Objectively measured sedentary behaviour and self-esteem among children
Bibliographic record
Abstract
Background: Existing research suggests consistent negative mental health associations (e.g., self-esteem) with sedentary behaviour (primarily screen viewing) among children. Sedentary behaviour has typically been measured using self-report or by objective measures of time spent sedentary. Objective: The objective of this study was to examine the association between self-esteem and patterns of objectively measured sedentary behaviour in terms of frequency of sedentary bouts and frequency of breaks in sedentary time. Methods: Participants were 787 boys and girls [mean age (standard deviation) = 11 years (0.6)] from 16 secondary schools in Toronto, Canada. Height, weight, physical activity and sedentary behaviour (accelerometers), global self-esteem and physical self-worth were assessed. Results: After adjusting for sex, age, weight status, parental socioeconomic status, physical activity, and accelerometer daily wear time, global self-esteem and physical self-worth were not associated with any of the sedentary behaviour outcomes. There was a significant positive association between physical self-worth and minutes spent in moderate to vigorous physical activity (MVPA; b = 1.514, p = 0.002). The association between global self-esteem and MVPA was not statistically significant. Conclusions: What children are actually doing when sedentary is likely more important in terms of associations with mental health outcomes like self-esteem. The development of objective measures of specific sedentary behaviours and the context that they occur in is likely needed to advance understanding of the relationship between sedentary behaviour and mental health.Acknowledgments: This research was funded by the Built Environment, Obesity and Health Strategic Initiative of the Heart and Stroke Foundation and the Canadian Institutes of Health Research (CIHR).
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".