Research paradigms and methodology

One of the features of research is to identify the methodological approaches that inform it (Groenewald, 2004). It is necessary therefore, to give a brief overview of the methodological issues involved in undertaking this study and their philosophical basis.

Prior to this, it is important to define the term ‘methodology’, which is often confused or interchanged with the term ‘methods’.

Appleton (2009: 20) gave an explicit definition of both terms:

“Methodology is the rationale and philosophy underpinning the study design and its execution, including the researcher’s ontological or epistemological perspective and method, is a specific data collection and analysis technique, such as systematic reviews, surveys or focus groups”.

This, therefore, implies that methodology underpins the choice of research methods for collecting data. Yet, methodological issues rest on the researcher’s theoretical

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perspective of ontology (the nature of existence) and epistemology (what is it possible to know about the world and how can it be known) (Corbin and Strauss, 2008). Patton (2002) indicated that theoretical positions should not be the main drivers for research.

However, Green and Thorogood (2009) argued that employing theoretical perspective in research enhances the transparency or reliability of research findings by informing the research questions asked, and how the researcher intends answering them.

In relation to ontology, Snape and Spencer (2003: 11) identified three distinctive categories based on the assumption of social reality and, its construction. First, materialism, which acknowledges that there is a real world yet “only material features, such as economic relations or physical features of that world” constitute reality. The second is idealism, and it assumes that “reality is only knowable through the human mind and through socially constructed meanings”. Realism is the third branch of ontology and positions itself within epistemological poles of positivism and relativism (Rycroft-Malone et al., 2010). It presumes that there is an external reality, which exists, independent of our beliefs and understanding, and that events, and experiences are triggered by underlying mechanisms and structures, which may be described (Bhaskar, 1975). Its distinctive feature is that it places emphasis on generative causal explanations and uses such explanatory strategies to further scientific knowledge (Pawson and Tilley, 1997). A variant of realism, critical realism, forms the theoretical basis of realistic evaluation (Wilson and McCormack, 2006; Marchal et al., 2010) and is discussed below.

4.2.1 Critical Realism

Byng et al. (2005) noted that critical realism is often attributed to the works of Bhaskar and colleagues. It is a philosophical approach that combines realist ontological and

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relativist epistemological perspectives (Isaac, 1990 quoted in McEvoy and Richards, 2003). Critical realists concur with the interpretivists’ view of causation in relation to the cause and effect explanation to social phenomena. They consider that variables that reflect facts are conceptual interpretations and the correlation between variables should be regarded as descriptions rather than explanations of causal relations in themselves (Cruickshank, 2003). They also agree with positivists that the social world is observable and exists independently of our representation of it (Cruickshank, 2003;

Denzin and Lincoln, 2005). In addition, they agree with the post-positivist view that scientific observations are fallible since the scientists operating within that conceptual framework influence them (McEvoy and Richards, 2003).

However, critical realists oppose positivists on the basis that, critical realists suggest that social phenomena are meaningful and should be constructed socially, therefore they cannot be subjected to measurements. Critical realists also believe that the role of the researcher is to contribute to the construction of a narrative rather than aiming to discover the truth (Cruickshank, 2003). Overall, they posit that reality consists of strata and that scientific enquiry should be concerned with analysis of the mechanisms, processes, and structures that account for the patterns observed rather than emphasizing on statement of regularity (Denzin and Lincoln, 2005).

McEvoy and Richards (2003) outlined four distinctive features of critical realism. The first, and perhaps most important, is that critical realists’ focus of scientific enquiry is to obtain knowledge about mechanism of causation based on generative principles or mechanisms (Byng et al., 2005). Generative mechanisms are the structures, powers and relations that offer explanation to how things work, discovering if they have been activated and under what condition, yet they are non-observable and are only

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recognised through their effects (McEvoy and Richards, 2003; Wilson and McCormack, 2006). Secondly, critical realists assert that it is necessary to recognise the multi-layers of reality through which various mechanisms of causation operate, including the influence of environment and social behaviour. Thirdly, they acknowledge the interdependence between social structures and human agency. Social structures provide the resources for individuals to operate, yet under certain circumstances, individuals are able to manipulate the social structures in which they operate (McEvoy and Richards, 2003). Finally, critical realists offer a critique of prevailing social order and are not necessarily committed to a specific theory.

4.2.2 Realistic evaluation

Realistic evaluation is a theory-driven approach to evaluation of social programmes, developed by Pawson and Tilley (1997) in response to recent interest in understanding how interventions or social programmes work rather than emphasizing on whether they work or not (McEvoy and Richards, 2003; Pawson, 2006). Pawson and Tilley (1997) asserted that weaknesses in the previous experimental format of evaluation necessitated the introduction of a realistic approach to evaluation. The weaknesses included the

‘Martinson problem’, which refers to the tendency of experimental evaluations to produce conflicting results, and the ‘black box problem’ which describes the overemphasizing of programme outcomes rather than interrogating, what ‘mechanisms’

are acting to produce which ‘outcomes’ and within what ‘context’ (Pawson and Tilley, 1997: 30; Gill and Turbin, 1999). These weaknesses resulted in a situation where much of the emphasis on causation focussed on cause-and-effect relationships. Pawson and Tilley (1997) argued that programmes are often introduced within complex social systems, which are in constant transformation, therefore evaluation needs to take account of the settings within which it is implemented. Wilson and McCormack (2006)

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explicitly explained that mechanisms of causation always occur within a particular context and it is important to understand their relationship. The tenet of realistic evaluation therefore, is to understand what makes a programme work, for whom, how and under what circumstances. Alternatively, it describes, what mechanisms (ideas and opportunities) cause which outcome patterns (whether a programme works or not) and in which context (social and cultural conditions). This is often denoted as context (C) and mechanism (M) and Outcome (O) configuration or CMO configuration and it is represented as:

Context + Mechanism = Outcome

4.2.2.1 Context

Context is described as the pre-existing conditions within which a programme or public health intervention is implemented (Marchal et al., 2010). Because these conditions are pre-existing they are significant because they may facilitate or impede the intended mechanism of change of the embedded intervention. In other words, context dictates how a programme operates. Therefore, whether an intervention works or not is largely, dependent on the contextual factors. However, context does not just imply locality.

Pawson (2006) identified four areas of contextual factors that may influence the implementation of an intervention. They are the capabilities of key actors; the interpersonal relationships that develop in the locality within which the intervention is implemented (e.g. lines of communication in the organisation); the institutional settings (culture, rules, routines); and wider contexts (national policies, guidelines, social rules).

4.2.2.2 Mechanism

Mechanism is the main arm of the CMO framework on which realistic evaluation revolves (Pawson and Tilley, 1997; Pawson, 2002). Mechanism explains what aspects of the system enable it to produce change (Pawson, 2006). They are therefore the

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drivers or factors of the intervention that influence change or bring about an effect.

Pawson and Tilley (1997) defined it as the process by which participants interpret and act upon the intervention components. Wand et al. (2010) further described that mechanisms refers to the reasons, decisions and choices people make when confronted with an intervention. Overall, Pawson and Tilley (1997) identified the three main features of a programme mechanism. First, it should reflect the concept that the programme is embedded within layers of social reality. Thus, it should take account of the point that it is through the conjunction of social structure and human agency within a complex social system to effects change. Secondly, “it (the mechanism) is expected to take the form of a proposition which will take account of how both macro and micro processes constitute the programme” (Pawson and Tilley, 1997: 66). Finally, it should be able to “demonstrate how programme outputs follow from stakeholders’ choices (reasoning) and their capacity (resources) to put these into practice” (Pawson and Tilley, 1997: 66).

4.2.2.3 Outcomes patterns

Outcome patterns are the intended and unintended consequences of a programme emerging from the interaction between context and mechanism. Outcome patterns are varied and it is necessary that that programmes should be tested against a range of output and outcome measures including implementation variation, temporal outcome variations, and personal attribute outcome variations (Pawson and Tilley, 1997).

4.2.3 Strategies and methods of realistic evaluation

Realistic evaluation may employ quantitative or qualitative methods, but the choice of method is dependent on the hypothesis being tested and the availability of data (Pawson and Tilley, 1997). Yet, Maluka et al. (2011) noted that it has a predisposition towards qualitative methods. In this study, qualitative methods were utilized. As noted in

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chapter one, considering the stage of the implementation of screening and ABIs in antenatal care settings, it was considered important for this study to focus on process rather than summative outcomes. If a quantitative research strategy had been employed, it would have been used to measure aspects such as ‘perception’, ‘attitudes’,

‘intentions’ and ‘expectations’, this would have been unlikely to cover the depth and richness required to explore fully participants’ views and understanding of the issues relating to the research questions outlined in this study. Quantitative study methods would assume that concepts such as perception and attitude for enquiring about the social world are static rather than a process (Snape and Spencer, 2003). Moreover, a quantitative study method would attempt to code the social world based on predetermined operational variables, which would narrow the parameters of the subject and destroy valuable data (Marshall and Rossman, 2011).

Pawson and Tilley (1997) identified three stages of realistic evaluation enquiry. The first stage is the identification of the programme theory or consideration of a plausible CMO configuration. This involves the generation of concepts or ideas of contextual factors that are likely to influence the intervention or programme, identification of potential mechanisms and deciding on which programme outcome patterns should be considered (Byng et al., 2005). This stage may be informed by data sources such as literature review, policy document review as well as interviews with stakeholders and practitioners.

The next stage focuses on gathering appropriate data to interrogate the hypothesis formed in stage one. Based on the findings of the previous stage, some key individuals or institutions may be considered as important sources of data for this stage. The likely

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source of the data may include administrative records, interviews, focus groups and surveys.

The final stage involves the assessment and interpretation of the analyses, determining whether theories about how the programme works are refuted or supported. The results are then used to revise the programme theories or initial CMO configurations and to build an explanation of the programme. Pawson and Tilley (1997) however, made an important observation that although realistic evaluation seeks to offer explanations based on the CMO propositions, it is often impossible to attend to all the elements in the proposition and there may be more elaboration of the findings on some particular sub-sets than others. Nevertheless, they explained that the findings of realistic evaluation should always identify the configuration of features needed to sustain a programme.

Several limitations of the realistic evaluation methodology have been noted in research practice. First and perhaps most importantly is that although the principles are clear in the text, the lack of adequate procedures regarding how its methodological enquiry should progress in practice presents a challenge regarding the operationalisation of the approach (Rycroft-Malone et al., 2010). Another limitation noted by Tolson et al.

(2007) concerns the evaluation of an evolving programme. In this regard, they suggested that realistic evaluation does not provide adequate guidance about the appropriate time to construct a full CMO configuration. Gill and Turbin (1999) also indicated that while it is relatively easy to propose a plausible CMO configuration, obtaining relevant data for all three elements is difficult. Finally, and possibly the most common challenge that has been highlighted in several projects that have applied the

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approach entails the difficulty involved in clearly distinguishing and defining ‘context’

and ‘mechanism’ (Gill and Turbin, 1999; Rycroft-Malone et al., 2010).