Construction of the descriptive system for the assessment of quality of life AQoL-6D utility instrument

Health and Quality of Life Outcomes

Neil A Day²  Gerald Elsworth¹  Angelo Iezzi⁵  Graeme Hawthorne³  Stuart J Peacock⁴  Jeffrey RJ Richardson⁶ 

[1] Public Health Innovation, Deakin Population Health Strategic Research Centre, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia;Centre for Program Evaluation, University of Melbourne, 100 Leicester Street, Parkville, VIC 3052, Australia;Department of Psychiatry, University of Melbourne, Level 1 North Main Block, Royal Melbourne Hospital, Melbourne, VIC 3050, Australia;School of Population and Public Health, University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada;Centre for Health Economics, Monash University, Wellington Road, Clayton, VIC 3800, Australia;Prof Jeff Richardson, Foundation Director, Centre for Health Economics, Monash University, Wellington Road, Clayton, VIC 3800, Australia

关键词: Economic evaluation;    HRQoL;    MAU instrument;    Quality of Life;   

Others  :  825749
DOI  :  10.1186/1477-7525-10-38

 received in 2011-09-27, accepted in 2012-04-17,  发布年份 2012

【 摘 要 】

Background

Multi attribute utility (MAU) instruments are used to include the health related quality of life (HRQoL) in economic evaluations of health programs. Comparative studies suggest different MAU instruments measure related but different constructs. The objective of this paper is to describe the methods employed to achieve content validity in the descriptive system of the Assessment of Quality of Life (AQoL)-6D, MAU instrument.

Methods

The AQoL program introduced the use of psychometric methods in the construction of health related MAU instruments. To develop the AQoL-6D we selected 112 items from previous research, focus groups and expert judgment and administered them to 316 members of the public and 302 hospital patients. The search for content validity across a broad spectrum of health states required both formative and reflective modelling. We employed Exploratory Factor Analysis and Structural Equation Modelling (SEM) to meet these dual requirements.

Results and Discussion

The resulting instrument employs 20 items in a multi-tier descriptive system. Latent dimension variables achieve sensitive descriptions of 6 dimensions which, in turn, combine to form a single latent QoL variable. Diagnostic statistics from the SEM analysis are exceptionally good and confirm the hypothesised structure of the model.

Conclusions

The AQoL-6D descriptive system has good psychometric properties. They imply that the instrument has achieved construct validity and provides a sensitive description of HRQoL. This means that it may be used with confidence for measuring health related quality of life and that it is a suitable basis for modelling utilities for inclusion in the economic evaluation of health programs.

【 授权许可】

   
2012 Richardson et al; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

【 参考文献 】

• [1]Richardson J, Peacock S, Iezzi A, Day NA, Hawthorne G: Construction and Validation of the Assessment of Quality of Life (AQoL) Mark 2 Instrument Research Paper 24. Melbourne: Centre for Health Economics, Monash University; 2007.
• [2]Brazier J, Ratcliffe J, Salomon J, Tsuchiya A: Measuring and Valuing Health Benefits for Economic Evaluation. Oxford: Oxford University Press; 2007.
• [3]Fryback DG, Palta M, Cherepanov D, Bolt D, Kim J: Comparison of 5 health related quality of life indexes using item response theory analysis. Med Decis Making 2010, 30(1):5-15.
• [4]Hawthorne G, Richardson J, Day NA: A comparison of the Assessment of Quality of Life (AQoL) with four other generic utility instruments. Ann Med 2001, 33:358-370.
• [5]Richardson J, McKie J, Bariola E: Review and Critique of Related Multi Attribute Utility Instruments, Research Paper 64. In Encyclopedia of Health Economics, Elsevier Science San Diego. Edited by Culyer AJ. Melbourne: Centre for Health Economics, Monash University; 2011.
• [6]Fayers PM, Machin D: Quality of Life: Assessment, Analysis and Interpretation. Chichester: John Wiley & Sons Ltd; 2000.
• [7]Streiner D, Norman GR: Health Measurement Scales: A Practical Guide to their Development and Use. Oxford: Oxford University Press; 2003.
• [8]Hawthorne G, Richardson J, Osborne R: The Australian Quality of Life (AQoL) instrument: a psychometric measure of health related quality of life. Qual Life Res 1999, 8:209-224.
• [9]Hawthorne G: Assessing utility where short measures are required: development of the short Assessment of Quality of Life 8 (AQoL 8) instrument. Value in Health 2009, 12(6):948-957.
• [10]Richardson J, Iezzi A, Peacock S, Sinha K, Misajon R, Keeffe J: Utility weights for the Vision Related Assessment of Quality of Life (AQoL) 7D instrument, Research Paper 67. Melbourne: Centre for Health Economics; 2011.
• [11]Misajon R, Hawthorne G, Richardson J, Barton J, Peacock S, Iezzi A, Keeffe J: Vision and quality of life: The development of a utility measure. Invest Ophthalmol Vis Sci 2005, 46(11):4007-4015.
• [12]Richardson J, Elsworth G, Iezzi A, Mihalopoulos C, Schweitzer I, Herrman H: Increasing the Sensitivity of the AQoL Inventory for Evaluation of Interventions Affecting Mental Health, Research Paper 61. Melbourne: Centre for Health Economics, Monash University; 2011.
• [13]Richardson J, Sinha K, Iezzi A, Khan M: Modelling the Utility of Health States with the Assessment of Quality of Life (AQoL) 8D Instrument: Overview and Utility Scoring Algorithm, Research Paper 63. Melbourne: Centre for Health Economics, Monash University; 2011.
• [14]World Health Organisation: International Classification of Impairments, Disabilities and Handicaps. Geneva: WHO; 1980.
• [15]Raykov T: Estimation of composite reliability for congeneric measures. Applied Psychological Measurement 1997, 21:173-184.
• [16]Day NA, Richardson J, Hawthorne G: Modelling Health Related Quality of Life for the AQoL-6D, Research Paper 51. Melbourne: Centre for Health Economics, Monash University; 2010.
• [17]SPSS: SPSS for Windows Version 11.5. Chicago: SPSS Inc; 2004.
• [18]Yu CY: Evaluating Cut-off Criteria of Model Fit Indices for Latent Variable Models with Binary and Continuous Outcomes, Dissertation for PhD. Los Angeles: University of California; 2002.
• [19]Brown MW, Cudeck R: Alternate ways of assessing model fit. In Testing Structural Equation Models. Edited by Bollen KA, Long JS. Thousand Oaks: Sage; 1993.
• [20]Edwards J, Bagozzi R: On the nature and direction of relationships between constructs and measures. Psychological Methods 2000, 5:155-174.
• [21]Richardson J, Day NA, Hawthorne G, Peacock S, Iezzi A: AQoL-6D Questionnaire, vol. [http://www.aqol.com.au/aqolquestionnaires/56.html] webcite 2012. [Accessed 13 March 2012]; 2012