We can do that! Collaborative assessment of school environments to promote healthy adolescent nutrition and physical activity behaviors
Bibliographic record
Abstract
Evidence for effectiveness of school-based studies for prevention of adolescent obesity is equivocal. Tailoring interventions to specific settings is considered necessary for effectiveness and sustainability. The PRECEDE framework provides a formative research approach for comprehensive understanding of school environments and identification of key issues/areas to focus resources and energies. No reported studies have tested applicability of the PRECEDE framework in schools in relation to obesity. Adolescents (n = 362), parents (n = 349) and teachers (n = 146) from six secondary schools participated in two quantitative studies and two qualitative studies. Data collected from these studies permitted confirmation of adolescent overweight/obesity a health issue for schools; the need for secondary schools to focus health promotion efforts on healthy nutrition, with inclusion of parents/homes and appreciation for gender differences in developing interventions. Community buy-in and commitment to school-based obesity prevention programs may be dependent on initially addressing what may be perceived as minor issues, and developing policies to guide practices within schools in relation to supply and access to healthy foods, use of sporting equipment and participation in physical activities. The PRECEDE framework allows systematic assessment of school environments and provided opportunity to identify realistic and relevant interventions for promoting healthy adolescent physical activity and nutrition behaviors.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".