Physical activity patterns in urban neighbourhood parks: insights from a multiple case study
Notice bibliographique
Résumé
BACKGROUND: Many characteristics of urban parks and neighbourhoods have been linked to patterns of physical activity, yet untangling these relationships to promote increased levels of physical activity presents methodological challenges. Based on qualitative and quantitative data, this article describes patterns of activity within urban parks and the socio-demographic characteristics of park visitors. It also accounts for these patterns in relation to the attributes of parks and their surrounding neighbourhoods. METHODS: A multiple case study was undertaken that incorporated quantitative and qualitative data derived from first-hand observation in a purposive sample of four urban parks. Quantitative data, based on direct observation of visitors' patterns of use and socio-demographic characteristics, were collected using a structured instrument. Differences in frequencies of observed activities and socio-demographic characteristics of visitors were compared between the four parks. Qualitative data, based on direct observation of park characteristics and patterns of use, were generated through digital photography and analyzed through captioning. Quantitative data on patterns in activity and socio-demographic characteristics were synthesized with the qualitative data on park and usage characteristics. RESULTS: A comprehensive portrait of each park in the study was generated. Activity types (sedentary, walking, dog-related, cycling, and play), patterns of park use (time of day, day of week), and socio-demographic characteristics (age group, social group) differed between the four parks. Patterns in park use and activity appeared to be associated with socio-demographic characteristics of the surrounding neighbourhoods as well as the physical and social environmental characteristics specific to each park. CONCLUSIONS: Both park and neighbourhood characteristics influence patterns of use and physical activity within parks. The study findings suggest that socio-demographic characteristics of neighbourhoods surrounding parks need be considered in planning, development and management. Engaging local communities could help planners to develop and update urban parks in ways that reflect the needs and characteristics of community residents and, in turn, encourage visits and more physical activity amongst visitors.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».