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BMJ Open ; 6(1): e009887, 2016 Jan 20.
Article in English | MEDLINE | ID: mdl-26792219

ABSTRACT

INTRODUCTION: Welfare advice services can be used to address health inequalities, for example, through Citizens Advice Bureau (CAB). Recent reviews highlight evidence for the impact of advice services in improving people's financial position and improving mental health and well-being, daily living and social relationships. There is also some evidence for the impact of advice services in increasing accessibility of health services, and reducing general practitioner appointments and prescriptions. However, direct evidence for the impact of advice services on lifestyle behaviour and physical health is currently much less well established. There is a need for greater empirical testing of theories around the specific mechanisms through which advice services and associated financial or non-financial benefits may generate health improvements. METHODS AND ANALYSIS: A realist evaluation will be conducted, operationalised in 5 phases: building the explanatory framework; refining the explanatory framework; testing the explanatory framework through empirical data (mixed methods); development of a bespoke data recording template to capture longer term impact; and verification of findings with a range of CAB services. This research will therefore aim to build, refine and test an explanatory framework about how CAB services can be optimally implemented to achieve health improvement. ETHICS AND DISSEMINATION: The study was approved by the ethics committee at Northumbria University, UK. Project-related ethical issues are described and quality control aspects of the study are considered. A stakeholder mapping exercise will inform the dissemination of results in order to ensure all relevant institutions and organisations are targeted.


Subject(s)
Health Services Accessibility/organization & administration , Health Status Disparities , Healthcare Disparities , Patient Advocacy , Primary Health Care/organization & administration , Social Welfare , Humans , Models, Statistical , Program Evaluation , United Kingdom
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