MétaCan
Menu
← Back to cohort
Record W4410149689 · doi:10.1093/pch/pxae107

Optimizing energy balance in youth: reducing sugar-sweetened beverages and screen time

2025· review· en· W4410149689 on OpenAlexafffund
Hannah M. Murphy, Kelsey M Stanford, Scott Harding

Bibliographic record

VenuePaediatrics & Child Health · 2025
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Institutes of Health Research
KeywordsObesityScreen timeEnvironmental healthChildhood obesityEnergy balanceConsumption (sociology)Balance (ability)Intervention (counseling)MedicinePsychologyGerontologyOverweightPhysical therapyBiologyPsychiatry

Abstract

fetched live from OpenAlex

The high prevalence of children and adolescents living with obesity, as well as the multitude of associated risks, stress the need for refined weight management strategies for this population. While an overarching lifestyle intervention may be an ideal way to improve energy balance, more practical recommendations would likely improve adherence rates. This review set out to investigate sugar-sweetened beverage consumption and screen time as potential lifestyle targets to reduce paediatric obesity. We report strong evidence that both sugar-sweetened beverage consumption and screen time influence childhood obesity directly, as well as through interactions with sleep patterns. Potential mechanisms are discussed with focus on the energy balance framework of obesity. We also present methodological considerations to improve applicability and consistency of future studies.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
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 head0.021
GPT teacher head0.300
Teacher spread0.279 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venuePaediatrics & Child Health→Same topicObesity, Physical Activity, Diet→French-language works237,207→