Zhengzijin Yang, Siyu Zhao
Background: Robot-assisted gynecological surgery (RAGS) represents a major advancement in minimally invasive care with demonstrated clinical benefits. Yet, its adoption depends on individual acceptance shaped by complex psychosocial factors, particularly salient in China due to healthcare disparities and information asymmetry. Prior studies on health technology acceptance have seldom examined discrepancies between individual expectations and actual clinical outcomes. This study investigates Chinese women's acceptance of RAGS, introducing the concept of perceived postoperative difference to capture the perception-reality gap and its influence on behavioral intention. Methods: A cross-sectional survey was conducted among Chinese women using convenience sampling, yielding 546 valid responses. An extended UTAUT framework incorporating trust, perceived risk, and perceived postoperative difference (PPD) was applied. The perception-reality gap was quantified by matching participants' perceived postoperative outcomes with objective clinical data. Structural Equation Modeling (SEM) tested the framework, and multi-group SEM examined behavioral differences across gap-defined groups. Analysis of variance and chi-square tests were used to assess demographic variations among these groups. Results: The model showed good fit. Analyses indicated that effort expectancy was the strongest predictor of behavioral intention, followed by perceived postoperative difference and performance expectancy. Facilitating conditions enhanced both behavioral intention and performance expectancy, while trust increased both and reduced perceived risk. Multi-group analysis revealed notable heterogeneity. In the overestimation group, behavioral intention mainly depended on effort expectancy, while social influence and perceived risk reduced intention. In the alignment group, facilitating conditions and trust improved performance expectancy. In the underestimation group, behavioral intention was primarily shaped by performance expectancy and social influence. Higher education and technical jobs characterized the overestimation group, whereas lower education and unstable employment defined the underestimation group. Conclusion: This study reveals that the perception-reality gap reconfigures women's decision pathways, demonstrating that adoption mechanisms are highly heterogeneous across perceptual groups. These gaps reflect underlying socioeconomic and structural factors, highlighting the necessity of targeted patient education and communication strategies. This research expands the boundaries of traditional technology adoption models in high-risk medical contexts, refines user acceptance theory, and provides valuable empirical evidence for formulating personalized communication strategies and optimizing the promotion of novel medical technologies.