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The application of crowdsourcing approaches to cancer research: a systematic review
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 poten...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5673951/ https://www.ncbi.nlm.nih.gov/pubmed/28960834 http://dx.doi.org/10.1002/cam4.1165 |
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author | Lee, Young Ji Arida, Janet A. Donovan, Heidi S. |
author_facet | Lee, Young Ji Arida, Janet A. Donovan, Heidi S. |
author_sort | Lee, Young Ji |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5673951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-56739512017-11-15 The application of crowdsourcing approaches to cancer research: a systematic review Lee, Young Ji Arida, Janet A. Donovan, Heidi S. Cancer Med Clinical Cancer Research 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. John Wiley and Sons Inc. 2017-09-29 /pmc/articles/PMC5673951/ /pubmed/28960834 http://dx.doi.org/10.1002/cam4.1165 Text en © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Clinical Cancer Research Lee, Young Ji Arida, Janet A. Donovan, Heidi S. The application of crowdsourcing approaches to cancer research: a systematic review |
title | The application of crowdsourcing approaches to cancer research: a systematic review |
title_full | The application of crowdsourcing approaches to cancer research: a systematic review |
title_fullStr | The application of crowdsourcing approaches to cancer research: a systematic review |
title_full_unstemmed | The application of crowdsourcing approaches to cancer research: a systematic review |
title_short | The application of crowdsourcing approaches to cancer research: a systematic review |
title_sort | application of crowdsourcing approaches to cancer research: a systematic review |
topic | Clinical Cancer Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5673951/ https://www.ncbi.nlm.nih.gov/pubmed/28960834 http://dx.doi.org/10.1002/cam4.1165 |
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