ArticleJournal of medical Internet research2018
Exploring Genetic Data Across Individuals: Design and Evaluation of a Novel Comparative Report Tool.
Article in Journal of medical Internet research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 6 citations in OpenAlex.
- Valuable Genomes: Taxonomy and Archetypes of Business Models in Direct-to-Consumer Genetic Testing.Journal of medical Internet research · 2020Article
- Open Humans: A platform for participant-centered research and personal data exploration.GigaScience · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe growth in the availability of personal genomic data to nonexperts poses multiple challenges to human-computer interaction research; data are highly sensitive, complex, and have health implications for individuals and families. However, there has been little research on how nonexpert users explore their genomic data.
objectiveWe focus on how to support nonexperts in exploring and comparing their own personal genomic report with those of other people. We designed and evaluated CrossGenomics, a novel tool for comparing personal genetic reports, which enables exploration of shared and unshared genetic variants. Focusing on communicating comparative impact, rarity, and certainty, we evaluated alternative novel interactive prototypes.
methodsWe conducted 3 user studies. The first focuses on assessing the usability and understandability of a prototype that facilitates the comparison of reports from 2 family members. Following a design iteration, we studied how various prototypes support the comparison of genetic reports of a 4-person family. Finally, we evaluated the needs of early adopters-people who share their genetic reports publicly for comparing their genetic reports with that of others.
resultsIn the first study, sunburst- and Venn-based comparisons of two genomes led to significantly higher domain comprehension, compared with the linear comparison and with the commonly used tabular format. However, results show gaps between objective and subjective comprehension, as sunburst users reported significantly lower perceived understanding and higher levels of confusion than the users of the tabular report. In the second study, users who were allowed to switch between the different comparison views presented higher comprehension levels, as well as more complex reasoning than users who were limited to a single comparison view. In the third study, 35% (17/49) reported learning something new from comparing their own data with another person's data. Users indicated that filtering and toggling between comparison views were the most useful features.
conclusionsOur findings (1) highlight features and visualizations that show strengths in facilitating user comprehension of genomic data, (2) demonstrate the value of affording users the flexibility to examine the same report using multiple views, and (3) emphasize users' needs in comparison of genomic data. We conclude with design implications for engaging nonexperts with complex multidimensional genomic data.
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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.