Exploring methods for creating or adapting knowledge mobilization products for culturally and linguistically diverse audiences: a scoping review
Notice bibliographique
Résumé
BACKGROUND: Connecting end-users to research evidence has the power to improve patient knowledge and inform health decision-making. Differences in the culture and language of the end users may shape the effectiveness of knowledge mobilization (KMb). This scoping review set out to understand current approaches and methods when creating or adapting KMb products for culturally and linguistically diverse (CALD) audiences. METHODS: We searched 3 databases (Ovid Medline, CINAHL via EBSCOhost, PsychINFO) from 2011 until August 2023. We included any literature about KMb product creation or adaptation processes serving CALD communities. A primary reviewer screened all identified publications and a second reviewer screened publications excluded by the primary. Data were extracted using a standardized form by one reviewer and verified by a second reviewer. Studies were categorized by type of adaptations ('surface' and/or 'deep' structure) and mapped based on type of stakeholder engagement used in the research approach (i2S model), and end-user involvement (content, design, evaluation and dissemination) in KMb product creation or adaptation. RESULTS: Ten thousand two hundred ninety-nine unique titles and abstracts were reviewed, 670 full-text studies were retrieved and reviewed, and 78 studies were included in final data extraction and mapping. Twenty-four studies (31%) created or adapted exclusively text-based KMb products such as leaflets and pamphlets and 49 (63%) produced digital products such as videos (n = 16, 33%), mobile applications (n = 14, 29%), and eHealth websites (n = 7, 14%). Twenty-five studies (32%) reported following a framework or theory for their creation or adaptation efforts. Twenty-eight studies (36%) engaged stakeholders in the research approach. Nearly all (96%) involved end-users in creating or adapting the KMb products through involvement in content development (n = 64), design features (n = 52), evaluation (n = 44) and dissemination (n = 20). Thirty-two (41%) studies included reflections from the research teams on the processes for creating or adapting KMb products for CALD communities. CONCLUSION: Included studies cited a variety of methods to create or adapt KMb products for CALD communities. Successful uptake of created or adapted KMb products was often the result of collaboration and involvement with end-users for more applicable, accessible and meaningful products. Further research developing guidance and best practices is needed to support the creation or adaptation of KMb products with CALD communities. REGISTRATION: Protocol submitted to Open Science Framework on August 16, 2022 ( https://osf.io/9jcw4/ ).
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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 | 0,017 | 0,063 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».