Evidence map›Paper›PMID 39776507›Full record

ArticleArthroscopy, sports medicine, and rehabilitation2024

Both English- and Spanish-Language Anterior Cruciate Ligament Reconstruction Online Patient Education Materials Are Written at Higher-Than-Recommended Reading Levels.

Jacob S Ghahremani, Michael Chapek, Virginia Xie, Tanya Watarastaporn, Nala A Al-Khatib, Ronald A Navarro

Abstract read
In one paragraph

Article in Arthroscopy, sports medicine, and rehabilitation, 2024. 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

6 authors.

Jacob S GhahremaniKaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, U.S.A.
Michael ChapekKaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, U.S.A.
Virginia XieKaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, U.S.A.
Tanya WatarastapornKaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, U.S.A.
Nala A Al-KhatibKaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, U.S.A.
Ronald A NavarroKaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, U.S.A.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To examine the overall reading levels of anterior cruciate ligament reconstruction online patient education materials (OPEMs) written in English and Spanish. Methods: We conducted Google searches for OPEMs using "ACL surgery" and " Results: English-language OPEMs showed a higher mean overall grade level than Spanish-language OPEMs (10.48 ± 1.86 vs 8.64 ± 1.22, Conclusions: Although Spanish-language OPEMs were written at a lower reading level, average readability for both English- and Spanish-language OPEMs was significantly higher than the recommended level. Across both languages, only a single English-language webpage met the American Medical Association-recommended sixth-grade reading level. More Spanish-language articles were written at or below the average adult reading level in the United States. Clinical Relevance: It is imperative that patient educational materials be written at a reading level that is understood by the most patients. This is especially true for OPEMs, when a medical provider is not present to answer questions. Therefore, it is important to evaluate the reading level of OPEMs to determine whether they are written at an appropriate level for the best patient understanding.

Identifiers

PMID39776507
PMCPMC11701936

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.