Associations between different types of sedentary behavior and mental health: Gender-stratified analyses among 97,171 South Korean adolescents
Bibliographic record
Abstract
Background Sedentary behavior (SB) is known to be detrimental to the overall health of adolescents. However, it is less understood if mental health outcomes differ by different types of SB. The objective of this study was to examine the association between different types of SB and mental health outcomes among South Korean adolescents. Methods Self-reported, nation-wide, cross-sectional data from 2018 to 2019 Korea Web-based Youth Risk Behavior Surveys (N = 122,923) were used. Different types of SB were categorized into quartiles. Mental health outcomes were dichotomized (yes/no). Multivariate logistic regressions were performed after adjusting for relevant covariates. Results Of 97,171 (age:12–18yrs; girls:49.4%) eligible adolescents, the overall prevalence of sadness/hopelessness, suicidal thoughts, and suicide plan/attempt were 26.8%, 12.6%, and 4·9%, respectively. Overall, prolonged total and non-academic SB (4th quartile) were associated with sadness/hopelessness and suicidal thoughts for both genders and suicidal plan/attempt for girls only. Academic SB was not associated with any of the mental health outcomes. Prolonged Internet use (4th quartile) was also associated with sadness/hopelessness (OR:1.26, 95%CI:1.19–1.34), suicidal thoughts (OR:1.42, 95%CI:1.32–1.53), and suicidal plan/attempt (OR:1.26, 95%CI:1.13–1.40) among girls, but only with suicidal thoughts (OR:1.24, 95%CI:1.13–1.36) among boys. In contrast, the 2nd and 3rd quartiles of Internet use were inversely associated with sadness/hopelessness (OR:0.91, 95%CI:0.85–0.97, 3rd quartile) and suicidal plan/attempt (OR:0.69, 95%CI:0.59–0.80, 3rd quartile) among boys. Conclusions Prolonged total and non-academic SB are detrimental to mental health outcomes among Korean adolescents. More consistent negative associations were found between Internet use and mental health outcomes among girls.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".