Associations between adolescent mental health and pedestrian- and transit-oriented urban design qualities: Evidence from a national-level online Canadian survey
Bibliographic record
Abstract
Different types of environment stimuli (e.g. noise, aesthetics) in urban environments are becoming better understood as determinants of the mental health of urban dwellers. Research on the impacts of urban exposures, especially those related to urban designs, and their potential impacts on the mental health of adolescents specifically, however, is currently lacking. In this study, we examine the relationships between five pedestrian- and transit-oriented design (PTOD) concepts – imageability, enclosure, human scale, transparency and complexity – and adolescent emotional responses to six settings of varied PTOD quality, and discuss potential design-related emotional affordances within Gibson’s Theory of Affordances (ToA). Using an online survey method with videos of each setting, a nationally representative sample of Canadian adolescents viewed the videos and indicated responses to six mental health indicators (positive affect, negative affect, calmness, anxiousness, perceived restorativeness and mental demand). Adjusted linear mixed models (LMMs) were constructed to examine the association between different urban settings and each outcome. Results indicated that, generally, as the quality of five PTOD concepts increased, as reflected in the scores of the different settings, positive emotional responses tended to increase while negative responses decreased (excluding mental demand). Within the frame of the ToA, multiple emotional response outcomes were significantly associated with settings high in aggregate PTOD quality (e.g. Plaza-Positive Affect: β = 0.116, 95% CI: 0.010–0.222, p = 0.033; Bluespace-Mental Demand: β = −1.634, 95% CI: −1.770 to −1.498, p = <0.000), suggesting such spaces may be perceived by adolescents as possessing greater emotional richness with respect to affordances. Future studies should further explore these relationships with other means (e.g. objective methods).
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".