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Online volunteer laboratories for human subjects research

Author

Listed:
  • Austin M Strange
  • Ryan D Enos
  • Mark Hill
  • Amy Lakeman

Abstract

Once a fixture of research in the social and behavioral sciences, volunteer subjects are now only rarely used in human subjects research. Yet volunteers are a potentially valuable resource, especially for research conducted online. We argue that online volunteer laboratories are able to produce high-quality data comparable to that from other online pools. The scalability of volunteer labs means that they can produce large volumes of high-quality data for multiple researchers, while imposing little or no financial burden. Using a range of original tests, we show that volunteer and paid respondents have different motivations for participating in research, but have similar descriptive compositions. Furthermore, volunteer samples are able to replicate classic and contemporary social science findings, and produce high levels of overall response quality comparable to paid subjects. Our results suggest that online volunteer labs represent a potentially significant untapped source of human subjects data.

Suggested Citation

  • Austin M Strange & Ryan D Enos & Mark Hill & Amy Lakeman, 2019. "Online volunteer laboratories for human subjects research," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-13, August.
    • Handle: RePEc:plo:pone00:0221676
    DOI: 10.1371/journal.pone.0221676
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    References listed on IDEAS

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    1. John Horton & David Rand & Richard Zeckhauser, 2011. "The online laboratory: conducting experiments in a real labor market," Experimental Economics, Springer;Economic Science Association, vol. 14(3), pages 399-425, September.
    2. Stephan Meier & Alois Stutzer, 2008. "Is Volunteering Rewarding in Itself?," Economica, London School of Economics and Political Science, vol. 75(297), pages 39-59, February.
    3. Mullinix, Kevin J. & Leeper, Thomas J. & Druckman, James N. & Freese, Jeremy, 2015. "The Generalizability of Survey Experiments," Journal of Experimental Political Science, Cambridge University Press, vol. 2(2), pages 109-138, January.
    4. Neil Stewart & Christoph Ungemach & Adam J. L. Harris & Daniel M. Bartels & Ben R. Newell & Gabriele Paolacci & Jesse Chandler, "undated". "The Average Laboratory Samples a Population of 7,300 Amazon Mechanical Turk Workers," Mathematica Policy Research Reports f97b669c7b3e4c2ab95c9f805, Mathematica Policy Research.
    5. Berinsky, Adam J. & Huber, Gregory A. & Lenz, Gabriel S., 2012. "Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk," Political Analysis, Cambridge University Press, vol. 20(3), pages 351-368, July.
    6. repec:cup:judgdm:v:10:y:2015:i:5:p:479-491 is not listed on IDEAS
    7. Santoso, Lie Philip & Stein, Robert & Stevenson, Randy, 2016. "Survey Experiments with Google Consumer Surveys: Promise and Pitfalls for Academic Research in Social Science," Political Analysis, Cambridge University Press, vol. 24(3), pages 356-373, July.
    8. Kathryn Sharpe Wessling & Joel Huber & Oded Netzer, 2017. "MTurk Character Misrepresentation: Assessment and Solutions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(1), pages 211-230.
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