Place attachment and walking behaviour: Mediation by perceived neighbourhood walkability
Bibliographic record
Abstract
The urban design features of a location are important for facilitating people’s attachment to places. Attachment to particular places, such as residential neighbourhoods, may encourage people to adopt and maintain physical activity routines. Moreover, the ways in which people perceive the built features in their neighbourhood (e.g., neighbourhood walkability) may mediate the relations between place attachment and physical activity behaviour. Therefore, this exploratory study examined the associations between place attachment and neighbourhood-specific physical activity and explored the extent to which perceived neighbourhood walkability mediates these associations. The study included data from 1,800 adults living in Calgary, Canada. Place attachment (including identity and dependence), physical activity, and neighbourhood walkability were self-reported using validated tools. Linear and logistic regression models were applied to estimate the associations between variables. Mediation was assessed using structural equation modelling. Place attachment dimensions were significantly positively associated ( p < 0.05) with weekly participation (odds) and time spent walking for transport and recreation. The associations between place attachment and walking for transport were also mediated by perceived neighbourhood walkability. Together, these findings emphasise the crucial role of place attachment, particularly human bonding and relationships with the neighbourhood environment , in supporting physically active lifestyles and promoting public health.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".