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Record W2159612062 · doi:10.1177/1090198110385772

Links Between Adolescent Physical Activity, Body Mass Index, and Adolescent and Parent Characteristics

2011· article· en· W2159612062 on OpenAlexaff
Susan L. Williams, W. Kerry Mummery

Bibliographic record

VenueHealth Education & Behavior · 2011
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIntrapersonal communicationOverweightBody mass indexObesityPsychological interventionPsychologyRecreationAdolescent healthLogistic regressionPhysical activityDevelopmental psychologyPhysical activity levelScreen timeInterpersonal communicationMedicineClinical psychologyGerontologyPhysical therapyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Identification of the relationships between adolescent overweight and obesity and physical activity and a range of intrapersonal and interpersonal factors is necessary to develop relevant interventions which target the health needs of adolescents. This study examined adolescent body mass index (BMI) and participation in moderate and vigorous physical activity (MVPA) and their associations with school year, adolescent nutrition and sedentary behaviors, parent BMI, parent physical activity, and parent support adolescent physical activity. Participants included 295 adolescents and their parents. Logistic regression was used to examine associations between adolescent BMI, MVPA, and the range of adolescent and parent characteristics. Results indicated that parents and home environments play significant roles in the development and maintenance of adolescent overweight/obesity of physical activity behaviors. School-based interventions should ensure high levels of parent involvement and target male adolescents to reduce time spent in small screen recreation and female adolescents to increase participation in MVPA.

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 score0.003
Threshold uncertainty score0.006

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 head0.078
GPT teacher head0.371
Teacher spread0.293 · 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

Citations24
Published2011
Admission routes1
Has abstractyes

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