ArticleJournal of the American Medical Informatics Association : JAMIA2016
Interactive use of online health resources: a comparison of consumer and professional questions.
Article in Journal of the American Medical Informatics Association : JAMIA, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed.
- Semantic classification of Indonesian consumer health questions.Journal of biomedical semantics · 2025Article
- Quality Measurement of Consumer Health Questions: Content and Language Perspectives.Journal of medical Internet research · 2024Article
- Exploring the Efficacy of Large Language Models in Summarizing Mental Health Counseling Sessions: Benchmark Study.JMIR mental health · 2024Article
- Identifying Medical Concepts and Semantic Types in Lay Vocabularies of Health Consumers Who are Concerned with Diabetes on Social Media Using the UMLS and NLP.Proceedings : Annual International Computer Software and Applications Conference. COMPSAC · 2024Article
- A conversational agent system for dietary supplements use.BMC medical informatics and decision making · 2022Article
- What Would it Take to get Biomedical QA Systems into Practice?Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing · 2021Article
- The Unified Medical Language System SPECIALIST Lexicon and Lexical Tools: Development and applications.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Multidimensional Feature Classification of the Health Information Needs of Patients With Hypertension in an Online Health Community Through Analysis of 1000 Patient Question Records: Observational Study.Journal of medical Internet research · 2020Observational
- Consumer health information and question answering: helping consumers find answers to their health-related information needs.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- A question-entailment approach to question answering.BMC bioinformatics · 2019Article
- How user intelligence is improving PubMed.Nature biotechnology · 2018Article
- Developing Embedded Taxonomy and Mining Patients' Interests From Web-Based Physician Reviews: Mixed-Methods Approach.Journal of medical Internet research · 2018Review
- UMLS to DBPedia link discovery through circular resolution.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Qcorp: an annotated classification corpus of Chinese health questions.BMC medical informatics and decision making · 2018Article
- Semantic annotation of consumer health questions.BMC bioinformatics · 2018Article
- Exploring patient information needs in type 2 diabetes: A cross sectional study of questions.PloS one · 2018Article
- Making Sense of Big Textual Data for Health Care: Findings from the Section on Clinical Natural Language Processing.Yearbook of medical informatics · 2017Review
- Classifying Chinese Questions Related to Health Care Posted by Consumers Via the Internet.Journal of medical Internet research · 2017Article
- Enriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach.Journal of biomedical informatics · 2017Article
- A Semantic Parsing Method for Mapping Clinical Questions to Logical Forms.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
objectiveTo understand how consumer questions on online resources differ from questions asked by professionals, and how such consumer questions differ across resources. MATERIALS AND
methodsTen 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.
resultsConsumer 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).
conclusionWebsites 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.