Literature DB >> 27147494

Interactive use of online health resources: a comparison of consumer and professional questions.

Kirk Roberts1, Dina Demner-Fushman2.   

Abstract

OBJECTIVE: To understand how consumer questions on online resources differ from questions asked by professionals, and how such consumer questions differ across resources.
MATERIALS AND METHODS: Ten online question corpora, 5 consumer and 5 professional, with a combined total of over 40 000 questions, were analyzed using a variety of natural language processing techniques. These techniques analyze questions at the lexical, syntactic, and semantic levels, exposing differences in both form and content.
RESULTS: Consumer questions tend to be longer than professional questions, more closely resemble open-domain language, and focus far more on medical problems. Consumers ask more sub-questions, provide far more background information, and ask different types of questions than professionals. Furthermore, there is substantial variance of these factors between the different consumer corpora. DISCUSSION: The form of consumer questions is highly dependent upon the individual online resource, especially in the amount of background information provided. Professionals, on the other hand, provide very little background information and often ask much shorter questions. The content of consumer questions is also highly dependent upon the resource. While professional questions commonly discuss treatments and tests, consumer questions focus disproportionately on symptoms and diseases. Further, consumers place far more emphasis on certain types of health problems (eg, sexual health).
CONCLUSION: Websites for consumers to submit health questions are a popular online resource filling important gaps in consumer health information. By analyzing how consumers write questions on these resources, we can better understand these gaps and create solutions for improving information access.This article is part of the Special Focus on Person-Generated Health and Wellness Data, which published in the May 2016 issue, Volume 23, Issue 3. Published by Oxford University Press on behalf of the American Medical Informatics Association 2016. This work is written by US Government employees and is in the public domain in the United States.

Entities:  

Keywords:  consumer health informatics; consumer language; online information seeking; question answering

Mesh:

Year:  2016        PMID: 27147494      PMCID: PMC4926747          DOI: 10.1093/jamia/ocw024

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


  19 in total

1.  In their own words? A terminological analysis of e-mail to a cancer information service.

Authors:  Catherine Arnott Smith; P Zoë Stavri; Wendy Webber Chapman
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2.  A frequency-based technique to improve the spelling suggestion rank in medical queries.

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Journal:  J Am Med Inform Assoc       Date:  2004-02-05       Impact factor: 4.497

3.  Positive attitudes and failed queries: an exploration of the conundrums of consumer health information retrieval.

Authors:  Qing T Zeng; Sandra Kogan; Robert M Plovnick; Jonathan Crowell; Eve-Marie Lacroix; Robert A Greenes
Journal:  Int J Med Inform       Date:  2004-02       Impact factor: 4.046

4.  A new readability yardstick.

Authors:  R FLESCH
Journal:  J Appl Psychol       Date:  1948-06

5.  Automatically classifying question types for consumer health questions.

Authors:  Kirk Roberts; Halil Kilicoglu; Marcelo Fiszman; Dina Demner-Fushman
Journal:  AMIA Annu Symp Proc       Date:  2014-11-14

6.  Internet health information seeking is a team sport: analysis of the Pew Internet Survey.

Authors:  Rajani S Sadasivam; Rebecca L Kinney; Stephenie C Lemon; Stephanie L Shimada; Jeroan J Allison; Thomas K Houston
Journal:  Int J Med Inform       Date:  2012-11-11       Impact factor: 4.046

7.  From health search to healthcare: explorations of intention and utilization via query logs and user surveys.

Authors:  Ryen W White; Eric Horvitz
Journal:  J Am Med Inform Assoc       Date:  2013-05-11       Impact factor: 4.497

Review 8.  Clinical questions raised by clinicians at the point of care: a systematic review.

Authors:  Guilherme Del Fiol; T Elizabeth Workman; Paul N Gorman
Journal:  JAMA Intern Med       Date:  2014-05       Impact factor: 21.873

9.  Analysis of questions asked by family doctors regarding patient care.

Authors:  J W Ely; J A Osheroff; M H Ebell; G R Bergus; B T Levy; M L Chambliss; E R Evans
Journal:  BMJ       Date:  1999-08-07

10.  An evaluation of information-seeking behaviors of general pediatricians.

Authors:  Donna M D'Alessandro; Clarence D Kreiter; Michael W Peterson
Journal:  Pediatrics       Date:  2004-01       Impact factor: 7.124

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  18 in total

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Journal:  AMIA Annu Symp Proc       Date:  2017-02-10

Review 2.  Aspiring to Unintended Consequences of Natural Language Processing: A Review of Recent Developments in Clinical and Consumer-Generated Text Processing.

Authors:  D Demner-Fushman; N Elhadad
Journal:  Yearb Med Inform       Date:  2016-11-10

3.  A Semantic Parsing Method for Mapping Clinical Questions to Logical Forms.

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4.  How user intelligence is improving PubMed.

Authors:  Nicolas Fiorini; Robert Leaman; David J Lipman; Zhiyong Lu
Journal:  Nat Biotechnol       Date:  2018-10-01       Impact factor: 54.908

5.  Annotating Logical Forms for EHR Questions.

Authors:  Kirk Roberts; Dina Demner-Fushman
Journal:  LREC Int Conf Lang Resour Eval       Date:  2016-05

Review 6.  Making Sense of Big Textual Data for Health Care: Findings from the Section on Clinical Natural Language Processing.

Authors:  A Névéol; P Zweigenbaum
Journal:  Yearb Med Inform       Date:  2017-09-11

7.  Consumer health information and question answering: helping consumers find answers to their health-related information needs.

Authors:  Dina Demner-Fushman; Yassine Mrabet; Asma Ben Abacha
Journal:  J Am Med Inform Assoc       Date:  2020-02-01       Impact factor: 4.497

8.  Enriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach.

Authors:  Zhe He; Zhiwei Chen; Sanghee Oh; Jinghui Hou; Jiang Bian
Journal:  J Biomed Inform       Date:  2017-03-27       Impact factor: 6.317

9.  Exploring the Readability of Ingredients Lists of Food Labels with Existing Metrics.

Authors:  Kathryn Cooper; William Gasper; Ricky Flores; Martina Clarke; Erin Bass; Leslie Evans; Jana Ponce
Journal:  AMIA Annu Symp Proc       Date:  2022-05-23

10.  Consumers' Use of UMLS Concepts on Social Media: Diabetes-Related Textual Data Analysis in Blog and Social Q&A Sites.

Authors:  Min Sook Park; Zhe He; Zhiwei Chen; Sanghee Oh; Jiang Bian
Journal:  JMIR Med Inform       Date:  2016-11-24
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