Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Assessing ChatGPT’s ability to answer questions pertaining to erectile dysfunction: can our patients trust it?

Abstract

Erectile dysfunction (ED) is a disorder that can cause distress and shame for men suffering from it. Men with ED will often turn to online support and chat groups to ask intimate questions about their health. ChatGPT is an artificial intelligence (AI)-based software that has been trained to engage in conversation with human input. We sought to assess the accuracy, readability, and reproducibility of ChatGPT’s responses to frequently asked questions regarding the diagnosis, management, and care of patients with ED. Questions pertaining to ED were derived from clinic encounters with patients as well as online chat forums. These were entered into the free ChatGPT version 3.5 during the month of August 2023. Questions were asked on two separate days from unique accounts and computers to prevent the software from memorizing responses linked to a specific user. A total of 35 questions were asked. Outcomes measured were accuracy using grading from board certified urologists, readability with the Gunning Fog Index, and reproducibility by comparing responses between days. For epidemiology of disease, the percentage of responses that were graded as “comprehensive” or “correct but inadequate” was 100% across both days. There was fair reproducibility and median readability of 15.9 (IQR 2.5). For treatment and prevention, the percentage of responses that were graded as “comprehensive” or “correct but inadequate” was 78.9%. There was poor reproducibility of responses with a median readability of 14.5 (IQR 4.0). Risks of treatment and counseling both had 100% of questions graded as “comprehensive” or “correct but inadequate.” The readability score for risks of treatment was median 13.9 (IQR 1.1) and for counseling median 13.8 (IQR 0.5), with good reproducibility for both question domains. ChatGPT provides accurate answers to common patient questions pertaining to ED, although its understanding of treatment options is incomplete and responses are at a reading level too advanced for the average patient.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Grade of Responses by ChatGPT to Questions Pertaining to ED.

Similar content being viewed by others

Data availability

All data generated or analyzed during this study are included in this published article and Supplementary Files and are available open access using ChatGPT software.

References

  1. Rew KT, Heidelbaugh JJ. Erectile dysfunction. Am Fam Physician. 2016;94:820–7.

    PubMed  Google Scholar 

  2. Yafi FA, Jenkins L, Albersen M, Corona G, Isidori AM, Goldfarb S, et al. Erectile dysfunction. Nat Rev Dis Prim. 2016;2:16003.

    Article  PubMed  Google Scholar 

  3. Matsui H, Sopko NA, Hannan JL, Bivalacqua TJ. Pathophysiology of erectile dysfunction. Curr Drug Targets. 2015;16:411–9.

    Article  CAS  PubMed  Google Scholar 

  4. Nguyen HMT, Gabrielson AT, Hellstrom WJG. Erectile dysfunction in young men-a review of the prevalence and risk factors. Sex Med Rev. 2017;5:508–20.

    Article  PubMed  Google Scholar 

  5. Jain V, Raut DK. Medical literature search dot com. Indian J Dermatol Venereol Leprol. 2011;77:135–40.

    Article  PubMed  Google Scholar 

  6. Will ChatGPT transform healthcare? Nat Med. 2023;29:505–6.

  7. Grajales FJ 3rd, Sheps S, Ho K, Novak-Lauscher H, Eysenbach G. Social media: a review and tutorial of applications in medicine and health care. J Med Internet Res. 2014;16:e13.

    Article  PubMed  Google Scholar 

  8. Sallam M. ChatGPT utility in healthcare education, research, and practice: systematic review on the promising perspectives and valid concerns. Healthcare. 2023;11:887.

  9. Thorp HH. ChatGPT is fun, but not an author. Science. 2023;379:313.

    Article  PubMed  Google Scholar 

  10. Contreras Kallens P, Kristensen-McLachlan RD, Christiansen MH. Large language models demonstrate the potential of statistical learning in language. Cogn Sci. 2023;47:e13256.

    Article  PubMed  Google Scholar 

  11. Kung TH, Cheatham M, Medenilla A, Sillos C, De Leon L, Elepaño C, et al. Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models. PLoS Digit Health. 2023;2:e0000198.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Waisberg E, Ong J, Masalkhi M, Kamran SA, Zaman N, Sarker P, et al. GPT-4 and ophthalmology operative notes. Ann Biomed Eng. 2023;51:2353–5.

  13. Yeo YH, Samaan JS, Ng WH, Ting PS, Trivedi H, Vipani A, et al. Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma. Clin Mol Hepatol. 2023;29:721–32.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Karabacak M, Margetis K. Embracing large language models for medical applications: opportunities and challenges. Cureus. 2023;15:e39305.

    PubMed  PubMed Central  Google Scholar 

  15. Świeczkowski D, Kułacz S. The use of the Gunning Fog Index to evaluate the readability of Polish and English drug leaflets in the context of health literacy challenges in medical linguistics: an exploratory study. Cardiol J. 2021;28:627–31.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Foe G, Larson EL. Reading level and comprehension of research consent forms: an integrative review. J Empir Res Hum Res Ethics. 2016;11:31–46.

    Article  PubMed  Google Scholar 

  17. Eltorai AE, Naqvi SS, Ghanian S, Eberson CP, Weiss AP, Born CT, et al. Readability of invasive procedure consent forms. Clin Transl Sci. 2015;8:830–3.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Peate I. Breaking the silence: helping men with erectile dysfunction. Br J Community Nurs. 2012;17:310, 2, 4–7.

  19. Foster P, Luebke M, Razzak AN, Anderson DJ, Hasoon J, Viswanath O, et al. Stigmatization as a barrier to urologic care: a review. Health Psychol Res. 2023;11:84273.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Brown AF, Ma GX, Miranda J, Eng E, Castille D, Brockie T, et al. Structural interventions to reduce and eliminate health disparities. Am J Public Health. 2019;109:S72–8.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Purnell TS, Calhoun EA, Golden SH, Halladay JR, Krok-Schoen JL, Appelhans BM, et al. Achieving health equity: closing the gaps in health care disparities, interventions, and research. Health Aff. 2016;35:1410–5.

    Article  Google Scholar 

  22. Eppler MB, Ganjavi C, Knudsen JE, Davis RJ, Ayo-Ajibola O, Desai A, et al. Bridging the gap between urological research and patient understanding: the role of large language models in automated generation of Layperson’s summaries. Urol Pract. 2023;10:436–43.

    Article  PubMed  Google Scholar 

  23. Gabriel J, Shafik L, Alanbuki A, Larner T. The utility of the ChatGPT artificial intelligence tool for patient education and enquiry in robotic radical prostatectomy. Int Urol Nephrol. 2023;55:2717–32.

  24. Lebhar MS, Velazquez A, Goza S, Hoppe IC. Dr. ChatGPT: utilizing artificial intelligence in surgical education. Cleft Palate Craniofac J. 2023:10556656231193966

  25. McGowan A, Gui Y, Dobbs M, Shuster S, Cotter M, Selloni A, et al. ChatGPT and Bard exhibit spontaneous citation fabrication during psychiatry literature search. Psychiatry Res. 2023;326:115334.

    Article  PubMed  Google Scholar 

  26. Emsley R. ChatGPT: these are not hallucinations - they’re fabrications and falsifications. Schizophrenia. 2023;9:52.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Dave T, Athaluri SA, Singh S. ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations. Front Artif Intell. 2023;6:1169595.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Russo GI, di Mauro M, Cocci A, Cacciamani G, Cimino S, Serefoglu EC, et al. Consulting “Dr Google” for sexual dysfunction: a contemporary worldwide trend analysis. Int J Impot Res. 2020;32:455–61.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors have no acknowledgements.

Author information

Authors and Affiliations

Authors

Contributions

SR: conceptualization, data curation, formal analysis, original draft writing, review and editing. ARS: conceptualization, data curation, formal analysis, review and editing. YB: review and editing. MS: review and editing. RJV: conceptualization, review and editing, supervision.

Corresponding author

Correspondence to Shirin Razdan.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethical approval and consent to participate

Not applicable.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Razdan, S., Siegal, A.R., Brewer, Y. et al. Assessing ChatGPT’s ability to answer questions pertaining to erectile dysfunction: can our patients trust it?. Int J Impot Res (2023). https://doi.org/10.1038/s41443-023-00797-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41443-023-00797-z

This article is cited by

Search

Quick links