Integrating citizen engagement into evidence-informed health policy-making in eastern Europe and central Asia: scoping study and future research priorities
Notice bibliographique
Résumé
BACKGROUND: The perspectives of citizens are an important and often overlooked source of evidence for informing health policy. Despite growing encouragement for its adoption, little is known regarding how citizen engagement may be integrated into evidence-informed health policy-making in low- and middle-income counties (LMICs) and newly democratic states (NDSs). We aimed to identify the factors and variables affecting the potential integration of citizen engagement into evidence-informed health policy-making in LMICs and NDSs and understand whether its implementation may require a different approach outside of high-income western democracies. Further, we assessed the context-specific considerations for the practical implementation of citizen engagement in one focus region-eastern Europe and central Asia. METHODS: First, adopting a scoping review methodology, we conducted and updated searches of six electronic databases, as well as a comprehensive grey literature search, on citizen engagement in LMICs and NDSs, published before December 2019. We extracted insights about the approaches to citizen engagement, as well as implementation considerations (facilitators and barriers) and additional political factors, in developing an analysis framework. Second, we undertook exploratory methods to identify relevant literature on the socio-political environment of the focus region, before subjecting these sources to the same analysis framework. RESULTS: Our searches identified 479 unique sources, of which 28 were adjudged to be relevant. The effective integration of citizen engagement within policy-making processes in LMICs and NDSs was found to be predominantly dependent upon the willingness and capacity of citizens and policy-makers. In the focus region, the implementation of citizen engagement within evidence-informed health policy-making is constrained by a lack of mutual trust between citizens and policy-makers. This is exacerbated by inadequate incentives and capacity for either side to engage. CONCLUSIONS: This research found no reason why citizen engagement could not adopt the same form in LMICs and NDSs as it does in high-income western democracies. However, it is recognized that certain political contexts may require additional support in developing and implementing citizen engagement, such as through trialling mechanisms at subnational scales. While specifically outlining the potential for citizen engagement, this study highlights the need for further research on its practical implementation.
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 | 0,040 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,005 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,002 |
| 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 ».