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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

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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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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. 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spelling v2 67028 2024-07-09 Optimising and profiling pre-implementation contexts to create and implement a public health network intervention for tackling loneliness 06b53a31f254b004de8649a376ce2fbd 0000-0001-5403-1708 Becky Band Becky Band true false 2024-07-09 HSOC 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. Journal Article Implementation Science 15 1 Springer Science and Business Media LLC 1748-5908 19 5 2020 2020-05-19 10.1186/s13012-020-00997-x COLLEGE NANME Health and Social Care School COLLEGE CODE HSOC Swansea University 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. 2024-09-02T14:50:28.4232020 2024-07-09T15:23:12.5007550 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Biomedical Science J. Ellis 0000-0003-0068-3318 1 Becky Band 0000-0001-5403-1708 2 K. Kinsella 3 T. Cheetham-Blake 4 E. James 5 S. Ewings 6 A. Rogers 7 67028__31225__a005ebcdfd154e92b8365699866e317b.pdf 67028.VoR.pdf 2024-09-02T14:49:18.5122068 Output 417208 application/pdf Version of Record true This article is licensed under a Creative Commons Attribution 4.0 International License. true eng http://creativecommons.org/licenses/by/4.0/
title Optimising and profiling pre-implementation contexts to create and implement a public health network intervention for tackling loneliness
spellingShingle Optimising and profiling pre-implementation contexts to create and implement a public health network intervention for tackling loneliness
Becky Band
title_short Optimising and profiling pre-implementation contexts to create and implement a public health network intervention for tackling loneliness
title_full Optimising and profiling pre-implementation contexts to create and implement a public health network intervention for tackling loneliness
title_fullStr Optimising and profiling pre-implementation contexts to create and implement a public health network intervention for tackling loneliness
title_full_unstemmed Optimising and profiling pre-implementation contexts to create and implement a public health network intervention for tackling loneliness
title_sort Optimising and profiling pre-implementation contexts to create and implement a public health network intervention for tackling loneliness
author_id_str_mv 06b53a31f254b004de8649a376ce2fbd
author_id_fullname_str_mv 06b53a31f254b004de8649a376ce2fbd_***_Becky Band
author Becky Band
author2 J. Ellis
Becky Band
K. Kinsella
T. Cheetham-Blake
E. James
S. Ewings
A. Rogers
format Journal article
container_title Implementation Science
container_volume 15
container_issue 1
publishDate 2020
institution Swansea University
issn 1748-5908
doi_str_mv 10.1186/s13012-020-00997-x
publisher Springer Science and Business Media LLC
college_str Faculty of Medicine, Health and Life Sciences
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hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Biomedical Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Biomedical Science
document_store_str 1
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description 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.
published_date 2020-05-19T14:50:26Z
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