ArticleApplied health economics and health policy2021
Using Eye-Tracking Technology with Older People in Memory Clinics to Investigate the Impact of Mild Cognitive Impairment on Choices for EQ-5D-5L Health States Preferences.
Article in Applied health economics and health policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.
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Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 6 citations in OpenAlex.
- The Evolving Landscape of Discrete Choice Experiments in Health Economics: A Systematic Review.PharmacoEconomics · 2025Pooled it
- Discrete Choice Experiments in Health State Valuation: A Systematic Review of Progress and New Trends.Applied health economics and health policy · 2023Pooled it
- Unravelling the Self-Report Versus Proxy-Report Conundrum for Older Aged Care Residents: Findings from a Mixed-Methods Study.The patient · 2024Trial
- Feasibility of self-reported health related quality of life assessment with older people in residential care: insights from the application of eye tracking technology.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2023Article
- Examining the Association between Polish Migrant Status and Health Preferences Using a Novel Application of a Smaller Design EQ-5D-5L Valuation Study.PharmacoEconomics - open · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPopulation ageing is a phenomenon taking place in almost every global region. Current estimates indicate that 10-20% of older people in developed countries have mild cognitive impairment (MCI), with these percentages predicted to rise markedly by 2050.
objectiveOur objective was to apply eye-tracking technology to investigate the information processes adopted by older people with and without MCI in determining preferences for health states in the five-level EuroQol-5 Dimensions (EQ-5D-5L) instrument.
methodsOlder people (aged ≥ 65 years; including both patients and family carers) attending outpatient memory clinics in Southern Adelaide between July 2017 and June 2018, competent to read and converse in English and with a Mini-Mental State Examination (MMSE) cognition score of ≥ 19 were invited to participate. In total, 52 people met the inclusion criteria, of whom 20 (38%) provided informed consent and fully participated. Participants were categorised into two subgroups (each n = 10) for comparison based upon established MMSE cognition thresholds (19-23, lower MMSE indicative of MCI; ≥ 24, higher MMSE indicative of good cognition). A discrete-choice experiment (DCE) comprising a series of pairwise choices between alternative EQ-5D-5L health states of varying survival duration with differential levels of task complexity (approximated by the degree of attribute level overlap in each choice), was administered as a face-to-face interview with the participant wearing an eye-tracking device.
resultsAttribute non-attendance (ANA) was higher for the lower MMSE subgroup than for the higher MMSE subgroup, although these differences were generally not statistically significant. ANA remained relatively low and consistent for participants with good cognition regardless of task complexity. In contrast, ANA increased notably in participants exhibiting MCI, increasing from 10% on average per participant in the lower MMSE subgroup with five attribute level overlap to 23% on average per participant in the lower MMSE subgroup with zero attribute level overlap.
conclusionsThis exploratory study provided important insights into the information processes adopted by older people with varying levels of cognitive functioning when choosing between alternative EQ-5D-5L health states of varying survival duration and specifically the relationships between cognitive capacity, task complexity and the extent of ANA. Recent advances in econometric modelling of health state valuation data have demonstrated the added value of capturing ANA information as this can be accounted for in the DCE data analysis, thereby improving the precision of model estimates. Eye-tracking technology can usefully inform the design, conduct and econometric modelling of DCEs, driving the inclusion of this rapidly growing population traditionally excluded from preference-elicitation studies of this nature.
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