An innovative approach to addressing gender-based violence and adverse childhood experiences: An evaluation of the Alliance against Violence and Adversity (AVA) community agency internship program
Notice bibliographique
Résumé
Gender-based violence (GBV) and Adverse Childhood Experiences (ACEs) are associated with numerous detrimental health, social and economic impacts across the life course. Despite overwhelming evidence of GBV and ACEs as global health concerns, current approaches to prevent and respond to GBV and ACEs have been insufficient to address these problems. Drawing on evaluation and implementation research, innovations in GBV and ACEs training may help solve this problem. This study evaluated the Community Agency Internship Program (CAIP) of the Alliance against Violence and Adversity (AVA), a health research training platform that funds graduate student interns in community agencies focused on GBV and ACEs interventions in Canada. This evaluation focused on interns’ and community agency leaders’ self-reported perspectives of: the interns’ tasks and activities conducted during the internship, barriers and challenges, benefits and impacts, and satisfaction with CAIP. A pilot evaluation employed survey data collected between 2022 and 2024. Nine interns and four community agency leaders completed surveys at the conclusion of the CAIP placement. Quantitative and qualitative data were analyzed using descriptive statistics and deductive thematic analysis, respectively. The CAIP positively impacted interns’ and leaders’ professional practice, goals, and personal growth, with most reporting high satisfaction with the program. Interns became comfortable with the pace of community-based work and engaging with diverse community members. Community agency leaders reported readiness to integrate research within their organizations and emphasized how the CAIP provided them with resources to engage in research and evaluation of their practice and implementation of services. The AVA CAIP promoted community agencies’ engagement in evaluation activities, and increased reciprocal learning about uptake, dosage, and maintenance of innovative programs to optimize service delivery to address the crisis of GBV and ACEs in Canada. • It is well documented that Gender-based violence (GBV) and adverse childhood experiences (ACEs) have profound health, social, and economic effects throughout the lifespan, yet current prevention and response strategies remain insufficient. • The Alliance Against Violence and Adversity (AVA) Community Agency Internship Program (CAIP) is an innovative training initiative that connects graduate student interns with community agencies to tackle GBV and ACEs through integrated research and practice. • Evaluation of AVA’s CAIP shows that the program enhances interns' and community leaders' professional growth, personal development, and aspirations while preparing agencies to integrate research and evaluation into their practices. • AVA’s CAIP equips community agencies to adapt implementation and evaluation strategies, optimize evidence-based service delivery, and bridge the gap between research and practice in addressing GBV and ACEs in Canada. • As a reproducible model, the AVA CAIP illustrates how reciprocal learning, collaborative research, and community-driven approaches can effectively address GBV and ACEs while advancing the field through program evaluation and implementation science.
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 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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».