Chengcheng Gao, Xicheng Chen, Yan Wang, Weijia Dou, Qiongjie Shao, Rui Zhang, Ying Liang, Nan Li, Fang Hu, Yang Zhao, Zhenxiong Liu, Lei Shang
The main contribution is the Chinese EPES. S-EPES and EPE-DSS are exploratory prototypes demonstrating score-prediction feasibility, not validated clinical instruments; multicenter validation, comparison with conventional item-reduction methods, and measurement-invariance testing are required.
BACKGROUND AND OBJECTIVE: Chinese-language patient-reported experience measures (PREMs) for gastrointestinal endoscopy remain limited. We developed and psychometrically evaluated a 54-item Endoscopy Patient Experience Scale (EPES) for Chinese patients; because the field survey had a valid-response rate of 99.28% (965/972), simplification was framed as a prospective methodological exploration rather than as a response to demonstrated burden.
METHODS: Colonoscopy responses (n = 662) were split by stratified random sampling into an exploration set (n = 463) for exploratory factor analysis and a validation set (n = 199) for confirmatory factor analysis. A 303-patient gastroscopy cohort was used only as a cross-procedure applicability test. A multi-objective black-winged kite algorithm selected Simplified EPES (S-EPES) items to reproduce EPES dimension scores under reliability and item-reduction constraints, and an exploratory decision support system (EPE-DSS) was built from S-EPES and clustering outputs.
RESULTS: The EPES showed acceptable structural, convergent and discriminant validity and reliability in the colonoscopy validation set, and the retained structure was compatible with gastroscopy after removal of bowel-preparation dimensions. The 24-item S-EPES achieved per-dimension R2 > 0.85 against EPES dimension scores; post-hoc classification yielded a weighted-average F1 of 0.917 in colonoscopy data.
CONCLUSION: The main contribution is the Chinese EPES. S-EPES and EPE-DSS are exploratory prototypes demonstrating score-prediction feasibility, not validated clinical instruments; multicenter validation, comparison with conventional item-reduction methods, and measurement-invariance testing are required.