The application of a network approach to Health-Related Quality of Life (HRQoL): introducing a new method for assessing HRQoL in healthy adults and cancer patients

Quality of Life Research

Volumn 25, Issue 4, 2016, Pages 781-792

  Kossakowski, Jolanda J ^a   Epskamp, Sacha ^a   Kieffer, Jacobien M ^b   van Borkulo, Claudia D ^a,c   Rhemtulla, Mijke ^a   Borsboom, Denny ^a  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b NETHERLANDS CANCER INSTITUTE   (Netherlands)

^c UNIVERSITY MEDICAL CENTER GRONINGEN   (Netherlands)

Author keywords

Cancer; Health Related Quality of Life; Network analysis; Psychometrics; SF 36; Short Form Health Survey

Indexed keywords

ADULT; ARTICLE; CANCER PATIENT; CONTROLLED STUDY; DATA ANALYSIS; FEMALE; HUMAN; MAJOR CLINICAL STUDY; MALE; MENTAL HEALTH; MODEL; PAIN; PSYCHOMETRY; QUALITY OF LIFE; QUALITY OF LIFE ASSESSMENT; SHORT FORM 36; SOCIAL INTERACTION; AGED; HEALTH STATUS; MIDDLE AGED; NEOPLASM; QUESTIONNAIRE; VERY ELDERLY;

ADULT; AGED; AGED, 80 AND OVER; FEMALE; HEALTH STATUS; HUMANS; MALE; MIDDLE AGED; NEOPLASMS; PSYCHOMETRICS; QUALITY OF LIFE; SURVEYS AND QUESTIONNAIRES;

EID: 84941730317     PISSN: 09629343     EISSN: 15732649     Source Type: Journal    
DOI: 10.1007/s11136-015-1127-z     Document Type: Article

References (42)

1. Edwards, J. R., & Bagozzi, R. P. (2000). On the nature and direction of relationships between constructs and measures. Psychological Methods,5, 155–174.
2. Kieffer, J. M., Verrips, E., & Hoogstraten, J. (2009). Model specification in oral health-related quality of life research. European Journal of Oral Sciences,117, 481–484.
3. De Vet, H. C. W., Adèr, H. J., Terwee, C. B., & Pouwer, F. (2005). Are factor analytical techniques used appropriately in the validation of health status questionnaires? A systematic review on the quality of factor analysis of the SF-36. Quality of Life Research,14, 1203–1218.
4. Ware, J. E, Jr, & Sherbourne, C. D. (1992). The MOS 36-item short-form health survey (SF-36): I. Conceptual framework and item selection. Medical Care,30, 473–483.
5. Wright, S. (1971). Path coefficients and path regressions: alternative or complementary concepts? In H. M. Blalock Jr (Ed.), Causal models in the social sciences. Chicago, USA: The Macmillan Press Ltd.
6. Borsboom, D., & Markus, K. (2013). Truth and evidence in validity theory. Journal of Educational Measurement,50, 110–114.
7. Howell, R. D., Breivik, E., & Wilcox, J. B. (2007). Reconsidering formative measurement. Psychological Methods,12, 205–218.
8. Wolinsky, F. D., & Stump, T. E. (1996). A measurement model of the Medical Outcomes Study 36-Item Short-Form Health Survey in a clinical sample of disadvantaged, older, black, and white men and women. Medical Care,34, 537–548.
9. Wu, C., Lee, K., & Yao, G. (2007). Examining the hierarchical factor structure of the SF-36 Taiwan version by exploratory and confirmatory factor analysis. Journal of Evaluation in Clinical Practice,13, 889–900.
10. Bollen, K. A., & Lennox, R. (1991). Conventional wisdom on measurement: A structural equation perspective. Psychological Bulletin,110, 305–314.
11. Borsboom, D. (2005). Measuring the mind: Conceptual issues in contemporary psychometrics. Cambridge, UK: Cambridge University Press.
12. Fayers, P. M., & Hand, D. J. (1997). Factor analysis, causal indicators and quality of life. Quality of Life Research,6, 139–150.
13. Fayers, P. M., Hand, D. J., Bjordal, K., & Groenvold, M. (1997). Causal indicators in quality of life research. Quality of Life Research,6, 393–406.
14. Eaton, N. R. (2015). Latent variable and network models of comorbidity: toward an empirically derived nosology. Social Psychiatry and Psychiatric Epidemiology,50, 845–849.
15. Koller, D., & Friedman, N. (2009). Probabilistic graphical models: principles and techniques. Cambridge, USA: MIT Press.
16. Van der Maas, H. L. J., Dolan, C. V., Grasman, R., Wicherts, J. M., Huizenga, H. M., & Raijmakers, M. E. J. (2006). A dynamical model of general intelligence: The positive manifold of intelligence by mutualism. Psychological Review,113, 842–861.
17. Cramer, A. O. J., Waldorp, L. J., van der Maas, H. L. J., & Borsboom, D. (2010). Comorbidity: A network perspective. Behavioral and Brain Sciences,33, 137–150.
18. Cramer, A. O. J., Sluis, S., Noordhof, A., Wichers, M., Geschwind, N., Aggen, S. H., et al. (2012). Dimensions of normal personality as networks in search of equilibrium: You can’t like parties if you don’t like people. European Journal of Personality,26, 414–431.
19. Whittaker, J. (1990). Graphical models in applied multivariate statistics. West Sussex, UK: John Wiley & Sons Ltd.
20. Aaronson, N. K., Muller, M., Cohen, P. D. A., Essink-Bot, M.-L., Fekkes, M., Sanderman, R., et al. (1998). Translation, validation, and norming of the Dutch language version of the SF-36 Health Survey in community and chronic disease populations. Journal of Clinical Epidemiology,51, 1055–1068.
21. Ware, J. E, Jr, & Gandek, B. (1998). Overview of the SF-36 health survey and the international quality of life assessment (IQOLA) project. Journal of Clinical Epidemiology,51, 903–912.
22. Ware, J. E, Jr. (2000). SF-36 health survey update. Spine,25, 3130–3139.
23. Jenkinson, C., Wright, L., & Coulter, A. (1994). Criterion validity and reliability of the SF-36 in a population sample. Quality of Life Research,3, 7–12.
24. Ware, J. E, Jr, Kosinski, M., Gandek, B., Aaronson, N. K., Apolone, G., Bech, P., et al. (1998). The factor structure of the SF-36 Health Survey in 10 countries: results from the IQOLA Project. Journal of Clinical Epidemiology,51, 1159–1165.
25. Brazier, J., Harper, R., Jones, N., O’cathain, A., Thomas, K., Usherwood, T., & Westlake, L. (1992). Validating the SF-36 health survey questionnaire: new outcome measure for primary care. British Medical Journal,305, 160–164.
26. McHorney, C. A., Ware, J. E, Jr, & Raczek, A. E. (1993). The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical Care,31, 247–263.
27. Ware, J. E, Jr, Kosinski, M., & Keller, S. D. (1994). SF-36 physical and mental health summary scales: A user’s manual. Boston, USA: The Health Institute.
28. Borsboom, D. (2008). Psychometric perspectives on diagnostic systems. Journal of Clinical Psychology,64, 1089–1108.
29. Newman, M. (2009). Networks: An introduction. Oxford, UK: Oxford University Press.
30. Lauritzen, S. L., & Wermuth, N. (1989). Graphical models for associations between variables, some of which are qualitative and some quantitative. The Annals of Statistics,17, 31–57.
31. Friedman, J. H., Hastie, T., & Tibshirani, R. (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics,9, 432–441.
32. Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological),58, 267–288.
33. Foygel, R., & Drton, M. (2010). Extended Bayesian information criteria for Gaussian graphical models. In J. D. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R. S. Zemel, & A. Culotta (Eds.), Advances in neural information processing systems 23 (pp. 604–612). USA: Curran Associates, Inc.
34. Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mõttus, R., Waldorp, L. J., & Cramer, A. O. J. (2015). State of the aRt personality research: A tutorial on network analysis of personality data in R. Journal of Research in Personality, 54, 13–29.
35. Borkulo van, C. D., Waldorp, L. J., Boschloo, L., Schoevers, R. A., & Borsboom, D. (2015). Statistical comparison of two networks with respect to global strength. Retrieved from https://github.com/cvborkulo/NetworkComparisonTest.
36. Barrat, A., Barthelemy, M., Romualdo, P.-S., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences of the United States of America,101, 3747–3752.
37. Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks,32, 245–251.
38. Zhao, T., Liu, H., Roeder, K., Lafferty, J., & Wasserman, L. (2014). Huge: High-dimensional undirected graph estimation. Retrieved from http://cran.r-project.org/package=huge.
39. Epskamp, S., Cramer, A. O. J., Waldorp, L. J., Schmittmann, V. D., & Borsboom, D. (2012). qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48(4), 1–18. Retrieved from http://www.jstatsoft.org/v48/i04/.
40. Fruchterman, T. M. J., & Reingold, E. M. (1991). Graph drawing by force-directed placement. Software: Practice and Experience,21, 1129–1164.
41. Ware, J. E, Jr, Gandek, B., Kosinski, M., Aaronson, N. K., Apolone, G., Brazier, J. E., et al. (1998). The equivalence of SF-36 summary health scores estimated using standard and country-specific algorithms in 10 countries: results from the IQOLA project. Journal of Clinical Epidemiology,51, 1167–1170.
42. Marsman, M., Maris, G., Bechger, T., & Glas, C. (2015). Bayesian inference for low-rank Ising networks. Scientific Reports,5, 1–7.