New Frontiers in Health Literacy: Using ChatGPT to Simplify Health Information for People in the Community
Open accessPublished version of a preprint
Abstract
Background: Most health information does not meet the health literacy needs of our communities. Writing health information in plain language is time-consuming but the release of tools like ChatGPT may make it easier to produce reliable plain language health information. Objective: To investigate the capacity for ChatGPT to produce plain language versions of health texts. Design: Observational study of 26 health texts from reputable websites. Methods: ChatGPT was prompted to ‘rewrite the text for people with low literacy’. Researchers captured three revised versions of each original text. Main Measures: Objective health literacy assessment, including Simple Measure of Gobbledygook (SMOG), proportion of the text that contains complex language (%), number of instances of passive voice and subjective ratings of key messages retained (%). Key Results: On average, original texts were written at grade 12.8 (SD = 2.2) and revised to grade 11.0 (SD = 1.2), p < 0.001. Original texts were on average 22.8% complex (SD = 7.5%) compared to 14.4% (SD = 5.6%) in revised texts, p < 0.001. Original texts had on average 4.7 instances (SD = 3.2) of passive text compared to 1.7 (SD = 1.2) in revised texts, p < 0.001. On average 80% of key messages were retained (SD = 15.0). The more complex original texts showed more improvements than less complex original texts. For example, when original texts were ≥ grade 13, revised versions improved by an average 3.3 grades (SD = 2.2), p < 0.001. Simpler original texts (< grade 11) improved by an average 0.5 grades (SD = 1.4), p < 0.001. Conclusions: This study used multiple objective assessments of health literacy to demonstrate that ChatGPT can simplify health information while retaining most key messages. However, the revised texts typically did not meet health literacy targets for grade reading score, and improvements were marginal for texts that were already relatively simple.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
LLM-enabled chatbots may assist with symptom triage and patient education, including lifestyle-related counseling.
“LLM-enabled chatbots may assist with symptom triage and patient education, including lifestyle-related counseling.40,41”
From Artificial Intelligence in Oncology: Practical Applications Across Clinical Care, Scholarship, and Translation. (2026) · cites this paper as [40]
The Discussion (page unavailable) reports that ChatGPT simplified health information while retaining key messages, supporting a potential role in patient education. The paper does not establish symptom-triage or lifestyle-counseling uses; its Methods section instead notes safeguards against personalised health advice. (LLM, conf=0.87)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., et al. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000198 · Cited by 4,115 · see citing works
Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2023) · JMIR Medical Education · doi:10.2196/45312 · Cited by 2,078 · see citing works
A SWOT analysis of ChatGPT: Implications for educational practice and research
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2195846 · Cited by 1,384 · see citing works
Shoemaker, S. J., Wolf, M. S., & Brach, C. (2014) · Patient Education and Counseling · doi:10.1016/j.pec.2014.05.027 · Cited by 1,366 · see citing works
ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports
Jeblick, K., Schachtner, B., Dexl, J., Mittermeier, A., Stüber, A. T., Topalis, J., Weber, T., Wesp, P., Sabel, B. O., Ricke, J., et al. (2023) · European Radiology · doi:10.1007/s00330-023-10213-1 · Cited by 549 · see citing works
Using ChatGPT to write patient clinic letters
Ali, S. R., Dobbs, T. D., Hutchings, H. A., & Whitaker, I. S. (2023) · The Lancet Digital Health · doi:10.1016/s2589-7500(23)00048-1 · Cited by 375 · see citing works
Lyu, Q., Tan, J., Zapadka, M. E., Ponnatapura, J., Niu, C., Myers, K. J., Wang, G., & Whitlow, C. T. (2023) · Visual Computing for Industry, Biomedicine, and Art · doi:10.1186/s42492-023-00136-5 · Cited by 367 · see citing works
Walker, H. L., Ghani, S., Kuemmerli, C., Nebiker, C. A., Müller, B. P., Raptis, D. A., & Staubli, S. M. (2023) · Journal of Medical Internet Research · doi:10.2196/47479 · Cited by 363 · see citing works
McCaffery, K. J., Dodd, R. H., Cvejic, E., Ayre, J., Batcup, C., Isautier, J., Copp, T., Bonner, C., Pickles, K. M., Nickel, B., et al. (2020) · Public Health Research & Practice · doi:10.17061/phrp30342012 · Cited by 293 · see citing works
Self-citationSamaan, J. S., Yeo, Y. H., Rajeev, N., Hawley, L., Abel, S., Ng, W. H., Srinivasan, N., Park, J., Burch, M., Watson, R., et al. (2023) · Obesity Surgery · doi:10.1007/s11695-023-06603-5 · Cited by 282 · see citing works
Readability of online health information: A meta-narrative systematic review
Daraz, L., Morrow, A. S., Ponce, O. J., Farah, W., Katabi, A., Majzoub, A., Seisa, M. O., Benkhadra, R., Alsawas, M., Larry, P., et al. (2018) · American Journal of Medical Quality · doi:10.1177/1062860617751639 · Cited by 278 · see citing works
Health literacy and the Internet: a study on the readability of Australian online health information
Cheng, C. C., & Dunn, M. (2015) · Australian and New Zealand Journal of Public Health · doi:10.1111/1753-6405.12341 · Cited by 158 · see citing works
Wild, A., Kunstler, B., Goodwin, D. M., Onyala, S., Zhang, L., Kufi, M., Salim, W., Musse, F., Mohideen, M., Asthana, M., et al. (2021) · Public Health Research & Practice · doi:10.17061/phrp3112105 · Cited by 114 · see citing works
Comparison Between ChatGPT and Google Search as Sources of Postoperative Patient Instructions
Ayoub, N., Lee, Y.-J., Grimm, D. R., & Balakrishnan, K. (2023) · JAMA Otolaryngology–Head & Neck Surgery · doi:10.1001/jamaoto.2023.0704 · Cited by 98 · see citing works
Mishra, V., & Dexter, J. P. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.18033 · Cited by 97 · see citing works
ChatGPT Makes Medicine Easy to Swallow: An Exploratory Case Study on Simplified Radiology Reports
Jeblick, K., Schachtner, B., Dexl, J., Mittermeier, A., Stüber, A. T., Topalis, J., Weber, T., Wesp, P., Sabel, B., Ricke, J., et al. (2022) · arXiv · doi:10.48550/arxiv.2212.14882 · Cited by 97 · see citing works
Mac, O. A., Ayre, J., Bell, K., McCaffery, K. J., & Muscat, D. M. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.46051 · Cited by 92 · see citing works
Self-citationAyre, J., Bonner, C., Muscat, D. M., Dunn, A. G., Harrison, E., Dalmazzo, J., Mouwad, D., Aslani, P., Shepherd, H. L., & McCaffery, K. J. (2023) · JMIR Formative Research · doi:10.2196/40645 · Cited by 70 · see citing works
Self-citationWhite, S. J., Barello, S., Marco, E. C. D. S., Colombo, C., Eeckman, E., Gilligan, C., Graffigna, G., Jirasevijinda, T., Mosconi, P., Mullan, J., et al. (2020) · Patient Education and Counseling · doi:10.1016/j.pec.2020.12.025 · Cited by 64 · see citing works
The readability of official public health information on COVID‐19
Mac, O. A., Muscat, D. M., Ayre, J., et al. (2021) · The Medical Journal of Australia · doi:10.5694/mja2.51282 · Cited by 56 · see citing works
Self-citationAyre, J., Muscat, D. M., Mac, O. A., Batcup, C., Cvejic, E., Pickles, K. M., Dolan, H., Bonner, C., Mouwad, D., Zachariah, D., et al. (2022) · Patient Education and Counseling · doi:10.1016/j.pec.2022.03.028 · Cited by 24 · see citing works
Self-citationLeroy, G., Kauchak, D., Haeger, D., et al. (2022) · JAMIA Open · doi:10.1093/jamiaopen/ooac044 · Cited by 15 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [27]McLaughlin GH SMOG Grading-a New Readability Formula Journal of Reading. 1969 12 8 639 646
Cited by
Sorted by citations
The quality and safety of using generative AI to produce patient-centred discharge instructions
Stanceski, K., Zhong, S., Zhang, X., Khadra, S., Tracy, M., Koria, L., Lo, S., Naganathan, V., Kim, J., Dunn, A. G., et al. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01336-w · Cited by 45 · see citing works
Self-citationWardle, C., Urbani, S., & Wang, E. (2025) · Journal of Medical Internet Research · doi:10.2196/79961 · Cited by 43 · see citing works
“While comprehensive research into the use of ChatGPT or other LLMs to seek out health information is not yet available, some scholars have argued that the technology has the potential to not only provide information in accessible formats but also to simplify complicated advice [62].”
Deng, J., Li, L., Oosterhof, J. J., Malliaras, P., Silbernagel, K. G., Breda, S. J., Eygendaal, D., Oei, E. H., & de Vos, R.-J. (2025) · Musculoskeletal Science and Practice · doi:10.1016/j.msksp.2025.103275 · Cited by 12 · see citing works
Meyer, B., Kfuri‐Rubens, R., Schmidt, G., Tariq, M., Riedel, C., Recker, F., Riedel, F., Kiechle, M., & Riedel, M. (2025) · International Journal of Gynecology & Obstetrics · doi:10.1002/ijgo.70251 · Cited by 10 · see citing works
Hundal, J., Veettil, A. A. V., Chung, C., & Hosseini, M. (2026) · American Society of Clinical Oncology Educational Book · doi:10.1200/edbk-26-517280 · Cited by 1 · see citing works
- Authors
- Ayre, J., Mac, O., McCaffery, K., McKay, B. R., Liu, M., Shi, Y., Rezwan, A., & Dunn, A. G.
- Affiliations
- The University of Sydney (AU)
- Corresponding author
- Ayre, Julie
- Venue
- Journal of General Internal Medicine
- Published
- 2023-11-08
- Volume
- 39
- Issue
- 4
- Pages
- 573-577
- ISSN
- 0884-8734 (ISSN-L)
- 1525-1497
- PMC
- PMC10973278
- OpenAlex
- W4388488343
- Cited by
- 124
- References
- 22
- Citations by year
- 2026: 34 · 2025: 55 · 2024: 32 · 2023: 3
- FWCI
- 43.91
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of General Internal Medicine (publishedVersion, cc-by)
- medRxiv (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- University of Sydney
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Physical Sciences › Computer Science › Artificial Intelligence › Text Readability and Simplification
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- health literacy, ChatGPT, text simplification, passive voice, large language models, health communication, community health information
- MeSH terms
- Humans, Language, Reading, Comprehension, Health Literacy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
