Influence des facteurs socioenvironnementaux sur la prévalence de la violence dans les relations amoureuses chez les adolescent-e-s à Montréal
Notice bibliographique
Résumé
Dating violence (DV) is a widespread phenomenon among adolescents and is likely to have significant negative consequences for victims’ health and well-being. Although individual, family, and peer determinants of DV have been widely studied, knowledge regarding the influence of socio-environmental characteristics of residential neighbourhoods on DV remains limited. This doctoral thesis aims to assess the association between neighbourhood characteristics and both experienced and perpetrated DV among adolescents living on the island of Montreal. It focuses more specifically on the effects of certain sociodemographic characteristics (socioeconomic status (SES), single-parent families, residential instability, and ethnocultural diversity), several built-environment features (density of alcohol outlets, density of bars, density of community organizations, density of parks, greenness, and walkability), and social-environment characteristics (crime, social support, and social participation) on DV. The thesis also seeks to explore the modifying effect of gender and the influence of spatial scale in the analysis of these relationships.To address these objectives, data from the Québec Health Survey of High School Students (QHSHSS) were used to measure DV as well as neighbourhood social support and social participation. Egocentric neighbourhoods were operationalized for all participants with a postal code on the island of Montreal using polygon-based network buffers of four different sizes (250 m, 500 m, 750 m, and 1,000 m). Population census data (2016) were used to describe neighbourhood sociodemographic characteristics. Various data sources were used to measure built-environment features and crime. Associations between socio-environmental factors and both experienced and perpetrated DV were estimated using logistic regression models. All analyses were conducted separately for girls and boys to assess gender-specific effects.The results are presented in three scientific articles. The first article, entitled “Assessing the influence of spatial scale on the effects of neighborhood sociodemographic characteristics on dating violence” and submitted to Social Science Research, describes analyses of the relationships between sociodemographic characteristics and DV. The second article, “Associations between neighborhood characteristics and dating violence: does spatial scale matter?”, published in the International Journal of Health Geographics, examines the associations between built-environment features and crime, on the one hand, and DV on the other. Finally, the third article, “Neighborhood social support and social participation as predictors of dating violence”, submitted to the Journal of Interpersonal Violence, investigates the association between social participation and social support in the community environment, on the one hand, and DV on the other.Findings from these studies suggest that several neighbourhood characteristics are associated with DV. The effects of these factors vary according to gender, the specific form of DV considered, and the spatial scale of analysis. Among girls, SES, residential instability, bar density, and walkability are associated with psychological DV victimization, while single-parenthood, ethnocultural diversity, and walkability are associated with physical/sexual DV victimization. Social support is associated with the perpetration of psychological DV, whereas social participation is associated with the perpetration of physical/sexual DV. Among boys, single-parenthood and greenness are linked to psychological DV victimization, while crime is associated with both victimization and perpetration of physical/sexual DV. Residential instability, ethnocultural diversity, alcohol outlet density, and social participation are associated with the perpetration of psychological DV.Furthermore, the results suggest that the effects of SES, single-parenthood, ethnocultural diversity, density of community organizations, and crime are primarily observable at finer spatial scales (250 m or 500 m), whereas the effects of residential instability, alcohol outlet density, walkability, and greenness tend to emerge at larger scales (500 m to 1,000 m). Neighbourhoods therefore appear to play an important role in DV, and several socio-environmental factors may influence these behaviors. The findings of this thesis also highlight the importance of considering gender, the specific form of DV, and the choice of spatial scale to achieve a better understanding of these relationships. Moreover, these results have significant implications for practice, as they point to new avenues for intervention development, particularly emphasizing the importance of improving neighbourhood conditions (e.g., programs enhancing social cohesion, greening initiatives, urban design improvements) to reduce the prevalence of DV.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 source (Gemma direct ou Codex distillé), 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 ».