Would You Like Some (Artificial) Help with That? Personalizing Health Supplements with AI
DOI:
https://doi.org/10.47611/jsr.v12i4.2343Keywords:
vitamin supplements, health supplements, healthcare technology, artificial intelligence, extended self, IKEA effect, uniqueness neglect, consumer trustAbstract
A growing number of companies in the healthcare industry are offering consumers the option to personalize their products. The growing use of vitamins and dietary supplements prompts the exploration of artificial intelligence (AI)’s role in optimizing supplement recommendations. This paper investigates the potential integration of medical AI into the personalization of vitamin supplements to enhance consumer healthcare. The influence of AI-assisted medical recommendations was assessed by considering the interplay of patient self-identity and health concerns in choosing between human doctors and AI as evidenced by the Extended Self Theory, the IKEA Effect, uniqueness neglect, and consumer openness. By surveying the literature, this paper aims to explore the benefits of medical AI in the vitamin supplement market; the issues affecting AI uptake in the vitamin supplement market; and a broad theoretical profile of consumers best prepared to switch from a human doctor to AI customization. While acknowledging the current gaps in AI’s capabilities and the challenges of establishing consumer trust in AI-enabled healthcare, this review envisions a future where AI stands as a tool to empower patients and collaborate with human doctors to optimize patient well-being and healthcare. Subsequent investigation might bridge the disparity between the current capabilities of AI in medical support and its potential for widespread adoption.
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Aaker, J. L. (1999). The Malleable Self: The Role of Self-Expression in Persuasion. Journal of Marketing Research, 36(1), 45. https://doi.org/10.2307/3151914
Adams, S. H., Anthony, J. C., Carvajal, R., Chae, L., Khoo, C. S., Latulippe, M. E., Matusheski, N. V., McClung, H. L., Rozga, M., Schmid, C. H., Wopereis, S., & Yan, W. (2020). Perspective: Guiding Principles for the Implementation of Personalized Nutrition Approaches That Benefit Health and Function. Advances in Nutrition, 11(1), 25–34. https://doi.org/10.1093/advances/nmz086
Agyekum, C. K., Haifeng, H., & Agyeiwaa, A. (2015). Consumer Perception of Product Quality. Microeconomics and Macroeconomics, 3(2), 25–29. https://doi.org/10.5923/j.m2economics.20150302.01
André, Q., Carmon, Z., Wertenbroch, K., Crum, A., Frank, D., Goldstein, W., Huber, J., van Boven, L., Weber, B., & Yang, H. (2017). Consumer Choice and Autonomy in the Age of Artificial Intelligence and Big Data. Customer Needs and Solutions, 5(1–2), 28–37. https://doi.org/10.1007/s40547-017-0085-8
Arora, N., Dreze, X., Ghose, A., Hess, J. D., Iyengar, R., Jing, B., Joshi, Y., Kumar, V., Lurie, N., Neslin, S., Sajeesh, S., Su, M., Syam, N., Thomas, J., & Zhang, Z. J. (2008). Putting One-to-One Marketing to Work: Personalization, Customization, and Choice. Marketing Letters, 19(3–4), 305–321. https://doi.org/10.1007/s11002-008-9056-z
Azevedo, D., Legay, A., & Kieffer, S. (2022). User Reception of Babylon Health’s Chatbot. Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. https://doi.org/10.5220/0010803000003124
Belk, R. W. (1988). Possessions and the Extended Self. Journal of Consumer Research, 15(2), 139–168. https://doi.org/10.1086/209154
Berger, J., & Heath, C. (2007). Where Consumers Diverge from Others: Identity Signaling and Product Domains. Journal of Consumer Research, 34(2), 121–134. https://doi.org/10.1086/519142
Blumberg, J., Bailey, R., Sesso, H., & Ulrich, C. (2018). The Evolving Role of Multivitamin/Multimineral Supplement Use Among Adults in the Age of Personalized Nutrition. Nutrients, 10(2), 248. https://doi.org/10.3390/nu10020248
Briganti, G., & Le Moine, O. (2020). Artificial Intelligence in Medicine: Today and Tomorrow. Frontiers in Medicine, 7. https://doi.org/10.3389/fmed.2020.00027
Carmon, Z., Schrift, R., Wertenbroch, K., & Yang, H. (2019). Designing AI Systems That Customers Won’t Hate. MITSloan Management Review.
Castelo, N., Bos, M., & Lehmann, D. (2018). Consumers’ Trust in Algorithms. Advances in Consumer Research, 46, 63–67.
Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2019). How Artificial Intelligence Will Change the Future of Marketing. Journal of the Academy of Marketing Science, 48(1), 24–42. https://doi.org/10.1007/s11747-019-00696-0
de Jong, N., Ocké, M. C., Branderhorst, H. A., & Friele, R. (2003). Demographic and Lifestyle Characteristics of Functional Food Consumers and Dietary Supplement Users. British Journal of Nutrition, 89(2), 273–281. https://doi.org/10.1079/bjn2002772
Dickinson, A., MacKay, D., & Wong, A. (2015). Consumer Attitudes About the Role of Multivitamins and Other Dietary Supplements: Report of a Survey. Nutrition Journal, 14(1). https://doi.org/10.1186/s12937-015-0053-9
Efendic, E., van de Calseyde, P., Bahník, Š., & Vranka, M. A. (2023). Taking Algorithmic (vs. Human) Advice Reveals Different Goals to Others. https://doi.org/10.31234/osf.io/bp24r
Frank, D.-A., Elbæk, C. T., Børsting, C. K., Mitkidis, P., Otterbring, T., & Borau, S. (2021). Drivers and Social Implications of Artificial Intelligence Adoption in Healthcare During the COVID-19 Pandemic. PLOS ONE, 16(11). https://doi.org/10.1371/journal.pone.0259928
Greger, J. L. (2001). Dietary Supplement Use: Consumer Characteristics and Interests. The Journal of Nutrition, 131(4). https://doi.org/10.1093/jn/131.4.1339s
Huo, W., Zhang, Z., Qu, J., Yan, J., Yan, S., Yan, J., & Shi, B. (2023). Speciesism and Preference of Human–Artificial Intelligence Interaction: A Study on Medical Artificial Intelligence. International Journal of Human–Computer Interaction, 1–13. https://doi.org/10.1080/10447318.2023.2176985
Kirk, S. F., Cade, J. E., Barrett, J. H., & Conner, M. (1999). Diet and Lifestyle Characteristics Associated with Dietary Supplement Use in Women. Public Health Nutrition, 2(1), 69–73. https://doi.org/10.1017/s1368980099000099
Larkin, C., Drummond Otten, C., & Árvai, J. (2021). Paging Dr. Jarvis! Will People Accept Advice from Artificial Intelligence for Consequential Risk Management Decisions? Journal of Risk Research, 25(4), 407–422. https://doi.org/10.1080/13669877.2021.1958047
Longoni, C., Bonezzi, A., & Morewedge, C. K. (2018). Consumer Reluctance Toward Medical Artificial Intelligence: the Underlying Role of Uniqueness Neglect. Advances in Consumer Research, 46, 63–67.
Mochon, D., Norton, M. I., & Ariely, D. (2012). Bolstering and Restoring Feelings of Competence Via the IKEA Effect. International Journal of Research in Marketing, 29(4), 363–369. https://doi.org/10.1016/j.ijresmar.2012.05.001
Mugge, R., Schoormans, J. P. L., & Lange, A. de. (2007). Consumers’ Appreciation of Product Personalization. Advances in Consumer Research, 34, 339–341.
Norton, M. I., Mochon, D., & Ariely, D. (2012). The IKEA effect: When Labor Leads to Love. Journal of Consumer Psychology, 22(3), 453–460. https://doi.org/10.1016/j.jcps.2011.08.002
Pezzo, M. V., & Beckstead, J. W. (2020). Patients Prefer Artificial Intelligence to a Human Provider, Provided the AI is Better Than the Human: A Commentary on Longoni, Bonezzi and Morewedge (2019). Judgment and Decision Making, 15(3), 443–445. https://doi.org/10.1017/s1930297500007221
Rosenbaum, G., Goren, A., Shermohammed, M., Wolk, D. M., Tice, A. M., Doyle, J., Meyer, M. N., & Chabris, C. F. (2023). Algorithm Aversion or Appreciation? Four Randomized Field Trials of Personalized Risk-Communication Nudges to Encourage Flu Vaccination. https://doi.org/10.31234/osf.io/vtxza
Soellner, M., & Koenigstorfer, J. (2021). Compliance With Medical Recommendations Depending on the Use of Artificial Intelligence as a Diagnostic Method. BMC Medical Informatics and Decision Making, 21(1). https://doi.org/10.1186/s12911-021-01596-6
Varlamov, O. O., Chuvikov, D. A., Adamova, L. E., Petrov, M. A., Zabolotskaya, I. K., & Zhilina, T. N. (2019). Logical, Philosophical and Ethical Aspects of AI in Medicine. International Journal of Machine Learning and Computing, 9(6), 868–873. https://doi.org/10.18178/ijmlc.2019.9.6.885
Yokoi, R., Eguchi, Y., Fujita, T., & Nakayachi, K. (2020). Artificial Intelligence is Trusted Less Than a Doctor in Medical Treatment Decisions: Influence of Perceived Care and Value Similarity. International Journal of Human–Computer Interaction, 37(10), 981–990. https://doi.org/10.1080/10447318.2020.1861763
Zhou, Y., Shi, Y., Lu, W., & Wan, F. (2022). Did Artificial Intelligence Invade Humans? The Study on the Mechanism of Patients’ Willingness to Accept Artificial Intelligence Medical Care: From the Perspective of Intergroup Threat Theory. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.866124
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