Multisite Agricultural Veterans Affairs Farming and Recovery Mental Health Services (VA FARMS) Pilot Program: Protocol for a Responsive Mixed Methods Evaluation Study
Notice bibliographique
Résumé
BACKGROUND: Veterans Affairs Farming and Recovery Mental Health Services (VA FARMS) is an innovative pilot program to provide supportive resources for veterans with interests in agricultural vocations. Implemented at 10 pilot sites, VA FARMS will provide mental health services and resources for veterans while supporting training in gardening and agriculture. As each pilot site project has unique goals, outreach strategies, and implementation efforts based on the local environment and veteran population, evaluating the pilot program provides a unique challenge for evaluators. This paper describes the protocol to evaluate VA FARMS, which was specifically designed to enable site variation by providing both site-specific and cross-site understanding of site implementation processes and outcomes. OBJECTIVE: The objectives of this paper are to (1) describe the protocol used for evaluating VA FARMS, as an innovative Department of Veterans Affairs (VA) agriculturally based, mental health, and employment pilot program serving veterans at 10 pilot sites across the Veterans Health Administration enterprise; and (2) provide guidance to other evaluators assessing innovative programs. METHODS: This evaluation uses the context, inputs, process, product (CIPP) model, which evaluates a program's content and implementation to identify strengths and areas for improvement. Data collection will use a concurrent mixed methods approach. Quantitative data collection will involve quarterly program surveys, as well as three individual veteran participant surveys administered upon the veteran's entrance and exit of the pilot program and 3 months postexit. Quantitative data will include baseline descriptive statistics and follow-up statistics on veteran health care utilization, health care status, and agriculture employment status. Qualitative data collection will include participant observation at each pilot site, and interviews with participants, staff, and community stakeholders. Qualitative data will provide insights about pilot program implementation processes, veterans' experiences, and short-term participation outcomes. RESULTS: Evaluation efforts began in December 2018 and are ongoing. Between October 2018 and September 2020, 494 veterans had enrolled in VA FARMS and 1326 veterans were reached through program activities such as demonstrations, informational presentations, and town-hall discussions. A total of 1623 community members and 655 VA employees were similarly reached by VA FARMS programming during that time. Data were collected between October 2018 and September 2020 in the form of 336 veteran surveys, 30 veteran interviews, 27 staff interviews, and 11 community partner interviews. Data analysis is expected to be completed by October 2022. CONCLUSIONS: This evaluation protocol will provide guidance to other evaluators assessing innovative programs. In its application to the VA FARMS pilot, the evaluation aims to add to existing literature on nature-based therapies and the rehabilitation outcomes of agricultural training programs for veterans. Results will provide programmatic insights on the implementation of pilot programs, along with needed improvements and modifications for the future expansion of VA FARMS and other veteran-focused agricultural programs. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/40496.
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.
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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 | 0,009 | 0,000 |
| 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 | 0,003 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| 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 ».