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Predicting unmet need for social care

Dunatchik, Allison, Icardi, Rossella and Blake, Margaret 2019. Predicting unmet need for social care. Journal of Long-Term Care , pp. 194-205.

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Abstract

Context: Demographic and other pressures have placed strains on the social (long-term) care systems in many countries. An ageing population and cuts to local authority budgets have put pressure on the availability of local authority funded adult social care in England and have raised concerns about unmet social care needs among older people. To prevent care needs going unmet, it is crucial to understand their predictors. However, research on this topic is limited. Objective(s): To understand the predictors of unmet needs for adult social care in England. Method(s): Using data from the English Longitudinal Study of Ageing (2002–2012), we employed an activities-based approach to develop a definition of unmet social care needs, drawing on available data, previous literature and consultations with social care users and carers. We then used logistic regression to analyse the factors that predict developing an unmet care need over a 10-year period among a sample of those aged 50 and older. Findings: The likelihood of developing unmet care needs does not differ by factors like gender, wealth, social contact, education or health behaviours. The only significant predictors for unmet needs are living alone, being relatively young (though still over 50), not having a longstanding illness, losing a spouse and developing more severe needs. These findings are robust to a variety of model specifications. Limitations: Results of this analysis may be sensitive to the definition of unmet need employed. Implications: These findings contribute to the current debate on the funding and organisation of adult social care in England and will inform policymakers interested in addressing the issue of unmet social care needs among older people.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Social Sciences (Includes Criminology and Education)
ISSN: 2516-9122
Date of First Compliant Deposit: 3 March 2020
Date of Acceptance: 5 November 2019
Last Modified: 03 Mar 2020 09:35
URI: http://orca.cf.ac.uk/id/eprint/130093

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