Evidence supporting a combined movement behavior approach for children and youth's mental health – A scoping review and environmental scan
Bibliographic record
Abstract
Associations between physical activity (PA), sedentary behavior (SED), and sleep – 24-h movement behaviors (MBs) – and children/youth's mental health (MH) is well-established though often only examined separately. This scoping review sought to answer the question: What evidence is there on the association between 24-h movement behaviors and children/youth's mental health and what integrated knowledge mobilization applications/tools exist? Included articles examined all three MBs and MH among children/youth. The electronic search was conducted in June 2022 on PsycINFO, MEDLINE, CINAHL, Scopus. An environmental was conducted to search for MB and MH integrated knowledge mobilization applications/tools. A total of 55 articles were included, where 42 reported on combined MB and MH; 27/42 (64%) examined MB and mental wellness; 27/42 (64%) examined MB and indicators of mental illness; an overlap of 12/42 (29%) articles examined MB in relation to both mental wellness and illness. In total, 21/27 (78%) articles reported a positive and 6/27 (22%) reported no association between combined MB and mental wellness. Additionally, 23/27 (85%) reported a negative association between combined MB and indicators of mental illness and 4/27 (15%) reported no association. The environmental scan revealed one tool that examined how integrated MBs are associated with MH outcomes. There is a wealth of knowledge on the association between combined MB and MH though only one tool examined how combined MB and MH are associated. Efforts are warranted to better track and intervene on population and individual-level 24-h MB for MH promotion and disease prevention.
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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 | 0.022 | 0.097 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.027 | 0.025 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".