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Original Article Psychometric Properties of the Areas of Worklife Survey in an Industrial Context in Thailand
Jate Ratanachina1corresp_iconorcid , Inthuon Hongsiri1orcid , Watcharakorn Chuthong1orcid , Wiroj Jiamjarasrangsi1orcid

DOI: https://doi.org/10.3961/jpmph.25.569 [Accepted]
Published online: October 16, 2025
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Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
Corresponding author:  Jate Ratanachina,
Email: jate.r@chula.ac.th
Received: 15 July 2025   • Revised: 14 August 2025   • Accepted: 3 September 2025

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.

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