Co-learning commentary: a patient partner perspective in mental health care research
Notice bibliographique
Résumé
BACKGROUND: Although including patients as full, active members of research teams is becoming more common, there are few accounts about how to do so successfully, and almost none of these are written by patient partners themselves. Three patient partners contributed their lived experience to a three-year, multi-component mental health research project in British Columbia, Canada. As patient partners, we contributed to innovative co-learning in this project, resulting in mutual respect and wide-ranging benefits. To guide future patient partners and researchers seeking patient engagement, we outline the processes that helped our research team 'get it right'. MAIN BODY: From the outset, we were integrated into components of the project that we chose: thematically coding a rapid review, developing questions and engagement processes for focus groups, and shaping an economic model. Our level of engagement in each component was determined by us. Additionally, we catalyzed the use of surveys to evaluate our engagement and the perceptions of patient engagement from the wider team. At our request, we had a standing place on each monthly meeting agenda. Importantly, we broke new ground when we moved the team from using previously accepted psychiatric terminology that no longer fit the reality of patients' experiences. We worked diligently with the team to represent the reality that was appropriate for all parties. The approach taken in this project led to meaningful and successfully integrated patient experiences, fostered a shared understanding, which positively impacted team development and cohesion. The resulting 'lessons learned' included engaging early, often, and with respect; carving out and creating a safe place, free from stigma; building trust within the research team; drawing on lived experience; co-creating acceptable terminology; and cultivating inclusivity throughout the entire study. CONCLUSION: We believe that lived experience can and should go hand-in-hand with research, to ensure study outcomes reflect the knowledge of patients themselves. We were willing to share the truth of our lived experience. We were treated as co-researchers. Successful engagement came from the 'lessons learned' that can be used by other teams who wish to engage patient partners in health research.
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 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 | 0,026 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,009 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,024 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».