User Satisfaction of Self-Service Kiosks Among Older Patients: A Study Based on the DeLone and McLean IS success model (Preprint)

Read full text
Authors: Huilin Wang, Hongjun Fang, Sinan Shang Guan, Yiming Tian, Jing Li
Cited by: 0

Abstract

BACKGROUND The aging population has become a rapidly expanding user base in smart hospital outpatient departments, posing a significant challenge. Their lower familiarity with digital technology, together with inherent device design flaws, hinders the overall satisfaction among older patients. OBJECTIVE To better understand these potential barriers and promote equitable access to digital healthcare for this demographic, this study examined user satisfaction of self-service kiosks and its influencing factors among older patients. METHODS A cross-sectional study was conducted among 240 older outpatients recruited from a tertiary hospital in Beijing from July to September 2025. Using a 26-item questionnaire and based on the DeLone and McLean IS Success Model (D&M IS Success Model), we employed statistical description and ordinal logistic regression to analyze the determinants of user satisfaction, which were visualized via a forest plot. RESULTS Results of this study showed that user satisfaction exhibited significant positive associations with both information quality and interface quality among older patients. Our findings are in line with the D&M IS Success Model. Additionally, the role of seeking assistance from fellow patients as a marginally significant predictor of user satisfaction merits further consideration. CONCLUSIONS The aged-friendly optimization of self-service kiosks, particularly in information quality and interface quality, serves as a cornerstone for equitable digital healthcare and enhanced patient satisfaction within smart services. Furthermore, interpersonal peer support may act as a critical driver in promoting the utilization of self-service kiosks among older patients.

Fields of Study & Subjects

Technology Use by Older Adults Health Technology Consumer Behavior Technology Adoption and User Behaviour

Publication details

Publication date
14 February 2026
Language
EN
Document type
Preprint