19
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Applications of crowdsourcing in health: an overview

      research-article
      Journal of Global Health
      Edinburgh University Global Health Society

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Crowdsourcing is a nascent phenomenon that has grown exponentially since it was coined in 2006. It involves a large group of people solving a problem or completing a task for an individual or, more commonly, for an organisation. While the field of crowdsourcing has developed more quickly in information technology, it has great promise in health applications. This review examines uses of crowdsourcing in global health and health, broadly.

          Methods

          Semantic searches were run in Google Scholar for “crowdsourcing,” “crowdsourcing and health,” and similar terms. 996 articles were retrieved and all abstracts were scanned. 285 articles related to health. This review provides a narrative overview of the articles identified.

          Results

          Eight areas where crowdsourcing has been used in health were identified: diagnosis; surveillance; nutrition; public health and environment; education; genetics; psychology; and, general medicine/other. Many studies reported crowdsourcing being used in a diagnostic or surveillance capacity. Crowdsourcing has been widely used across medical disciplines; however, it is important for future work using crowdsourcing to consider the appropriateness of the crowd being used to ensure the crowd is capable and has the adequate knowledge for the task at hand. Gamification of tasks seems to improve accuracy; other innovative methods of analysis including introducing thresholds and measures of trustworthiness should be considered.

          Conclusion

          Crowdsourcing is a new field that has been widely used and is innovative and adaptable. With the exception of surveillance applications that are used in emergency and disaster situations, most uses of crowdsourcing have only been used as pilots. These exceptions demonstrate that it is possible to take crowdsourcing applications to scale. Crowdsourcing has the potential to provide more accessible health care to more communities and individuals rapidly and to lower costs of care.

          Related collections

          Most cited references58

          • Record: found
          • Abstract: found
          • Article: not found

          The viability of crowdsourcing for survey research.

          Online contract labor portals (i.e., crowdsourcing) have recently emerged as attractive alternatives to university participant pools for the purposes of collecting survey data for behavioral research. However, prior research has not provided a thorough examination of crowdsourced data for organizational psychology research. We found that, as compared with a traditional university participant pool, crowdsourcing respondents were older, were more ethnically diverse, and had more work experience. Additionally, the reliability of the data from the crowdsourcing sample was as good as or better than the corresponding university sample. Moreover, measurement invariance generally held across these groups. We conclude that the use of these labor portals is an efficient and appropriate alternative to a university participant pool, despite small differences in personality and socially desirable responding across the samples. The risks and advantages of crowdsourcing are outlined, and an overview of practical and ethical guidelines is provided.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Towards an integrated crowdsourcing definition

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection

              The detection of somatic mutations from cancer genome sequences is key to understanding the genetic basis of disease progression, patient survival and response to therapy. Benchmarking is needed for tool assessment and improvement but is complicated by a lack of gold standards, by extensive resource requirements and by difficulties in sharing personal genomic information. To resolve these issues, we launched the ICGC-TCGA DREAM Somatic Mutation Calling Challenge, a crowdsourced benchmark of somatic mutation detection algorithms. Here we report the BAMSurgeon tool for simulating cancer genomes and the results of 248 analyses of three in silico tumors created with it. Different algorithms exhibit characteristic error profiles, and, intriguingly, false positives show a trinucleotide profile very similar to one found in human tumors. Although the three simulated tumors differ in sequence contamination (deviation from normal cell sequence) and in subclonality, an ensemble of pipelines outperforms the best individual pipeline in all cases. BAMSurgeon is available at https://github.com/adamewing/bamsurgeon/.
                Bookmark

                Author and article information

                Journal
                J Glob Health
                J Glob Health
                JGH
                Journal of Global Health
                Edinburgh University Global Health Society
                2047-2978
                2047-2986
                June 2018
                07 March 2018
                : 8
                : 1
                : 010502
                Affiliations
                [1]Centre for Global Health Research, Usher Institute of Informatics and Population Sciences, University of Edinburgh, Edinburgh, UK
                Author notes
                Correspondence to:
Kerri Wazny
Centre for Global Health Research
Usher Institute of Population Health Sciences and Informatics
University of Edinburgh
Old Medical School
Teviot Place
Edinburgh EH8 9AG
United Kingdom
 kerri.wazny@ 123456ed.ac.uk
                Article
                jogh-08-010502
                10.7189/jogh.08.010502
                5840433
                29564087
                458b253d-3653-4f10-a93b-9332fb812fdd
                Copyright © 2018 by the Journal of Global Health. All rights reserved.

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                Page count
                Figures: 0, Tables: 1, Equations: 0, References: 93, Pages: 20
                Categories
                Research Theme 1: Global Health Research Priorities

                Public health
                Public health

                Comments

                Comment on this article