eprintid: 10158002
rev_number: 8
eprint_status: archive
userid: 699
dir: disk0/10/15/80/02
datestamp: 2023-05-11 15:53:56
lastmod: 2023-05-11 15:53:56
status_changed: 2023-05-11 15:53:56
type: conference_item
metadata_visibility: show
sword_depositor: 699
creators_name: O'Mara-Eves, Alison
creators_name: Kneale, Dylan
creators_name: Oliver, Sandy
creators_name: Cain, Lizzie
creators_name: Hutchinson Pascal, Niccola
creators_name: Catchpole, Jessica
creators_name: Chesworth, Angela
creators_name: Candy, Bridget
creators_name: Sutcliffe, Katy
creators_name: Thomas, James
title: How co-production underpinned the development of a logic model and testing of novel statistical methods for evidence synthesis
ispublished: pub
divisions: B14
divisions: J81
divisions: B16
divisions: UCL
keywords: co-production, logic model, evidence synthesis, systematic review, meta-analysis
abstract: Background: The CEPHI project sought to develop and test four methods for synthesizing evidence that better accounted for context than standard statistical meta-analysis approaches. To explore context, we had to understand what was important in different contexts. We identified co-production as an approach to achieve this. /

Methods: Supported by the Co-Production Collective, we worked closely with an Advisory Group of people with lived, professional, and/or academic expertise. We held a series of workshops with others bringing lived, professional, and/or academic expertise, to co-produce a logic model that subsequently informed novel synthesis methods. Evaluation of the co-production element was through reflexive notes, feedback from participants, and discussions during and after the project. /

Results: The impact of co-production was profound. It fundamentally redesigned the entire logic model. This enabled novel statistical methods to answer important questions about context and impact. There were emotional impacts (highs and lows) and resource implications. /

Discussion: Co-production is a powerful way to develop logic models and to inform synthesis methods development, by focusing on what is important to the affected communities. We will discuss lessons learned, what we would do differently next time, and what might be some of the key conditions and mechanisms for meaningful co-production.
date: 2022-10-20
date_type: published
official_url: https://wwgs2022.mailchimpsites.com/
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1984256
lyricists_name: O'Mara-Eves, Alison
lyricists_id: AJOMA15
actors_name: O'Mara-Eves, Alison
actors_id: AJOMA15
actors_role: owner
full_text_status: public
pres_type: presentation
event_title: 2022 What Works Global Summit (WWGS)
event_location: Virtual conference
event_dates: 18 - 20 October 2022
citation:        O'Mara-Eves, Alison;    Kneale, Dylan;    Oliver, Sandy;    Cain, Lizzie;    Hutchinson Pascal, Niccola;    Catchpole, Jessica;    Chesworth, Angela;             ... Thomas, James; + view all <#>        O'Mara-Eves, Alison;  Kneale, Dylan;  Oliver, Sandy;  Cain, Lizzie;  Hutchinson Pascal, Niccola;  Catchpole, Jessica;  Chesworth, Angela;  Candy, Bridget;  Sutcliffe, Katy;  Thomas, James;   - view fewer <#>    (2022)    How co-production underpinned the development of a logic model and testing of novel statistical methods for evidence synthesis.                   Presented at: 2022 What Works Global Summit (WWGS), Virtual conference.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10158002/1/221020%20WWGS%20How%20co-production%20underpinned%20the%20development%20of%20a%20logic%20model_final.pdf