Participatory evaluation of the Alberta Healthy Communities Approach (AHCA)
Notice bibliographique
Résumé
Background: The Alberta Healthy Communities Approach (AHCA) project aimed to strengthen supportive environments for cancer and chronic disease prevention in rural communities across Alberta. Approach: The Alberta Healthy Communities Approach (AHCA) is an evidence-based, participatory approach to creating supportive environments for health across key risk factors for cancer and chronic disease (e.g., healthy eating, mental health, UVR protection). In the AHCA project (209-2023), the Community Team in Cancer Prevention and Screening Innovation (CPSI), Alberta Health Services (AHS), collaborated with members from multi-sectoral teams (MSTs) across nineteen rural communities to implement and evaluate the AHCA. The MSTs included diverse representation from community-at-large, facilities and organizations, healthcare, schools, and workplaces. Using the AHCA five-step process, MSTs created connections; identified community strengths and capacity; co-created a shared vision and goal; and planned, implemented, and evaluated healthy community initiatives to address local priorities. Community surveys and assessments were developed and conducted by MSTs to determine the outcomes of their initiatives. Members of MSTs also participated in evaluation activities conducted by CPSI (e.g., focus groups, surveys) to contextualize findings and determine the overall impact and effectiveness of the AHCA in communities. Results: Despite facing challenges due to the COVID-9 pandemic, communities implemented 232 healthy community initiatives - including creating walking trails, building community gardens, and organizing cooking classes - with an estimated reach of over 72,000 community members. Pre-post assessments demonstrated statistically significant increases in community capacity in addition to improvements in supportive environments for health (i.e., social, physical, economic). Community surveys also indicated increased awareness of available resources and facilities, improved knowledge about healthy lifestyles, and adoption of healthy behaviors. Furthermore, MST members shared that the AHCA created new and strengthened existing relationships in their communities, supported investment in community, and reduced social isolation and mental health stigma. After the four-year project, most MSTs remain operational and have continued to maintain, enhance, and develop healthy community initiatives through the AHCA. Implications: By using a participatory approach, the AHCA project has demonstrated impact and effectiveness in strengthening community capacity and supportive environments for health. Building on the success of the AHCA in rural communities, CPSI is currently engaging urban communities in the AHCA process to develop, implement, and evaluate healthy community initiatives. In doing so, the AHCA Urban project will leverage lessons learned from the AHCA rural evaluation while adapting to a new context to increase reach and adoption. By combining community knowledge with rigorous research and evaluation, the AHCA is well-positioned to support community health and well-being for all Albertans.
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 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 | 0,218 | 0,118 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,012 | 0,007 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,005 | 0,014 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,001 |
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 ».