This paper is in the following e-collection/theme issue:

Crowdsourcing and Mechanical Turks (98) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (832) Consumer & Patient Education and Shared-Decision Making (679) New Methods (944) Recruitment of Research Participants (296)

Published on in Vol 17, No 12 (2015): December

Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches

Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches

Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches

Authors of this article:

Jinqiu Kuang1 Author Orcid Image ;   Lauren Argo1 Author Orcid Image ;   Greg Stoddard2 Author Orcid Image ;   Bruce E Bray1 Author Orcid Image ;   Qing Zeng-Treitler1, 3 Author Orcid Image
Article Authors Cited by (15) Tweetations (6) Metrics

Journals

  1. Mortensen K, Hughes T. Comparing Amazon’s Mechanical Turk Platform to Conventional Data Collection Methods in the Health and Medical Research Literature. Journal of General Internal Medicine 2018;33(4):533 View
  2. Lu W, Guttentag A, Elbel B, Kiszko K, Abrams C, Kirchner T. Crowdsourcing for Food Purchase Receipt Annotation via Amazon Mechanical Turk: A Feasibility Study. Journal of Medical Internet Research 2019;21(4):e12047 View
  3. Baruch A, May A, Yu D. The motivations, enablers and barriers for voluntary participation in an online crowdsourcing platform. Computers in Human Behavior 2016;64:923 View
  4. Cai C, Gippel J, Zhu Y, Singh A. The power of crowds: Grand challenges in the Asia-Pacific region. Australian Journal of Management 2019;44(4):551 View
  5. Créquit P, Mansouri G, Benchoufi M, Vivot A, Ravaud P. Mapping of Crowdsourcing in Health: Systematic Review. Journal of Medical Internet Research 2018;20(5):e187 View
  6. Bardos J, Friedenthal J, Spiegelman J, Williams Z. Cloud Based Surveys to Assess Patient Perceptions of Health Care: 1000 Respondents in 3 days for US $300. JMIR Research Protocols 2016;5(3):e166 View
  7. Sescleifer A, Francoisse C, Lin A. Systematic Review: Online Crowdsourcing to Assess Perceptual Speech Outcomes. Journal of Surgical Research 2018;232:351 View
  8. Lin S, Thompson H, Hart L, Fu M, Demiris G. Evaluation of pharmaceutical pictograms by older “turkers”: A cross-sectional crowdsourced study. Research in Social and Administrative Pharmacy 2021;17(6):1079 View
  9. van Veldhuisen C, Kamali P, Wu W, Becherer B, Sinno H, Ashraf A, Ibrahim A, Tobias A, Lee B, Lin S. Prospective, Double-Blind Evaluation of Umbilicoplasty Techniques Using Conventional and Crowdsourcing Methods. Plastic & Reconstructive Surgery 2017;140(6):1151 View
  10. Lin S. Discussion: Crowdsourcing as a Novel Method to Evaluate Aesthetic Outcomes of Treatment for Unilateral Cleft Lip. Plastic & Reconstructive Surgery 2016;138(4):875 View
  11. Mastboom M, Planje R, van de Sande M. The Patient Perspective on the Impact of Tenosynovial Giant Cell Tumors on Daily Living: Crowdsourcing Study on Physical Function and Quality of Life. Interactive Journal of Medical Research 2018;7(1):e4 View
  12. Katz A. The Role of Crowdsourcing in Assessing Surgical Skills. Surgical Laparoscopy, Endoscopy & Percutaneous Techniques 2016;26(4):271 View
  13. Washington P, Kalantarian H, Tariq Q, Schwartz J, Dunlap K, Chrisman B, Varma M, Ning M, Kline A, Stockham N, Paskov K, Voss C, Haber N, Wall D. Validity of Online Screening for Autism: Crowdsourcing Study Comparing Paid and Unpaid Diagnostic Tasks. Journal of Medical Internet Research 2019;21(5):e13668 View
  14. Thompson L, Van Liew C, Patrus A, Azzoo K, Cronan T. Are we measuring the same health constructs? Amazon’s Mechanical Turk versus a community sample. Current Psychology 2022;41(10):6700 View