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Record W2166444978 · doi:10.1186/1824-7288-36-52

Excessive recreational computer use and food consumption behaviour among adolescents

2010· article· en· W2166444978 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue˜The œItalian Journal of Pediatrics/Italian journal of pediatrics · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineLogistic regressionDemographyConsumption (sociology)RecreationEnvironmental healthScreen timeEthnic groupGerontologyObesity

Abstract

fetched live from OpenAlex

INTRODUCTION: Using the 2005 California Health Interview Survey (CHIS) data, we explore the association between excessive recreational computer use and specific food consumption behavior among California's adolescents aged 12-17. METHOD: The adolescent component of CHIS 2005 measured the respondents' average number of hours spent on viewing TV on a weekday, the average number of hours spent on viewing TV on a weekend day, the average number of hours spent on playing with a computer on a weekday, and the average number of hours spent on playing with computers on a weekend day. We recode these four continuous variables into four variables of "excessive media use," and define more than three hours of using a medium per day as "excessive." These four variables are then used in logistic regressions to predict different food consumption behaviors on the previous day: having fast food, eating sugary food more than once, drinking sugary drinks more than once, and eating more than five servings of fruits and vegetables. We use the following variables as covariates in the logistic regressions: age, gender, race/ethnicity, parental education, household poverty status, whether born in the U.S., and whether living with two parents. RESULTS: Having fast food on the previous day is associated with excessive weekday TV viewing (O.R.=1.38, p<0.01). Having sugary food more than once is associated with excessive weekend TV viewing (O.R.=1.50, p<0.001). Having sugary drinks more than once is associated with excessive weekday TV viewing (O.R.=1.41, p<0.01), excessive weekday recreational computer use (O.R.=1.38, p<0.05), and excessive weekend TV viewing (O.R.=1.43, p<0.001). Finally, having more than five servings of fruits and vegetables on the previous day is negatively associated with all four media use variables: excessive weekday TV viewing (O.R.=0.64, p<0.001), excessive weekday recreational computer use (O.R.=0.68, p<0.01), excessive weekend TV viewing (O.R.=0.80, p<0.05), and excessive weekend recreational computer use (O.R.=0.78, p<0.05). CONCLUSION: Excessive recreational computer use independently predicts undesirable eating behaviors that could lead to overweight and obesity. Preventive measures ranging from parental/youth counseling to content regulations might be addressing the potential undesirable influence from excessive computer use on eating behaviors among children and adolescents.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
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 head0.023
GPT teacher head0.263
Teacher spread0.240 · 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