Wang Junkai, Fu Linru, Huang Zeguang, Hu Kan, Lin Zhizhuo, Tang Qiuhong
Information Technology Department, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
School of Business, Guangxi University, Nanning, China.
Digit Health. 2025 Jul 25;11:20552076251358673. doi: 10.1177/20552076251358673. eCollection 2025 Jan-Dec.
This study explores how AI-powered consultation services in internet hospitals influence patient satisfaction through perceived value and emotions. A dual-path analytical framework was developed: the technical path uses the E-S-QUAL model to assess the quality of intelligent consultation guidance services in terms of efficiency, system availability, privacy, and fulfillment; the experiential path is based on the Patient Experience-Driven Model, which integrates service encounter theory (focusing on patient-system interactions) and the Stimulus-Organism-Response theory (explaining how external stimuli trigger psychological and behavioral responses).
The dual-path framework includes two submodels. The technical path examines how service quality dimensions affect patient satisfaction through perceived value (i.e., patients' subjective evaluation of the service's usefulness and reliability). The experiential path investigates how service encounters-including interaction, recommendation, and security-indirectly influence satisfaction via perceived value and patient emotions. A structural equation model was applied to analyze data from 1113 valid survey responses.
Both paths significantly influenced satisfaction. Fulfillment and privacy had the most significant effects in the technical path. In the experiential path, service encounters impacted satisfaction through perceived value and emotions. Emotions acted as psychological amplifiers, with positive emotions enhancing the positive effect of perceived value on satisfaction, while negative emotions weakened this effect. Notably, service encounters suppressed negative emotions more strongly than they enhanced positive ones.
This study clarifies the dual role of technical service quality and emotional experience in shaping patient satisfaction, providing theoretical and practical insights for optimizing AI-powered healthcare consultations.
本研究探讨互联网医院中人工智能驱动的咨询服务如何通过感知价值和情感影响患者满意度。构建了一个双路径分析框架:技术路径使用E-S-QUAL模型从效率、系统可用性、隐私性和完整性方面评估智能咨询指导服务的质量;体验路径基于患者体验驱动模型,该模型整合了服务接触理论(关注患者与系统的交互)和刺激-机体-反应理论(解释外部刺激如何触发心理和行为反应)。
双路径框架包括两个子模型。技术路径考察服务质量维度如何通过感知价值(即患者对服务有用性和可靠性的主观评价)影响患者满意度。体验路径研究服务接触(包括交互、推荐和安全性)如何通过感知价值和患者情感间接影响满意度。应用结构方程模型对1113份有效调查回复的数据进行分析。
两条路径均对满意度有显著影响。在技术路径中,完整性和隐私性的影响最为显著。在体验路径中,服务接触通过感知价值和情感影响满意度。情感起到心理放大器的作用,积极情绪增强感知价值对满意度的积极影响,而消极情绪则削弱这种影响。值得注意的是,服务接触抑制消极情绪的作用比增强积极情绪的作用更强。
本研究阐明了技术服务质量和情感体验在塑造患者满意度方面的双重作用,为优化人工智能驱动的医疗咨询提供了理论和实践见解。