Dataset Information

Problematic Social-Networks-Use in German Children and Adolescents-The Interaction of Need to Belong, Online Self-Regulative Competences, and Age.

ABSTRACT: Adolescents nowadays spend much time communicating via social networks. Recent investigations also report a noticeable proportion showing a problematic usage behavior, underlining the importance of better understanding its development and maintenance in young individuals. Theoretical views on Internet-use disorders assume that specific predispositions and needs can contribute to addictive behaviors in interaction with further aspects including Internet-related cognitive biases. This study focuses on vulnerable individuals due to their age and investigates interactions between possible risk (need to belong, NTB) and protective factors (online self-regulative competences, OSRC). Participants (N = 466) between 10 and 17 years answered questionnaires assessing social-networks-use disorder symptoms, NTB, and OSRC. Moderated regression analysis revealed significant effects of age, NTB, and OSRC. Three-way interaction was also significant (potentially mainly caused by females), with highest social-networks-use disorder symptoms found for individuals with high NTB and low OSRC, especially when older. With high OSRC, symptoms were significantly lower for both younger and older individuals having high NTB. However, even if NTB was low, older individuals showed high social-networks-use disorder symptoms if their OSRC were low. The results highlight the importance of improving specific competences to prevent problematic usage behaviors, which should be considered in youth-tailored prevention and intervention programs.

SUBMITTER: Ostendorf S

PROVIDER: S-EPMC7177510 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Problematic Social-Networks-Use in German Children and Adolescents-The Interaction of Need to Belong, Online Self-Regulative Competences, and Age.

Ostendorf Sina S Wegmann Elisa E Brand Matthias M

International journal of environmental research and public health 20200407 7

Adolescents nowadays spend much time communicating via social networks. Recent investigations also report a noticeable proportion showing a problematic usage behavior, underlining the importance of better understanding its development and maintenance in young individuals. Theoretical views on Internet-use disorders assume that specific predispositions and needs can contribute to addictive behaviors in interaction with further aspects including Internet-related cognitive biases. This study focuse ...[more]

PMID: 32272612

Similar Datasets

Project description:BackgroundAlcohol expectancies are beliefs regarding positive (e.g., tension reduction) or negative (e.g., loss of motor coordination) effects of alcohol. Based on Social Learning Theory, social media can influence alcohol expectancies in adolescents. In particular, problematic social media use - which can reflect elements of addiction, including mood modification, tolerance, withdrawal, conflict, and relapse - could be linked to alcohol expectancies. We aimed to determine the associations between problematic social media use and alcohol expectancies in a national (U.S.) cohort of 10-14-year-old early adolescents.MethodsWe analyzed cross-sectional data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 9,008) at the Year 2 assessment (2018-2020). Unadjusted and adjusted linear regression analyses were conducted to examine the associations between problematic social media use and alcohol expectancies (positive and negative), adjusting for race/ethnicity, sex, household income, parent education, sexual orientation, parental marital status, and study site. Furthermore, we computed marginal predicted probabilities to aid in interpreting findings.ResultsThe sample was 48.7% female and racially and ethnically diverse (43.0% non-White), with a mean age of 12.02 ± 0.66 years old. In models adjusted for confounders including both time spent on social media and problematic social media use, time spent on social media was not associated with positive or negative alcohol expectancies, but higher problematic social media use score was associated with higher positive (B = 0.045, 95% confidence interval [CI] 0.020-0.069) and negative (B = 0.072, 95% CI 0.043-0.101) alcohol expectancies scores.ConclusionProblematic social media use was associated with both positive and negative alcohol expectancies in a demographically diverse national sample of early adolescents in the U.S. Given the small effect sizes of the current study, future studies should further examine these relationships prospectively, as well as the mechanisms linking problematic social media use to alcohol expectancies and alcohol consumption. Because alcohol expectancies are modifiable and linked with alcohol initiation, they could be a target for future prevention efforts.

Project description:BACKGROUND:While online health social networks (OHSNs) serve as an effective platform for patients to fulfill their various social support needs, predicting the needs of users and providing tailored information remains a challenge. OBJECTIVE:The objective of this study was to discriminate important features for identifying users' social support needs based on knowledge gathered from survey data. This study also provides guidelines for a technical framework, which can be used to predict users' social support needs based on raw data collected from OHSNs. METHODS:We initially conducted a Web-based survey with 184 OHSN users. From this survey data, we extracted 34 features based on 5 categories: (1) demographics, (2) reading behavior, (3) posting behavior, (4) perceived roles in OHSNs, and (5) values sought in OHSNs. Features from the first 4 categories were used as variables for binary classification. For the prediction outcomes, we used features from the last category: the needs for emotional support, experience-based information, unconventional information, and medical facts. We compared 5 binary classifier algorithms: gradient boosting tree, random forest, decision tree, support vector machines, and logistic regression. We then calculated the scores of the area under the receiver operating characteristic (ROC) curve (AUC) to understand the comparative effectiveness of the used features. RESULTS:The best performance was AUC scores of 0.89 for predicting users seeking emotional support, 0.86 for experience-based information, 0.80 for unconventional information, and 0.83 for medical facts. With the gradient boosting tree as our best performing model, we analyzed the strength of individual features in predicting one's social support need. Among other discoveries, we found that users seeking emotional support tend to post more in OHSNs compared with others. CONCLUSIONS:We developed an initial framework for automatically predicting social support needs in OHSNs using survey data. Future work should involve nonsurvey data to evaluate the feasibility of the framework. Our study contributes to providing personalized social support in OHSNs.

Dataset Information

Problematic Social-Networks-Use in German Children and Adolescents-The Interaction of Need to Belong, Online Self-Regulative Competences, and Age.

Publications

Problematic Social-Networks-Use in German Children and Adolescents-The Interaction of Need to Belong, Online Self-Regulative Competences, and Age.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets