Storytelling for impact: the creation of a storytelling program for patient partners in research
Notice bibliographique
Résumé
Storytelling is a powerful means to evoke empathy and understanding among people. When patient partners, which include patients, family members, caregivers and organ donors, share their stories with health professionals, this can prompt listeners to reflect on their practice and consider new ways of driving change in the healthcare system. However, a growing number of patient partners are asked to 'share their story' within health care and research settings without adequate support to do so. This may ultimately widen, rather than close, the gap between healthcare practitioners and people affected by chronic disease in this new era of patient and public involvement in research. To better support patient partners with storytelling in the context of a patient-oriented research network, Canadians Seeking Solutions and Innovations to Overcome Chronic Kidney Disease (Can-SOLVE CKD) Network adapted an existing in-person storytelling workshop for patient educators within a hospital setting. The result is a 6-week virtual program called Storytelling for Impact, which guides patients, family members, caregivers and organ donors in developing impactful stories and sharing them at health care and research events, e.g., conferences. The online series of synchronous workshops is co-facilitated by story coaches, who are program alumni and Can-SOLVE CKD staff with trained storytelling experience. Each story follows a structure that includes a call to action, which aims to positively impact the priority-setting and delivery of care and research in Canada. The program has been a transformational process for many who have completed it, and numerous other health organizations have expressed interest in sharing this tool with their own patient partners. As result, we have also created an asynchronous online program that can be used by other interested parties outside our network. Patient partners who share their stories can be powerful mediators for inspiring changes in the health care and research landscape, with adequate structured support. We describe two novel programs to support patient partners in impactful storytelling, which are applicable across all health research disciplines. Additional resources are required for sustainability and scale up of training, by having alumni train future storytellers.
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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 | 0,019 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,003 |
| 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 ».