Research Article
Psychometric Evaluation of the Indonesian SF-12 Health Survey among Informal Female Workers: A CFA Approach
@INPROCEEDINGS{10.4108/eai.30-7-2025.2360970, author={Dina Lusiana Setyowati and Nur Rohmah and Hanifa M Denny and Indah Fitri Astuti and Fatimah Fatimah}, title={Psychometric Evaluation of the Indonesian SF-12 Health Survey among Informal Female Workers: A CFA Approach}, proceedings={Proceedings of the 2nd Faletehan International Conference, FIC 2025, 30-31 July 2025, Serang, Banten, Indonesia}, publisher={EAI}, proceedings_a={FIC}, year={2025}, month={12}, keywords={sf-12 health survey; psychometric validation; confirmatory factor analysis; health-related quality of life; informal workers}, doi={10.4108/eai.30-7-2025.2360970} }- Dina Lusiana Setyowati
Nur Rohmah
Hanifa M Denny
Indah Fitri Astuti
Fatimah Fatimah
Year: 2025
Psychometric Evaluation of the Indonesian SF-12 Health Survey among Informal Female Workers: A CFA Approach
FIC
EAI
DOI: 10.4108/eai.30-7-2025.2360970
Abstract
The Short Form-12 Health Survey (SF-12) is a widely used tool for assessing health-related quality of life (HRQoL). Cultural adaptation and psychometric validation are essential for accuracy across diverse populations, particularly in marginalized or small-sample settings. This study examined the construct validity and internal consistency of the Indonesian SF-12 among informal female workers using a unidimensional model. A cross-sectional survey was conducted with 31 participants. Confirmatory Factor Analysis (CFA) using Maximum Likelihood Estimation in JASP assessed model fit (CFI, TLI, RMSEA, SRMR). SF-12 showed high reliability (Cronbach’s alpha = 0.884; McDonald’s omega = 0.878). Eleven of 12 items had significant factor loadings; SFa did not. Model fit indices and AVE (0.431) were below recommended cutoffs, indicating limited convergent validity. Despite strong reliability, the unidimensional structure showed inadequate fit, suggesting cultural misalignment. Future studies should explore alternative models, increase sample sizes, and adjust for cultural factors to improve psychometric robustness.
