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Enregistrement W7161996932 · doi:10.82308/29714

Healthy aging in the neighborhood: Examining the relationship between the micro-scale built environment and walking in older adults

2021· dissertation· en· W7161996932 sur OpenAlexaboutno aff
Madeleine Steinmetz-Wood

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineSocial Sciences
ThématiqueUrban Transport and Accessibility
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBuilt environmentReliability (semiconductor)Field (mathematics)PopulationLevel designHealthy agingAudit

Résumé

récupéré en direct d'OpenAlex

Evidence suggests that neighborhood-built environments influence walking behavior in older adults. Most studies to date have examined how macro-scale features (connectivity, land-use mix, and population density) encourage walking in this population. Findings about neighborhood macro-scale features and walking, however, are not often practical to apply in existing neighborhood settings, as changing these features can require substantial reconfiguration of the neighborhood layout. Altering micro-scale features of neighborhoods (e.g., presence and quality of sidewalks, benches) may be a relatively cost-effective and efficient method of creating environments that are conducive to walking. This dissertation adopted an explanatory mixed methods approach to better understand the relationship between the micro-scale environment and walking. The main findings of this dissertation are: 1. Reporting a research design and an integration strategy in mixed methods studies in the built environment and health field could help to strengthen our ability to gain new insights into the multidimensional nature of the relationship between the built environment and health.2. Virtual-STEPS is a reliable tool for virtually assessing the micro-scale environment of neighborhoods. Percentage agreement between virtual and field audits, and for inter-rater agreement was 80% or more for most items. There was high reliability between virtual and field audits with Kappa and ICC statistics indicating that 50.0% of items had almost perfect agreement and 32.5% of items had substantial agreement. Inter-rater reliability was also high with 42.5% of items with almost perfect agreement and 27.5% of items with substantial agreement.3. The micro-scale environment collectively promoted leisure walking in adults. The grand micro-scale score was associated with elevated odds of walking for leisure for at least 150 minutes per week in adults from Montreal and Toronto, even after accounting for self-selection. Conversely, the association between micro-scale walkability and walking for utilitarian purposes was inconclusive. 4. The micro-scale environment promoted leisure walking in older adults. The grand micro-scale score was associated with greater odds of walking for leisure for at least 150 minutes per week. After stratifying for health conditions, the grand micro-scale score and the traffic calming total section score were only associated with walking for leisure in the sample with health conditions, further the aesthetics section score became significantly associated with walking for leisure in the sample of older adults with health conditions. 5. Semi-structured interviews conducted with older adults living in the suburbs of Montreal during the COVID-19 pandemic revealed that aesthetics, pedestrian infrastructure, proximity to shops/facilities, and building characteristics were perceived as walk-friendly, whereas traffic as well as unsafe intersections were perceived as barriers to walking. Older adults also reported avoiding crowded parks and crowded or narrow boardwalks, sidewalks, and walking paths due to difficulties with physical distancing. Interventions to improve the micro-scale environment of neighborhoods could increase walking for leisure in older adults, a vulnerable population group, that may be particularly sensitive to the micro-scale features of their neighborhood environment

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,017

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,038
Tête enseignante GPT0,316
Écart entre enseignants0,278 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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