Assessing the implementation and outcomes of a food prescription program in Ontario, Canada: A realist evaluation
Notice bibliographique
Résumé
Background: Social prescribing has grown in popularity around the world as a method for health care practitioners to address the social determinants of health. Social prescribing is the process of a practitioner identifying a non-medical, social need in a patient, and then developing a non-medical prescription to connect them to community services. A subset of social prescribing is food prescribing, in which patients who are typically identified as food insecure are connected with services to provide access to nutritious foods. The Fresh Food Prescription Program (FFRx) was implemented beginning in 2021 by the SEED, a working group of the Guelph Community Health Centre (GCHC). Clients of the GCHC who were identified as food insecure and experiencing a cardiometabolic health condition were provided weekly vouchers for fruits and vegetables at the SEED’s online grocery store. \n \nResearch question: The objectives of this research were 1) to describe the experiences of participants with FFRx 2) to evaluate impacts of FFRx on household food security, diet patterns, health, and well-being and 3) to identify how various contexts and mechanisms shaped differential program experiences and outcomes among FFRx participants. \n \nMethods: Semi-structured interviews (n=23) were conducted with FFRx participants along with follow-up focus groups and individual discussions (n=10). Guided by realist evaluation, a hybrid thematic analysis was utilized to identify context, mechanisms, and outcomes in the data. \n \nResults: Three key program outcomes were identified: 1) increased food access; 2) improved physical health and diet quality; and 3) improved mental health. Participants shared that they enjoyed having more food available to them and were able to purchase produce that was previously inaccessible due to financial constraints. Participants also noted that they consumed more fruits and vegetables during the program, as well as less nutrient poor foods. As a consequence, many participants associated their increased consumption of fruits and vegetables with improved physical health symptoms, more energy, and better sleep. Participants highlighted that they felt less stress throughout the program due to the stability of food access, increased social connections, and improved self-esteem. \n \nDiscussion and conclusion: This study builds on current understandings of food prescribing, through demonstrating how these program can benefit participants through enhancing food access as well as self-reported physical and mental health. Importantly, this study also acknowledges the need for long-term, sustainable programming and funding to support food prescribing initiatives. The research elucidated the importance of developing programs that are context-aware and include supportive mechanisms that foster agency among participants. Further, this research serves as a starting point for future realist evaluations to be conducted, and highlights program design elements that could be implemented in future food prescribing programs.
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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 | 0,025 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,011 | 0,004 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,005 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| 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 ».