Establishing a Health CASCADE-Curated Open-Access Database to Consolidate Knowledge About Co-Creation: Novel Artificial Intelligence-Assisted Methodology Based on Systematic Reviews.
J Med Internet Res
; 25: e45059, 2023 07 18.
Article
en En
| MEDLINE
| ID: mdl-37463024
ABSTRACT
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.Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Inteligencia Artificial
/
Investigación Biomédica
Tipo de estudio:
Guideline
/
Prognostic_studies
/
Systematic_reviews
Límite:
Humans
Idioma:
En
Año:
2023
Tipo del documento:
Article