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Population norms and meaningful differences for the Assessment of Quality of Life (AQoL) measure
Open accessAbstract
Objective The Assessment of Quality of Life (AQoL) instrument is widely used in Australian health research. To assist researchers interpret and report their work, this paper reports population and health status norms, general minimal important differences (MIDs) and effect sizes.Method Data from the 1998 South Australian Health Omnibus Survey (n=3,010 population-based respondents) were analysed by gender, age group and health status. Data from four other longitudinal studies were analysed to obtain estimated MIDs.Results The mean (SD) AQoL utility score was 0.83 (0.20). Gender and age subgroup differences were apparent; the mean scores for women were consistent until their 50s, when scores declined. Greater variability was observed for males whose scores declined more slowly but consistently between 40-80 years. For both genders, those aged 80+ years had the lowest scores. When assessed by health status, those reporting excellent health obtained the highest utility scores; progressive declines were observed with decreasing health status. Effect sizes of 0.13 or greater may reflect important differences between groups. A difference in AQoL scores of 0.06 utility points over time suggests a general MID.Conclusions AQoL population norms, MIDs and effect sizes can be used as reference points for the interpretation of AQoL data. These findings add to the growing evidence that the AQoL is a robust and sensitive measure that has wide applicability.Implications The availability of population norms will assist researchers using the AQoL to more easily interpret and report their work.
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“HRQoL was assessed via participants’ completion of the Assessment of Quality of Life (AQoL)-8D scale, which is a 35-item multi-attribute utility instrument covering 8 dimensions focused on independent living, happiness, mental health, coping, relationships, self-worth, pain, and senses [26,27].”
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“previous literature indicates that even a small effect size for HRQoL may bring substantial well-being benefit in the long term [8,27,38].”
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Metadata
- Authors
- Hawthorne, G., & Osborne, R.
- Affiliations
- The University of Melbourne (AU)
- The Royal Melbourne Hospital (AU)
- Corresponding author
- Hawthorne, Graeme
- ORCID
- Osborne, Richard
- Venue
- Australian and New Zealand Journal of Public Health
- Publisher
- Elsevier BV
- Published
- 2005-04
- Volume
- 29
- Issue
- 2
- Pages
- 136-142
- ISSN
- 1326-0200 (ISSN-L)
- OpenAlex
- W2092659488
- Cited by
- 294
- References
- 42
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 15 · 2023: 14 · 2022: 16 · 2021: 14 · 2020: 14 · 2019: 14 · 2018: 17 · 2017: 12 · 2016: 12 · 2015: 11 · 2014: 21 · 2013: 22 · 2012: 18
- FWCI
- 23.63
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Australian and New Zealand Journal of Public Health (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Health Sciences › Nursing › Research and Theory › Health Education and Validation
- Keywords
- AQoL, population norms, minimal important difference, effect size, health status, utility scores, gender differences, age differences, health-related quality of life, reference values
- MeSH terms
- Activities of Daily Living, Adolescent, Adult, Aged, Aged, 80 and over, Data Interpretation, Statistical, Female, Health Status Indicators, Humans, Male, Middle Aged, Quality of Life, Surveys and Questionnaires, South Australia, Age Distribution, Sex Distribution, Quality-Adjusted Life Years
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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