Higher independent mobility to school among adolescents: A secondary analysis using cross‐sectional data between 2010 and 2017 in Spanish youth
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".