ArticleDigital health
How AI-powered consultation services in internet hospitals influence patient satisfaction: A structural analysis.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Reconfiguring Care Practices Through Technology-Supported Services: Pathways to Outpatient Satisfaction in Urban and Rural Public Hospitals.Inquiry : a journal of medical care organization, provision and financingArticle
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: 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). Methods: 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. Results: 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. Conclusions: 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.