Correlates of Sedentary Behaviour in Children and Adolescents Aged 7-18: A Systematic Review
Bibliographic record
Abstract
Background and Purpose: Risks posed by sedentary behaviours, independent of physical activity, have become evident. This review includes the current literature on the correlates of sedentary behaviours among children and adolescents to inform future interventions for reducing sedentary behaviours. Methods: Search engine literature searches were conducted up to February 2012. Eligible papers were published in English in peer-reviewed journals, and examined correlates of sedentary behaviours in youth aged 7-18 yr. Results: A total of 188 samples were included. Sedentary behaviour was correlated to age, physical maturity, gender, ethnicity, socioeconomic status, location, week/weekend day, neighborhood satisfaction, access, emotional and physical health status, risk behaviors, family and social influences, physical activity, and nutrition. Significant differences by specific sedentary behaviors were present in the findings. Conclusions: Correlates differed by type of sedentary behaviour, suggesting this is a complex area of research that cannot be assessed simply as an absence of physical activity. Several factors seem to be reliably linked to sedentary behavior; however, evidence suggests that specific sedentary behaviours have opposing effects compared to sedentary behavior in general. Research focused on sedentary behaviour specific interventions appears necessary.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".