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ChatGPT for Tinnitus Information and Support: Response Accuracy and Retest after Three and Six Months

Jedrzejczak, W. Wiktor, Skarzynski, Piotr H., Raj-Koziak, Danuta, Sanfins, Milaine Dominici, Hatzopoulos, Stavros, Kochanek, Krzysztof·2024·Brain Sciences

Published version of a preprint

Abstract

Testing of ChatGPT has recently been performed over a diverse range of topics. However, most of these assessments have been based on broad domains of knowledge. Here, we test ChatGPT’s knowledge of tinnitus, an important but specialized aspect of audiology and otolaryngology. Testing involved evaluating ChatGPT’s answers to a defined set of 10 questions on tinnitus. Furthermore, given the technology is advancing quickly, we re-evaluated the responses to the same 10 questions 3 and 6 months later. The accuracy of the responses was rated by 6 experts (the authors) using a Likert scale ranging from 1 to 5. Most of ChatGPT’s responses were rated as satisfactory or better. However, we did detect a few instances where the responses were not accurate and might be considered somewhat misleading. Over the first 3 months, the ratings generally improved, but there was no more significant improvement at 6 months. In our judgment, ChatGPT provided unexpectedly good responses, given that the questions were quite specific. Although no potentially harmful errors were identified, some mistakes could be seen as somewhat misleading. ChatGPT shows great potential if further developed by experts in specific areas, but for now, it is not yet ready for serious application.

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Figure 1 A screenshot of a portion of a ChatGPT response to question number 8 in which references were asked for. The prompt used was: “Is there a link between tinnitus and the psychological state of the patient? Provide sources of information”. Only the part of the response with references is shown.
Figure 1 A screenshot of a portion of a ChatGPT response to question number 8 in which references were asked for. The prompt used was: “Is there a link between tinnitus and the psychological state of the patient? Provide sources of information”. Only the part of the response with references is shown.CC BY · PubMed Central

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Research works printed but not linked: 41

  1. Trust, 2023, ChatGPT: Challenges, Opportunities, and Implications for Teacher Education, Contemp. Issues Technol. Teach. Educ., 23, 1
  2. Yanagita, 2023, Accuracy of ChatGPT on Medical Questions in the National Medical Licensing Examination in Japan: Evaluation Study, JMIR Form. Res., 7, e48023, 10.2196/48023 · DOI
  3. Gobira, 2023, Performance of ChatGPT-4 in answering questions from the Brazilian National Examination for Medical Degree Revalidation, Rev. Assoc. Med. Bras., 69, e20230848, 10.1590/1806-9282.20230848 · DOI
  4. Luykx, 2023, The performance of ChatGPT in generating answers to clinical questions in psychiatry: A two-layer assessment, World Psychiatry, 22, 479, 10.1002/wps.21145 · DOI
  5. Iarossi, 2023, How good does ChatGPT answer frequently asked questions about haemophilia?, Haemophilia, 29, 1646, 10.1111/hae.14858 · DOI
  6. Emile, 2023, How appropriate are answers of online chat-based artificial intelligence (ChatGPT) to common questions on colon cancer?, Surgery, 174, 1273, 10.1016/j.surg.2023.06.005 · DOI
  7. Nielsen, 2023, Validity of the large language model ChatGPT (GPT4) as a patient information source in otolaryngology by a variety of doctors in a tertiary otorhinolaryngology department, Acta Oto-Laryngol., 143, 779, 10.1080/00016489.2023.2254809 · DOI
  8. Kim, 2023, A Case Report on Ground-Level Alternobaric Vertigo Due to Eustachian Tube Dysfunction With the Assistance of Conversational Generative Pre-trained Transformer (ChatGPT), Cureus, 15, e36830
  9. Swanepoel, 2023, The rise of AI Chatbots in hearing health care, Heart J., 76, 26
  10. Langguth, 2013, Tinnitus: Causes and clinical management, Lancet Neurol., 12, 920, 10.1016/S1474-4422(13)70160-1 · DOI
  11. Jackson, 2019, Objective Measures of Tinnitus: A Systematic Review, Otol. Neurotol., 40, 154, 10.1097/MAO.0000000000002116 · DOI
  12. Henry, 2014, Underlying mechanisms of tinnitus: Review and clinical implications, J. Am. Acad. Audiol., 25, 5, 10.3766/jaaa.25.1.2 · DOI
  13. Jarach, 2022, Global Prevalence and Incidence of Tinnitus, JAMA Neurol., 79, 888, 10.1001/jamaneurol.2022.2189 · DOI
  14. Davis, 2019, Hearing loss: Rising prevalence and impact, Bull. World Health Organ., 97, 646, 10.2471/BLT.19.224683 · DOI
  15. AStohler, 2019, A study on the epidemiology of tinnitus in the United Kingdom, Clin. Epidemiol., 11, 855, 10.2147/CLEP.S213136 · DOI
  16. Kutyba, 2022, Self-help interventions chosen by subjects with chronic tinnitus—A retrospective study of clinical patients, Int. J. Audiol., 61, 686, 10.1080/14992027.2021.1964040 · DOI
  17. Manchaiah, 2022, Online Discussions about Tinnitus: What Can We Learn from Natural Language Processing of Reddit Posts?, Am. J. Audiol., 31, 993, 10.1044/2021_AJA-21-00158 · DOI
  18. Moons, 2024, What if your patient switches from Dr. Google to Dr. ChatGPT? A vignette-based survey of the trustworthiness, value, and danger of ChatGPT-generated responses to health questions, Eur. J. Cardiovasc. Nurs., 23, 95, 10.1093/eurjcn/zvad038 · DOI
  19. Jan, 2003, Clinical Evaluation of Tinnitus: A Review, Audiol. Med., 1, 101, 10.1080/16513860301714 · DOI
  20. Penner, 1988, Audible and annoying spontaneous otoacoustic emissions. A case study, Arch. Otolaryngol. Head Neck Surg., 114, 150, 10.1001/archotol.1988.01860140048019 · DOI
  21. Jedrzejczak, W.W., Pilka, E., Ganc, M., Kochanek, K., and Skarzynski, H. (2022). Ultra-High Frequency Distortion Product Otoacoustic Emissions for Detection of Hearing Loss and Tinnitus. Int. J. Environ. Res. Public Health, 19. · DOI
  22. Trevis, 2018, A systematic review and meta-analysis of psychological functioning in chronic tinnitus, Clin. Psychol. Rev., 60, 62, 10.1016/j.cpr.2017.12.006 · DOI
  23. Newman, 1996, Development of the Tinnitus Handicap Inventory, Arch. Otolaryngol. Neck Surg., 122, 143, 10.1001/archotol.1996.01890140029007 · DOI
  24. Lee, 2015, Otologic manifestations of acoustic neuroma, Acta Oto-Laryngol., 135, 140, 10.3109/00016489.2014.952334 · DOI
  25. Milloy, 2017, Auditory Brainstem Responses in Tinnitus: A Review of Who, How, and What?, Front. Aging Neurosci., 9, 237, 10.3389/fnagi.2017.00237 · DOI
  26. Patil, 2023, Comparative performance of ChatGPT and bard in a text-based radiology knowledge assessmen, Can. Assoc. Radiol. J., 75, 344, 10.1177/08465371231193716 · DOI
  27. Benjamini, 1995, Controlling the false discovery rate: A practical and powerful approach to multiple testing, J. R. Stat. Soc. Ser. B Methodol., 57, 289, 10.1111/j.2517-6161.1995.tb02031.x · DOI · Paper page
  28. Buhr, 2023, ChatGPT Versus Consultants: Blinded Evaluation on Answering Otorhinolaryngology Case–Based Questions, JMIR Med. Educ., 9, e49183, 10.2196/49183 · DOI
  29. Huang, Y., and Sun, L. (2023). Harnessing the power of chatgpt in fake news: An in-depth exploration in generation, detection and explanation. arXiv.
  30. Marcrum, S.C., Engelke, M., Goedhart, H., Langguth, B., Schlee, W., Vesala, M., and Simoes, J.P. (2022). The Influence of Diet on Tinnitus Severity: Results of a Large-Scale, Online Survey. Nutrients, 14. · DOI
  31. Zurek, 1981, Spontaneous narrowband acoustic signals emitted by human ears, J. Acoust. Soc. Am., 69, 514, 10.1121/1.385481 · DOI
  32. Hiller, 1992, A psychometric study of complaints in chronic tinnitus, J. Psychosom. Res., 36, 337, 10.1016/0022-3999(92)90070-I · DOI · Paper page
  33. Hiller, 1994, Reliability of self-rated tinnitus distress and association with psychological symptom patterns, Br. J. Clin. Psychol., 33, 231, 10.1111/j.2044-8260.1994.tb01117.x · DOI
  34. Goddard, 2023, Hallucinations in ChatGPT: A Cautionary Tale for Biomedical Researchers, Am. J. Med., 136, 1059, 10.1016/j.amjmed.2023.06.012 · DOI
  35. Sanfins, 2023, Skarzynski Tinnitus Scale: Cultural Adaptation and Validation to Brazilian Portuguese, Int. Arch. Otorhinolaryngol., 27, e400, 10.1055/s-0042-1742351 · DOI
  36. Halily, 2021, Validation of a Moroccan Arabic Version of the Tinnitus Handicap Inventory (THI-M), Otol. Neurotol., 42, e1432, 10.1097/MAO.0000000000003311 · DOI
  37. Jedrzejczak, W.W., and Kochanek, K. (2023). Comparison of the audiological knowledge of three chatbots: ChatGPT, Bing Chat, and Bard. medRxiv. · DOI
  38. Freire, 2024, ChatGPT performance in prosthodontics: Assessment of accuracy and repeatability in answer generation, J. Prosthet. Dent., 131, 659.e1, 10.1016/j.prosdent.2024.01.018 · DOI
  39. Lewandowski, M., Łukowicz, P., Świetlik, D., and Barańska-Rybak, W. (2023). An original study of ChatGPT-3.5 and ChatGPT-4 Dermatological Knowledge Level based on the Dermatology Specialty Certificate Examinations. Clin. Exp. Dermatol., llad255. · DOI
  40. Plevris, 2023, Chatbots Put to the Test in Math and Logic Problems: A Comparison and Assessment of ChatGPT-3.5, ChatGPT-4, and Google Bard, AI, 4, 949, 10.3390/ai4040048 · DOI
  41. Rahsepar, 2023, How AI Responds to Common Lung Cancer Questions: ChatGPT versus Google Bard, Radiology, 307, e230922, 10.1148/radiol.230922 · DOI

Metadata

Authors
Jedrzejczak, W. W., Skarzynski, P. H., Raj-Koziak, D., Sanfins, M. D., Hatzopoulos, S., & Kochanek, K.
Affiliations
  • Department of Experimental Audiology, World Hearing Center, Institute of Physiology and Pathology of Hearing, 05-830 Kajetany, Poland
  • Department of Teleaudiology and Screening, World Hearing Center, Institute of Physiology and Pathology of Hearing, 05-830 Kajetany, Poland
  • Tinnitus Department, World Hearing Center, Institute of Physiology and Pathology of Hearing, 05-830 Kajetany, Poland
  • ENT and Audiology Unit, Department of Neurosciences and Rehabilitation, University of Ferrara, 44121 Ferrara, Italy
Venue
Brain Sciences
Publisher
MDPI AG
Published
2024-05-07
Volume
14
Issue
5
Pages
465
ISSN
2076-3425
Cited by
28
References
4
Language
en

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CoChat. (2026). Citation check: ChatGPT for Tinnitus Information and Support: Response Accuracy and Retest after Three and Six Months. https://app.cochat.ai/papers/10.3390/brainsci14050465
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Jedrzejczak, W. W., Skarzynski, P. H., Raj-Koziak, D., Sanfins, M. D., Hatzopoulos, S., & Kochanek, K. (2024). ChatGPT for Tinnitus Information and Support: Response Accuracy and Retest after Three and Six Months. Brain Sciences. https://doi.org/10.3390/brainsci14050465

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