Appl Clin Inform 2011; 02(02): 177-189
DOI: 10.4338/ACI-2011-01-RA-0006
Research Article – MedInfo Special Topic
Schattauer GmbH

How Online Crowds Influence the Way Individual Consumers Answer Health Questions

An Online Prospective Study
A.Y.S. Lau
1  Centre for Health Informatics, Australian Institute of Health Innovation, University of New South Wales, Sydney, Australia
,
T.M.Y. Kwok
2  Faculty of Medicine, University of New South Wales, Sydney, Australia
,
E. Coiera
1  Centre for Health Informatics, Australian Institute of Health Innovation, University of New South Wales, Sydney, Australia
› Author Affiliations
Further Information

Correspondence to:

Annie Y.S. Lau, PhD
Centre for Health Informatics
Australian Institute of Health Innovation
University of New South Wales
UNSW Sydney NSW 2052
Australia

Publication History

Received: 20 January 2011

Accepted: 16 April 2011

Publication Date:
16 December 2017 (online)

 

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.


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Conflict of Interest

The University of New South Wales and some of the researchers could benefit from the commercial exploitation of the Quick Clinical search engine or its technologies.


Correspondence to:

Annie Y.S. Lau, PhD
Centre for Health Informatics
Australian Institute of Health Innovation
University of New South Wales
UNSW Sydney NSW 2052
Australia