Intersectional identity, risk behaviors, and adolescent mental health in South Korea: who suffers the most in the loneliness epidemic?
Bibliographic record
Abstract
Purpose: Intersectionality is a theoretical framework that allows researchers to examine how multiple, overlapping social identities such as gender and socioeconomic status (SES) interact to shape individuals' experiences and contribute to inequalities. This study examined the associations between intersectional identity and mental health among South Korean adolescents and whether risk behaviors modify these associations. Methods: The 2023 Korea Youth Behavior Web-Based Survey (n=52,880; 12-18 years) was used. Gender and family SES served as intersectional identities. Outcome included stress, depression, and loneliness. Alcohol, tobacco, and smartphone use were considered as potential effect modifiers. Decision tree models, logistic regressions, and moderation analyses were performed. Results: Overall, girls reported poorer mental health than boys. When SES was considered, gender X SES was associated with loneliness only, and not with stress or depression. Among boys, the odds of reporting loneliness were higher with lower SES, and this association was further compounded by alcohol or tobacco use within each SES level. Girls reported higher odds of loneliness across all SES levels compared to boys, with low-SES girls experiencing the greatest burden. Alcohol and tobacco use further exacerbated the associations between intersectional identity and loneliness across all groups, particularly in girls. Smartphone use did not modify these associations. Conclusions: Interventions targeting alcohol and tobacco use may be important to prevent loneliness for adolescents with intersectional identities. Loneliness may be shaped by both structural and behavioral factors, supporting the intersectionality as a useful analytical framework to better understand mental health disparities among adolescents.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".