چكيده به لاتين
The aim of this research is to identify the factors influencing customer trust in medical human-like artificial intelligence (AI) within health systems, to prioritize these factors, and to propose a model for them. A comprehensive review of the literature was conducted, yielding a series of relevant and effective factors related to the topic. Utilizing expert opinions and achieving theoretical saturation, 15 factors were selected as the most impactful, leading to the design and distribution of a questionnaire. The statistical population comprised all individuals capable of using a mobile phone or computer to search for a specific website on the internet. From this population, 244 respondents were included in the sample. The data extracted from the questionnaires were analyzed using Exploratory Factor Analysis (EFA). The analyses from this method, along with the statistical outputs from SPSS software, grouped all the extracted factors into three latent variables. The prioritization of these factors, along with the development of a model to enhance their influence, was performed as an outcome of the questionnaire data analysis. Finally, using a neural network, the factors in the proposed model were ranked. The results of this research are beneficial to technology companies and AI developers, health policy-making organizations and institutions such as the Ministry of Health, physicians and specialists, and the general public. This study is unique in that, to date, no research has examined the factors influencing customer trust in a medical AI that possesses the same appearance and functionality as a human doctor within health systems. By addressing this gap, the research provides valuable insights for the development and implementation of humanoid AI in healthcare, aiming to enhance patient trust and acceptance of such technologies.
