REBECCA R. CARTER

Case Study 2

Understanding Ovarian Cancer Awareness through Crowdsourcing

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Carter, R.R., Difeo, A., Bogie, K., Zhang, G.Q., & Sun, J.S. Crowdsourcing Awareness: Exploration of Ovarian Cancer Awareness through Amazon Mechanical Turk. (January, 2014).

Methods:

  • Correspondence analysis
  • Epidemiological crowdsourcing
  • Survey design for web-based population
  • Embedded quality control components for item validity and bias prevention
  • Contingency table analyses
  • Multinomial logistic regression

Summary:

This study examined current public awareness and knowledge about ovarian cancer. We developed unbiased survey with quality control measures. The survey assessed a reasonable representation of the American public by crowdsourcing participants at a highly condensed rate of cost and time compared to traditional recruitment methods.  Using correspondence analysis we defined a distinct knowledge gap of breast cancer awareness compared to ovarian cancer awareness, where responses concerning a woman’s lifetime risk of breast cancer were consistent, while respondents concerning ovarian cancer lifetime risk varied widely. However, individuals with prior knowledge of breast cancer tended to possess some knowledge of ovarian cancer. Ovarian cancer survivorship is radically different from early stage to advanced stage, therefore the findings underscore the importance of efforts to improve awareness of ovarian cancer early diagnosis.

Recognition:

  • Named top 20% most cited publications by PLOS One.

  • More than 4,000 views since 2014.

 

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