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Record W4310537669 · doi:10.1111/apa.16612

Higher independent mobility to school among adolescents: A secondary analysis using cross‐sectional data between 2010 and 2017 in Spanish youth

2022· article· en· W4310537669 on OpenAlexaff
Patricia Gálvez‐Fernández, Palma Chillón, Romina Gisele Saucedo‐Araujo, Guy Faulkner, Francisco Javier Huertas‐Delgado, Manuel Herrador‐Colmenero

Bibliographic record

VenueActa Paediatrica · 2022
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of British Columbia
FundersJunta de AndalucíaMinisterio de Educación y Formación ProfesionalMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaEuropean Regional Development FundUniversidad de Granada
KeywordsMedicineDemographyCross-sectional studyLogistic regressionOdds ratioPublic healthOddsMale genderPediatricsInternal medicine

Abstract

fetched live from OpenAlex

AIM: To describe and to analyse the associations between independent mobility to school (IM) with gender and age in Spanish youth aged 6-18 years old from 2010 to 2017. Moreover, to study the changes in the rates of IM from 2010 to 2017 by gender and age. METHODS: Cross-sectional data were obtained from 11 Spanish studies. The study sample comprised 3460 children and 1523 adolescents. Logistic regressions models (IM with gender and age) and multilevel logistic regressions (IM with time period) were used. RESULTS: Boys had higher odds ratio (OR) of IM than girls in children (OR = 1.86; CI: 1.50-2.28, p < 0.01). Adolescents showed higher IM than children: 12-14 years old (OR: 6.30; CI: 1.65-23.97) and 14-16 years old (OR: 7.33; CI: 1.18-45.39) had higher IM than 6-8 years old for boys (all, p < 0.05). Moreover, 12-14 years old (OR: 4.23; CI: 1.01-17.81) had higher IM than 6-8 years old for girls (p < 0.001). IM was not associated with the time period. CONCLUSION: The IM is higher in boys and in adolescents, highlighting the relevance to promote IM strategies targeting girls and children. In these strategies is essential the support of researchers, public health practitioners and families to achieve positive results.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.309
Teacher spread0.265 · 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.

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

Citations4
Published2022
Admission routes1
Has abstractyes

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