ArticleFrontiers in psychology2025
Psychometric properties and network analysis of the Chinese version of the uncertainty about disease and treatment scale for patients undergoing hemodialysis.
Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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5 authors.
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Abstract
Purpose: This study aimed to translate and culturally adapt the Uncertainty about Disease and Treatment Scale (UC-D&TS), systematically evaluate its reliability and validity among Chinese hemodialysis patients, and use network analysis to explore the latent structural relationships among constructs, providing tools and theoretical support for precise identification and intervention in the future. Methods: The study was conducted across five hemodialysis centers in the eastern and northeast part of China. Following Brislin translation model, the original UC-D&TS were developed to Chinese version. EFA was used to clarify the scale structure. Network analysis via EGA examined inter-item associations and centrality features. CFA assessed model fit. Additionally, test-retest reliability, convergent validity, and criterion-related validity were evaluated to comprehensively examine the psychometric properties of the scale. Results: A total of 404 hemodialysis patients were included. EFA led to the removal of two items with factor loadings below 0.4, resulting in a five-factor structure. EGA confirmed the robustness of the structure and identified core items related to key psychological themes such as crisis preparedness, alternative treatment cognition based on expected influence and strength values. CFA supported a well-fitting second-order model and the scale demonstrated excellent internal consistency. All factors showed average variance extracted values > 0.50 and composite reliability values above 0.70, indicating good psychometric characteristics. Conclusion: The Chinese version of UC-D&TS exhibits strong reliability and validity in hemodialysis patients. Network analysis reveals meaningful relationships among key psychological constructs, facilitating identification of core areas of patient distress. This scale serves as an effective tool for assessing uncertainty perceptions, offering valuable guidance for clinical psychological support and personalized interventions.
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