Factors affecting parental safety perception, satisfaction with school travel and mood in primary school children in the Netherlands
Bibliographic record
Abstract
An increasing number of studies in transportation research have recently focused on well-being and travel satisfaction. These studies argue that satisfaction with travel is an indicator of the trip's contribution to subjective wellbeing of the traveler. Although the attention on satisfaction with travel is increasing, relatively few studies have considered satisfaction with travel of children. As children's travel is strongly linked to distance and the built environment, they would be important additional considerations to such research. Therefore, this study looks into the household, built environment and trip characteristics influencing satisfaction with travel and mood among Dutch children attending primary school. Additionally, the study considers the mediating effect of parental safety perception on satisfaction with travel and the relationship between satisfaction with travel and mood. In order to study these relationships, survey data were collected in the Netherlands from 660 children (7–12 years) and their parents. The data were analyzed using a path analysis. Findings show that parental safety perceptions are related to the age of the child, income, perceptions of neighborhood infrastructure and social cohesion. Satisfaction with school travel is higher when parental safety perception is higher, when it is sunny, when traveling with a friend and when traveling by bike when this is the favorite transport mode. Satisfaction with travel is related to children reporting a better mood. These insights can be used by policy makers to create safe school environments stimulating active travel, which in turn will improve satisfaction with travel, well-being and health among primary school-going children.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".