Skip to main content

ORIGINAL RESEARCH article

Front. Psychol.
Sec. Cognitive Science
Volume 15 - 2024 | doi: 10.3389/fpsyg.2024.1437915
This article is part of the Research Topic Towards Emotion AI to Next Generation Healthcare and Education View all 6 articles

The Effect of Subjective Understanding on Patients' Trust in AI Pharmacy Intravenous Admixture Services

Provisionally accepted
Yongzhi Gong Yongzhi Gong 1Xiaofei Tang Xiaofei Tang 1Haoyu Peng Haoyu Peng 2*
  • 1 School of Business Administration, Southwestern University of Finance and Economics, Chengdu, China
  • 2 University of Peradeniya, Peradeniya, Central Province, Sri Lanka

The final, formatted version of the article will be published soon.

    Medical services are getting automated and intelligent. An emerging medical service is the AI pharmacy intravenous admixture service (PIVAS) that prepares infusions through robots. However, patients may distrust these robots. Therefore, this study aims to investigate the psychological mechanism of patients' trust in AI PIVAS. We conducted one field study and four experimental studies to test our hypotheses. Study 1 and 2 investigated patients' trust of AI PIVAS. Study3 and 4 examined the effect of subjective understanding on trust in AI PIVAS. Study 5 examined the moderating effect of informed consent. The results indicated that patients' reluctance to trust AI PIVAS (Studies 1-2) stems from their lack of subjective understanding (Study 3). Particularly, patients have an illusion of understanding humans and difficulty in understanding AI (Study 4). In addition, informed consent emerges as a moderating factor, which improves patients' subjective understanding of AI PIVAS, thereby increasing their trust (Study 5). The findings suggest that medical service providers should explain the criteria or process to improve patients' subjective understanding of medical AI, thus increasing the trust in algorithm-based services.

    Keywords: artificial intelligence, Subjective understanding, illusion of explanatory depth, Informed Consent, Trust

    Received: 24 May 2024; Accepted: 26 Aug 2024.

    Copyright: © 2024 Gong, Tang and Peng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Haoyu Peng, University of Peradeniya, Peradeniya, 20400, Central Province, Sri Lanka

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.