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Early adolescent Body Mass Index and the constructed environment

2014· article· en· W2008921851 on OpenAlexaff
Randall M. Jones, J. Mitchell Vaterlaus

Bibliographic record

VenueJournal of Adolescence · 2014
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsBedroomPsychologyBody mass indexRecreationAffect (linguistics)Developmental psychologyExploratory researchDemographyGeographyCommunicationMedicineEcology

Abstract

fetched live from OpenAlex

Previous research has shown that macro-level environmental features such as access to walking trails and recreational facilities are correlated with adolescent weight. Additionally, a handful of studies have documented relationships between micro-level environmental features, such as the presence (or absence) of a television in the bedroom, and adolescent weight. In this exploratory study we focus exclusively on features of the micro-level environment by examining objects that are found within adolescent personal bedrooms in relation to the adolescent occupant's Body Mass Index score (BMI). Participants were 234 early adolescents (eighth graders and ninth graders) who lived with both biological parents and who had their own private bedroom. Discriminant analyses were used to identify the bedrooms belonging to adolescents with below and above average BMI using objects contained within the micro-level environment as discriminating variables. Bedrooms belonging to adolescents with above average BMI were more likely to contain objects associated with sedentary behavior (e.g., magazines, electronic games, dolls), whereas the bedrooms belonging to the average and below average BMI adolescents were more likely to contain objects that reflect past physical activity (e.g., trophies, souvenirs, pictures of places that they had visited). If causal connections between micro-environmental variables and adolescent BMI can be established in future longitudinal research, environmental manipulations may affect adolescent BMI.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.219
Teacher spread0.213 · 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 teacher head, 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

Citations3
Published2014
Admission routes1
Has abstractyes

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