skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

Comparing Amazon’s Mechanical Turk Platform to Conventional Data Collection Methods in the Health and Medical Research Literature

Journal of general internal medicine : JGIM, 2018-04, Vol.33 (4), p.533-538 [Peer Reviewed Journal]

Society of General Internal Medicine 2017 ;Journal of General Internal Medicine is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 0884-8734 ;EISSN: 1525-1497 ;DOI: 10.1007/s11606-017-4246-0 ;PMID: 29302882

Full text available

Citations Cited by
  • Title:
    Comparing Amazon’s Mechanical Turk Platform to Conventional Data Collection Methods in the Health and Medical Research Literature
  • Author: Mortensen, Karoline ; Hughes, Taylor L.
  • Subjects: Biomedical Research - methods ; Crowdsourcing ; Data collection ; Data Collection - methods ; Health ; Health services ; Humans ; Internal Medicine ; Medical research ; Medicine ; Medicine & Public Health ; Reproducibility of Results ; Review Paper ; Scientific papers ; Search engines ; Studies
  • Is Part Of: Journal of general internal medicine : JGIM, 2018-04, Vol.33 (4), p.533-538
  • Description: Background The goal of this article is to conduct an assessment of the peer-reviewed primary literature with study objectives to analyze Amazon.com ’s Mechanical Turk (MTurk) as a research tool in a health services research and medical context. Methods Searches of Google Scholar and PubMed databases were conducted in February 2017. We screened article titles and abstracts to identify relevant articles that compare data from MTurk samples in a health and medical context to another sample, expert opinion, or other gold standard. Full-text manuscript reviews were conducted for the 35 articles that met the study criteria. Results The vast majority of the studies supported the use of MTurk for a variety of academic purposes. Discussion The literature overwhelmingly concludes that MTurk is an efficient, reliable, cost-effective tool for generating sample responses that are largely comparable to those collected via more conventional means. Caveats include survey responses may not be generalizable to the US population.
  • Publisher: New York: Springer US
  • Language: English
  • Identifier: ISSN: 0884-8734
    EISSN: 1525-1497
    DOI: 10.1007/s11606-017-4246-0
    PMID: 29302882
  • Source: GFMER Free Medical Journals
    MEDLINE
    PubMed Central
    ProQuest Central
Back to results list
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait