Human vs Chatbot: The Role of AI in Healthcare Marketing

  • Tanish Arora Shiv Nadar School, Noida, Uttar Pradesh, India
Keywords: AI, Artificial Intelligence; Chatbot; Sexual and Reproductive Health; Health Promotion; Marginalised Population; Vulnerable Groups

Abstract

With recent innovations in artificial intelligence (AI) and its increased usage in healthcare, medical chatbots have emerged as valuable tools in healthcare promotion. These chatbots, acting as conversational agents, can play a crucial role in addressing disparities in healthcare access, particularly in countries like India. This issue becomes even more complex when addressing stigmatised health concerns, such as those related to gynaecology and sexual health. While existing scholarship has explored factors like awareness, trust, and comfort influencing the uptake of chatbots, limited research has focused on using chatbots for healthcare marketing among socioeconomically marginalised groups. Against this backdrop, this study employs a quantitative approach with a structured survey to assess the general understanding and perceptions of reproductive health-related chatbots among vulnerable women, as well as the factors influencing both adoption and aversion. Additionally, this paper examines whether factors such as confidentiality, accuracy, physical and technological convenience, and anonymity impact the adoption of medical chatbots for sexual health information by economically vulnerable women. The findings reveal notable relationships between prior sexual health education and the willingness to use a chatbot for reproductive health information. Furthermore, the survey indicates that chatbots, due to their anonymity, confidentiality, neutral tone, and ease of access, are often preferred over gynaecologists and even search engines like Google.

References

Agarwal, R., Sanghavi, K., & Kulkarni, M. (2021). The impact of COVID-19 on India’s healthcare sector: Emerging challenges and opportunities. Journal of Health Management, 23(1), 112–122.

Agbo, C. C., Mahmoud, Q. H., & Eklund, J. M. (2019). Blockchain technology in healthcare: A systematic review. Healthcare, 7(2), 56.

Bibault, J.-E., Chaix, B., Guillemassé, A., Cousin, S., Escande, A., Perrin, M., Pienkowski, A., Delamon, G., Nectoux, P., & Brouard, B. (2019a). A Chatbot Versus Physicians to Provide Information for Patients with Breast Cancer: Blind, Randomized Controlled Noninferiority Trial. Journal of Medical Internet Research, 21(11), e15787. https://doi.org/10.2196/15787.

Bickmore, T. W., Pfeifer, L. M., & Jack, B. W. (2009). Taking the time to care: Empowering low health literacy hospital patients with virtual nurse agents. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1265–1274.

Cabitza, F., Rasoini, R., & Gensini, G. F. (2017). Unintended consequences of machine learning in medicine. JAMA, 318(6), 517–518. https://jamanetwork.com/journals/jama/article-abstract/2656134.

Dinesen, B., Nonnecke, B., Lindeman, D., Toft, E., Kidholm, K., Jethwani, K., ... & Young, H. M. (2016). Personalized telehealth in the future: A global research agenda. Journal of Medical Internet Research, 18(3), e53. https://www.jmir.org/2016/3/e53.

Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118. https://www.nature.com/articles/nature21056.

Fan, X., Chao, D., Zhang, Z., Wang, D., Li, X., & Tian, F. (2021a). Utilization of Self-Diagnosis Health Chatbots in Real-World Settings: Case Study. Journal of Medical Internet Research, 23(1), e19928. https://doi.org/10.2196/19928.

Ganapathy, K., & Ravindra, A. (2021). Telemedicine in India: A tool to improve healthcare accessibility. Telemedicine and e-Health, 27(4), 356–365.

Greer, S., Ramo, D., Chang, Y. J., Fu, M., Moskowitz, J., Haritatos, J., & Elfenbein, H. (2022). Chatbots for medical interventions in low-resource settings: A review. Journal of Medical Internet Research, 24(7), e38912. https://www.jmir.org/2022/7/e38912.

Io, H. N., & Lee, C. B. (2018). Understanding the adoption of chatbot. Advances in Intelligent Systems and Computing, 886, 632–643. https://doi.org/10.1007/978-3-030-03402-3_44.

Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., ... & Wang, Y. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology, 2(4), 230–243. https://svn.bmj.com/content/2/4/230.

Kennedy, B., Tyson, A., & Saks, E. (2023). Public awareness of artificial intelligence in everyday activities. Pew Research Center Science & Society. https://www.pewresearch.org/science/2023/02/15/public-awareness-of-artificial-intelligence-in-everyday-activities/.

Krittanawong, C., Johnson, K. W., Rosenson, R. S., Wang, Z., Aydar, M., & Kitai, T. (2017). Deep learning for cardiovascular medicine: A practical primer. European Heart Journal, 40(27), 2147–2159. https://academic.oup.com/eurheartj/article/40/27/2147/5477215.

Kumar, V., Sharma, D., & Gupta, R. (2021). Addressing healthcare access disparities in rural India: Challenges and solutions. Indian Journal of Health Sciences and Biomedical Research, 14(2), 89–96.

Laranjo, L., Dunn, A. G., Tong, H. L., Kocaballi, A. B., Chen, J., Bashir, R., ... & Lau, A. Y. (2018). Conversational agents in healthcare: A systematic review. Journal of the American Medical Informatics Association, 25(9), 1248–1258.

Liu, B., & Sundar, S. S. (2018). Should machines express sympathy and empathy? Experiments with a health advice chatbot. Cyberpsychology, Behavior, and Social Networking, 21(10), 625–636. https://doi.org/10.1089/cyber.2018.0110.

Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2021). A survey on bias and fairness in machine learning. ACM Computing Surveys, 54(6), 1–35.

Mills, R., Mangone, E. R., Lesh, N., Mohan, D., & Baraitser, P. (2023). Chatbots to improve sexual and reproductive health: Realist synthesis. Journal of Medical Internet Research, 25(1), e46761. https://doi.org/10.2196/46761.

Mohamad-Hani Temsah, Fadi Aljamaan, Malki, K. H., Khalid Alhasan, Altamimi, I., Razan Aljarbou, Faisal Bazuhair, Abdulmajeed Alsubaihin, Naif Abdulmajeed, Alshahrani, F., Reem Temsah, Turki Alshahrani, Lama Al-Eyadhy, Serin Mohammed Alkhateeb, Basema Saddik, Rabih Halwani, Jamal, A., Al-Tawfiq, J. A., & Ayman Al-Eyadhy. (2023a). ChatGPT and the Future of Digital Health: A Study on Healthcare Workers’ Perceptions and Expectations. ChatGPT and the Future of Digital Health: A Study on Healthcare Workers’ Perceptions and Expectations, 11(13), 1812–1812. https://doi.org/10.3390/healthcare11131812.

Murdoch, T. B. (2021). Privacy and artificial intelligence: Challenges for protecting health information in the digital age. Canadian Medical Association Journal, 193(8), E282–E284.

Nadarzynski, T., Bayley, J., Llewellyn, C., Kidsley, S., & Graham, C. A. (2020a). Acceptability of artificial intelligence (AI)-enabled chatbots, video consultations and live webchats as online platforms for sexual health advice. BMJ Sexual & Reproductive Health, bmjsrh-2018-200271. https://doi.org/10.1136/bmjsrh-2018-200271.

Nadarzynski, T., Miles, O., Cowie, A., & Ridge, D. (2020). Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study. Digital Health, 6, 2055207620935980. https://journals.sagepub.com/doi/full/10.1177/2055207620935980.

Nadarzynski, T., Puentes, V., Pawlak, I., Mendes, T., Montgomery, I., Bayley, J., & Ridge, D. (2021). Barriers and facilitators to engagement with AI-based chatbots for sexual and reproductive health advice: A qualitative analysis. Sexual Health. https://doi.org/10.1071/sh21123.

Obermeyer, Z., & Emanuel, E. J. (2016). Predicting the future—Big data, machine learning, and clinical medicine. New England Journal of Medicine, 375(13), 1216–1219. https://www.nejm.org/doi/full/10.1056/NEJMp1606181.

Patel, V., Jain, H., & Sharma, S. (2022). Digital health mission and healthcare transformation in India. Indian Journal of Public Health, 66(1), 4–10. https://www.ijph.in/article.asp?issn=0019-557X;year=2022;volume=66;issue=1;spage=4;epage=10;aulast=Patel.

Pillai, R., & Sivathanu, B. (2020a). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199–3226. https://doi.org/10.1108/ijchm-04-2020-0259.

Rajpurkar, P., Irvin, J., Zhu, K., Yang, B., Mehta, H., Duan, T., ... & Ng, A. Y. (2018). CheXNet: Radiologist-level pneumonia detection on chest X-rays with deep learning. arXiv preprint arXiv:1711.05225.

Serra, C. M. (2021). Utility of SanIA Chatbot to maintain continuity of care during COVID-19 pandemic. Biomedical Journal of Scientific & Technical Research, 33(5). https://doi.org/10.26717/bjstr.2021.33.005474.

Shen, J., Zhang, C. J., Jiang, B., Chen, J., Song, J., Liu, Z., et al. (2021). Artificial intelligence versus clinicians in disease diagnosis: Systematic review. JMIR Medical Informatics, 9(4), e24045. https://www.jmir.org/2021/4/e24045.

Topol, E. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books. https://www.basicbooks.com/titles/eric-topol/deep-medicine/9781541644632/.

Wang, H., Gupta, S., Singhal, A., & Muttreja, P. (2015a). An Artificial Intelligence Chatbot for Young People’s Sexual and Reproductive Health in India (SnehAI): Instrumental Case Study. JMIR Preprints. https://preprints.jmir.org/preprint/29969.

WHO. (2020). Digital health in primary care: Overview of the evidence and best practices. World Health Organization. https://www.who.int/publications/i/item/9789240017628.

Winkler, J. A., & Witte, M. (2021). Cultural aspects of AI in healthcare: How cultural values shape acceptance of AI in healthcare services. Journal of Global Health Science, 3(2), e31. https://www.joghs.org/article/doi/10.35500/joghs.2021.3.e31.

World Health Organisation. (2024a, March 22). Unpacking artificial intelligence in sexual and reproductive health and rights. Www.who.int. https://www.who.int/news/item/22-03-2024-unpacking-artifical-intelligence-in-sexual-and-reproductive-health-and-rights.

Published
2024-11-28
How to Cite
Arora, T. (2024). Human vs Chatbot: The Role of AI in Healthcare Marketing. International Journal of Social Science Research and Review, 7(11), 233-254. https://doi.org/10.47814/ijssrr.v7i11.2403