Abstract
Assessments for quality of life (QOL) of the adolescent have received relatively little attention in the literature. Although there is no consensus on the definition of adolescent QOL and what aspects should be measured, it is generally accepted that QOL is a multidimensional construct. The objective of this study is to determine the measurement properties of the latent factors underlying adolescent QOL based on a second-order confirmatory factor analysis (CFA). A recursive structural equation model (SEM) is then proposed to determine the direction and magnitude of the interdependent effects among the latent factors. The questionnaire used was the Quality of Life Profile-Adolescent Version (QOLPAV). A sample of 363 adolescents was recruited from 20 secondary schools in Perth, Australia. The second-order CFA suggested that adolescent QOL may be measured by five underlying constructs namely social, environment, psychological, health, and opportunities for growth. The interdependent relations among these constructs identified the environment factor as primary, exerting both direct and indirect effects on the other four factors.
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References
Aaronson NK. Quality of life: What is it? How should it be measured? Oncology 1988; 2(5): 69–76.
Eiser C. Children's quality of life measures. Arch Dis Childhood 1997; 77: 350–354.
Fayers P, Machin D. Quality of Life-Assessment, Analysis and Interpretation. West Sussex, England: John Wiley & Son, 2000.
Smith K, Avis N, Assman S. Distinguishing between quality of life and health status in quality of life research: A meta-analysis. Qual Life Res 1998; 8: 447–459.
Spieth LE, Harris CV. Assessment of health related quality of life in children and adolescence: An integrated review. J Pediatr Psychol 1996; 21(2): 175–193.
Drotar D (ed.), Measuring Health-Related Quality of Life in Children and Adolescents: Implications for research and practice. Mahwah, New Jeresy: Lawrence Erlbaum Associates 1998.
Raphael D, Rukholm E, Brown I, Hill-Bailey P, Donato E. The quality of life profile-adolescent version. J Adoles Health 1996; 19: 366–375.
Fayers PM, Hand DJ. Factor analysis, causal indicators and quality of life. Qual Life Res 1997; 6: 139–150.
Anderson JC, Gerbing DW. Structural equation modelling in practice: A review and recommended two-step approach. Psychol Bull 1998; 103(3): 411–423.
Byrne B. Structural Equation Modeling with Lisrel, Prelis, and Simplis. Mahwah, New Jersey: Lawrence Erlbaum Associates, 1998.
Perrin E, Newacheck P, Pless I, et al. Issues involved in the definition and classification of chronic health conditions. Pediatrics 1993; 91(4): 787–793.
Guggenmoos-Holzmann I, Bloomfield K, Brenner H, Flick U. Quality of Life and Health: Concepts, Methods, and Applications. Berlin, Germany: Blackwell Wissenschafts-Verlag, 1995.
MacCallum RC, Austin JT. Applications of structural equation modeling in psychological research. Ann Rev Psychol 2000; 51: 201–226.
Hu L, Bentler PM. Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychol Meth 1998; 3: 424–453.
Bollen KA, Scott Long J (eds), Testing Structural Equation Models. Newbury Park, CA: Sage Publications, 1993.
Kelloway EK. Using Lisrel for Structural Equation Modeling-A Researcher's Guide. Thousand Oak, CA: Sage Publications, 1998.
Kline RB. Principles and Practice of Structural Equation Modeling. New York: The Guilford Press, 1998.
Chou CP, Bentler PM, Satorra A. Scaled test statistics and robust standard errors for non-normal data in covariance structure analysis: A Monte Carlo study. Br J Mathematical and Statis Psychol 1991; 44: 347–357.
Tepper K, Shaffer BC, Tepper BJ. Latent structure of mentoring function scales. Edu Psychol Measur 1996; 56(5): 848–857.
Curran PJ, West SG, Finch JF. The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychol Meth 1996; 1(1): 16–29.
Holmes-Smith P, Rowe KJ. The development and use of congeneric measurement models in school effectiveness research: Improving the reliability and validity of composite and latent variables for fitting multilevel and structural equation models. Paper presented at the International Congress for School Effectiveness and Improvement, The World Congress Center, Melbourne, Australia, January 3-6, 1994.
Joreskog KG, Sorbom D. Lisrel 8: User's Reference Guide. Chicago: Scientific Software International, 1996.
Australian Institute of Health and Welfare. Australia's Health-The Sixth Biennial Health Report of the Australian Institute of Health and Welfare, 1998.
Comrey A, Lee H. A First Course in Factor Analysis. Hillsdale, New Jersey: Lawrence Erlbaum Associates, 1992.
Coates S, Steed L. SPSS: Analysis without Anguish: Version 10 for Windows. Brisbane: John Wiley & Sons, 2001.
Coleman JS. Youth: Transition to Adulthood. Chicago: University of Chicago Press, 1974.
Hechlinger PM. Fateful Choices: Healthy youth for the 21st century. New York: Carnegie Foundation, 1992.
Parkin P, Kirpaiani H, Rosenbaum P, et al. Development of a health-related quality of life instrument for use in children with spina bifida. Qual Life Res 1997; 6: 123–132.
Jessor R. Risk behaviour in adolescence: A psychosocial framework for understanding and action. J Adoles Health 1991; 12: 597–605.
Millstein SG, Peterson AC, Nightingale EO (eds) Promoting the Health of Adolescents: New Directions for the Twenty-first Century. New York: Oxford University Press, 1993.
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Meuleners, L.B., Lee, A.H., Binns, C.W. et al. Quality of life for adolescents: Assessing measurement properties using structural equation modelling. Qual Life Res 12, 283–290 (2003). https://doi.org/10.1023/A:1023221913292
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DOI: https://doi.org/10.1023/A:1023221913292