Valuing informal carers’ quality of life using best-worst scaling—Finnish preference weights for the Adult Social Care Outcomes Toolkit for carers (ASCOT-Carer)

Nguyen, Lien, Jokimäki, Hanna, Linnosmaa, Ismo, Saloniki, Eirini Christina, Batchelder, Laurie, Malley, Juliette ORCID: 0000-0001-5759-1647, Lu, Hui, Burge, Peter, Trukeschitz, Birgit and Forder, Julien (2022) Valuing informal carers’ quality of life using best-worst scaling—Finnish preference weights for the Adult Social Care Outcomes Toolkit for carers (ASCOT-Carer). European Journal of Health Economics, 23 (3). 357 - 374. ISSN 1618-7598

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Abstract

This study developed Finnish preference weights for the seven-attribute Adult Social Care Outcomes Toolkit for carers (ASCOT-Carer) and investigated survey fatigue and learning in best-worst scaling (BWS) experiments. An online survey that included a BWS experiment using the ASCOT-Carer was completed by a sample from the general population in Finland. A block of eight BWS profiles describing different states from the ASCOT-Carer were randomly assigned to each respondent, who consecutively made four choices (best, worst, second best and second worst) per profile. The analysis panel data had 32,160 choices made by 1005 respondents. A scale multinomial logit (S-MNL) model was used to estimate preference weights for 28 ASCOT-Carer attribute levels. Fatigue and learning effects were examined as scale heterogeneity. Several specifications of the generalised MNL model were employed to ensure the stability of the preference estimates. The most and least-valued states were the top and bottom levels of the control over daily life attribute. The preference weights were not on a cardinal scale. We observed the position effect of the attributes on preferences associated with the best or second-best choices. A learning effect was found. The established preference weights can be used in evaluations of the effects of long-term care services and interventions on the quality of life of service users and caregivers. The learning effect implies a need to develop study designs that ensure equal consideration to all profiles (choice tasks) in a sequential choice experiment.

Item Type:	Article
Official URL:	https://www.springer.com/journal/10198
Additional Information:	Open access funding provided by Finnish Institute for Health and Welfare (THL). © 2021 The Authors
Divisions:	Care Policy and Evaluation Centre
Subjects:	R Medicine > RA Public aspects of medicine H Social Sciences > HV Social pathology. Social and public welfare. Criminology
JEL classification:	C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C35 - Discrete Regression and Qualitative Choice Models C - Mathematical and Quantitative Methods > C9 - Design of Experiments > C90 - General I - Health, Education, and Welfare > I1 - Health > I18 - Government Policy; Regulation; Public Health I - Health, Education, and Welfare > I3 - Welfare and Poverty > I31 - General Welfare; Basic Needs; Living Standards; Quality of Life; Happiness I - Health, Education, and Welfare > I3 - Welfare and Poverty > I39 - Other
Date Deposited:	09 Sep 2021 09:30
Last Modified:	16 Nov 2024 05:15
URI:	http://eprints.lse.ac.uk/id/eprint/111885

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