Predictors of Problematic Social Media Use in a Nationally Representative Sample of Adolescents in Luxembourg.

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.

Patterns of Health-Related Gender Inequalities-A Cluster Analysis of 45 Countries.

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.

Suicide prevention: Using the number of health complaints as an indirect alternative for screening suicidal adolescents.

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 = 0.770). 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.