基于SSO模型的生成式AI用户依赖形成机制研究
首发时间:2025-12-11
摘要:随着生成式AI在知识创作、数据分析等领域的深度融合,用户对其产生的功能性依赖现象日益凸显。为探究此依赖形成机制,本研究基于SSO模型与认知负荷理论,结合结构方程模型分析,探讨任务复杂性、信息过载与时间压力通过AI落后焦虑与认知负荷影响用户依赖,并检验了AI能力的调节作用。研究结果表明:任务复杂性、信息过载、时间压力均对生成式AI用户依赖产生显著正向影响,AI能力负向调节AI错失焦虑、认知负荷与生成式AI用户依赖间的关系。研究结果揭示了生成式AI用户依赖的心理形成机制,为促进健康、可持续的人机协作模式提供了重要启示。
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Research on the Formation Mechanism of User Dependence on Generative AI: Based on the SSO Model
Abstract:With the deep integration of generative AI into fields such as knowledge creation and data analysis, users\' functional dependence on it has become increasingly evident. To explore the mechanisms underlying this dependence, this study draws on the Stressor-Strain-Outcome model and cognitive load theory, employing structural equation modeling to analyze task complexity, information overload, and time pressure influence user dependence through the mediating roles of AI backward anxiety and cognitive load, while also examining the moderating effect of AI capability. The results indicate that task complexity, information overload, and time pressure significantly positively affect users\' dependence on generative AI. Furthermore, AI capability negatively moderates the relationships between AI backward anxiety, cognitive load, and generative AI dependence. This study reveals the psychological mechanisms driving users\' dependence on generative AI and offers important insights for fostering healthy and sustainable human-AI collaboration.
Keywords: stressor-strain-outcome model generative AI dependency cognitive load theory
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