MétaCan
Menu
← Back to cohort
Record W7028567567

EXPLORING MOTHERS ’ INFLUENCE ON PRESCHOOLERS ’ PHYSICAL ACTIVITY LEVELS AND SEDENTARY TIME

2015· article· en· W7028567567 on OpenAlexaff

Bibliographic record

VenueScholarship@Western (Western University) · 2015
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsWestern University
Fundersnot available
KeywordsPhysical activitySedentary behaviorSedentary lifestyleEarly childhoodMotor activitySample (material)Physical activity levelMultilevel model
DOInot available

Abstract

fetched live from OpenAlex

Physical activity (PA) patterns continue from childhood into adulthood; therefore, establishing healthy PA levels early is imperative. Mothers have been identified as influencing preschoolers’ activity behaviours; however, a holistic exploration of maternal influence is lacking. The purpose of this study was to explore maternal influence on preschoolers’ PA and sedentary time. Preschoolers (n = 30) and their mothers wore ActicalTM accelerometers, and mothers completed the adapted Environmental Determinants of Physical Activity in Preschool Children - Parent Survey. Direct entry regression analyses were conducted to explore maternal influence (e.g., support, enjoyment) on preschoolers’ activity levels. Maternal support was a significant predictor of preschoolers’ PA and sedentary time (p < .05), while mothers’ enjoyment of PA was related to preschoolers’ sedentary time, light PA, and total PA (p < .05). Further research using a large diverse sample is warranted to clarify and understand the ways in which mothers impact their preschoolers’ PA behaviours.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.216
GPT teacher head0.337
Teacher spread0.120 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueScholarship@Western (Western University)→Same topicObesity, Physical Activity, Diet→French-language works237,207→