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Measuring worksite health promotion programs: an application of structural equation modeling with ordinal data
Fredrik Odegaard1, Pontus Roos
1Richard Ivey School of Business, Western University, 1150 Richmond Street, London, ON, N5Y 4B3, Canada. fodegaard@ivey.uwo.ca
Summary
This study introduces a new model to measure worksite health promotion program outcomes using structural equation modeling. It analyzes individual health status, lifestyle, and stress levels over time in manufacturing employees.
Area of Science:
- Occupational Health
- Biostatistics
- Psychometrics
Background:
- Worksite health promotion programs aim to improve employee well-being.
- Measuring program effectiveness requires robust analytical methods.
- Existing models may not adequately capture complex health indicators.
Purpose of the Study:
- To present a novel Structural Equation Modeling (SEM) approach for evaluating Worksite Health Promotion Programs.
- To model 'being healthy' using latent variables: Health Status, Lifestyle, and Stress.
- To analyze individual-level changes in these health indicators over time.
Main Methods:
- Application of Structural Equation Modeling (SEM) specifically designed for ordinal data.
- Development of a measurement model with latent variables (Health Status, Lifestyle, Stress) and observable ordinal indicators.
- Empirical analysis using data from three large Swedish manufacturing firms.
Main Results:
- The proposed SEM model effectively measures latent health-related variables using ordinal indicators.
- Analysis revealed distributions and temporal changes in individual Health Status, Lifestyle, and Stress.
- The model provides a framework for assessing the impact of health interventions in occupational settings.
Conclusions:
- SEM is a suitable method for measuring complex health outcomes in worksite programs.
- Understanding individual-level changes in latent health variables is crucial for program evaluation.
- This approach offers valuable insights for optimizing workplace health strategies.
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