Evidence map›Paper›PMID 42244731›Full record

ArticlebioRxiv : the preprint server for biology2026

Psychometric Validation of the Education and Assessment of Genetic Literacy (EAGL) Measure.

Lily S Barna, Yi Liao, Michael R Wierzbicki, Gabriela M Ramírez-Renta, Kimberly A Kaphingst, Chris Gunter

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In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Lily S BarnaEngagement Methods Unit, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, 20892, USA.
Yi LiaoHuntsman Cancer Institute and Department of Communication, University of Utah, Salt Lake City, UT, 84112, USA.
Michael R WierzbickiEmmes Company, Rockville, MD, 20850, USA.
Gabriela M Ramírez-RentaEngagement Methods Unit, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, 20892, USA.
Kimberly A KaphingstHuntsman Cancer Institute and Department of Communication, University of Utah, Salt Lake City, UT, 84112, USA.
Chris GunterEngagement Methods Unit, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, 20892, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic literacy is an integral measure for examining society's interaction with genetics, but widely-used "genetic literacy" measures lack both knowledge comprehension measures and psychometric validation. To address these issues, we validated the Education and Assessment of Genetic Literacy measure (EAGL) in a sample of 2708 US participants, using both exploratory and confirmatory factor analysis. In addition to standard subjective and objective knowledge subscales, our measure's distinct knowledge comprehension subscale focuses on autism as an example of a complex condition. Regression analyses showed a statistically significant interaction when looking at education and personal connection to autism in relation to knowledge comprehension (F=3.68, p=0.003). Separately, those in our sample with a connection to autism scored higher on the subjective knowledge section (F=19.52, p<0.001) only, concurring with previous demonstrations of a subjective-objective knowledge gap in science literacy. We explored geographic location as one potential factor in genetic literacy and found that metropolitan vs non-metropolitan status had no significant main effects on overall levels. After the validation process, we have two multi-domain measures which accurately capture the construct of genetic literacy and are available for wide use: the multi-faceted EAGL-long, which has previously been tested in thousands of participants, or the validated three-factor EAGL-short.

Indexed as

autismgenetic literacygenomic literacyinformation literacynumeracy

Identifiers

PMID42244731
PMCPMC13232185

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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.