Evidence map›Paper›PMID 41037781›Full record

ArticleJournal of medical Internet research2025

Parallel Corpus Analysis of Text and Audio Comprehension to Evaluate Readability Formula Effectiveness: Quantitative Analysis.

Arif Ahmed, Gondy Leroy, David Kauchak, Prosanta Barai, Philip Harber, Stephen Rains

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Arif AhmedManagement Information Systems (MIS), Eller College of Management, The University of Arizona, 401 E University Blvd, Tucson, AZ, 85719, United States, 1 (520) 621-2211.ORCID http://orcid.org/0009-0003-5746-1975
Gondy LeroyManagement Information Systems (MIS), Eller College of Management, The University of Arizona, 401 E University Blvd, Tucson, AZ, 85719, United States, 1 (520) 621-2211.ORCID http://orcid.org/0000-0003-4751-6680
David KauchakComputer Science Department, Pomona College, Claremont, CA, United States.ORCID http://orcid.org/0000-0002-5208-634X
Prosanta BaraiManagement Information Systems (MIS), Eller College of Management, The University of Arizona, 401 E University Blvd, Tucson, AZ, 85719, United States, 1 (520) 621-2211.ORCID http://orcid.org/0009-0003-5427-2300
Philip HarberDepartment of Public Health, University of Arizona, Tucson, AZ, United States.ORCID http://orcid.org/0000-0003-0290-4989
Stephen RainsDepartment of Communication, University of Arizona, Tucson, AZ, United States.ORCID http://orcid.org/0000-0002-1639-8557

Funding

Evidence-based Strategy and Tool to Simplify Text for Patients and ConsumersR01LM011975 · NLM · UNIVERSITY OF ARIZONA · PI LEROY, GONDY · 2015 to 2024
$2.9M
NLM NIH HHS R01 LM011975
6 · The paper itself

Abstract

Background: Health literacy, the ability to understand and act on health information, is critical for patient outcomes and health care system effectiveness. While plain language guidelines enhance text-based communication, audio-based health information remains underexplored, despite the growing use of digital assistants and smart devices in health care. Traditional readability formulas, such as Flesch-Kincaid, provide limited insights into the complexity of health-related texts and fail to address challenges specific to audio formats. Factors like syntax and semantic features significantly influence comprehension and retention across modalities. Objective: This study investigates features that affect comprehension of medical information delivered via text or audio formats. We also examine existing readability formulas and their correlation with perceived and actual difficulty of health information for both modalities. Methods: We developed a parallel corpus of health-related information that differed in delivery format: text or audio. We used text from the British Medical Journal (BMJ) Lay Summary (n=193), WebMD (n=40), Patient Instruction (n=40), Simple Wikipedia (n=243), and BMJ journal (n=200). Participants (n=487) read or listened to a health text and then completed a questionnaire evaluating perceived difficulty of the text, measured using a 5-point Likert scale, and actual difficulty measured using multiple-choice and true-false questions (comprehension) as well as free recall of information (retention). Questions were generated by generative artificial intelligence (ChatGPT-4.0). Underlying syntactic, semantic, and domain-specific features, as well as common readability formulas, were evaluated for their relation to information difficulty. Results: Text versions were perceived as easier than audio, with BMJ Lay Summary scoring 1.76 versus 2.1 and BMJ journal 2.59 versus 2.83 (lower is easier). Comprehension accuracy was higher for text across all sources (eg, BMJ journal: 76% vs 58%; Patient Instructions: 86% vs 66%). Retention was better for text, with significant differences in exact word matching for Patient Instructions and BMJ journal. Longer texts increased perceived difficulty in text but reduced free recall in both modalities (-0.23,-0.25 in audio). Higher content word frequency improved retention (0.23, 0.21) and lowered perceived difficulty (-0.20 in audio). Verb-heavy content eased comprehension (-0.29 in audio), while nouns and adjectives increased difficulty (0.20, 0.18). Readability formulas' outcomes were unrelated to comprehension or retention, but correlated with perceived difficulty in text (eg, Smog Index: 0.334 correlation). Conclusions: Text was more effective for conveying complex health information, but audio can be suitable for easier content. In addition, several textual features affect information comprehension and retention for both modalities. Finally, existing readability formulas did not explain actual difficulty. This study highlighted the importance of tailoring health information delivery to content complexity by using appropriate style and modality.

Indexed as

ComprehensionHealth LiteracyAdultFemaleHumansMaleMiddle AgedReadingactual difficultycomprehensiongenerative AIhealth literacyparallel corporaperceived difficulty.retentiontext and audio readabilityuser evaluation

Identifiers

PMID41037781
PMCPMC12490814

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.