Methods of mobilizing collective intelligence through crowdsourcing: a scoping review

Article type
Authors
Nguyen TV1, Benchoufi M1, Young B2, El Chall L1, Ravaud P1, Boutron I1
1INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of Therapeutic Evaluation of Chronic Diseases Team (METHODS), Paris
2Department of Psychological Sciences, Institute of Psychology, Health and Society, University of Liverpool
Abstract
Background:
Collective intelligence (CI) defined as shared intelligence emerging from a group of people when they work on the same tasks, is a cornerstone of science where researchers interact and collaborate. However, a new kind of CI through crowdsourcing is emerging by inclusively mobilizing people who are not usually involved in research to create more innovative outcomes. Thus, to determine whether CI through crowdsourcing could change how research is performed, we need an in-depth understanding of how it is being used in different fields.

Objectives:
This scoping review aims to describe methods of mobilizing CI through crowdsourcing in different fields.

Methods:
We searched six databases for all reports describing a project that had applied methods of CI through crowdsourcing. We extracted data on:
1) purposes of using CI;
2) type of participants;
3) motivation;
4) type of participants’ contribution;
5) type of interaction between participants; and
6) methods to evaluate participants’ contribution and decision making.
We applied content analysis to develop themes and categories inductively for each domain.

Results: We identified 141 reports. Most research projects (76%) were open to the public without restrictions on the expertise of participants. Incentives to participants and intrinsic motivation were reported in 74% of articles. Independent contribution (i.e. no interaction with other participants) (37%), collaboration (31%), competitions (26%), and playing games (11%), were the methods by which participants contributed to projects. Overall, 61% of articles reported methods to evaluate participants’ contribution and decision-making process with 18% involving end-users in evaluation and decision making.

Conclusions:
Our results provide an in-depth description of methods for mobilizing CI, and we propose a framework to facilitate its use in research.

Patient or healthcare consumer involvement:
Current patient involvement practices often involve a narrow group of patients. CI through crowdsourcing focuses on opening the process inclusively to harness the ability of a diverse population to enrich research with new innovative ideas from different perspectives. Thus, this approach can be used to enhance patient involvement in research.