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International school‐based interventions for preventing obesity in children

2006· review· en· W2090248941 on OpenAlexaboutno aff
Manoj Sharma

Bibliographic record

VenueObesity Reviews · 2006
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionChildhood obesityObesityIntervention (counseling)MedicineGerontologyOverweightNursing

Abstract

fetched live from OpenAlex

The purpose of this article was to review international (excluding the United States) school-based interventions for preventing obesity in children published between 1999 and 2005. A total of 21 such interventions were found from Australia (1), Austria (1), Canada (1), Chile (1), France (1), Germany (3), Greece (1), New Zealand (1), Norway (1), Singapore (1) and the United Kingdom (9). The grade range of these interventions was from pre-school to high school with the majority (17) from elementary schools. Nine of these interventions targeted nutrition behaviours followed by seven aiming to modify both physical activity and nutrition behaviours. Only five interventions in international settings were based on any explicit behavioural theory which is different than the interventions developed in the United States. Majority of the interventions (9) were one academic year long. It can be speculated that if the interventions are behavioural theory-based, then the intervention length can be shortened. All interventions that documented parental involvement successfully influenced obesity indices. Most interventions (16) focused on individual-level behaviour change approaches. Most published interventions (16) used experimental designs with at least 1-year follow-up. Recommendations from international settings for enhancing the effectiveness of school-based childhood obesity interventions are presented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.082
GPT teacher head0.395
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations167
Published2006
Admission routes1
Has abstractyes

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