Evidence map›Paper›PMID 39991597›Full record

ArticleJournal of hand surgery global online2025

Leveraging ChatGPT to Produce Patient Education Materials for Common Hand Conditions.

George Abdelmalek, Harjot Uppal, Daniel Garcia, Joseph Farshchian, Arash Emami, Andrew McGinniss

Abstract read
In one paragraph

Article in Journal of hand surgery global online, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

George AbdelmalekDepartment of Orthopaedic Surgery, St. Joseph's University Medical Center, Paterson, NJ.
Harjot UppalDepartment of Orthopaedic Surgery, St. Joseph's University Medical Center, Paterson, NJ.
Daniel GarciaDepartment of Orthopaedic Surgery, St. Joseph's University Medical Center, Paterson, NJ.
Joseph FarshchianDepartment of Orthopaedic Surgery, St. Joseph's University Medical Center, Paterson, NJ.
Arash EmamiDepartment of Orthopaedic Surgery, St. Joseph's University Medical Center, Paterson, NJ.
Andrew McGinnissDepartment of Orthopaedic Surgery, St. Joseph's University Medical Center, Paterson, NJ.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Many adults in the United States possess basic or below basic health literacy skills, making it essential for patient education materials (PEMs) to be presented at or below a sixth-grade reading level. We evaluate the readability of PEMs generated by ChatGPT 3.5 and 4.0 for common hand conditions. Methods: We used Chat Generative Pre-Trained Transformer (ChatGPT) 3.5 and 4.0 to generate PEMs for 50 common hand pathologies. Two consistent questions were asked to minimize variability: 1. "Please explain [Condition] to a patient at a sixth-grade reading level, including details on anatomy, symptoms, doctors' examination, and treatment (both surgical and nonsurgical)." 2. "Create a detailed patient information sheet for the general patient population at a sixth-grade reading level explaining [Condition], including points such as anatomy, symptoms, physical examination, and treatment (both surgical and nonsurgical)." Before asking the second question, a priming phase was conducted where ChatGPT 3.5 and 4.0 were presented with a text sample written at a sixth-grade reading level and informed that this was the desired output level. Multiple readability tests were used to evaluate the output, with a consensus reading level created from the results of all eight readability scores. Statistical analyses were performed using SAS 9.4. Results: ChatGPT 4.0 successfully produced 28% of its responses at the appropriate reading level following the priming phase, compared to none by ChatGPT 3.5. ChatGPT 4.0 showed superior performance across all readability metrics. Conclusions: ChatGPT 4.0 is a more effective tool than ChatGPT 3.5 for generating PEMs at a sixth-grade reading level for common hand conditions. Clinical relevance: The results suggest that Artificial Intelligence could significantly enhance patient education and health literacy with further refinement.

Indexed as

Artificial intelligenceHandPatient education materials

Identifiers

PMID39991597
PMCPMC11846566

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.