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Record W4399790501 · doi:10.1186/s44167-024-00054-8

The sleep and activity database for the early years (SADEY) study: design and methods

2024· article· en· W4399790501 on OpenAlexafffundabout
Dylan P. Cliff, Devan Antczak, Catherine E. Draper, Tim Olds, Rute Santos, Diego Augusto Santos Silva, Mark S. Tremblay, Esther van Sluijs, Byron J. Kemp, Eivind Aadland, Katrine Nyvoll Aadland, Thaynã Alves Bezerra, Jade Burley, Valerie Carson, Hayley Christian, Marieke De Craemer, Katherine Downing, Kylie D. Hesketh, Rachel A. Jones, Nicholas Kuzik, Reetta Lehto, Clarice Martins, Jorge Mota, Andrea Nathan, Anthony D. Okely, Eva Roos, Eduarda Sousa‐Sá, Susana Vale, Sandra A. Wiebe, Ian Janssen

Bibliographic record

VenueJournal of Activity Sedentary and Sleep Behaviors · 2024
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of OttawaUniversity of AlbertaQueen's UniversityChildren's Hospital of Eastern Ontario
FundersFundação para a Ciência e a TecnologiaNational Health and Medical Research CouncilMedical Research CouncilCanadian Institutes of Health ResearchUniversity of WollongongUniversity of AlbertaHøgskulen på VestlandetNational Heart Foundation of AustraliaAustralian Research CouncilWellcome Trust
KeywordsDatabaseGross motor skillEarly childhoodGuidelineMedicinePsychologyGerontologyMotor skillDevelopmental psychologyComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Canada, Australia, the World Health Organization and other countries have released 24-hour movement guidelines for the early years which integrate physical activity, sedentary behaviour, and sleep, focusing on supporting children to achieve a healthy 24-hour day. The guideline evidence synthesis, however, highlighted the dearth of high-quality evidence, particularly from large-scale studies. The Sleep and Activity Database for the Early Years (SADEY) project aims to assemble a large, pooled database of 24-hour movement behaviours and health indicators in young children (birth to 5.99 years), to advance knowledge in these areas. This paper describes the SADEY design and methods. METHODS: Data sets were identified with > 100 children and device-measured (hip-worn ActiGraph accelerometers) physical activity and sedentary behaviour, parent-reported or device-measured sleep, and at least one health outcome: physical (BMI, waist circumference, blood pressure), social-emotional (Strength and Difficulties Questionnaire), cognitive (Early Years Toolbox), or motor development (Test of Gross Motor Development 2). Led by the University of Wollongong co-ordinating centre, the SADEY project collates the datasets to create a pooled database. FINDINGS: To date, 13 studies from 7 countries have been included in the database. Ethics clearance and data sharing agreements have been secured for all studies and the SADEY 1.0 database is being assembled including ~ 8,000 participants. DISCUSSION: SADEY will be used to address questions of global importance to public health policy and practice, for example - Is the mix of movement behaviours across the 24-hour day associated with healthy development?, What is the optimal mix of these behaviours?, and; What factors can be targeted to support young children in achieving the optimal mix of 24-hour movement behaviours? Additionally, SADEY seeks to develop and disseminate protocols, develop capacity on the device-based measurement of movement behaviours, and seeks partnerships with stakeholders that promote knowledge translation on movement behaviours to support healthy development among young children.

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)0.023
metaresearch head score (Gemma)0.025
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: Methods · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.025
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0040.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0150.004

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 head0.037
GPT teacher head0.366
Teacher spread0.329 · 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
GenreMethods

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

Citations12
Published2024
Admission routes3
Has abstractyes

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