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Online recruitment and testing of infants with Mechanical Turk

Michelle Tran1, Laura Cabral1, Ronak Patel1

  • 1Brain and Mind Institute, Western University, London, Ontario N6A 5B7, Canada.

Insights

Researchers used Amazon Mechanical Turk (MTurk) to effectively recruit and test infants online. This method identified engaging video features like faces and songs, improving infant behavioral studies.

Area of Science:

  • Developmental Psychology
  • Human-Computer Interaction
  • Media Psychology

Background:

  • Laboratory-based infant testing is costly and time-consuming, often leading to underpowered studies.
  • Reproducibility in infant behavioral research is a significant challenge due to recruitment and logistical hurdles.

Purpose of the Study:

  • To evaluate Amazon Mechanical Turk (MTurk) as a viable platform for recruiting and measuring infant behavior.
  • To identify specific cinematic features that capture and maintain infant attention.

Main Methods:

  • A looking time paradigm was employed, recording infant (5-8 months) attention via webcams on the MTurk platform.
  • Infants viewed various children's television programs to assess engagement levels.

Main Results:

  • Significant variability in infant engagement across different programs was observed (N=57).
  • Highly engaging programs maintained infant attention for approximately 70% of a 10-13 minute viewing period.
  • Cinematic elements such as faces, singing/rhyming content, and camera zooms were identified as key attention-grabbers.

Conclusions:

  • Amazon Mechanical Turk (MTurk) provides a rapid and effective solution for recruiting and testing infant populations.
  • This online approach enhances the feasibility and potential reproducibility of infant behavioral research.

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