour. These groups are coherent in terms of health behaviour, many outcome variables and socio-demographic variables. [less ▲]

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See detailGesundheit von Schülerinnen und Schülern in Luxemburg - Bericht zur luxemburgischen HBSC-Befragung 2018
Heinz, Andreas UL; Kern, Matthias Robert; van Duin, Claire UL et al

Report (2021)

Der Bericht gibt Auskunft über Gesundheit und Wohlbefinden der Schüler im Jahr 2018 in ihrem sozialen Kontext. Darüber hinaus informiert er, wie sich die entsprechenden Indikatoren von 2006—2018 in ... [more ▼]

Der Bericht gibt Auskunft über Gesundheit und Wohlbefinden der Schüler im Jahr 2018 in ihrem sozialen Kontext. Darüber hinaus informiert er, wie sich die entsprechenden Indikatoren von 2006—2018 in Luxemburg entwickelt haben. Verbesserungen gab es vor allem beim Gesundheitsverhalten — die Schüler rauchen und trinken weniger, sie putzen sich häufiger die Zähne und essen mehr Obst und Gemüse. Verschlechterungen betreffen die mentale Gesundheit: Die Schüler haben häufiger psychosomatische Beschwerden und sie fühlen sich häufiger von der Schularbeit gestresst. Des Weiteren sind die Schüler häufiger übergewichtig und sie sind seltener körperlich aktiv. Der Bericht zeigt auch, dass Gesundheitsrisiken mit soziodemografischen Merkmalen zusammenhängen, wie u. a. dem Geschlecht, dem Alter, dem Wohlstand und dem Migrationshintergrund. So verhalten sich Mädchen zwar häufig gesundheitsbewusster als Jungen, aber dennoch schätzen sie ihren Gesundheitszustand schlechter ein und sie haben mehr Stress und sie sind häufiger von multiplen psychosomatischen Beschwerden betroffen. Aus Clusteranalysen geht hervor, dass es typische Konstellationen von Gesundheitsverhaltensweisen gibt, die zudem mit soziodemografischen Merkmalen sowie Übergewicht, Stress und der Lebenszufriedenheit zusammenhängen. [less ▲]

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See detailPredictors of Problematic Social Media Use in a Nationally Representative Sample of Adolescents in Luxembourg
van Duin, Claire UL; Heinz, Andreas UL; Willems, Helmut Erich UL

in International Journal of Environmental Research and Public Health (2021), 18(22),

Social media use has increased substantially over the past decades, especially among adolescents. A proportion of adolescents develop a pattern of problematic social media use (PSMU). Predictors of PSMU ... [more ▼]

Social media use has increased substantially over the past decades, especially among adolescents. A proportion of adolescents develop a pattern of problematic social media use (PSMU). Predictors of PSMU are insufficiently understood and researched. This study aims to investigate predictors of PSMU in a nationally representative sample of adolescents in Luxembourg. Data from the Health Behavior in School-aged Children (HBSC) study in Luxembourg were used, in which 8687 students aged 11–18 years old participated. The data were analyzed using hierarchical multiple regression. A range of sociodemographic, social support, well-being and media use predictors were added to the model in four blocks. The predictors in the final model explained 22.3% of the variance in PSMU. The block of sociodemographic predictors explained the lowest proportion of variance in PSMU compared with the other blocks. Age negatively predicted PSMU. Of the predictors related to social support, cyberbullying perpetration was the strongest predictor of PSMU. Perceived stress and psychosomatic complaints positively predicted PSMU. The intensity of electronic media communication and preference for online social interaction were stronger predictors of PSMU than the other predictors in the model. The results indicate that prevention efforts need to consider the diverse range of predictors related to PSMU. [less ▲]

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See detailWhat is problematic about binary questions on gender in health surveys – a missing answer analysis
Heinz, Andreas UL; Költő, András; Godeau, Emmanuelle et al

in Cogent Medicine (2020, December 04)

Background: In many studies, participants who do not state their gender are excluded from the analysis. This may be appropriate if they do not answer the questionnaire seriously. However, some ... [more ▼]

Background: In many studies, participants who do not state their gender are excluded from the analysis. This may be appropriate if they do not answer the questionnaire seriously. However, some participants may have understandable reasons for not reporting their gender, e.g. questioning their gender identity. Research question: How many students and which students do not answer the question on gender? Methods: We analyzed data of the Health Behaviour in School-aged Children study from Ireland, France, Hungary, Scotland, Belgium (Flemish) and Luxembourg (n = 40,053). To explore the reasons for non-response, we divided the participants into 3 groups: 1. Responders answered both socio- demographic questions (age and gender) 2. age non-responders did not answer the question on age. 3. Gender non-responders answered the question on age, but not the one on gender. Results: 311 out of 40,053 (0.8%) pupils aged 11–18 did not report their gender. About 40% of them did not answer the age question either. However, the other 60% belong to the group of gender non-responders and this group is disadvantaged compared to responders: they report lower self-rated health, more health complaints, less family support and more substance use (alcohol, tobacco, cannabis). 1.9% of pupils did not answer the question about age. These age non-responders answered the questionnaire more selectively overall and skipped more questions. Conclusion: The data suggest that the reasons for age non-response and gender non-response are different. For age non-responders, the fear of de-anonymization seems to be the reason for not indicating their age. Not answering the question on gender is rare. If the participants answered the question on age, but not the question on gender, then the variable gender is missing not at random. The health problems of gender non-responders correspond to the health problems of gender non-conforming adolescents. Thus, the question arises if the group of gender non-responders should be included in the analysis and if the question on gender should be asked differently in the future [less ▲]

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See detailScanning of questionnaires as a tool to identify difficult questions - lessons learned
Heinz, Andreas UL; van Duin, Claire UL; Catunda, Carolina UL et al

Scientific Conference (2020, November 10)

Background: In 2018, the Luxembourg HBSC team scanned the questionnaires to make the data available faster and to avoid entry errors. Scanning has been shown to be suitable for identifying difficult ... [more ▼]

Background: In 2018, the Luxembourg HBSC team scanned the questionnaires to make the data available faster and to avoid entry errors. Scanning has been shown to be suitable for identifying difficult questions. Objective: The presentation shows which questions were difficult to answer and what the difficulty was. Method: The questionnaires were scanned by student assistants and the data was validated by them if the scanning programme did not detect any errors. If errors occurred (e.g. missing answers or multiple answers), then these questionnaires were checked by HBSC team members. This gave us a systematic overview of which questions were difficult to answer. Results 1. The data from 10000 questionnaires were entered in 6 weeks (half the time needed compared to manual entry in 2014). 2. The MVPA question was frequently the subject of multiple answers. This may indicate that these students use the answer scale as a counting aid. 3. Students who state that they have never smoked in their lives often skip the question about tobacco use in the last month. This behaviour can be explained by Grice's conversational maxims. 4. Behaviours indicating that the answers are not serious (crossed-out questions, crosses outside the boxes, fun answers to open questions) are rare. Conclusions: Scanning is an efficient way to enter many questionnaires in a short time and high quality. Furthermore, it can help to discover difficult questions and to find out what the difficulty is. [less ▲]

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See detailTrends from 2006-2018 in Health, Health Behaviour, Health Outcomes and Social Context of Adolescents in Luxembourg
Heinz, Andreas UL; van Duin, Claire UL; Kern, Matthias Robert UL et al

Report (2020)

This report shows how 30 health indicators developed in the four Luxembourg HBSC surveys conducted in 2006, 2010, 2014 and 2018. There were positive trends especially in the health behaviour of the pupils ... [more ▼]

This report shows how 30 health indicators developed in the four Luxembourg HBSC surveys conducted in 2006, 2010, 2014 and 2018. There were positive trends especially in the health behaviour of the pupils: they smoke less and drink less alcohol. They also report more frequently that they brush their teeth regularly, eat more fruit and fewer sweets and consume fewer soft drinks. From 2006-2018, however, there were also deteriorations. For example, more pupils feel stressed from school and rate the climate among classmates worse. In addition, there are more pupils who are overweight and exercise less and more pupils report having psychosomatic health complaints. [less ▲]

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See detailSuicidal Behaviour in Youth in Luxembourg - Findings from the HBSC 2014 Luxembourg Study
Catunda, Carolina UL; van Duin, Claire UL; Heinz, Andreas UL et al

Report (2020)

Suicide is one of the leading causes of death among young people worldwide. In order to prevent suicides, early identification of groups at risk is needed. In the Luxembourgish HBSC study, data on ... [more ▼]

Suicide is one of the leading causes of death among young people worldwide. In order to prevent suicides, early identification of groups at risk is needed. In the Luxembourgish HBSC study, data on suicidal behaviours among adolescents were collected in 2006, 2010 and 2014. These can be used to identify suicide risk factors and to develop comprehensive suicide prevention programs. In Luxembourg, the suicide rate has fluctuated around 15 deaths per 100 000 inhabitants per year, for more than ten years. In the period 2006 – 2016, 20 deaths were registered as suicide in the age group of 10 to 19-year-olds. These suicides represent approximately 19% of all deaths registered in this age group. In the Luxembourgish HBSC study conducted in 2014, 875 adolescents indicated to have contemplated suicide in the last 12 months, which amounts to 15.1% of the adolescents in the study. In the same year, 811 adolescents (14.0%) indicated to have made a suicide plan in the last 12 months, and 448 adolescents (7.7%) to have attempted suicide (at least once) in the last year. In first instance, bivariate logistic regressions analyses were conducted for 24 independent variables with three suicidal behaviours (contemplation of suicide, planning of suicide and suicide attempt) and sadness as dependent variables in order to identify potential risk factors. These risk factors were further tested in multivariate logistic regressions, in order to make a statement about the relevance of these factors for suicidal behaviour of adolescents in Luxembourg, while taking into account the dependence between the risk factors. Results from multivariate logistic regressions indicate that subjective health complaints are the most important risk factor for suicidal behaviour. Adolescents who have recurrent multiple health complaints are at higher risk for suicidal behaviour than adolescents who do not have health complaints. Life satisfaction is the second most important risk factor for suicidal behaviour. Adolescents with lower levels of life satisfaction are at higher risk for suicidal behaviour than adolescents who have higher levels of life satisfaction. Gender-specific analyses show that the risk factors differ between girls and boys for suicidal behaviour. [less ▲]

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See detailSuicide Prevention: Using the Number of Health Complaints as an Indirect Alternative for Screening Suicidal Adolescents
Heinz, Andreas UL; Catunda, Carolina UL; van Duin, Claire UL et al

in Journal of Affective Disorders (2020), 260

Background: Suicide is the second leading cause of death in adolescents. Screening for persons at risk usually includes asking about suicidal ideation, which is considered inappropriate in some societies ... [more ▼]

Background: Suicide is the second leading cause of death in adolescents. Screening for persons at risk usually includes asking about suicidal ideation, which is considered inappropriate in some societies and situations. To avoid directly addressing suicide, this paper investigates whether the Health Behaviour in School-aged Children Symptom Checklist (HBSC-SCL), a validated non-clinical measure of eight subjective health complaints (e.g. headache, feeling low), could be used as a tool for screening suicidal ideation and behavior in adolescents. Methods: 5262 secondary school students aged 12-18 answered the Luxembourgish HBSC 2014 survey, including the HBSC-SCL items and suicidal ideation and behavior questions. Results: Each HBSC-SCL item correlates with suicidal ideation and behavior. A sum score was calculated ranging from zero to eight health complaints to predict respondents who considered suicide (area under the ROC curve = .770). The ideal cut-off for screening students who consider suicide is three or more health complaints: sensitivity is 66.3%, specificity is 75.9% and positive predictive value is 32.9%. Limitations: One limitation is HBSC-SCL's low positive predictive value. This is a general problem of screening rare events: the lower the prevalence, the lower the positive predictive value. Sensitivity and specificity could be improved by taking age-, gender- and country-specific cut-off values, but such refinements would make the score calculation more complicated. Conclusions: The HBSC-SCL is short, easy to use, with satisfactory screening properties. The checklist can be used when suicide cannot be addressed directly, and also in a more general context, e.g. by school nurses when screening adolescents. [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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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 detailCommunication with father and mother differently impacts suicidal behaviour
Catunda, Carolina UL; van Duin, Claire UL; Heinz, Andreas UL et al

Poster (2019, September)

Background: Positive relationships with parents can reduce the risk of suicidal behaviour in adolescents. Previous research has indicated that adolescents who report poor communication with their parents ... [more ▼]

Background: Positive relationships with parents can reduce the risk of suicidal behaviour in adolescents. Previous research has indicated that adolescents who report poor communication with their parents are more likely to display suicidal behaviour. The aim of this study is to find out whether communication with the father or mother is equally important for suicidal behaviour. Methods: A total of 5595 students aged from 12 to 18 years old in secondary school participated in the 2014 HBSC Luxembourg survey. They responded to a questionnaire including, among others: 4 questions regarding sadness, suicide ideation, planning and attempt, and 2 questions about ease of communication with their father and mother. Findings: Adolescents who indicate poorer communication with their mother or father have higher odds for all suicidal behaviours. Poor communication with fathers has a bigger influence on the odds for sadness, whereas poor communication with mothers has a bigger influence on the odds for attempted suicide. Lastly, adolescents who don`t have or don`t see their mother or father are at increased risk for the suicidal behaviours, although the odds are not as high as for those indicating very difficult communication with their parent(s). Discussion: The Luxembourgish findings confirm the results of previous research and go further showing that, as a determinant, communication with mother differs from the communication with father. More studies should confirm these findings and include other variables, such as social support and stress, in order to see their relation with the communication with both parental figures and suicidal behaviours. [less ▲]

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See detailTrends in cannabis consumption among youth in Luxembourg
Catunda, Carolina UL; van Duin, Claire UL; Heinz, Andreas UL et al

Scientific Conference (2019, September)

Background: Cannabis is the most widely consumed illegal drug worldwide. Among adolescents, cannabis use is a risk factor for cognitive decline, mental illness, social problems, and the use of other ... [more ▼]

Background: Cannabis is the most widely consumed illegal drug worldwide. Among adolescents, cannabis use is a risk factor for cognitive decline, mental illness, social problems, and the use of other psychoactive drugs. The current study presents trends in cannabis consumption among adolescents in Luxembourg. Methods: The Health Behaviour in School Aged Children (HBSC) Study in Luxembourg collected data in 2006, 2010, 2014 and 2018 using a standardized paper-pencil questionnaire. In total, 23,346 secondary schools students aged 11 to 18 years old (M=15.51, SD=1.53) responded to questions on cannabis, tobacco and alcohol consumption (lifetime and the past 30 days). Findings: In general, students who never used cannabis significantly increased over the four HBSC study waves (78%, 81.2%, 81%, 84%), whereas trends are similar for boys (74.5%, 77%, 78.2%, 81.4%), but not for girls (81.5%, 85%, 83.2%, 86.3%). Cannabis use (past 30 days) significantly differ for girls (94.1%, 94.1%, 92.8%, 93.7%), but not in general (91.7%, 92%, 90.9%, 91.7%), neither for boys (89.3%, 90.1%, 88.6%, 89.6%). Discussion: Cannabis lifetime use remains high for both genders. While consumption in the last 30 days remained stable for boys, it increased for girls over the past years. Tailored preventive interventions, based on health psychological models, are essential to educate adolescents about the social-cognitive risks of cannabis use and strengthen their capacities and resilience to resist experimental drug use and social pressure. In a context where legalization policies are discussed in various European countries, e-health approaches, for example, could be widely implemented in a cost-effective manner. [less ▲]

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See detail"Are you a boy or girl?" Who are the non-responders
Heinz, Andreas UL; Catunda, Carolina UL; van Duin, Claire UL et al

Scientific Conference (2019, June 20)

Background: In many studies, participants who do not state their gender are excluded from the analysis. This may be appropriate if they do not answer the questionnaire seriously. However, some ... [more ▼]

Background: In many studies, participants who do not state their gender are excluded from the analysis. This may be appropriate if they do not answer the questionnaire seriously. However, some participants may have understandable reasons for not reporting their gender, e.g. questioning their gender identity. Objective: How many students and which students do not answer the question on gender? Methods: HBSC 2018 raw data from Ireland, Luxembourg, Belgium and France are compared. To explore the reasons for non-response, we divided the participants into 3 groups: 1. Responders answered both sociodemographic questions (age and gender) 2. age non-responders did not answer the question on age. 3. Gender non-responders answered the question on age, but not the one on gender. Results: Between 0.8% (Ireland) and 1.2% (Luxembourg) of participants did not report their gender. About half of them did not answer the age question either. However, the other half belong to the group of gender non-responders and this group is disadvantaged compared to responders: they report lower life satisfaction, lower self-rated health, more health complaints, less peer support and their WHO-5 Well-being score is lower. Not answering the question on gender is rare. If the participants answered the question on age, but not the question on gender, then the variable gender is missing not at random. Implication: The question arises whether the group of gender non-responders should be included in the analysis and whether the question on gender should be asked differently in the future. [less ▲]

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See detailIs Life Satisfaction Contagious?
Catunda, Carolina UL; Heinz, Andreas UL; van Duin, Claire UL et al

Scientific Conference (2019, June)

Background: Life satisfaction (LS) is a major component of adolescents’ subjective well-being, facilitating adaptive development and influencing health. Literature shows that social support influences ... [more ▼]

Background: Life satisfaction (LS) is a major component of adolescents’ subjective well-being, facilitating adaptive development and influencing health. Literature shows that social support influences adolescents LS. In addition, the social network can affect health-related behaviors of adults - individuals that smoke or exercise tend to group together. However, the effects of others` LS on adolescents’ individual evaluation of LS (the contagion hypothesis) is still to be addressed. Objective(s): To test the contagion hypothesis of adolescents’ life satisfaction (how LS of proxies influences the individual LS appraisal). Method: Data is from 9738 students (aged 9-20) from the 2018 HBSC Luxembourg survey. A multilevel analysis was used to evaluate LS, with the school classes as subjects (model 1) to estimate the influence of being in a certain school class. Later, FAS, age and gender were entered as control variables (model 2). Results: The grand mean (intercept) for LS in model 1 was 7.57 (SE=.03, p<.001). For model 2, FAS (b=.47, SE=.03, p<.001), age (b=-.14, SE=.01, p<.001) and gender (b=-.23, SE=.04, p<.001) were significantly predictive of LS. The grand mean for LS, conditioned on the presence of FAS, age and gender, was 9.02 (SE=.05, p<.001). Interclass Correlation Coefficient decreased from model 1 (ICC=.08) to model 2 (ICC=.04). Conclusions: Results suggest that part of the variance of LS can be explained by the school class level. In other words, school class clusters have an influence on their LS, indicating that the LS of adolescents from a class partially accounts for individual LS. [less ▲]

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See detailUsing data from the HBSC study for evidence-based suicide prevention in Luxembourg
van Duin, Claire UL; Heinz, Andreas UL; Catunda, Carolina UL et al

in European Journal of Public Health (2019), 29

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See detailNorms in and between the philosophical ivory tower and public health practice: A heuristic model of translational ethics
Schröder-Bäck, Peter; van Duin, Claire UL; Brall, Caroline et al

in South Eastern European Journal of Public Health (2019)

Detailed reference viewed: 122 (4 UL)