Evidence map›Paper›PMID 28269960›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2016

Evaluating a Novel Summary Visualization for Clinical Trial Reports: A Usability Study.

Maurine Tong, William Hsu, Ricky K Taira

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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.

Maurine TongUniversity of California Los Angeles, Los Angeles, CA.
William HsuUniversity of California Los Angeles, Los Angeles, CA.
Ricky K TairaUniversity of California Los Angeles, Los Angeles, CA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Contributions of clinical trials are captured in published reports that are unstructured and often require extensive manual review to gain a deeper understanding of the study itself. Our goal is to increase comprehension and decrease the time necessary to understand these reports through the use of visualization tools. In this paper, we specify and evaluate the visualization of a previously developed representation as well as gain insight from user input for further development. The usability experiment consisted of a two-arm study with users either having or not having access to the visualization. A user questionnaire was used to measure time spent and accuracy in comprehension; intuitiveness and reproducibility of the visualization; and preferences. We found that having the visualization required on average 28.1% less time (25.8 min vs. 35.8 min, p=0.01) while maintaining similar accuracy (73.7% vs. 67.0%). Users were then asked to create their own visualizations, with their visualizations averaging 86.1% similar to the gold standard. All participants either preferred the visualization over the status quo or preferred both equally. These results demonstrate that novel visualizations for trial reports could provide time savings and achieve similar accuracy as reviewing the paper itself. Understanding the strength and quality of clinical trials can be alleviated with a visualization that makes content explicit.

Indexed as

Audiovisual AidsClinical Trials as TopicComprehensionData DisplayHumansInformation Storage and RetrievalPublicationsSurveys and Questionnaires

Identifiers

PMID28269960
PMCPMC5333215

What OpenQuestion holds

Textmetadata
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.