Swipe om te navigeren naar een ander artikel
The online version of this article (doi:10.1007/s11136-016-1337-z) contains supplementary material, which is available to authorized users.
(i) to demonstrate a method which ameliorates the problem of self-selection in the estimation of population norms from web-based data and (ii) to use the method to calculate population norms for two multi-attribute utility (MAU) instruments, the AQoL-6D and AQoL-8D, and population norms for the sub-scales from which they are constructed.
A web-based survey administered the AQoL-8D MAU instrument (which subsumes the AQoL-6D questionnaire), to members of the public along with the AQoL-4D which has extant population norms. Age, gender and the AQoL-4D were used as post-stratification auxiliary variables to construct weights to ameliorate the potential effects of self-selection associated with web-based surveys. The weights were used to estimate unbiased population norms. Standard errors from the weighted samples were calculated using Jackknife estimation.
For both AQoL-6D and AQoL-8D, physical health dimensions decline significantly with age. In contrast, for the majority of the psycho-social dimensions there is a significant U-shaped profile. The net effect is a shallow U-shaped relationship between age and both the AQoL-6D and AQoL-8D utilities. This contrasts with the almost monotonic decline in the utilities derived from the AQoL-4D and SF-6D MAU instruments.
Post-stratification weights were used to ameliorate potential bias in the derivation of norms from web-based data for the AQoL-6D and AQoL-8D. The methods may be used generally to obtain norms when suitable auxiliary variables are available. The inclusion of an enlarged psycho-social component in the two instruments significantly alters the demographic profile.
Log in om toegang te krijgen
Met onderstaand(e) abonnement(en) heeft u direct toegang:
Supplementary material 1 (DOCX 37 kb)11136_2016_1337_MOESM1_ESM.docx
Simmons, C. A., & Lehmann, P. (2013). Tools for strengths-based assessment and evaluation. New York: Springer.
Bowling, A. (2005). Measuring health: A review of quality of life measurement scales (3rd ed.). Maidenhead, Berkshire: Open University Press.
McDowell, I. (2006). Measuring health: A guide to rating scales and questionnaires. Oxford: Oxford University Press. CrossRef
Brazier, J., Ratcliffe, J., Salomon, J., & Tsuchiya, A. (2007). Measuring and valuing health benefits for economic evaluation. Oxford: Oxford University Press.
Richardson, J., McKie, J., & Bariola, E. (2014). Multi attribute utility instruments and their use. In A. J. Culyer (Ed.), Encyclopedia of health economics (pp. 341–357). San Diego: Elsevier Science. CrossRef
EuroQol Group. (1990). EuroQol—a new facility for the measurement of health-related quality of life. Health Policy,16, 199–208. CrossRef
Dolan, P., Gudex, C., Kind, P., Williams, A. (1995). A social tariff for EuroQoL: Results from a UK general population survey. Discussion Paper No 138. York: Centre for Health Economics, University of York.
Sintonen, H., & Pekurinen, M. (1989). A generic 15 dimensional measure of health-related quality of life (15D). Journal of Social Medicine,26, 85–96.
Richardson, J., Elsworth, G., Iezzi, A., Khan, M. A., Mihalopoulos, C., Schweitzer, I., Herrman, H. (2011). Increasing the sensitivity of the AQoL inventory for evaluation of interventions affecting mental health. Research Paper 61. Melbourne: Centre for Health Economics, Monash University.
Richardson, J., Sinah, K., Iezzi, A., Khan, M. A. (2014). Modelling utility weights for the Assessment of Quality of Life (AQoL)-8D. Quality of Life Research, 23, 2395–2404.
Chen, G., Khan, M. A., Iezzi, A., Ratcliffe, J., & Richardson, J. (2016). Mapping between 6 multi attribute utility instruments. Medical Decsion Making,36(2), 160–175. CrossRef
Richardson, J., Khan, M. A., Iezzi, A., Maxwell, A. (2015). Measuring the sensitivity and construct validity of six utility instruments in seven disease states. Medical Decision Making, Accepted 22 Sep 2015.
Richardson, J., Khan, M. A., Iezzi, A., & Maxwell, A. (2015). Comparing and explaining differences in the content, sensitivity and magnitude of incremental utilities predicted by the EQ-5D, SF-6D, HUI 3, 15D, QWB and AQoL-8D multi attribute utility instruments’. Medical Decision Making,35(3), 276–291. CrossRefPubMed
Richardson, J., Chen, G., Khan, M. A., & Iezzi, A. (2015). Can multi attribute utility instruments adequately account for subjective well-being? Medical Decision Making, 35(3), 292–304. doi: 10.1177/0272989X14567354
Campbell, J. A., Palmer, A. J., Venn, A., Sharman, M., Otahal, P., Neil, A. (2016). A head-to-head comparison of the EQ-5D-5L and AQoL-8D multi-attribute utility instruments in patients who have previously undergone bariatric surgery. The Patient—Patient-Centered Outcomes Research, 2016 1–12. doi: 10.1007/s40271-015-0157-5
ABS. (1995). Austalian Bureau of Statistics, National Health Survey SF-36 Population Norms Australia ABS Catalogue No. 4399. Canberra: http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/4399.01995?OpenDocument. Accessed 19 Apr 2012.
Hawthorne, G., Herrman, H., & Murphy, B. (2006). Interpreting the WHOQoL-Brèf: Preliminary population norms and effect size. Social Indicators Research,77, 37–59. CrossRef
Cummins, R. A., Knapp, T. M., Woerner, J., Walter, J., Page, K. (2005). The personal Wellbeing of Australians living within federal electoral divisions. Report No: 13.1. Melbourne: Deakin University.
Hawthorne, G., Korn, S., & Richardson, J. (2013). Population norms for the AQoL derived from the 2007 Australian National Survey of Mental Health and Wellbeing. Australian and New Zealand Journal of Public Health,37(1), 17–23. CrossRef
ABS. (2013). Australian demographic statistics, population by age and sex, Cat 3201.0. Canberra: Australian Bureau of Statistics http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/3201.0Jun%202010?OpenDocument. Accessed 12 Aug 2013.
Richardson, J., Iezzi, A., Khan, M. A., Chen, G. (2014). Interim population norms for the AQoL-6D and AQoL-8D multi attribute utility instruments. Research Paper 87. Melbourne: Centre for Health Economics, Monash University.
Gatz, D. F., & Smith, L. (1995). The standard error of a weighted mean concentration-I: Bootstrapping vs other methods. Atmospheric Environment,29(11), 1185–1193. CrossRef
AQoL. (2016) Assessment of Quality of Life (AQoL). http://www.aqol.com.au.
Frijters, P., & Beatton, T. (2012). The mystery of the U-shaped relationship between happiness and age. Journal of Economic Behavior and Organization,82, 525–542. CrossRef
Iezzi, A., & Richardson, J. (2016). A comparison of AQoL-4D, AQoL-6D, AQoL-7D and AQoL-8D multi attribute utility instruments. Research Paper 93. Melbourne: Centre for Health Economics, Monash University.
- Deriving population norms for the AQoL-6D and AQoL-8D multi-attribute utility instruments from web-based data
- Springer International Publishing