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Record W2042841318 · doi:10.1155/2014/794539

Television Time among Brazilian Adolescents: Correlated Factors are Different between Boys and Girls

2014· article· en· W2042841318 on OpenAlexaff
Diego Augusto Santos Silva, Mark S. Tremblay, Eliane Cristina de Andrade Gonçalves, Roberto Jerônimo dos Santos Silva

Bibliographic record

VenueThe Scientific World JOURNAL · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsAgricultural Research Institute of OntarioUniversity of Ottawa
Fundersnot available
KeywordsSocioeconomic statusScreen timeDemographyAlcohol consumptionMedicineCross-sectional studyPhysical activityEnvironmental healthPsychologyAlcoholPopulation

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to identify the prevalence of excess television time and verify correlated factors in adolescent males and females. METHODS: This cross-sectional study included 2,105 adolescents aged from 13 to 18 years from the city of Aracaju, Northeastern Brazil. Television time was self-reported, corresponding to the time spent watching television in a typical week. Several correlates were examined including age, skin color, socioeconomic status, parent education, physical activity level, consumption of fruits and vegetables, smoking status, alcohol use, and sports team participation. RESULTS: The prevalence excess television time (≥ 2 hours/day) in girls and boys was 70.9% and 66.2%, respectively. Girls with low socioeconomic status or inadequate consumption of fruits and vegetables were more likely to have excess television time. Among boys, those >16 years of age or with black skin color were more likely to have excess television time. CONCLUSIONS: Excess television time was observed in more than two-thirds of adolescents, being more evident in girls. Correlated factors differed according to sex. Efforts to reduce television time among Brazilian adolescents, and replace with more active pursuits, may yield desirable public health benefits.

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)0.000
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.013
GPT teacher head0.246
Teacher spread0.233 · 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

Citations25
Published2014
Admission routes1
Has abstractyes

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Same venueThe Scientific World JOURNALSame topicChild Development and Digital TechnologyFrench-language works237,207