1Health Promotion Research, Havre, Montana, USA
2Kinesmetrics Lab, Tallahassee, Florida, USA
Research in Psychology and Behavioral Sciences.
2025,
Vol. 13 No. 1, 9-15
DOI: 10.12691/rpbs-13-1-2
Copyright © 2025 Science and Education PublishingCite this paper: Peter D. Hart. Validation of A Physical Activity Scale for Older Adults Participating in the Health and Retirement Study.
Research in Psychology and Behavioral Sciences. 2025; 13(1):9-15. doi: 10.12691/rpbs-13-1-2.
Correspondence to: Peter D. Hart, Health Promotion Research, Havre, Montana, USA. Email:
pdhart@outlook.comAbstract
Background: The surveillance of physical activity (PA) at the population level generally involves administering a small number of survey questions. The combining of multiple related items to create a scale that yields a score has many psychometric benefits. Purpose: The aim of this research was to validate a new scale measuring physical activity (PA) using items contained in a large national survey of older adults. Methods: Data from 12,145 adults 50+ years of age participating in the 2022 Health and Retirement Study were used. The assessment strategy involved six steps: 1) defining the PA scale (PAS) items and categories, 2) factor analysis, 3) internal consistency reliability, 4) item response theory (IRT) analysis, 5) construct validity correlations, and 6) modeling PAS scores with a general health (GH) outcome. Polychoric correlations between items were used for the analyses. A graded response model (GRM) for polytomous items was employed for the IRT analysis. Multinomial logistic regression was used to model GH categories with both categorical and numeric PAS scores. Results: The PAS included three items of vigorous (VPA), moderate (MPA), and light PA (LPA), each with the same rating scale consisting of “inactive,” “low/moderately active,” and “highly active.” Factor analysis retained a single factor with 70% explained variance, whilst the reliability coefficient for items was 0.79. IRT calibration showed category thresholds ranging from -1.89 to 1.07 and item discrimination parameters between 1.37 and 5.27. IRT theta scores correlated with the PAS sum score (r=0.96), age (r=-0.22), GH (r=0.41), and timed walk performance (r=0.38). Modeling showed that for each point increase in the numeric PAS score, odds of poor (OR=0.31, 0.27-0.34), fair (OR=0.47, 0.43-0.52), good (OR=0.60, 0.56-0.65), and very good (OR=0.79, 0.73-0.85) GH, as compared to excellent (reference), decreased. Conclusion: These results support the use of a simple 3-item PAS to measure PA in older adults.
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