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In-depth case studies and Complex Adaptive Systems thinking

ACTIVE AGENCY

3 Features of complex adaptive systems and their application to the school setting

3.5 Research methods and use of theory to understand complex systems

3.5.4 In-depth case studies and Complex Adaptive Systems thinking

Whilst the use of cluster randomised controlled trials is advocated (Hawe, 2015), such traditional quantitative designs are not always appropriate to capture changes in complex systems as, even when cluster randomisation is employed, this may not eliminate bias due to the high context-dependence on initial conditions that are individual to each CAS (Shiell et al., 2008). Hawe and Ghali (2008) propose that flexible qualitative methods, such as interviews and case studies should be conducted alongside social network analysis in order to obtain an in-depth understanding of variance in pre-intervention system functioning from the perspective of multiple actors. This could form part of an in-depth case study, a methodology that has been endorsed by researchers in the field of education as aligned with CAS thinking (Byrne, 2005; Haggis, 2010).

Although the use of multiple methods with case studies can generate thick description of a case and a more thorough understanding of complexity and uncertainty, the use of in-depth case studies may limit the ability to generalise (Hetherington, 2013). However, it can be argued that the unique nature of each school context highlights the importance of designing interventions to promote transferability of key processes to different contexts.

Hetherington (2013) also emphasises the need to acknowledge complexity to obtain insight into interactions within a system, both in terms of a formal hierarchy and more informal emergent relationships, and the effect of time. Temporal influences would be more prominent during implementation and process evaluation in order to capture emergence, than understanding the system prior to implementation.

71 understanding of the process by which systems evolve throughout an intervention. Moreover, there is a need to consider researcher reflexivity as the decisions that a researcher makes throughout their interaction with the system under investigation could have an effect on system functioning (Hetherington, 2013).

3.6 Conclusion

This chapter provides an overview of CAS thinking and its advantages over

traditional approaches to school health improvement. Further to this, it provides an overview of the extent to which key features of CAS thinking are compatible with Strong Structuration Theory (Greenhalgh & Stones, 2010), Structural Hole Theory (Burt, 2004b) and the Theory of Health Promoting Schools and Human Functioning (Markham & Aveyard, 2003), before presenting key arguments for the

conceptualisation of schools as CASs (Keshavarz et al., 2010). However, since it is still an emerging concept, a challenge facing school health researchers is to realise the potential of CAS thinking and its implications for research methods and design. There is also a need to accept and acknowledge the inevitable level of uncertainty conceptualised within this approach (Haggis, 2010).

There have been a few attempts at understanding how schools engage with efforts to bring about change from a CAS perspective (Bond et al., 2004; Fletcher et al., 2015). However, there is a need to step backwards and undertake a more in-depth

investigation of the functioning of complex adaptive school systems prior to intervening. This shifts the emphasis from complexity of the intervention itself, to complexity of the system into which it will be implemented. It has been argued that understanding the system could represent an extra stage to the MRC Guidance on complex interventions prior to intervention development (Anderson, 2008) and could potentially be used to harness complexity and improve the chance of intervention success by enhancing positive feedback loops and counteracting negative ones between the different levels of the system (Axelrod & Cohen, 2000).

Furthermore, CAS thinking requires the application of a broad range of methods to understand system functioning prior to intervening, capture emergent outcomes and account for the fact that system functioning is greater than a sum of its parts, thus

72 rendering traditional component testing irrelevant (Hawe et al., 2009b). This thesis will, therefore, be approached from a complex systems perspective, whilst aspects of Strong Structuration (Greenhalgh & Stones, 2010; Stones, 2005), Markham and Aveyard’s Theory of Health Promoting Schools and Human Functioning (Markham & Aveyard, 2003) and Structural Hole Theory (Burt, 2004b) will be synthesised to provide a integrative framework for this thesis. The integration of these theories, and their application to evaluation methods will help to obtain a more in-depth insight into system starting points and help to synthesise the elements of CAS thinking.

This thesis will build upon the literature outlined within this chapter by advancing the depth of exploration of system starting points or pre-intervention system

functioning. It will aim to explore the variance in health improvement processes and level of engagement with SHRN within different school systems through conceiving schools as CASs. Survey, social network and qualitative methods will be employed and theorised in a manner consistent with CAS thinking.

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4 Methodology

4.1 Introduction

This chapter outlines the research methodology employed within this thesis. It begins by providing an overview of the research aims and questions. Then the epistemological and ontological stance from which this thesis was approached is discussed, before moving on to a discussion of the merits of mixed-methodology and triangulation for investigating school system functioning. After this a detailed

description of the quantitative and qualitative methods employed is presented

alongside the analytical and ethical considerations considered. SHRN will be used as a case study to map the context of school engagement with, and for, wider learning from a new research network. It is described in detail below.