Evidence map›Paper›PMID 31391091›Full record

ArticleBMC medical informatics and decision making2019

ALOHA: developing an interactive graph-based visualization for dietary supplement knowledge graph through user-centered design.

Xing He, Rui Zhang, Rubina Rizvi, Jake Vasilakes, Xi Yang, Yi Guo, Zhe He, Mattia Prosperi, Jinhai Huo, Jordan Alpert and 1 more

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. KGen: a knowledge graph generator from biomedical scientific literature.BMC medical informatics and decision making · 2020
    Article
  6. LionVu 2.0 Usability Assessment for Pennsylvania, United States.ISPRS international journal of geo-information · 2020
    Article
  7. Article
  8. Knowledge-Based Biomedical Data Science.Annual review of biomedical data science · 2020
    Article
  9. Article
  10. 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

11 authors.

Xing HeDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA.
Rui ZhangInstitute for Health Informatics and College of Pharmacy, University of Minnesota, Minneapolis, MN, USA.
Rubina RizviInstitute for Health Informatics and College of Pharmacy, University of Minnesota, Minneapolis, MN, USA.
Jake VasilakesInstitute for Health Informatics and College of Pharmacy, University of Minnesota, Minneapolis, MN, USA.
Xi YangDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA.
Yi GuoDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA.
Zhe HeSchool of Information, Florida State University, Tallahassee, FL, USA.
Mattia ProsperiEpidemiology, University of Florida, Gainesville, FL, USA.
Jinhai HuoCancer Informatics and eHealth Core, University of Florida Health Cancer Center, Gainesville, FL, USA.
Jordan AlpertCancer Informatics and eHealth Core, University of Florida Health Cancer Center, Gainesville, FL, USA.
Jiang BianDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA. bianjiang@ufl.edu.

Funding

Using social networks to map and evaluate team science across CTSA hubsUL1TR001427 · NCATS · UNIVERSITY OF FLORIDA · PI MITCHELL, DUANE A. · 2015 to 2024
$37.2M
A Translational Informatics Framework to Mine Efficacy and Safety of Dietary SupplementsR01AT009457 · NCCIH · UNIVERSITY OF MINNESOTA · PI RUI ZHANG · 2017 to 2026
$4.1M
NCATS NIH HHS UL1 TR001427NCCIH NIH HHS R01 AT009457
6 · The paper itself

Abstract

backgroundDietary supplements (DSs) are widely used. However, consumers know little about the safety and efficacy of DSs. There is a growing interest in accessing health information online; however, health information, especially online information on DSs, is scattered with varying levels of quality. In our previous work, we prototyped a web application, ALOHA, with interactive graph-based visualization to facilitate consumers' browsing of the integrated DIetary Supplement Knowledge base (iDISK) curated from scientific resources, following an iterative user-centered design (UCD) process.

methodsFollowing UCD principles, we carried out two design iterations to enrich the functionalities of ALOHA and enhance its usability. For each iteration, we conducted a usability assessment and design session with a focus group of 8-10 participants and evaluated the usability with a modified System Usability Scale (SUS). Through thematic analysis, we summarized the identified usability issues and conducted a heuristic evaluation to map them to the Gerhardt-Powals' cognitive engineering principles. We derived suggested improvements from each of the usability assessment session and enhanced ALOHA accordingly in the next design iteration.

resultsThe SUS score in the second design iteration decreased to 52.2 ± 11.0 from 63.75 ± 7.2 in our original work, possibly due to the high number of new functionalities we introduced. By refining existing functionalities to make the user interface simpler, the SUS score increased to 64.4 ± 7.2 in the third design iteration. All participants agreed that such an application is urgently needed to address the gaps in how DS information is currently organized and consumed online. Moreover, most participants thought that the graph-based visualization in ALOHA is a creative and visually appealing format to obtain health information.

conclusionsIn this study, we improved a novel interactive visualization platform, ALOHA, for the general public to obtain DS-related information through two UCD design iterations. The lessons learned from the two design iterations could serve as a guide to further enhance ALOHA and the development of other knowledge graph-based applications. Our study also showed that graph-based interactive visualization is a novel and acceptable approach to end-users who are interested in seeking online health information of various domains.

Indexed as

Dietary SupplementsHealth Knowledge, Attitudes, PracticeData DisplayFocus GroupsHeuristicsHumansPatient Education as TopicPattern Recognition, AutomatedSoftwareUser-Computer InterfaceDietary supplementKnowledge baseKnowledge graphOnline health informationUsabilityUser-centered design

Identifiers

PMID31391091
PMCPMC6686235

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.