AimsThis article evaluates the psychometric properties of the Chinese version of the 5-item WHO Well-Being Index (WHO-5) in mainland China.MethodsTwo cross-sectional studies with 1,414 participants from a university in China were conducted. The Chinese version of the WHO-5 was assessed to determine its internal consistency, concurrent validity, factorial validity, and construct validity.ResultsThe results indicate that the WHO-5 is unidimensional and has good internal consistency, with Cronbach's a = 0.85 and 0.81 in Study 1 (n = 903) and Study 2 (n = 511), respectively. The findings also demonstrate that the WHO-5 has good concurrent validity with other well-established measures of wellbeing, self-efficacy, self-esteem, and mental wellbeing. The results of confirmatory factor analysis also suggest that the scale has a good model fit.ConclusionsThis study provides empirical data demonstrating that the Chinese version of the WHO-5 has good psychometric properties. The scale can be a useful measure in epistemological studies and clinical research related to wellbeing in Chinese populations.

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Land surface temperature (LST) data in the thermal infrared (TIR) band measured by the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument are critical for studying surface urban heat islands (SUHIs); however, these acquired TIR LST data are contaminated by clouds, so it is crucial to develop a method to generate cloud-free LST products. In this paper, employing Tianjin as the research area, we combined the Weather Research and Forecasting (WRF) model with a random forest (RF) and a spatial optimization algorithm to propose a cloud-free MODIS-like model (WRFFM). The model can reconstruct cloud-free MODIS-like LSTs and SUHIs are studied. The spatial patterns of the WRFFM LSTs and the MODIS LSTs are consistent; the correlation coefficients in July and December range from 0.8~0.91 and 0.8~0.93, respectively, and the RMSEs range from 0.5~3.8 K and 0.4~1.8 K, respectively, indicating that the modeled results are accurate. We use these WRFFM LSTs to study SUHIs and evaluate the deviations between the MODIS SUHIs and WRFFM SUHIs. When the proportion of clear-sky pixels is below 30%, the deviation is above 3 K, and when the proportion of clear-sky pixels is above 80%, the deviation is below 0.6 K. The results indicate that the developed model can be applied to improve the study of SUHIs and that the number of clear-sky pixels for a city is an important factor that affects the bias relative to the actual SUHI.

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