How Important are Carer Tasks in Determining Carer Quality of Life? Evidence from a Shapley Decomposition Approach

Abstract While there is a large literature that examines the determinants of carer quality of life, there is a dearth of research that focuses on the usual activities that carers perform and how they are related to carer-specific measures of quality of life. We use data from the Survey of Adult Carers in England to investigate the role that the tasks that carers perform play in determining carer quality of life. We model the relationship between the variables through a series of simple linear regressions, multiple linear regressions, and a Shapley decomposition. We find that all of the individual tasks that we have information on are statistically significant predictors of carer quality of life. In addition, the Shapley decomposition shows that, when taken together, carer tasks explain a higher proportion of variance in carer quality of life than any other group of determinants. These results are largely robust to different measures of carer tasks, different measures of carer quality of life, and different subgroups. We also find that there is evidence of a causal link between carer tasks and carer quality of life as carers report that their caring responsibilities have affected tangible health outcomes such as illnesses and GP visits. From a policy perspective, local government services that are used to support carers should know that policies designed to help carers with their tasks could have a large impact on carer quality of life.

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Publication Details

Journal
Social Indicators Research
Published
2025-01-27
DOI
https://doi.org/10.1007/s11205-025-03520-1
Citations
1
Primary Topic
Retirement, Disability, and Employment
Type
article
Field-Weighted Citation Impact
5.59
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article

How Important are Carer Tasks in Determining Carer Quality of Life? Evidence from a Shapley Decomposition Approach

David Candon, Yu‐Ling Liu‐Smith, Michael P. Hewitt, Peter Murphy
1 citations
Social Indicators Research
Retirement, Disability, and Employment
5.59
article

How Important are Carer Tasks in Determining Carer Quality of Life? Evidence from a Shapley Decomposition Approach

David Candon, Yu‐Ling Liu‐Smith, Michael P. Hewitt, Peter Murphy
article en
1 citations

Abstract

Abstract While there is a large literature that examines the determinants of carer quality of life, there is a dearth of research that focuses on the usual activities that carers perform and how they are related to carer-specific measures of quality of life. We use data from the Survey of Adult Carers in England to investigate the role that the tasks that carers perform play in determining carer quality of life. We model the relationship between the variables through a series of simple linear regressions, multiple linear regressions, and a Shapley decomposition. We find that all of the individual tasks that we have information on are statistically significant predictors of carer quality of life. In addition, the Shapley decomposition shows that, when taken together, carer tasks explain a higher proportion of variance in carer quality of life than any other group of determinants. These results are largely robust to different measures of carer tasks, different measures of carer quality of life, and different subgroups. We also find that there is evidence of a causal link between carer tasks and carer quality of life as carers report that their caring responsibilities have affected tangible health outcomes such as illnesses and GP visits. From a policy perspective, local government services that are used to support carers should know that policies designed to help carers with their tasks could have a large impact on carer quality of life.

Social Indicators ResearchVol. 177(1)
Nottingham Trent University (GB)
Openalex Percentile: Top 9%
Retirement, Disability, and Employment
5.59
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How Important are Carer Tasks in Determining Carer Quality of Life? Evidence from a Shapley Decomposition Approach — David Candon, Yu‐Ling Liu‐Smith, et al. · Social Indicators Research (2025) | TGRS Research Map | TGRS