Validation of the translated version of the EVAN-G scale in a Chinese-speaking population

Abstract

Background This study aimed to translate the French version of a perioperative satisfaction questionnaire (EVAN-G) scale, a validated questionnaire for assessing perioperative patient satisfaction, into a Chinese version and validate it in Chinese-speaking patients. Methods We developed the Chinese version of the EVAN-G (EVAN-GC) scale based on the original French version of the EVAN-G. The EVAN-GC scale, the Short version of the Spielberger State-Trait Anxiety Inventory (S-STAI), and the McGill pain questionnaire (MGPQ) were administered on the WeChat mini program. We invited patients to complete these questionnaires within 4 to 24 h after surgery. The psychometric validation of the EVAN-GC scale included validity, reliability, and acceptability. Results Among 220 patients, 217 (98.6%) completed the EVAN-GC scale after surgery. The item-internal consistency revealed good construct validity. Compared with the total scores of the S-STAI and MGPQ, the EVAN-GC scale showed excellent convergent validity (ρ = − 0.32, P < 0.001; ρ = − 0.29, P < 0.001). The EVAN-GC scale could differentiate between groups, which showed good discriminate validity. The Cronbach’s alpha coefficient (0.85) of the translated scale demonstrated satisfactory internal consistency reliability, and a 36-patient subsample retest evidenced good test-retest reliability (ρ = 0.82, P < 0.001). In addition, the median [interquartile range] time of completing the EVAN-GC scale was 3.7 [2.9–4.9] min. Conclusions The EVAN-GC scale has good psychometric properties similar to those of the original French version. The EVAN-GC scale is a valid and reliable measurement to assess patient satisfaction in Chinese-speaking patients. Trial registration The Chinese Clinical Trial Registry, ChiCTR2100049555.

AI Literacy across Curriculum Design: Investigating College Instructor’s Perspectives

“…The scale was validated by assessing face validity and construct validity by administering the pre-existing scale to professors from various universities with specialties in educational psychology, educational technology, and information technology. To assess the construct validity of a scale, a principal component analysis with the Varimax rotation test was conducted (Wang et al, 2022). The exploratory factor analysis test was used to assess how well the 14 measured AI literacy items of this scale represented the number of constructs, with a pilot study consisting of 60 college instructors.…”