Aufsatz(elektronisch)18. Oktober 2023

Examining research systems and models for local government: a systematic review

In: Evidence & policy: a journal of research, debate and practice, S. 1-26

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Abstract

Background:Local authorities (LA) are key in improving population health, and LA public health decision makers need support from appropriately organised research capacity; however, few models of LA research systems are known to exist.
Aims and objectives:To explore potential and existing models of LA-based research systems.
Methods:This mapping review and time-constrained systematic review synthesises conceptual and empirical literature from 12 health and social science databases, grey literature and reference/citation tracking. Three reviewers screened titles, abstracts and full texts of retrieved records, and extracted key data from included papers. Evidence was synthesised based on characteristics of research systems and quality-assessed for relevance, rigour and richness.
Findings:Nine models were examined in depth. From these, we developed a typology of research systems. Few models were specifically designed for LA research activity; as a Whole System approach, the Local Authority Champions of Research model offers a potential blueprint. Useful lessons may be learned from UK Collaborations for Leadership in Applied Health Research, Academic Collaborative Centres in the Netherlands, local Research and Development units in Sweden, and generic University-Community partnerships.
Discussion and conclusions:An optimal research system requires the coexistence of multiple systems including Centre, Partnership, Collaboration, Network and Community types. The review is UK-focused, but the models appear to have wider relevance. Our classification offers those planning an LA research system the opportunity to choose an approach that meets their requirements and resources. A Whole System approach is optimal, with egalitarian input from the LA and academia.

Verlag

Bristol University Press

ISSN: 1744-2656

DOI

10.1332/17442648y2023d000000002

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