Background: Worldwide, mental well-being is a critical issue for public health, especially among medical staff; it affects professionalism, efficiency, quality of care delivery, and overall quality of life. Nevertheless, assessing mental well-being is a complex problem.

Objective: This study aimed to evaluate the psychometric properties of the Chinese-language version of the 14-item Warwick-Edinburgh Mental Well-being Scale (WEMWBS) in medical staff recruited mainly from 6 hospitals in China and provide a reliable measurement of positive mental well-being.

Methods: A cross-sectional online survey was conducted of medical staff from 15 provinces in China from May 15 to July 15, 2020. Confirmatory factor analysis (CFA) was conducted to test the structure of the Chinese WEMWBS. The Spearman correlations of the Chinese WEMWBS with the 5-item World Health Organization Well-Being Index (WHO-5) were used to evaluate convergent validity. The Cronbach α and split-half reliability (λ) represented internal consistency. A graded response model was adopted for an item response theory (IRT) analysis. We report discrimination, difficulty, item characteristic curves (ICCs), and item information curves (IICs). ICCs and IICs were used to estimate reliability and validity based on the IRT analysis.

Results: A total of 572 participants from 15 provinces in China finished the Chinese WEMWBS. The CFA showed that the 1D model was satisfactory and internal consistency reliability was excellent, with α=.965 and λ=0.947, while the item-scale correlation coefficients ranged from r=0.727 to r=0.900. The correlation coefficient between the Chinese WEMWBS and the WHO-5 was significant, at r=0.746. The average variance extraction value was 0.656, and the composite reliability value was 0.964, with good aggregation validity. The discrimination of the Chinese WEMWBS items ranged from 2.026 to 5.098. The ICCs illustrated that the orders of the category thresholds for the 14 items were satisfactory.

Conclusions: The Chinese WEMWBS showed good psychometric properties and can measure well-being in medical staff.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9752453PMC
http://dx.doi.org/10.2196/38108DOI Listing

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