Partnering with People with Lived/Living Experience of Mental Health and substance Use in Participatory Evaluation of an integrated virtual navigation support service for people experiencing substance use challenges.
Notice bibliographique
Résumé
Introduction/Background: This presentation shares how the Mid-West Toronto-Ontario Health Team (MWT-OHT) in Toronto, Canada involved patients and partners in the design, implementation, and evaluation of the “In Your Corner Program” to support people with substance use challenges. The experience of embedding the voices of people with living/lived experience in co-designing and evaluating the program will be shared. Who is it for? The “In Your Corner” program represents the actualization of key recommendations from people with lived/living experience with substance use challenges in MWT-OHT that identified a need for service navigation supports that helps to close transition gaps. The ‘In Your Corner’ program necessitated the MWT-OHT to take a collaborative, team, and consensus-based approach to coordinating services across the region, re-designing care pathways that better meet the needs of a dynamic and diverse population within the constraints of existing resources and structures. Who did you involve & engage with? The MWT-OHT brings together partners across health and social sectors in the mid-west downtown region of Toronto Canada to work together for better, more integrated care. In 2019, MWT-OHT completed co-design work with people with living/lived experiences of substance use and mental health focused on improving the care experience and outcomes for people with challenges related to substance use. The In Your Corner program was implemented in 2021 through a 5-month implementation funding and extended for an additional 4 months through in-kind support from implementation partners. During this time, a participatory evaluation approach was employed with partners as well as clients and providers of the program to inform next steps, scale, and sustainability. What results did you get? What impact did you have? Initial implementation findings of the program demonstrated that the model of care capitalizes on existing programs and was able to create a more robust scaffolding for integrated care for the clients served by the program. The opportunity to embed Peer support workers into the model was highlighted along with the need for follow-up supports over a longer period. The program was a first step toward working together with people with living and lived experiences from design to evaluation from a partnered approach that is hoped to be embedded in how the MWT-OHT approaches all initiatives. What is the learning for the international audience? The learnings from this program demonstrates the processes and supports needed to meaningfully embed the voices of patients and providers from design phase through implementation, evaluation, and scale at various points in the journey from a systems perspective. Considerations for scale are important, as well as minimizing and preventing tokenism and supporting true partnering. What are the next steps? Next steps identified from the co-design evaluation sessions with clients and providers of the In Your Corner Program have informed how to leverage, change, and scale the program to reach more people in the region with substance use challenges. More importantly, this process has become a blueprint for the MWT-OHT in how to embed the voices of patients, families, and caregivers in the designing and evaluating initiatives.
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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 | 0,048 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,011 | 0,006 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,013 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 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 ».