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Realist Research Design and Evaluation for Integrated Care SIG (RIC) - Part 2: Realist Quantitative Methods for Integrated Care Design and Evaluation

Authors:

John Eastwood ,

Sydney Local Health District, AU
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Roelof Ettema,

University of Applied Sciences Utrecht, NL
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Denise De Souza,

Nanyang Technological University, SG
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Hueiming Liu

The George Institute for Global Health, AU
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Abstract

Background: Realist research methodology is increasingly being used for the design and evaluation of integrated care initiatives.  Much of current realist research and evaluation is qualitative in nature and yet many realist methodologists, including Pawson, Tilley, Sayer and Olsen, have argued for the use of mixed methods.  There remains much debate regarding the role of quantitative methods, including statistics, within a critical realist philosophical framework.

For many realist researchers the use of quantitative methods is both a philosophical and methodological stumbling block.  Yet quantitative methods can contribute to realist theory building,, design and theory testing through their ability to use observable events to infer the existence of underlying mechanisms and to detect changes in both context and outcomes.

This workshop will examine debates about the use of quantitative methods in realist research and evaluation, either as part of a mixed-method design or on their own.  Examples of their use for both theory development and theory testing will be provided.  The workshop will provide practical demonstration of the use of quantitative methods for both small and large scale studies.

Knowledge, techniques and practices to be addressed include:

The philosophical debates concerning the use of quantitative methods for realist research and evaluation

Quantitative methods used for explanatory theory building research

Construction of quantitative tools from qualitative data

Quantitative methods used for evaluation and theory testing

Application of quantitative methods within realist mixed method study designs

Practical application of quantitative analysis to infer mechanistic action.

By the conclusion of the workshop, participants should be able to:

Understand the philosophical rejection of quantitative methods for both natural and social scientific realms

Determine how to interpret quantitative methods and incorporate them into realist research and evaluation while maintaining a distinction between method and methodology

Describe quantitative methods for inclusion in realist mixed method research and/or evaluation study designs

Undertake practical realist analysis of quantitative study data using simple statistical methods.

Aims and Objectives:

1) To examine debates about the use of quantitative methods in realist research and evaluation, either as part of a mixed-method design or on their own.

2) To demonstrate the use of realist quantitative methods for both integrated care design and evaluation.

Format: 90 minutes, one speaker and facilitator, Group work at tables using problem-based learning.  Discussion, debate and learning resources.

Target Audience: Integrated care design and evaluation practitioners and researchers. Qualitative and quantitative researchers. Mixed methodologists.

Learning and Takeaway: Increased understanding of how quantitative methods can be appropriately used with realist methodology.

Introduction to the use of advanced quantitative methods for design and evaluation of integrated care initiatives including latent class analysis, latent variable pathways, and discontiuity quasiexperimental designs. 

How to Cite: Eastwood J, Ettema R, De Souza D, Liu H. Realist Research Design and Evaluation for Integrated Care SIG (RIC) - Part 2: Realist Quantitative Methods for Integrated Care Design and Evaluation. International Journal of Integrated Care. 2018;18(s2):49. DOI: http://doi.org/10.5334/ijic.s2049
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Published on 23 Oct 2018.

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