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Record W4225281768 · doi:10.1542/peds.2021-053852m

Interventions for Health and Well-Being in School-Aged Children and Adolescents: A Way Forward

2022· article· en· W4225281768 on OpenAlexaff

Bibliographic record

VenuePEDIATRICS · 2022
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsUniversity of TorontoSickKids Foundation
Fundersnot available
KeywordsPsychological interventionMental healthVariety (cybernetics)Reproductive healthChild healthMEDLINE

Abstract

fetched live from OpenAlex

The health and well-being of school-aged children has received little attention compared with younger children aged < 5 years and adolescents. In this final article in a supplement of reviews that have assessed the effectiveness of interventions for school-aged children across a variety of health-related domains (including infectious diseases, noncommunicable diseases, healthy lifestyle, mental health, unintentional injuries, and sexual and reproductive health), we summarize the main findings and offer a way forward for future research, policy, and implementation. We complement this evidence base on interventions with a summary of the literature related to enabling policies and intersectoral actions supporting school-aged child health. The school represents an important platform for both the delivery of preventive interventions and the collection of data related to child health and academic achievement, and several frameworks exist that help to facilitate the creation of a health-promoting environment at school.

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)0.042
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.042
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.064
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0050.004
Science and technology studies0.0020.002
Scholarly communication0.0100.019
Open science0.0040.006
Research integrity0.0130.019
Insufficient payload (model declined to judge)0.0110.002

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 head0.032
GPT teacher head0.415
Teacher spread0.383 · 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 designNot applicable
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

Citations23
Published2022
Admission routes1
Has abstractyes

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