Health TAPESTRY: co-designing interprofessional primary care programs for older adults using the persona-scenario method
Notice bibliographique
Résumé
BACKGROUND: Working with patients and health care providers to co-design health interventions is gaining global prominence. While co-design of interventions is important for all patients, it is particularly important for older adults who often experience multiple and complex chronic conditions. Persona-scenarios have been used by designers of technology applications. The purpose of this paper is to explore how a modified approach to the persona-scenario method was used to co-design a complex primary health care intervention (Health TAPESTRY) by and for older adults and providers and the value added of this approach. METHODS: The persona-scenario method involved patient and clinician participants from two academically-linked primary care practices. Local prospective volunteers and community service providers (e.g., home care services, support services) were also recruited. Persona-scenario workshops were facilitated by researchers experienced in qualitative methods. Working mostly in homogenous pairs, participants created a fictitious but authentic persona that represented people like themselves. Core components of the Health TAPESTRY intervention were described. Then, participants created a story (scenario) involving their persona and an aspect of the proposed Health TAPESTRY program (e.g., volunteer roles). Two stages of analysis involved descriptive identification of themes, followed by an interpretive phase to extract possible actions and products related to ideas in each theme. RESULTS: Fourteen persona-scenario workshops were held involving patients (n = 15), healthcare providers/community care providers (n = 29), community service providers (n = 12), and volunteers (n = 14). Fifty themes emerged under four Health TAPESTRY components and a fifth category - patient. Eight cross cutting themes highlighted areas integral to the intervention. In total, 414 actions were identified and 406 products were extracted under the themes, of which 44.8% of the products (n = 182) were novel. The remaining 224 had been considered by the research team. CONCLUSIONS: The persona-scenario method drew out feasible novel ideas from stakeholders, which expanded on the research team's original ideas and highlighted interactions among components and stakeholder groups. Many ideas were integrated into the Health TAPESTRY program's design and implementation. Persona-scenario method added significant value worthy of the added time it required. This method presents a promising alternative to active engagement of multiple stakeholders in the co-design of complex interventions.
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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 | 0,020 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 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 ».