The application of crowdsourcing approaches to cancer research: a systematic review

• Published in: Cancer medicine (Malden, MA) MA), 2017-11, Vol.6 (11), p.2595-2605
• Main Authors: Lee, Young Ji, Arida, Janet A., Donovan, Heidi S.
• Format: Article
• Language: English
• Subjects: Biomedical Research - methods; Biopsy; Cancer; Cancer research; Cancer/neoplasm; citizen science; citizen scientists; Clinical Cancer Research; crowdsourced; Crowdsourcing; Crowdsourcing - methods; Data collection; diffusion of innovation; Health Knowledge, Attitudes, Practice; Humans; Intelligence; Internet; Medical research; Neoplasms - pathology; Neoplasms - therapy; Patient Care Planning; Prostate; Randomized Controlled Trials as Topic; Research Design; Review; Skin; Studies; Survival
• ISSN: 2045-7634; 2045-7634
• DOI: 10.1002/cam4.1165

Crowdsourcing is “the practice of obtaining participants, services, ideas, or content by soliciting contributions from a large group of people, especially via the Internet.” (Ranard et al. J. Gen. Intern. Med. 29:187, 2014) Although crowdsourcing has been adopted in healthcare research and its potential for analyzing large datasets and obtaining rapid feedback has recently been recognized, no systematic reviews of crowdsourcing in cancer research have been conducted. Therefore, we sought to identify applications of and explore potential uses for crowdsourcing in cancer research. We conducted a systematic review of articles published between January 2005 and June 2016 on crowdsourcing in cancer research, using PubMed, CINAHL, Scopus, PsychINFO, and Embase. Data from the 12 identified articles were summarized but not combined statistically. The studies addressed a range of cancers (e.g., breast, skin, gynecologic, colorectal, prostate). Eleven studies collected data on the Internet using web‐based platforms; one recruited participants in a shopping mall using paper‐and‐pen data collection. Four studies used Amazon Mechanical Turk for recruiting and/or data collection. Study objectives comprised categorizing biopsy images (n = 6), assessing cancer knowledge (n = 3), refining a decision support system (n = 1), standardizing survivorship care‐planning (n = 1), and designing a clinical trial (n = 1). Although one study demonstrated that “the wisdom of the crowd” (NCI Budget Fact Book, 2017) could not replace trained experts, five studies suggest that distributed human intelligence could approximate or support the work of trained experts. Despite limitations, crowdsourcing has the potential to improve the quality and speed of research while reducing costs. Longitudinal studies should confirm and refine these findings. Crowdsourcing has the potential to improve the quality and speed of cancer research while reducing costs. Thus, it is critical to increase the visibility and accessibility of crowdsourcing methods, perhaps by providing online educational offerings to cancer researchers.