Evidence map›Paper›PMID 39378036›Full record

Trial reportJAMA network open2024

Online Plain Language Tool and Health Information Quality: A Randomized Clinical Trial.

Julie Ayre, Carissa Bonner, Danielle M Muscat, Erin Cvejic, Olivia Mac, Dana Mouwad, Heather L Shepherd, Parisa Aslani, Adam G Dunn, Kirsten J McCaffery

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
  2. Article
  3. Ethical Considerations in Personal Health Large Language Models.Journal of medical Internet research · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Readability of Online Patient Education Materials for Myopia Management.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Observational
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. 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

10 authors.

Julie AyreSydney Health Literacy Lab, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Carissa BonnerSydney Health Literacy Lab, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Danielle M MuscatSydney Health Literacy Lab, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Erin CvejicSydney Health Literacy Lab, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Olivia MacSydney Health Literacy Lab, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Dana MouwadWestern Sydney Local Health District, Health Literacy Hub, Westmead, New South Wales, Australia.
Heather L ShepherdSusan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Parisa AslaniSydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Adam G DunnBiomedical Informatics and Digital Health, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Kirsten J McCafferySydney Health Literacy Lab, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Complex and ineffective health communication is a critical source of health inequity and occurs despite repeated policy directives to provide health information that is easy to understand and applies health literacy principles. Objective: To evaluate the effectiveness of the Sydney Health Literacy Lab Health Literacy Editor, an easy-to-use online plain language tool that supports health information providers to apply health literacy guidelines to written health information. Design, Setting, and Participants: This randomized clinical trial, conducted online in Australia from May 2023 to February 2024, included a convenience sample of health information providers with no previous experience using the Health Literacy Editor. Analysts were blinded to study group. Intervention: Participants were randomized 1:1 to the intervention or control group. Participants in the intervention group were provided access to the Health Literacy Editor and a 30-minute online training program prior to editing 3 prespecified health texts. The Health Literacy Editor gives objective, real-time feedback on words and sentences. Control participants revised the texts using their own standard health information development processes. Main Outcomes and Measures: The preregistered primary outcome was the text school grade reading score (using a validated instrument, the Simple Measure of Gobbledygook). Secondary outcomes were text complexity (percentage of text using complex language), use of passive voice (number of instances), and subjective expert ratings (5-point Likert scale corresponding to items on the Patient Education Materials Assessment Tool). Results: A total of 211 participants were randomized, with 105 in the intervention group and 106 in the control group. Of 181 participants in the intention-to-treat analysis (mean [SD] age, 41.0 [11.6] years; 154 women [85.1%]), 86 were in the intervention group and 95 in the control group. Texts revised in the intervention group had significantly improved grade reading scores (mean difference [MD], 2.48 grades; 95% CI, 1.84-3.12 grades; P < .001; Cohen d, 0.99), lower text complexity scores (MD, 6.86; 95% CI, 4.99-8.74; P < .001; Cohen d, 0.95), and less use of passive voice (MD, 0.95 instances; 95% CI, 0.44-1.47 instances; P < .001; Cohen d, 0.53) compared with texts revised in the control group in intention-to-treat analyses. Experts rated texts in the intervention group more favorably for word choice and style than those in the control group (MD, 0.44; 95% CI, 0.25-0.63; P < .001; Cohen d, 0.63), with no loss of meaning or content. Conclusions and Relevance: In this randomized clinical trial, the Health Literacy Editor helped users simplify health information and apply health literacy guidelines to written text. The findings suggest the tool has high potential to improve development of health information for people who have low health literacy. As an online tool, the Health Literacy Editor is also easy to access and implement at scale. Trial Registration: ANZCTR Identifier: ACTRN12623000386639.

Indexed as

Health LiteracyAdultAustraliaConsumer Health InformationFemaleHumansInternetMaleMiddle Aged

Identifiers

PMID39378036
PMCPMC11581667

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.