JMIR Publications

ABSTRACT

Background:

Co-creation is increasingly seen as a way to democratize research and bridge the implementation gap between research and practice. Despite promises of increased effectiveness, relevance, and uptake of health interventions, progress is hindered by the lack of comprehensive and consolidated knowledge about co-creation. Assembling this knowledge into a database is a crucial step toward making co-creation a more robust, trustworthy, and evidence-based methodology. However, there are two considerable challenges to achieving this. First, there is a lack of clarity and standardization of the terminology about co-creation. Second, the rapid increase in scientific publishing means that obtaining comprehensive knowledge requires dealing with a vast body of literature, which is beyond human capacity.

Objective:

This study aimed to develop a curated database consolidating literature published about co-creation in diverse fields. The objectives were to pull together relevant literature for stakeholders interested in co-creation and its use, and to better understand the co-creation landscape and the potential causes of fragmentation.

Methods:

To comprehensively include relevant literature, this study developed a novel methodology by combining attributes of systematic review methodology (eg, Preferred Reporting Items for Systematic Reviews and Meta-Analyses) with artificial intelligence technology. We set a broad definition of co-creation that captured the essence of existing definitions, and was inclusive of fields beyond public health, while still accommodating the variation in terminology. We then relied on artificial intelligence to effectively filter out irrelevant information. We also implemented a bibliometric analysis and a quality control procedure to assess the content and accuracy of the database.

Results:

The final version of the database includes 13,501 papers, which are indexed in Zenodo and accessible in an open-access downloadable format. The quality assessment showed that 20.35% (140/688) of the database likely contains irrelevant material, and that it captured 90.62% (58/64) of the relevant literature. Participatory, and forms of the term co-creation, occurred most frequently in the title and abstracts of included literature. Furthermore, the analysis of authorship, citations, and the source landscape, indicates that there is little collaboration within and between fields using co-creation.

Conclusions:

This study produced a high-quality curated open-access database consolidating the literature about co-creation. In doing so, the study demonstrates that it is possible to consolidate knowledge about diffuse concepts using a combination of human and artificial intelligence. Through the bibliometric analysis, this study also visualizes the current co-creation landscape and the potential causes of fragmentation. The database lifts the main barrier that most researchers and practitioners will face in seeking evidence about co-creation, namely, the fragmentation of knowledge and the ensuing dilemma of having to deal with a vast amount of information. This database makes it possible to perform rapid literature reviews about co-creation.