Principal Investigators

    Bunn, Frances

    Institution

    University of Hertfordshire

    Contact information of lead PI

    Country

    United Kingdom

    Title of project or programme

    Managing diabetes in people with dementia: a realist synthesis (DIaMonD)

    Source of funding information

    NIHR

    Total sum awarded (Euro)

    € 323,061

    Start date of award

    01/06/2015

    Total duration of award in years

    1.5

    The project/programme is most relevant to:

    Alzheimer's disease & other dementias

    Keywords

    Research Abstract

    Design The overall aim is to identify the most effective way of managing diabetes in people with dementia. There are a range of contextual factors, such as the type of diabetes, severity of dementia, the presence of additional comorbidities and the setting, that are likely to impact on diabetes management in people with dementia. Given these complexities a realist approach focusing on key programme theories and testing them in different contextual conditions is considered most appropriate. Realist synthesis will be used to identify the theories and the mechanisms, by which the authors of studies explicitly or implicitly assume that interventions to manage diabetes in people with dementia work. Research Plan We propose to use an iterative stakeholder driven four stage approach that optimises the knowledge and networks of the research team; it will be conducted over 18 months. Phase 1: Define scope and develop theories of how diabetes management interventions work. A consultation with key stakeholder groups and a first search and mapping of the literature will identify why certain approaches to addressing diabetes with people with dementia work (or not), in what circumstances and why. The project team will hold a one day workshop to review the findings and agree an explanatory model and associated candidate programme theories to guide the next stage of the review process. Phase 2: Retrieval, review and synthesis. This will involve systematic searches of the evidence to test and develop the theories identified in phase 1. An iterative approach to targeting evidence will be used across different databases, and other information sources. Synthesis of the data will involve the organisation of evidence tables and identification of cross cutting themes that either support or negate certain context–mechanism-outcome configurations. Findings, including hypotheses on the nature of the context, mechanism and outcome links, and the characteristics of the evidence underpinning them, will be reviewed at a second one-day workshop. Phase 3: Test and refine programme theory/ies (validation). To facilitate the development of a final review narrative and a refined set of hypotheses, we will validate our findings and final narrative from Phase two by testing them, and iteratively refining them, through discussion and review within the team and interviews with a purposive sample of participants from Phase 1. This will help establish their potential, and feasibility of implementation, for people with dementia and diabetes in a variety of settings. Phase 4: Development of actionable recommendations. Recommendations will be developed for practice and research of what works for whom and in what context in relation to programmes to manage diabetes for people with dementia. Dissemination To ensure maximum impact we will draw on our national and international networks. Outputs will include a final and full research report, and linked publications, workshop conference and online presentations to ensure that findings are accessible to as wide an audience as possible. Expertise in team The proposed synthesis will be carried out by a highly experienced team of multidisciplinary researchers and clinicians who bring to the project expertise in realist synthesis, dementia and diabetes.

    Lay Summary

    Further information available at:

Types: Investments > €500k
Member States: United Kingdom
Diseases: Alzheimer's disease & other dementias
Years: 2016
Database Categories: N/A
Database Tags: N/A

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