Methods of mobilizing collective intelligence through crowdsourcing: a scoping review

ID: 

304

Session: 

Poster session 3

Date: 

Tuesday 18 September 2018 - 12:30 to 14:00

All authors in correct order:

Nguyen TV1, Benchoufi M1, Young B2, El Chall L1, Ravaud P1, Boutron I1
1 INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of Therapeutic Evaluation of Chronic Diseases Team (METHODS), Paris, France
2 Department of Psychological Sciences, Institute of Psychology, Health and Society, University of Liverpool, UK
Presenting author and contact person

Presenting author:

Thu Van Nguyen

Contact person:

Thu Van Nguyen
Abstract text
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.

Relevance to patients and consumers: 

Current patient involvement practices often involve a narrow group of patients. Access for more patients with diverse perspectives would gain relevant knowledge and more applicable results. Collective intelligence (CI) through crowdsourcing focuses on opening the process inclusively to harness the ability of a diverse population. With different methods to approach a large population and improve communication within that community, CI through crowdsourcing enables participants to contribute their ideas regardless of their background. Thus, this approach can be applied to increase the involvement of more diverse groups of patients in research.