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Record W2588956836 · doi:10.1186/s12889-017-4125-y

Demographic correlates of screen time and objectively measured sedentary time and physical activity among toddlers: a cross-sectional study

2017· article· en· W2588956836 on OpenAlexafffundabout
Valerie Carson, Nicholas Kuzik

Bibliographic record

VenueBMC Public Health · 2017
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Alberta
FundersInstitute of Human Development, Child and Youth HealthCanadian Institutes of Health ResearchAlberta Health ServicesHeart and Stroke Foundation of Canada
KeywordsMedicineBiostatisticsCross-sectional studyScreen timePhysical activityPublic healthEnvironmental healthEpidemiologySedentary behaviorSedentary lifestyleGerontologyDemographyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Determining the most important demographic correlates of sedentary behavior and physical activity will help identify the groups of children that are most in need of intervention. Little is known in regards to the demographic correlates of sedentary behavior and physical activity in toddlers (aged 12-35 months), where long-term behavioral patterns may initially be formed. Therefore, the objective of this study was to examine the associations between demographic correlates and specific types of sedentary behavior and physical activity in this age group. METHODS: Findings are based on 149 toddlers (19.0 ± 1.9 months) and their parents (33.7 ± 4.7 years) recruited from immunization clinics in Edmonton, Canada as part of the Parents' Role in Establishing healthy Physical activity and Sedentary behavior habits (PREPS) project. Toddlers' and parental demographic characteristics and toddlers' television viewing, video/computer games, and overall screen time were measured via the PREPS parental questionnaire. Toddlers' objectively measured sedentary time and physical activity (light, moderate to vigorous, and total) were accelerometer-derived using Actigraph wGT3X-BT monitors. Simple and multiple linear regression models were conducted to examine associations. RESULTS: In the multiple linear regression models, toddlers' age, toddlers' sex (female versus male), toddlers' race/ethnicity (other versus European-Canadian/Caucasian), and household income ($50,001 to $100,000 versus > $100,000) were significantly positively associated, and main type of child care (child care center versus parental care) was significantly negatively associated with screen time. Similar findings were observed with television viewing, except null associations were observed for toddlers' sex. Toddlers' race/ethnicity (other versus European-Canadian/Caucasian) was significantly positively associated and main type of child care (child care center, day home, other versus parental care) was significantly negatively associated with video/computer games. Toddlers' sex (female versus male) was significantly positively associated with sedentary time and significantly negatively associated with moderate- to vigorous-intensity physical activity. CONCLUSIONS: Female toddlers, toddlers from ethnic minority groups, toddlers from families of lower income, and toddlers whose main type of child care is not center-based may be important targets for screen time interventions in toddlers. Apart from sex, demographic correlates may not be important targets for objectively measured sedentary time and physical activity in toddlers.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.335
Teacher spread0.285 · 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

Citations84
Published2017
Admission routes3
Has abstractyes

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