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Establishing a Health CASCADE–Curated Open-Access Database to Consolidate Knowledge About Co-Creation: Novel Artificial Intelligence–Assisted Methodology Based on Systematic Reviews

BACKGROUND: Co-creation is an approach that aims to democratize research and bridge the gap between research and practice, but the potential fragmentation of knowledge about co-creation has hindered progress. A comprehensive database of published literature from multidisciplinary sources can address...

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Autores principales: Agnello, Danielle Marie, Loisel, Quentin Emile Armand, An, Qingfan, Balaskas, George, Chrifou, Rabab, Dall, Philippa, de Boer, Janneke, Delfmann, Lea Rahel, Giné-Garriga, Maria, Goh, Kunshan, Longworth, Giuliana Raffaella, Messiha, Katrina, McCaffrey, Lauren, Smith, Niamh, Steiner, Artur, Vogelsang, Mira, Chastin, Sebastien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10394503/
https://www.ncbi.nlm.nih.gov/pubmed/37463024
http://dx.doi.org/10.2196/45059
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author Agnello, Danielle Marie
Loisel, Quentin Emile Armand
An, Qingfan
Balaskas, George
Chrifou, Rabab
Dall, Philippa
de Boer, Janneke
Delfmann, Lea Rahel
Giné-Garriga, Maria
Goh, Kunshan
Longworth, Giuliana Raffaella
Messiha, Katrina
McCaffrey, Lauren
Smith, Niamh
Steiner, Artur
Vogelsang, Mira
Chastin, Sebastien
author_facet Agnello, Danielle Marie
Loisel, Quentin Emile Armand
An, Qingfan
Balaskas, George
Chrifou, Rabab
Dall, Philippa
de Boer, Janneke
Delfmann, Lea Rahel
Giné-Garriga, Maria
Goh, Kunshan
Longworth, Giuliana Raffaella
Messiha, Katrina
McCaffrey, Lauren
Smith, Niamh
Steiner, Artur
Vogelsang, Mira
Chastin, Sebastien
author_sort Agnello, Danielle Marie
collection PubMed
description BACKGROUND: Co-creation is an approach that aims to democratize research and bridge the gap between research and practice, but the potential fragmentation of knowledge about co-creation has hindered progress. A comprehensive database of published literature from multidisciplinary sources can address this fragmentation through the integration of diverse perspectives, identification and dissemination of best practices, and increase clarity about co-creation. However, two considerable challenges exist. First, there is uncertainty about co-creation terminology, making it difficult to identify relevant literature. Second, the exponential growth of scientific publications has led to an overwhelming amount of literature that surpasses the human capacity for a comprehensive review. These challenges hinder progress in co-creation research and underscore the need for a novel methodology to consolidate and investigate the literature. OBJECTIVE: This study aimed to synthesize knowledge about co-creation across various fields through the development and application of an artificial intelligence (AI)–assisted selection process. The ultimate goal of this database was to provide stakeholders interested in co-creation with relevant literature. METHODS: We created a novel methodology for establishing a curated database. To accommodate the variation in terminology, we used a broad definition of co-creation that encompassed the essence of existing definitions. To filter out irrelevant information, an AI-assisted selection process was used. In addition, we conducted bibliometric analyses and quality control procedures to assess content and accuracy. Overall, this approach allowed us to develop a robust and reliable database that serves as a valuable resource for stakeholders interested in co-creation. RESULTS: The final version of the database included 13,501 papers, which are indexed in Zenodo and accessible in an open-access downloadable format. The quality assessment revealed that 20.3% (140/688) of the database likely contained irrelevant material, whereas the methodology captured 91% (58/64) of the relevant literature. Participatory and variations of the term co-creation were the most frequent terms in the title and abstracts of included literature. The predominant source journals included health sciences, sustainability, environmental sciences, medical research, and health services research. CONCLUSIONS: This study produced a high-quality, open-access database about co-creation. The study demonstrates that it is possible to perform a systematic review selection process on a fragmented concept using human-AI collaboration. Our unified concept of co-creation includes the co-approaches (co-creation, co-design, and co-production), forms of participatory research, and user involvement. Our analysis of authorship, citations, and source landscape highlights the potential lack of collaboration among co-creation researchers and underscores the need for future investigation into the different research methodologies. The database provides a resource for relevant literature and can support rapid literature reviews about co-creation. It also offers clarity about the current co-creation landscape and helps to address barriers that researchers may face when seeking evidence about co-creation.
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spelling pubmed-103945032023-08-03 Establishing a Health CASCADE–Curated Open-Access Database to Consolidate Knowledge About Co-Creation: Novel Artificial Intelligence–Assisted Methodology Based on Systematic Reviews Agnello, Danielle Marie Loisel, Quentin Emile Armand An, Qingfan Balaskas, George Chrifou, Rabab Dall, Philippa de Boer, Janneke Delfmann, Lea Rahel Giné-Garriga, Maria Goh, Kunshan Longworth, Giuliana Raffaella Messiha, Katrina McCaffrey, Lauren Smith, Niamh Steiner, Artur Vogelsang, Mira Chastin, Sebastien J Med Internet Res Review BACKGROUND: Co-creation is an approach that aims to democratize research and bridge the gap between research and practice, but the potential fragmentation of knowledge about co-creation has hindered progress. A comprehensive database of published literature from multidisciplinary sources can address this fragmentation through the integration of diverse perspectives, identification and dissemination of best practices, and increase clarity about co-creation. However, two considerable challenges exist. First, there is uncertainty about co-creation terminology, making it difficult to identify relevant literature. Second, the exponential growth of scientific publications has led to an overwhelming amount of literature that surpasses the human capacity for a comprehensive review. These challenges hinder progress in co-creation research and underscore the need for a novel methodology to consolidate and investigate the literature. OBJECTIVE: This study aimed to synthesize knowledge about co-creation across various fields through the development and application of an artificial intelligence (AI)–assisted selection process. The ultimate goal of this database was to provide stakeholders interested in co-creation with relevant literature. METHODS: We created a novel methodology for establishing a curated database. To accommodate the variation in terminology, we used a broad definition of co-creation that encompassed the essence of existing definitions. To filter out irrelevant information, an AI-assisted selection process was used. In addition, we conducted bibliometric analyses and quality control procedures to assess content and accuracy. Overall, this approach allowed us to develop a robust and reliable database that serves as a valuable resource for stakeholders interested in co-creation. RESULTS: The final version of the database included 13,501 papers, which are indexed in Zenodo and accessible in an open-access downloadable format. The quality assessment revealed that 20.3% (140/688) of the database likely contained irrelevant material, whereas the methodology captured 91% (58/64) of the relevant literature. Participatory and variations of the term co-creation were the most frequent terms in the title and abstracts of included literature. The predominant source journals included health sciences, sustainability, environmental sciences, medical research, and health services research. CONCLUSIONS: This study produced a high-quality, open-access database about co-creation. The study demonstrates that it is possible to perform a systematic review selection process on a fragmented concept using human-AI collaboration. Our unified concept of co-creation includes the co-approaches (co-creation, co-design, and co-production), forms of participatory research, and user involvement. Our analysis of authorship, citations, and source landscape highlights the potential lack of collaboration among co-creation researchers and underscores the need for future investigation into the different research methodologies. The database provides a resource for relevant literature and can support rapid literature reviews about co-creation. It also offers clarity about the current co-creation landscape and helps to address barriers that researchers may face when seeking evidence about co-creation. JMIR Publications 2023-07-18 /pmc/articles/PMC10394503/ /pubmed/37463024 http://dx.doi.org/10.2196/45059 Text en ©Danielle Marie Agnello, Quentin Emile Armand Loisel, Qingfan An, George Balaskas, Rabab Chrifou, Philippa Dall, Janneke de Boer, Lea Rahel Delfmann, Maria Giné-Garriga, Kunshan Goh, Giuliana Raffaella Longworth, Katrina Messiha, Lauren McCaffrey, Niamh Smith, Artur Steiner, Mira Vogelsang, Sebastien Chastin. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 18.07.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Review
Agnello, Danielle Marie
Loisel, Quentin Emile Armand
An, Qingfan
Balaskas, George
Chrifou, Rabab
Dall, Philippa
de Boer, Janneke
Delfmann, Lea Rahel
Giné-Garriga, Maria
Goh, Kunshan
Longworth, Giuliana Raffaella
Messiha, Katrina
McCaffrey, Lauren
Smith, Niamh
Steiner, Artur
Vogelsang, Mira
Chastin, Sebastien
Establishing a Health CASCADE–Curated Open-Access Database to Consolidate Knowledge About Co-Creation: Novel Artificial Intelligence–Assisted Methodology Based on Systematic Reviews
title Establishing a Health CASCADE–Curated Open-Access Database to Consolidate Knowledge About Co-Creation: Novel Artificial Intelligence–Assisted Methodology Based on Systematic Reviews
title_full Establishing a Health CASCADE–Curated Open-Access Database to Consolidate Knowledge About Co-Creation: Novel Artificial Intelligence–Assisted Methodology Based on Systematic Reviews
title_fullStr Establishing a Health CASCADE–Curated Open-Access Database to Consolidate Knowledge About Co-Creation: Novel Artificial Intelligence–Assisted Methodology Based on Systematic Reviews
title_full_unstemmed Establishing a Health CASCADE–Curated Open-Access Database to Consolidate Knowledge About Co-Creation: Novel Artificial Intelligence–Assisted Methodology Based on Systematic Reviews
title_short Establishing a Health CASCADE–Curated Open-Access Database to Consolidate Knowledge About Co-Creation: Novel Artificial Intelligence–Assisted Methodology Based on Systematic Reviews
title_sort establishing a health cascade–curated open-access database to consolidate knowledge about co-creation: novel artificial intelligence–assisted methodology based on systematic reviews
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10394503/
https://www.ncbi.nlm.nih.gov/pubmed/37463024
http://dx.doi.org/10.2196/45059
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