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Research Paper
- Formative versus reflective measurement models in nursing research: a secondary data analysis of a cross-sectional study in Korea
- Eun Seo Park, Young Il Cho, Hyo Jin Kim, YeoJin Im, Dong Hee Kim
- J Korean Acad Nurs 2025;55(1):107-118. Published online February 19, 2025
- DOI: https://doi.org/10.4040/jkan.24095
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Abstract
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ePub - Purpose
This study aimed to empirically verify the impact of measurement model selection on research outcomes and their interpretation through an analysis of children’s emotional and social problems measured by the Pediatric Symptom Checklist (PSC) using both reflective and formative measurement models. These models were represented by covariance-based structural equation modeling (CB-SEM) and partial least squares SEM (PLS-SEM), respectively.
Methods
This secondary data analysis evaluated children’s emotional and social problems as both reflective and formative constructs. Reflective models were analyzed using CB-SEM, while formative models were assessed using PLS-SEM. Comparisons between these two approaches were based on model fit and parameter estimates.
Results
In the CB-SEM analysis, which assumed a reflective measurement model, a model was not identified due to inadequate fit indices and a Heywood case, indicating improper model specification. In contrast, the PLS-SEM analysis, assuming a formative measurement model, demonstrated adequate reliability and validity with significant path coefficients, supporting the appropriateness of the formative model for the PSC.
Conclusion
The findings indicate that the PSC is more appropriately analyzed as a formative measurement model using PLS-SEM, rather than as a reflective model using CB-SEM. This study highlights the necessity of selecting an appropriate measurement model based on the theoretical and empirical characteristics of constructs in nursing research. Future research should ensure that the nature of measurement variables is accurately reflected in the choice of statistical models to improve the validity of research outcomes.
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Original Article
- Identifying Latent Classes of Risk Factors for Coronary Artery Disease
- Eunsil Ju, JiSun Choi
- J Korean Acad Nurs 2017;47(6):817-827. Published online January 15, 2017
- DOI: https://doi.org/10.4040/jkan.2017.47.6.817
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Abstract
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Abstract Purpose This study aimed to identify latent classes based on major modifiable risk factors for coronary artery disease.
Methods This was a secondary analysis using data from the electronic medical records of 2,022 patients, who were newly diagnosed with coronary artery disease at a university medical center, from January 2010 to December 2015. Data were analyzed using SPSS version 20.0 for descriptive analysis and Mplus version 7.4 for latent class analysis.
Results Four latent classes of risk factors for coronary artery disease were identified in the final model: ‘smoking-drinking’, ‘high-risk for dyslipidemia’, ‘high-risk for metabolic syndrome’, and ‘high-risk for diabetes and malnutrition’. The likelihood of these latent classes varied significantly based on socio-demographic characteristics, including age, gender, educational level, and occupation.
Conclusion The results showed significant heterogeneity in the pattern of risk factors for coronary artery disease. These findings provide helpful data to develop intervention strategies for the effective prevention of coronary artery disease. Specific characteristics depending on the subpopulation should be considered during the development of interventions.
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Citations
Citations to this article as recorded by
- Usefulness Evaluation of Laplacian Filter and Fast Non-Local Means Algorithm in Coronary Angiographic Images
Kyeongsoo Jeon, Jiwon Song, Jiwon Hur, Chaeeon Lee, Kang-Hyeon Seo, Youngjin Lee
Journal of Radiological Science and Technology.2025; 48(1): 93. CrossRef - The effect of preoperative training provided to patients undergoing coronary artery bypass graft surgery on postoperative comfort
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Journal of Surgery and Medicine.2024; 8(6): 00. CrossRef - Profiling the socioeconomic characteristics, dietary intake, and health status of Korean older adults for nutrition plan customization: a comparison of principal component, factor, and cluster analyses
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Epidemiology and Health.2024; 46: e2024043. CrossRef - Analysis of the Types and Affecting Factors of Older People's Health-related Quality of Life, Using Latent Class Analysis
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Journal of Korean Academy of Community Health Nursing.2020; 31(2): 212. CrossRef - Diagnosis and risk stratification of coronary artery disease in Yemeni patients using treadmill test
NouraddenN Aljaber, ShaneiA Shanei, SultanAbdulwadoud Alshoabi, KamalD Alsultan, MoawiaB Gameraddin, KhaledM Al-Sayaghi
Journal of Family Medicine and Primary Care.2020; 9(5): 2375. CrossRef - Latent Class Analysis for Health-Related Quality of Life in the Middle-Aged Male in South Korea
Youngsuk Cho, Dong Moon Yeum
Journal of Korean Academy of Nursing.2019; 49(1): 104. CrossRef
- Usefulness Evaluation of Laplacian Filter and Fast Non-Local Means Algorithm in Coronary Angiographic Images
- 284 View
- 2 Download
- 6 Crossref
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