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Deriving population norms for the AQoL-6D and AQoL-8D multi-attribute utility instruments from web-based data

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Abstract

Objectives

(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.

Methods

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.

Results

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.

Conclusions

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.

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Source: 2(a) to 2(j) Appendix 2 in ESM

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Acknowledgments

This research was funded by a National Health and Medical Research Council Project Grant ID: 1006334.

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Authors and Affiliations

  1. Centre for Health Economics, Monash Business School, Monash University, Melbourne, Australia

    Aimee Maxwell, Angelo Iezzi & Jeff Richardson

  2. Department of Econometrics and Business Statistics, Monash Business School, Monash University, Melbourne, Australia

    Mehmet Özmen

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  1. Aimee Maxwell
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  2. Mehmet Özmen
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  3. Angelo Iezzi
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  4. Jeff Richardson
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Corresponding author

Correspondence to Jeff Richardson.

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The research has been approved by the Monash University Human Research Ethics Committee Approval ID: CF15/2829-2015001164.

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The authors declare that they have no conflict of interest.

Funding

This research was funded by National Health and Medical Research Council Project Grant ID: 1006334.

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Maxwell, A., Özmen, M., Iezzi, A. et al. Deriving population norms for the AQoL-6D and AQoL-8D multi-attribute utility instruments from web-based data. Qual Life Res 25, 3209–3219 (2016). https://doi.org/10.1007/s11136-016-1337-z

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