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Methodological pluralism for better evaluations of complex interventions: lessons from evaluating an innovation platform in Australia

Complex interventions, such as innovation platforms, pose challenges for evaluators. A variety of methodological approaches are often required to build a more complete and comprehensive understanding of how complex interventions work. In this paper, we outline and critically appraise a methodologica...

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Detalles Bibliográficos
Autores principales: Bailie, J., Cunningham, F., Abimbola, S., Laycock, A., Bainbridge, R., Bailie, R., Conte, K., Passey, M., Peiris, D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8796351/
https://www.ncbi.nlm.nih.gov/pubmed/35090472
http://dx.doi.org/10.1186/s12961-022-00814-5
Descripción
Sumario:Complex interventions, such as innovation platforms, pose challenges for evaluators. A variety of methodological approaches are often required to build a more complete and comprehensive understanding of how complex interventions work. In this paper, we outline and critically appraise a methodologically pluralist evaluation of an innovation platform to strengthen primary care for Aboriginal and Torres Strait Islander Australians. In doing so, we aim to identify lessons learned from the approach taken and add to existing literature on implementing evaluations in complex settings, such as innovation platforms. The pluralist design used four evaluation approaches—developmental evaluation, principles-focused evaluation, network analysis, and framework analysis—with differing strengths and challenges. Taken together, the multiple evaluation approaches yielded a detailed description and nuanced understanding of the formation, functioning and outcomes of the innovation platform that would be difficult to achieve with any single evaluation method. While a methodologically pluralist design may place additional pressure on logistical and analytic resources available, it enables a deeper understanding of the mechanisms that underlie complex interventions.