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Crowdsourcing applications for public health.
Daren C Brabham1, Kurt M Ribisl2, Thomas R Kirchner3
1Annenberg School for Communication and Journalism, University of Southern California, Los Angeles, California.
Crowdsourcing, using collective intelligence, offers untapped potential for public health. This paper outlines a framework and approaches for its application in public health science and practice.
Area of Science:
- Public Health
- Information Science
- Computer Science
Background:
- Crowdsourcing leverages networked communities' collective intelligence for problem-solving and production.
- While beneficial in many sectors, crowdsourcing's application in public health remains underexplored.
- Effective frameworks are needed to harness crowdsourcing for public health advancements.
Purpose of the Study:
- To define crowdsourcing's core components.
- To propose a framework for understanding crowdsourcing's utility in public health.
- To enumerate potential applications of crowdsourcing in public health.
Main Methods:
- Literature review and conceptual framework development.
- Description of four discrete crowdsourcing approaches: knowledge discovery and management, distributed human intelligence tasking, broadcast search, and peer-vetted creative production.
- Identification and enumeration of potential public health applications.
Main Results:
- Crowdsourcing models can be applied to public health challenges.
- Four distinct crowdsourcing approaches offer varied functionalities for public health.
- Numerous potential applications exist across public health science and practice.
Conclusions:
- Crowdsourcing presents a significant, yet largely unrealized, opportunity for public health.
- A structured framework can guide the strategic implementation of crowdsourcing in public health.
- Further research and pilot projects are warranted to explore specific applications and optimize outcomes.
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