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Optimising and profiling pre-implementation contexts to create and implement a public health network intervention for tackling loneliness

J. Ellis Orcid Logo, Becky Band Orcid Logo, K. Kinsella, T. Cheetham-Blake, E. James, S. Ewings, A. Rogers

Implementation Science, Volume: 15, Issue: 1

Swansea University Author: Becky Band Orcid Logo

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DOI (Published version): 10.1186/s13012-020-00997-x

Abstract

BackgroundThe implementation of complex interventions experiences challenges that affect the extent to which they become embedded and scaled-up. Implementation at scale in complex environments like community settings defies universal replication. Planning for implementation in such environments requ...

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Published in: Implementation Science
ISSN: 1748-5908
Published: Springer Science and Business Media LLC 2020
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URI: https://cronfa.swan.ac.uk/Record/cronfa67028
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Abstract: BackgroundThe implementation of complex interventions experiences challenges that affect the extent to which they become embedded and scaled-up. Implementation at scale in complex environments like community settings defies universal replication. Planning for implementation in such environments requires knowledge of organisational capacity and structure. Pre-implementation work is an important element of the early phase of preparing the setting for the introduction of an intervention, and the factors contributing towards the creation of an optimal pre-implementation community context are under-acknowledged.MethodsTo explore the factors contributing towards the creation of an optimal pre-implementation context, a quasi-ethnographic approach was taken. The implementation of a social network intervention designed to tackle loneliness in a community setting acts as the case in example. Observations (of meetings), interviews (with community partners) and documentary analysis (national and local policy documents and intervention resources) were conducted. Layder’s adaptive theory approach was taken to data analysis, with the Consolidated Framework for Implementation Research (CFIR) and a typology of third-sector organisations used to interpret the findings.ResultsCommunity settings were found to sit along a continuum with three broad categories defined as Fully Professionalised Organisations; Aspirational Community, Voluntary and Social Enterprises; and Non-Professionalised Community-Based Groups. The nature of an optimal pre-implementation context varied across these settings. Using the CFIR, the results illustrate that some settings were more influenced by political landscape (Fully professional and Aspirational setting) and others more influenced by their founding values and ethos (Non-Professionalised Community-Based settings). Readiness was achieved at different speeds across the categories with those settings with more resource availability more able to achieve readiness (Fully Professional settings), and others requiring flexibility in the intervention to help overcome limited resource availability (Aspirational and Non-Professionalised Community-Based settings).ConclusionsThe CFIR is useful in highlighting the multiple facets at play in creating the optimal pre-implementation context, and where flex is required to achieve this. The CFIR illuminates the similarities and differences between and across settings, highlighting the complexity of open system settings and the important need for pre-implementation work.
College: Faculty of Medicine, Health and Life Sciences
Funders: This paper summarises independent research funded by the National Institute for Health Research (NIHR) under its Public Health Research Programme (Grant Reference Number 16/08/41). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Care.
Issue: 1

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