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<p>The development of scientifically rigorous evaluation methods is essential to overcome three persistent challenges in public navigation interfaces: inadequate guidance, low usability, and suboptimal user experience. Focusing on intelligent medical guidance systems, this study establishes a dual-dimensional analytical framework encompassing layout aesthetics (spatial composition principles) and visual cognition (information processing patterns). We propose an enhanced grey H-convex correlation model integrating Bayesian Best Worst Method (BBWM) and modified CRITIC with reference point (M-CRITIC-RP) to address weight determination limitations in existing models. Our experimental analysis reveals two key findings: First, the synergistic integration of layout aesthetics (e.g., visual hierarchy balance) and visual cognition characteristics (e.g., attention distribution patterns) significantly improves interface usability for medical service navigation. Second, the proposed BBWM-M-CRITIC-RP hybrid model demonstrates superior performance in quantifying aesthetic-cognition relationships, achieving 88% prediction accuracy compared to conventional methods. In a word, our research provides a new theoretical method for traditional visual display design and a new evaluation criterion for interface design, aiming at improving the user experience.</p>

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Evaluation method for public guidance service interface design based on improved grey H-Convex correlation model: integrating layout aesthetics and user visual cognition

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月5日

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  • Weiwei Wang,
  • Zhiqiang Wen,
  • Zhanmei Hu,
  • Jian Chen,
  • Yanhui Gu,
  • Qizhao Peng

摘要

The development of scientifically rigorous evaluation methods is essential to overcome three persistent challenges in public navigation interfaces: inadequate guidance, low usability, and suboptimal user experience. Focusing on intelligent medical guidance systems, this study establishes a dual-dimensional analytical framework encompassing layout aesthetics (spatial composition principles) and visual cognition (information processing patterns). We propose an enhanced grey H-convex correlation model integrating Bayesian Best Worst Method (BBWM) and modified CRITIC with reference point (M-CRITIC-RP) to address weight determination limitations in existing models. Our experimental analysis reveals two key findings: First, the synergistic integration of layout aesthetics (e.g., visual hierarchy balance) and visual cognition characteristics (e.g., attention distribution patterns) significantly improves interface usability for medical service navigation. Second, the proposed BBWM-M-CRITIC-RP hybrid model demonstrates superior performance in quantifying aesthetic-cognition relationships, achieving 88% prediction accuracy compared to conventional methods. In a word, our research provides a new theoretical method for traditional visual display design and a new evaluation criterion for interface design, aiming at improving the user experience.