Objectives: The Areas of Worklife Survey (AWS) is widely used to assess organizational factors contributing to burnout. However, evidence regarding its construct and criterion validity has been reported primarily in human service settings. This study evaluated the construct validity of the AWS measurement model and the criterion validity of the AWS–burnout relationship among industrial workers in Thailand. Methods: In this cross-sectional study, a Thai-language electronic questionnaire was administered to 446 industrial workers between June 2024 and August 2024. Of these, 390 participants (87.4%) completed both the AWS and the Maslach Burnout Inventory–General Survey. Data were analyzed using confirmatory factor analysis within a structural equation modeling framework. Results: A modified 6-factor (chi-square/degree of freedom [χ²/df], comparative fit index [CFI], Tucker– Lewis index [TLI], root mean square error of approximation [RMSEA], and standardized root mean square residual [SRMR]) AWS model—excluding 5 items and allowing 2 correlated error terms—demonstrated satisfactory fit (χ²(213)=436.02, p<0.001; χ²/df=2.05; CFI=0.94; TLI=0.92; RMSEA=0.053; SRMR=0.053). Convergent validity (composite reliability=0.74–0.87; average variance extracted [AVE]=0.49–0.58) and discriminant validity were acceptable for most dimensions; however, the Fairness dimension (AVE=0.36) and the Reward–Fairness correlation remained problematic. The partial mediation model demonstrated acceptable criterion validity, with all mediation paths—except reward to values—reaching statistical significance. Conclusions The AWS is a valid measure for assessing factors contributing to burnout among Thai industrial workers. Nevertheless, further refinement is necessary to ensure strong dimension-specific validity with minimal modification.

Objectives: This study investigated the association between baseline exposures to particulate matter with a diameter < 2.5 microns (PM2.5) and subsequent temporal changes in PM2.5 exposure with the incidence of type 2 diabetes among Royal Thai Army personnel. Methods: A retrospective cohort study was conducted using nationwide health check-up data from 21 325 Thai Army personnel between 2018 and 2021. Multilevel mixed-effects parametric survival statistics were utilized to analyze the relationship between baseline (i.e., PM2.5-baseline) and subsequent changes (i.e., PM2.5-change) in PM2.5 exposure and the occurrence of type 2 diabetes. Hazard ratios (HRs) and 95% confidence intervals (CIs) were employed to assess this association while considering covariates. Results: There was a significant association between both PM2.5 baseline and PM2.5-change and the incidence of type 2 diabetes in a dose-response manner. Compared to quartile 1, the HRs for quartiles 2 to 4 of PM2.5-baseline were 1.11 (95% CI, 0.74 to 1.65), 1.51 (95% CI, 1.00 to 2.28), and 1.77 (95% CI, 1.07 to 2.93), respectively. Similarly, the HRs for quartiles 2 to 4 of PM2.5-change were 1.41 (95% CI, 1.14 to 1.75), 1.43 (95% CI, 1.13 to 1.81) and 2.40 (95% CI, 1.84 to 3.14), respectively. Conclusions Our findings contribute to existing evidence regarding the association between short-term and long-term exposure to PM2.5 and the incidence of diabetes among personnel in the Royal Thai Army.