The development of the Evaluation Toolkit for the Alberta Healthy Communities Approach (AHCA)
Notice bibliographique
Résumé
Background: An evaluation toolkit was developed by Alberta Health Services to support rural community members in determining and evaluating the outcomes of healthy community initiatives from the Alberta Healthy Communities Approach (AHCA) project. Approach: Many community leaders and volunteers in Alberta rural communities are heavily involved in the health promotion and community development work. While they have a strong understanding of the needs and strengths of their communities and are highly capable of implementing healthy community initiatives, community members may lack the capacity and/or resources for evaluation. Understanding the process, outcome, and impact of healthy community initiatives and sharing success stories to wider audience are vital to implementation and sustainability. To address this gap, the Cancer Prevention and Screening Innovation (CPSI) unit at Alberta Health Services developed an evaluation toolkit to support community partners in evaluating their own initiatives. The evaluation toolkit includes key features such as the purpose and importance of conducting evaluation, a decision tree to help determine the most appropriate evaluation methods for different types of initiatives, assessment templates that are customizable based on the communities needs and preferences, and a survey bank that provides questions to be incorporated into the assessment templates. It aims to build community capacity by providing resources such as customizable data collection tools like surveys, observational assessments, and interview questions, and other creative and culturally sensitive data collection methods. The toolkit also aims to reduce barriers and facilitate collection of meaningful feedback from community members, and to better document the impact of the initiatives. Results: With the guidance of the evaluation toolkit, it strengthened capacity of leaders from 9 rural communities to develop and take ownership of evaluating their healthy community initiatives. As a result, over twenty community surveys involving 500+ respondents were conducted. Community members became more engaged and informed in the process of evaluation, with some results being presented to leadership and town hall meetings. Several communities also utilized these results to apply for additional grants to continue their health promotion efforts. Additionally, twelve digital stories showcasing the AHCA project were posted online, further disseminating the project's impact. Implications: The development and utilization of the evaluation toolkit played a pivotal role in ensuring that communities to effectively implement and evaluate their health promotion initiatives. By building community capacity and providing a user-friendly solution for evaluation, the CPSI aims to bridge the gap between implementation and evaluation. The AHCA project continues to support partnering communities in sharing their visions and hard work by measuring progress, disseminating results through various channels, and engaging diverse stakeholders.
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 | 0,205 | 0,142 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,005 | 0,005 |
| Communication savante | 0,008 | 0,004 |
| Science ouverte | 0,007 | 0,013 |
| Intégrité de la recherche | 0,002 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,004 |
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 ».