Literature DB >> 18436902

Is relevance relevant? User relevance ratings may not predict the impact of Internet search on decision outcomes.

Enrico W Coiera1, Victor Vickland.   

Abstract

OBJECTIVE: A common measure of Internet search engine effectiveness is its ability to find documents that a user perceives as 'relevant'. This study sought to test whether user provided relevance ratings for documents retrieved by an Internet search engine correlate with the decision outcome after use of a search engine.
DESIGN: 227 university students were asked to answer four randomly assigned consumer health questions, then to conduct an Internet search on one of two randomly assigned search engines of different performance, and to again answer the question. MEASUREMENTS: Participants were asked to provide a relevance score for each document retrieved as well as a pre and post search answer to each question.
RESULTS: User relevance rankings had little or no predictive power. Relevance rankings were unable to predict whether the user of a search engine could correctly answer a question after search and could not differentiate between two search engines with statistically different performance in the hands of users. Only when users had strong prior knowledge of the questions, and the decision task was of low complexity, did relevance appear to have modest predictive power.
CONCLUSIONS: User provided relevance rankings taken in isolation seem to be of limited to no value when designing a search engine that will be used in a general-purpose setting. Relevance rankings may have a place in situations in which experts provide rankings, and decision tasks are of complexity commensurate with the abilities of the raters. A more natural metric of search engine performance may be a user's ability to accurately complete a task, as this removes the inherent subjectivity of relevance rankings, and provides a direct and repeatable outcome measure which directly correlates with the performance of the search technology in the hands of users.

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Year:  2008        PMID: 18436902      PMCID: PMC2442252          DOI: 10.1197/jamia.M2663

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  7 in total

Review 1.  A new approach to the concept of "relevance" in information retrieval (IR).

Authors:  Y Kagolovsky; J R Möhr
Journal:  Stud Health Technol Inform       Date:  2001

2.  Which clinical decisions benefit from automation? A task complexity approach.

Authors:  Vitali Sintchenko; Enrico W Coiera
Journal:  Int J Med Inform       Date:  2003-07       Impact factor: 4.046

3.  Do online information retrieval systems help experienced clinicians answer clinical questions?

Authors:  Johanna I Westbrook; Enrico W Coiera; A Sophie Gosling
Journal:  J Am Med Inform Assoc       Date:  2005-01-31       Impact factor: 4.497

4.  Agreement, the f-measure, and reliability in information retrieval.

Authors:  George Hripcsak; Adam S Rothschild
Journal:  J Am Med Inform Assoc       Date:  2005-01-31       Impact factor: 4.497

Review 5.  How well do physicians use electronic information retrieval systems? A framework for investigation and systematic review.

Authors:  W R Hersh; D H Hickam
Journal:  JAMA       Date:  1998-10-21       Impact factor: 56.272

6.  Architecture for knowledge-based and federated search of online clinical evidence.

Authors:  Enrico Coiera; Martin Walther; Ken Nguyen; Nigel H Lovell
Journal:  J Med Internet Res       Date:  2005-10-24       Impact factor: 5.428

7.  Impact of web searching and social feedback on consumer decision making: a prospective online experiment.

Authors:  Annie Y S Lau; Enrico W Coiera
Journal:  J Med Internet Res       Date:  2008-01-22       Impact factor: 5.428

  7 in total
  1 in total

1.  Can cognitive biases during consumer health information searches be reduced to improve decision making?

Authors:  Annie Y S Lau; Enrico W Coiera
Journal:  J Am Med Inform Assoc       Date:  2008-10-24       Impact factor: 4.497

  1 in total

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