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Record W4392342327 · doi:10.1111/obr.13731

The range of outcomes and outcome measurement instruments collected in multisectoral community‐based obesity prevention interventions in children: A systematic review

2024· review· en· W4392342327 on OpenAlexaff
Marufa Sultana, Melanie Nichols, Jane Jacobs, Derin Karacabeyli, Steven Allender, Rachel Novotny, Vicki Brown

Bibliographic record

VenueObesity Reviews · 2024
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of British Columbia
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsPsychological interventionMedicineOverweightAnthropometrySystematic reviewObesityMEDLINEBody mass indexEnvironmental healthGerontologyPathology

Abstract

fetched live from OpenAlex

Multicomponent and multisectoral community-based interventions (CBIs) have proven potential in preventing overweight and obesity in children. Synthesizing evidence on the outcomes collected and reported in such CBIs is critical for the evidence of effectiveness and cost-effectiveness. This systematic review aimed to identify the range of outcomes and outcome measurement instruments collected and reported in multisectoral and multicomponent CBIs for obesity prevention in children. A systematic search updated an existing review and extended the search to 11 academic databases (2017-2023) and gray literature. Outcomes were classified into outcome domains, and common measurement instruments were summarized. Seventeen outcome domains from 140 unique outcomes were identified from 45 included interventions reported in 120 studies. The most frequently collected outcome domains included anthropometry and body composition (91% of included interventions), physical activity (84%), dietary intake (71%), environmental (71%), and sedentary behavior (62%). The most frequently collected outcomes from each of these domains included body mass index (89%), physical activity (73%), fruit and vegetable intake (58%), school environment (42%), and screen time (58%). Outcome measurement instruments varied, particularly for behavioral outcomes. Standardization of reported outcomes and measurement instruments is recommended to facilitate data harmonization and support quantifying broader benefits of CBIs for obesity prevention.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.003
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.170
GPT teacher head0.404
Teacher spread0.234 · 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 teacher head, not a consensus.

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

Citations7
Published2024
Admission routes1
Has abstractyes

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