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Vitality is an important domain reflecting both the physical and emotional components of health-related quality of life. Because of its complexity, it has been defined and measured both broadly and narrowly. We explored the dimensionality of a very comprehensive item bank hypothesized to measure vitality and its related concepts.
Secondary analyses were conducted using the responses of 1,343 adults representative of the US general population to Internet-based surveys including 42 items compiled from multiple scales (e.g., SF-36 Vitality, PROMIS-Fatigue), covering a broad range of vitality-related content areas (energy, fatigue, and their interference with physical, mental, social activities, and quality of life). Exploratory and confirmatory factor models were evaluated independently using split-half samples. Bifactor model was used to assess the essential unidimensionality of the items, in comparison with traditional unidimensional, multidimensional, and hierarchical models. Method effects of a common scale or phrase were modeled via correlating errors.
The exploratory factor analysis identified one dominant factor. The confirmatory factor analysis identified a best-fitting (CFI = 0.964, RMSEA = 0.084) bifactor model with one general (vitality) and two group (energy and fatigue) factors, explaining 69, 3, and 4 % of total variance. Correlating errors accounting for the method effects were important in identifying the substantive dimensionality of the items.
The bifactor model proved to be useful for evaluating the dimensionality of a complex construct. Results supported conceptualizing and measuring vitality as a unidimensional energy-fatigue construct. We encourage future studies comparing practical implications of measures based on the broader and narrower conceptualizations of vitality.
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Oxford desk dictionary and thesaurus, American edition, New York: Oxford University Press, 1997.
Hunt, S. M., & McEwen, J. (1989). The development of a subjective health indicator. Sociology of Health & Illness, 2, 231–246. CrossRef
Brook, R. H., Ware, J. E., Davies-Avery, A., et al. (1979). Overview of adult health status measures fielded in RAND’s Health Insurance Study. Medical Care, 17(7 Suppl), 1–131.
Cella, D., Riley, W., Stone, A., et al. (2010). PROMIS Cooperative Group. The patient-reported outcomes measurement information system (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 3(11), 1179–1194. CrossRef
Junghaenel, D. U., Christodoulou, C., Lai, J., & Stone, A. A. (2011). Demographic correlates of fatigue in the US general population: Results from the patient-reported outcomes measurement information system (PROMIS) initiative. Journal of Psychosomatic Research, 71, 117–123. PubMedCentralPubMedCrossRef
Lai, J. S., Cella, D., Choi, S., Junghaenel, D. U., Christodoulou, C., Gershon, R., et al. (2011). How item banks and their application can influence measurement practice in rehabilitation medicine: A PROMIS fatigue item bank example. Archives of Physical Medicine and Rehabilitation, 92(10 Suppl), S20–S27. PubMedCentralPubMedCrossRef
Levine, S., Croog, S. H., Sudilovsky, A., & Testa, M. A. (1987). Effects of antihypertensive medications on vitality and well-being. Journal of Family Practice, 25(4), 357–363. PubMed
Dupuy, H. J. (1984). The psychological general well-being (PGWB) Index. In N. K. Wenger, M. E. Mattson, C. D. Furberg, & J. Elinson (Eds.), Assessment of quality of life in clinical trials of cardiovascular therapies. New York: Le Jacq.
Ware, J.E., Brook, R.H., Ross, D.A., Williams, K.N., Stewart, A.L., Rogers, W.H., et al. (1980). Conceptualization and measurement of health for adults in the Health Insurance Study: Vol. I: Model of health and methodology. Doc. no. R-1987/1-HEW. Santa Monica, CA: RAND Corporation.
Stewart, A. L., & Ware, J. E. (Eds.). (1992). Measuring functioning and well-Being: the medical outcomes study approach. Durham: Duke University Press.
McNair, D., Lorr, M., & Dropplemen, L. (1971). Edits manual: Profile of mood states. San Diego: Educational and Industrial Testing Services.
Webster, K., Cella, D., & Yost, K. (2003). The functional assessment of chronic illness therapy (FACIT) measurement system: Properties, applications and interpretation. Health and Quality of Life Outcomes, 1, 1–7. CrossRef
Dupuy, H.J. (1972). The psychological section of the current Health and nutrition Examination Survey (HANES). Proceedings of the public health conference on records and statistics meeting jointly with the national conference on mental health statistics. US Dept. of Healthy, Education and Welfare publication no. (HRAS) 74-12-14. Washington DC: US Govt. Printing Office.
Holzinger, K. J., & Swineford, F. (1937). The bi-factor method. Psychometrika, 2, 41–54. CrossRef
Chen, F. F., Jing, Y., Hayes, A., & Lee, J. M. (2012). Two concepts or two approaches? A bifactor analysis of psychological and subjective well-being. Journal of Happiness Studies, 1, 1–36.
Ware, J. E, Jr, Kosinski, M., Dewey, J. E., & Gandek, B. (2001). How to score and interpret single-item health status measures: A manual for Users of the SF-8 health survey (with a Supplement on the SF-6 health survey). Lincoln, RI: QualityMetric Incorporated.
Neuberger, G. B. (2003). Measures of fatigue: The fatigue questionnaire, fatigue severity scale, multidimensional assessment of fatigue scale, and short form-36 vitality (energy/fatigue) subscale of the short form health survey. Arthritis Care & Research, 49, S175–S183. CrossRef
Schwartz, A. L. (1998). The Schwartz Cancer fatigue scale: Testing reliability and validity. Oncology Nursing Forum, 25(4), 711–717. PubMed
Kristensena, T.S., Borritza, M., Villadsena, E., Christensena, K.B. (2005). The Copenhagen Burnout Inventory: A new tool for the assessment of burnout. Work & Stress: An International Journal of Work, Health & Organisations, 19(3),192–207.
Ware, J. E., Harrington, M., Guyer, R., & Boulanger, R. (2012). A system for integrating generic and disease-specific patient-reported outcome (PRO) measures. Patient Reported Outcomes Newsletter, 48, 2–4.
Ware, J. E., & Guyer, R. (2014). Measuring physical and emotional health outcomes: How to use the general quality of life (QGEN ® ) measures in the QOLIX ® system. Worcester, MA: JWRG Incorporated.
Wu, H. S., & McSweeney, M. (2001). Measurement of fatigue in people with cancer. Oncology Nursing Forum, 28, 1371–1386. PubMed
Muthén, L.K., Muthén, B.O. (1998–2004). Mplus user’s guide (3rd ed.). Los Angeles, CA: Muthén & Muthén.
Chen, F. F., West, S. G., & Sousa, K. H. (2006). A comparison of bifactor and second-order models of quality-of-life. Multivariate Behavioral Research, 41, 189–225. CrossRef
Chernyshenko, O. S., Stark, S., & Chan, K. Y. (2001). Investigating the hierarchical factor structure of the fifth edition of the 16PF: An application of the Schmid-Leiman orthogonalization procedure. Educational and Psychological Measurement, 61, 290–302. CrossRef
Reddy, S. K. (1992). Effects of ignoring correlated measurement error in structural equation models. Educational and Psychological Measurement, 52, 549–570. CrossRef
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334. CrossRef
Sireci, S. G., Wainer, H., & Thissen, D. (1991). On the reliability of testlet-based tests. Journal of Educational Measurement, 28, 237–247. CrossRef
DeMars, C. E. (2006). Application of the bi-factor multidimensional item response theory model to testlet-based tests. Journal of Educational Measurement, 43, 145–168. CrossRef
Reise, S., Moore, T., & Maydeu-Olivares, A. (2011). Target rotations and assessing the impact of model violations on the parameters of unidimensional item response theory models. Educational and Psychological Measurement, 71, 684–711. CrossRef
Reeve, B. B., Hays, R. D., Bjorner, J. B., Cook, K. F., Crane, P. K., Teresi, J. A., et al. (2007). PROMIS Cooperative Group. Psychometric evaluation and calibration of health-related quality of life item banks: Plans for the patient-reported outcomes measurement information system (PROMIS). Medical Care, 45((5 Suppl 1)), s22–s31. PubMedCrossRef
Rose, M., Bjorner, J. B., Becker, J., Fries, J. F., & Ware, J. E. (2008). Evaluation of a preliminary physical function item bank supported the expected advantages of the patient-reported outcomes measurement information system (PROMIS). Journal of Clinical Epidemiology, 61(1), 17–33. PubMedCrossRef
McLeod, L. D., Swygert, K. A., & Thissen, D. (2001). Factor analysis for items scored in two categories. In D. Thissen & H. Wainer (Eds.), Test Scoring (pp. 189–216). Hillsdale, NJ: Lawrence Erlbaum Associates.
- Energy, fatigue, or both? A bifactor modeling approach to the conceptualization and measurement of vitality
John E. Ware Jr.
- Springer International Publishing
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