Evidence map›Paper›PMID 24513593›Full record

ArticleJournal of medical Internet research2014

Evaluation of a novel Conjunctive Exploratory Navigation Interface for consumer health information: a crowdsourced comparative study.

Licong Cui, Rebecca Carter, Guo-Qiang Zhang

Abstract readEvaluation Study
In one paragraph

Article in Journal of medical Internet research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Mapping of Crowdsourcing in Health: Systematic Review.Journal of medical Internet research · 2018
    Pooled it
  2. Trial
  3. Review
  4. Web-based Interactive Visualization of Non-Lattice Subgraphs (WINS) in SNOMED CT.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. SimQ: real-time retrieval of similar consumer health questions.Journal of medical Internet research · 2015
    Article
  12. COBE: A Conjunctive Ontology Browser and Explorer for Visualizing SNOMED CT Fragments.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2015
    Article
  13. Article
  14. A Semantic-based Approach for Exploring Consumer Health Questions Using UMLS.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Licong CuiDepartment of Electrical Engineering and Computer Science, Division of Medical Informatics, Case Western Reserve University, Cleveland, OH, United States.
Rebecca Carter
Guo-Qiang Zhang

Funding

Clinical and Translational Science Collaborative of ClevelandUL1TR000439 · NCATS · CASE WESTERN RESERVE UNIVERSITY · PI KONSTAN, MICHAEL W. · 2012 to 2016
$50.0M
NCATS NIH HHS UL1 TR000439NCATS NIH HHS UL1TR000439
6 · The paper itself

Abstract

backgroundNumerous consumer health information websites have been developed to provide consumers access to health information. However, lookup search is insufficient for consumers to take full advantage of these rich public information resources. Exploratory search is considered a promising complementary mechanism, but its efficacy has never before been rigorously evaluated for consumer health information retrieval interfaces.

objectiveThis study aims to (1) introduce a novel Conjunctive Exploratory Navigation Interface (CENI) for supporting effective consumer health information retrieval and navigation, and (2) evaluate the effectiveness of CENI through a search-interface comparative evaluation using crowdsourcing with Amazon Mechanical Turk (AMT).

methodsWe collected over 60,000 consumer health questions from NetWellness, one of the first consumer health websites to provide high-quality health information. We designed and developed a novel conjunctive exploratory navigation interface to explore NetWellness health questions with health topics as dynamic and searchable menus. To investigate the effectiveness of CENI, we developed a second interface with keyword-based search only. A crowdsourcing comparative study was carefully designed to compare three search modes of interest: (A) the topic-navigation-based CENI, (B) the keyword-based lookup interface, and (C) either the most commonly available lookup search interface with Google, or the resident advanced search offered by NetWellness. To compare the effectiveness of the three search modes, 9 search tasks were designed with relevant health questions from NetWellness. Each task included a rating of difficulty level and questions for validating the quality of answers. Ninety anonymous and unique AMT workers were recruited as participants.

resultsRepeated-measures ANOVA analysis of the data showed the search modes A, B, and C had statistically significant differences among their levels of difficulty (P<.001). Wilcoxon signed-rank test (one-tailed) between A and B showed that A was significantly easier than B (P<.001). Paired t tests (one-tailed) between A and C showed A was significantly easier than C (P<.001). Participant responses on the preferred search modes showed that 47.8% (43/90) participants preferred A, 25.6% (23/90) preferred B, 24.4% (22/90) preferred C. Participant comments on the preferred search modes indicated that CENI was easy to use, provided better organization of health questions by topics, allowed users to narrow down to the most relevant contents quickly, and supported the exploratory navigation by non-experts or those unsure how to initiate their search.

conclusionsWe presented a novel conjunctive exploratory navigation interface for consumer health information retrieval and navigation. Crowdsourcing permitted a carefully designed comparative search-interface evaluation to be completed in a timely and cost-effective manner with a relatively large number of participants recruited anonymously. Accounting for possible biases, our study has shown for the first time with crowdsourcing that the combination of exploratory navigation and lookup search is more effective than lookup search alone.

Indexed as

Consumer Health InformationCrowdsourcingUser-Computer InterfaceAnalysis of VarianceHumansInformation Storage and RetrievalInternetcomparative user evaluationconsumer health informationcrowdsourcinghuman computer interactioninformation retrievalsearch interfaces

Identifiers

PMID24513593
PMCPMC3936301

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.