Cross-national evidence for the clustering and psychosocial correlates of adolescent risk behaviours in 27 countries
Bibliographic record
Abstract
BACKGROUND: According to Jessor's Problem Behaviour Theory (PBT) and Moffitt's theory of adolescence-limited antisocial behaviour, adolescent risk behaviours cluster and can be predicted by various psychosocial factors including parent, peer and school attachment. This study tested the potential influence of the sociocultural, or macro-level, environment on the clustering and correlates of adolescent risk behaviour across 27 European and North American countries. METHODS: Analyses were based on data from the 2009-10 Health Behaviour in School-aged Children (HBSC) study. Participants compromised 56,090 adolescents (M(age) = 15.5 years) who self-reported on substance use (tobacco, alcohol, cannabis) and early sexual activity as well as on psychosocial factors (parent, peer and school attachment). RESULTS: Multiple group confirmatory factor analyses (with country as grouping variable) showed that substance use and early sexual activity loaded on a single underlying factor across countries. In addition, multiple group path analyses (with country as grouping variable) showed that associations between this factor and parent, peer and school attachment were identical across countries. CONCLUSION: Cross-national consistencies exist in the clustering and psychosocial correlates of substance use and early sexual activity across western countries. While Jessor's PBT stresses the problematic aspects of adolescent risk behaviours, Moffitt emphasizes their normative character. Although the problematic nature of risk behaviours overall receives more attention in the literature, it is important to consider both perspectives to fully understand why they cluster and correlate with psychosocial factors. This is essential for the development and implementation of prevention programmes aimed at reducing adolescent risk behaviours across Europe and North America.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".