Beyond "Two Cultures": Guidance for Establishing Effective Researcher/Health System Partnerships
Notice bibliographique
Résumé
BACKGROUND: The current literature proposing criteria and guidelines for collaborative health system research often fails to differentiate between: (a) various types of partnerships, (b) collaborations formed for the specific purpose of developing a research proposal and those based on long-standing relationships, (c) researcher vs. decision-maker initiatives, and (d) the underlying drivers for the collaboration. METHODS: Qualitative interviews were conducted with 16 decision-makers and researchers who partnered on a Canadian major peer-reviewed grant proposal in 2013. Objectives of this exploration of participants' experiences with health system research collaboration were to: (a) explore perspectives and experience with research collaboration in general; (b) identify characteristics and strategies associated with effective partnerships; and (c) provide guidance for development of effective research partnerships. Interviews were audio-recorded and transcribed: transcripts were qualitatively analyzed using a general inductive approach. RESULTS: Findings suggest that the common "two cultures" approach to research/decision-maker collaboration provides an inadequate framework for understanding the complexity of research partnerships. Many commonly-identified challenges to researcher/knowledge user (KU) collaboration are experienced as manageable by experienced research teams. Additional challenges (past experience with research and researchers; issues arising from previous collaboration; and health system dynamics) may be experienced in partnerships based on existing collaborations, and interact with partnership demands of time and communication. Current research practice may discourage KUs from engaging in collaborative research, in spite of strong beliefs in its potential benefits. Practical suggestions for supporting collaborations designed to respond to real-time health system challenges were identified. CONCLUSION: Participants' experience with previous research activities, factors related to the established collaboration, and interpersonal, intra- and inter-organizational dynamics may present additional challenges to research partnerships built on existing collaboration. Differences between researchers and KUs may pose no greater challenges than differences among KUs (at various levels, and representing diverse perspectives and organizations) themselves. Effective "relationship brokering" is essential for meaningful collaboration.
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 | 0,017 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».