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How Online Crowds Influence the Way Individual Consumers Answer Health Questions

Journal: Applied Clinical Informatics
ISSN: 1869-0327
DOI: http://dx.doi.org/10.4338/ACI-2011-01-RA-0006
Issue: Vol. 2: Issue 2 2011
Pages: 177-189

How Online Crowds Influence the Way Individual Consumers Answer Health Questions

An Online Prospective Study

Research Article

MedInfo Special Topic

A. Y .S. Lau (1), T. M. Y. Kwok (2), E. Coiera (1)

(1) Centre for Health Informatics, Australian Institute of Health Innovation, University of New South Wales, Sydney, Australia; (2) Faculty of Medicine, University of New South Wales, Sydney, Australia

Keywords

Consumer decision making, social feedback, online information searching, crowd influence, majority influence

Summary

Objective: To investigate whether strength of social feedback, i.e. other people who concur (or do not concur) with one’s own answer to a question, influences the way one answers health questions. Methods: Online prospective study. Two hundred and twenty-seven undergraduate students were recruited to use an online search engine to answer six health questions. Subjects recorded their pre- and post-search answers to each question and their level of confidence in these answers. After answering each question post-search, subjects were presented with a summary of post-search answers provided by previous subjects and were asked to answer the question again. Results: There was a statistically significant relationship between the absolute number of others with a different answer (the crowd’s opinion volume) and the likelihood of an individual changing an answer (P<0.001). For most questions, no subjects changed their answer until the first 10–35 subjects completed the study. Subjects’ likelihood of changing answer increased as the percentage of others with a different answer (the crowd’s opinion density) increased (P=0.047). Overall, 98.3% of subjects did not change their answer when it concurred with the majority (i.e. >50%) of subjects, and that 25.7% of subjects changed their answer to the majority response when it did not concur with the majority. When subjects had a post-search answer that did not concur with the majority, they were 24% more likely to change answer than those with answers that concurred (P<0.001). Conclusion: This study provides empirical evidence that crowd influence, in the form of online social feedback, affects the way consumers answer health questions.