AQoL 7D utility predicted from VisQoL data

Obtaining VisQoL score and predicted AQoL-7D utility

The AQol-7D is made up of the following 7 dimensions:
1.    Independent Living
2.    Relationships
3.    Mental Health
4.    Coping
5.    Pain
6.    Senses
7.    VisQoL

The VisQoL is a six item dimension (items 21, 22, 23, 24, 25 26) for measuring the quality of life associated with visual impairment.

Raw Data entry: The first response in any item, the item best, is entered as ‘1’, the second as ‘2’, third as ‘3’ and so on.

Please read the below carefully:

  • If you have the data for all 26 items of the AQoL-7D, this algorithm will produce a VisQoL Dimension Value plus an AQoL-7D utility plus values for all the dimensions.
  • If you have the raw data for only the 6 VisQoL items this algorithm will produce a Visqol Dimension Value. You can then obtain a predicted AQoL-7D Utility by inserting the VisQoL Dimension Value into equation A or by inserting the raw scores into equation B.
  • If you have only the VisQoL Dimension Value (and no raw data) insert it into equation A to produce a predicted AQoL-7D utility.

Equation A

AQoL-7D Predicted Utility = exp (-1.089250 + (0.756730 x VisQoL Dimension Value))

Alternately, using the 5 raw scores in equation B (The score for item 24 is insignificant)

Equation B

AQoL-7D Predicted utility = exp (-0.007715 – (0.028823 x aqol21) – (0.056232 x aqol22) – (0.027130 x aqol23) – (0.039109 x aqol25) – (0.038673 x aqol26))

Note: If you are experiencing any problem in executing the algorithm please contact the AQoL team.

Richardson, Iezzi, Peacock, Sinha, Khan, Misajon and Keefe. (2012) Utility weights for the Vision-related Assessment of Quality of Life (AQoL) 7D instrument. Opthalmic Epidemiology, 19:3, 172-182. doi: 10.3109/09286586.2012.674613