Human–machine trust has shifted over the past three decades from trust in automation to trust in AI, while research paradigms, disciplines, and problem spaces have expanded. Centered on AI in healthcare, this narrative review offers a longitudinal synthesis that traces and compares phase-specific changes in theory and method, providing design guidance for human-AI systems at different stages of maturity. From a cross-disciplinary view, we introduce an Interdisciplinary Human-AI Trust Research (I-HATR) framework that aligns explainable AI (XAI) with human–computer interaction/human factors engineering (HCI/HFE). We distill three core categories of determinants of human-AI trust in healthcare, user characteristics, AI system attributes, and contextual factors, and summarize the main measurement families and their evolution from self-report to behavioral and psychophysiological approaches, with growing use of multimodal and dynamic evaluation. Finally, we outline key trends, opportunities, and practical challenges to support the development of human-centered, trustworthy AI in healthcare, emphasizing the need to bridge actual trustworthiness and perceived trust through shared metrics, uncertainty communication, and trust calibration.

The purpose is to study the design method of the smart refrigerator man-machine interface. The method adopts conjoint analysis, starting from the human-machine interface of the smart refrigerator, and splitting and orthogonally reorganizing the main components and element types of the interface, allowing users to score the virtual experiment scheme and statistical data, and calculate the utility value of each element and type, analyzes the user preference in the smart refrigerator man-machine interface, and then draws the design principles of the smart refrigerator man-machine interface, and generates the final interface design plan. This paper concluded that through the conjoint analysis method, multi-factor data could be statistically analyzed. Therefore, enable designers to better understand the user preference for the smart refrigerator man-machine interface, improve user experience and user viscosity, and providing ideas for similar interface design in the future.

This research provides a theoretical basis and guidance for the design by establishing a demand index system for the external human-machine interface for automated vehicles. First of all, starting from literature research, combined with market product analysis and user interviews, to establish functional demand indicators for the design of external human-machine interface, then collect data through user surveys, and calculate through AHP to obtain the weights of each level and each element. Clarify the preference characteristics of each demand and carry out consistency test to establish an evaluation system to provide a basis for subsequent decision-making and design practice. Finally, combining the research conclusions and design practice, an external human-machine interface for automated vehicles is designed that meets the user's preferences and characteristics, and provides a usable and effective interface for pedestrians.

To enhance the scientific rigor and user alignment of children’s furniture design, this study proposes a data-driven multi-criteria evaluation framework for design optimization. Focusing on wooden seating products for children, online product reviews were collected and preprocessed using Python and the Jieba word segmentation tool to extract authentic user needs. An evaluation index system was established by filtering indicators through expert focus group discussions and the coefficient of variation method. During the weighting phase, subjective weights were derived using an improved Analytic Hierarchy Process (AHP), while objective weights were calculated via the CRITIC method. A game-theoretic approach was employed to integrate both into a composite weight vector. Finally, the TOPSIS–RSR model was applied to rank and classify the performance levels of four wooden children’s seating designs. Based on the results, specific design guidance strategies were proposed. The proposed framework effectively captures user requirements, balances subjective and objective information, and provides a clear decision-making pathway for selecting optimal design solutions. The study not only advances theoretical research but also offers practical guidance for design, with strong potential for extension to other furniture categories and resource-driven product design domains.

The recycling and reuse of resources is an important way for sustainable development. Through the construction of the service system model, starting from the pain points of the user's perspective, a solution is proposed for the transaction and processing of idle furniture. This paper uses questionnaire surveys and other methods to collect user information, build user portraits, and build a prototype of the idle furniture transaction APP design. The user-centered idle furniture transaction service design combines the analysis of user emotions, pain points and opportunities to provide users with a more expected idle furniture transaction method, and promote the green and sustainable development of the furniture industry.