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

Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (832) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Crowdsourcing and Mechanical Turks (98)

Published on in Vol 14, No 3 (2012): May-Jun

Using Crowdsourcing Technology for Testing Multilingual Public Health Promotion Materials

Using Crowdsourcing Technology for Testing Multilingual Public Health Promotion Materials

Using Crowdsourcing Technology for Testing Multilingual Public Health Promotion Materials

Authors of this article:

Anne M. Turner1, 2 Author Orcid Image ;   Katrin Kirchhoff3 ;   Daniel Capurro2, 4 Author Orcid Image
Article Authors Cited by (47) Tweetations (33) Metrics

Journals

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  17. Yu B, Willis M, Sun P, Wang J. Crowdsourcing Participatory Evaluation of Medical Pictograms Using Amazon Mechanical Turk. Journal of Medical Internet Research 2013;15(6):e108 View
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  19. Mitry D, Peto T, Hayat S, Morgan J, Khaw K, Foster P, Soyer H. Crowdsourcing as a Novel Technique for Retinal Fundus Photography Classification: Analysis of Images in the EPIC Norfolk Cohort on Behalf of the UKBiobank Eye and Vision Consortium. PLoS ONE 2013;8(8):e71154 View
  20. Zide M, Caswell K, Peterson E, Aberle D, Bui A, Arnold C. Consumers’ Patient Portal Preferences and Health Literacy: A Survey Using Crowdsourcing. JMIR Research Protocols 2016;5(2):e104 View
  21. Kristan J, Suffoletto B. Using online crowdsourcing to understand young adult attitudes toward expert-authored messages aimed at reducing hazardous alcohol consumption and to collect peer-authored messages. Translational Behavioral Medicine 2015;5(1):45 View
  22. Fernández D, Harel D, Ipeirotis P, McAllister T. Statistical considerations for crowdsourced perceptual ratings of human speech productions. Journal of Applied Statistics 2019;46(8):1364 View
  23. Ranard B, Ha Y, Meisel Z, Asch D, Hill S, Becker L, Seymour A, Merchant R. Crowdsourcing—Harnessing the Masses to Advance Health and Medicine, a Systematic Review. Journal of General Internal Medicine 2014;29(1):187 View
  24. Zhai H, Lingren T, Deleger L, Li Q, Kaiser M, Stoutenborough L, Solti I. Web 2.0-Based Crowdsourcing for High-Quality Gold Standard Development in Clinical Natural Language Processing. Journal of Medical Internet Research 2013;15(4):e73 View
  25. DeSmet A, Palmeira A, Beltran A, Brand L, Davies V, Thompson D. The Yin and Yang of Formative Research in Designing Serious (Exer-)games. Games for Health Journal 2015;4(1):63 View
  26. Mays D, Tercyak K. Framing Indoor Tanning Warning Messages to Reduce Skin Cancer Risks Among Young Women: Implications for Research and Policy. American Journal of Public Health 2015;105(8):e70 View
  27. 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
  28. Slattery P, Vidgen R, Finnegan P. Winning heads and hearts? How websites encourage prosocial behaviour. Behaviour & Information Technology 2021;40(9):933 View
  29. Palacios M, Martinez-Corral A, Nisar A, Grijalvo M. Crowdsourcing and organizational forms: Emerging trends and research implications. Journal of Business Research 2016;69(5):1834 View
  30. Short R, Middleton D, Befera N, Gondalia R, Tailor T. Patient-Centered Radiology Reporting: Using Online Crowdsourcing to Assess the Effectiveness of a Web-Based Interactive Radiology Report. Journal of the American College of Radiology 2017;14(11):1489 View
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  32. Grasso K, Bell R. Understanding Health Information Seeking: A Test of the Risk Perception Attitude Framework. Journal of Health Communication 2015;20(12):1406 View
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  34. Mittl G, Cook T, Hill P, Cho J, Shea J, Kahn C, Zafar H. Patient Understanding of Abnormal Imaging Findings Under Pennsylvania Act 112: A Call to Revise Mandated Notification Message Language. Journal of the American College of Radiology 2021;18(7):951 View
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  36. Kornfield R, Mohr D, Ranney R, Lattie E, Meyerhoff J, Williams J, Reddy M. Involving Crowdworkers with Lived Experience in Content-Development for Push-Based Digital Mental Health Tools: Lessons Learned from Crowdsourcing Mental Health Messages. Proceedings of the ACM on Human-Computer Interaction 2022;6(CSCW1):1 View
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