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RAMESES  December 2011

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Subject:

Interim summary – Realist synthesis and qualitative synthesis

From:

Geoff Wong <[log in to unmask]>

Reply-To:

Realist and Meta-narrative Evidence Synthesis: Evolving Standards" <[log in to unmask]>, Geoff Wong <[log in to unmask]>

Date:

Thu, 15 Dec 2011 11:35:40 +0000

Content-Type:

text/plain

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text/plain (16 lines)

In this thread, the role of using qualitative research in reviews was raised by Laura and Gill’s response was that we should perhaps think beyond just the process of integration and ask:
- what do we mean by integration?
- what is the purpose of integrating qualitative data?
A number of suggestions were made about what the purposes for integrating qualitative data. In summary, they all seemed to be aimed at making sense of different aspects of the topics of interest.
Comments were made that there seems to be a growing ‘trend’ in using qualitative data in reviews and Trish provided a document which summarised the various methods used. This document by Dixon-Wood et al. is one of many that summarises the methods available to date and tries to provide guidance as to when one might use each method.

IF the purpose of a review is to address some aspect of causation then an issue that might be worth raising in relationship to this thread is about the nature of causation itself and its implications to how the programmes or interventions might be conceptualised and analysed. To some extent this is an ontological issue that extends Gill’s comment that “form follows function”.
The drive to use qualitative data seems to be driven by the wish to draw in more data to explain ‘things’. The use of qualitative data might provide a richer explanation of a programme, intervention and/or outcome(s), but this does not necessarily mean that we will be able to provide a causal explanation. To do so we would need to have a model of causation and any model of causation would need to consider the question of how we believe the world to be constituted in the first place as well as how we conceptualise the programmes or interventions we are interested in.

To put it another way, if we want to provide causal explanations, we first need to ask the question of how we believe causation to occur in the programmes, interventions and/or outcome(s) we are interested in. In light of our beliefs, we would also then need to decide on how we would conceptualise the nature of our programmes and/or interventions as well as how we will go about analysing them. The purpose of any data, be they from qualitative and quantitative studies, helps us to build the causal explanations.

This ‘back to fundamentals’ approach is very much in line with one of the definitions of ‘critical’ provided by Tom in his message of 31st August:
"thinking critically about the basic categories and assumptions explicit and implicit in the thinking-apparatus and the practical-data-generation and data-interpretive practice that you are using, whether you realise it or not"

Geoff

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