Pubertal development and screen time among South Korean adolescents: testing body mass index and psychological well-being as mediators
Bibliographic record
Abstract
BACKGROUND: This study tested links between pubertal development and screen time among South Korean adolescent boys and girls. METHODS: = 13.14 years). Body mass index (BMI) at Grade 8 (baseline), self-esteem and depression at Grade 9 were examined as mediators of the relationship between pubertal development and screen time after adjusting for household income and academic performance. Structural equation modeling was used to assess direct and indirect pathways between pubertal development at Grade 8 and screen time at Grade 9. RESULTS: No direct effect of pubertal development on screen time was found. But, an indirect effect existed for boys from pubertal development to screen time through BMI. Earlier pubertal development predicted higher BMI, and in turn, higher BMI predicted more time spent in screen time. Among girls, pubertal development negatively predicted BMI; however, no mediation effect of BMI between pubertal development and screen time was observed. No mediation effect of self-esteem or depression was found among boys or girls. CONCLUSIONS: Pubertal development appears to have an indirect influence on screen time through BMI for South Korean boys. More studies examining potential pathways between pubertal development and sedentary behavior are needed to build on these findings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".