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Original Articles
- Psychometric Properties of the Areas of Worklife Survey in an Industrial Context in Thailand
- Jate Ratanachina, Inthuon Hongsiri, Watcharakorn Chuthong, Wiroj Jiamjarasrangsi
- Received July 15, 2025 Accepted September 3, 2025 Published online October 16, 2025
- DOI: https://doi.org/10.3961/jpmph.25.569 [Accepted]
- 65,535 View
- 40 Download
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Abstract
PDF - 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 and August 2024. Of these, 390 participants (87.4%) completed both the AWS and the Maslach Burnout Inventory–General Survey (MBI–GS). Data were analyzed using confirmatory factor analysis within a structural equation modeling framework.
Results
A modified 6-factor 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 (CR=0.74–0.87; 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. -
Summary
- The Association Between PM2.5 Exposure and Diabetes Mellitus Among Thai Army Personnel
- Apisorn Laorattapong, Sarun Poobunjirdkul, Thanapoom Thanapoom, Wiroj Jiamjarasrangsi
- J Prev Med Public Health. 2023;56(5):449-457. Published online September 26, 2023
- DOI: https://doi.org/10.3961/jpmph.23.292
- 5,795 View
- 150 Download
- 3 Web of Science
- 3 Crossref
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Abstract
Summary
PDF
Supplementary Material - 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. -
SummaryKey Message
We simultaneously investigated the impact of the baseline and temporal variations in the exposure to particulate matter (PM) with a diameter <2.5 microns (PM2.5) on type 2 diabetes risk among the Royal Thai Army personnel. We found stronger evidence on the impact of the temporal variation in PM2.5 exposure on the disease risk than that of the baseline variation. This finding may reflect the shorter time frame between the increased PM2.5 exposure and changes in fasting plasma glucose level.Citations
Citations to this article as recorded by
- Environmental Endocrine‐Disrupting Chemicals, Pancreatic β‐Cells, and Type 2 Diabetes Mellitus
Yan‐li Zhao, Yang Ou
Clinical Endocrinology.2025;[Epub] CrossRef - Epidemiological and mechanistic links between PM2.5 exposure and type 2 diabetes: focus on the TRPV1 receptor
Filippo Liviero, Sofia Pavanello
Frontiers in Endocrinology.2025;[Epub] CrossRef - Influence of Air Pollution Exposures on Cardiometabolic Risk Factors: a Review
Li-Hao Guo, Mohammed Zeeshan, Guo-Feng Huang, Duo-Hong Chen, Min Xie, Jun Liu, Guang-Hui Dong
Current Environmental Health Reports.2023; 10(4): 501. CrossRef
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