Chapter 3 Research methodology
3.5 Operationalising the mixed-methods research process
3.5.1 Summary of the sequential, explanatory mixed-methods research design
A range of mixed-methods research designs are reported in the literature. However there are arguably two main factors which determine the approach selected (445, 505, 506): first, the priority, weight or emphasis of different study methods (i.e. whether each research component (method) is assigned the same status as another); and second, the time orientation informing the process of data collection itself (i.e. whether data are collected in parallel or at different, successive time points). Cresswell et al have grouped the potential combinations of these two factors into six most frequently used models, which include three concurrent (in which all research components are conducted simultaneously), and three sequential designs (in which one research component is conducted after another) (445).
Amongst these various designs, the equal-weight sequential explanatory mixed- methods design is particularly popular among researchers (507), and generally implies collecting and analysing first quantitative, and then qualitative data in two consecutive phases within one study. The rationale for this approach is that the quantitative data and their subsequent analysis provide a general understanding of the research problem, whereas the qualitative data and their analysis refine and explain those statistical results by exploring participants’ views in more depth (445, 505). In theory at least, it represents a more straightforward, if often more time-consuming, approach to mixed-methods in comparison to concurrent models of research (508).
For this study, an equal-weight, sequential explanatory mixed-methods design was selected. This overarching sequential study design is summarised in the figure below (4), which highlights the equal weighting of the quantitative and qualitative data within the analysis and interpretation of results, and the multi-level data integration that occurred throughout the research process. The issues of sequence, prioritisation, integration and interpretation of data are explored in more depth in the sections to follow.
Figure 4: Visual representation of the mixed-methods research design
3.5.2 Sequence of study components
First, the findings of the systematic review to identify which factors influence the recording of routine practice data by Primary Care Physicians (PCPs) (Phase 1) were used to both contextualise the study on a macro level, as well as to inform the
development of the topic guide utilised in the semi-structured GP interviews in Phase 3. Next, quantitative methods were employed to compare and contrast the delivery of screening and brief alcohol interventions for alcohol across a sample of general
practices in North East of England using routinely collected electronic GP Read Code data (Phase 2), with the subsequent qualitative interviews (Phase 3) used to probe significant results emerging from the descriptive statistical analysis. In addition, a purposeful nested sampling approach allowed the quantitative phase to inform
recruitment of the interview participants in the qualitative component of the research, by highlighting “information-rich cases” of GPs’ use of routine data to record alcohol screening and brief interventions that would benefit from further investigation (509).
Specifically, the study employed stratified purposeful sampling in order to ensure that one or two interview cases were recruited that exemplified the key traits and degree of variation relevant to understanding the target phenomenon (510). The nested sampling strategy also informed the recruitment of the case study general practice, using convenience sampling. This case study would facilitate the in-depth investigation of the range of available alcohol Read codes in primary health care, as well as helping
to inform understanding of the extent to which these available Read codes are actually used in day-to-day practice by clinicians.
3.5.3 Prioritization of data from individual research components
As well as specifying the sequential research process, it is also necessary to consider the issue of how the data arising from the three individual study phases would be prioritised. Priority refers to the weight or attention assigned by the researcher to each component of the research throughout the data collection and analysis process. Generally speaking, in the sequential explanatory design, priority is given to the quantitative approach because the quantitative data collection comes first in the sequence of data collection, and moreover it often represents the major aspect of the mixed-methods data collection process. However, it is by no means a straightforward decision to make, and this common prioritisation is far from prescriptive. Cresswell et al suggest that choices should be based on: the specific interests of the researcher; the target audience for the findings; and the focus of the research itself (445). As the aim of this research was to determine the usefulness of routine data to assess GPs’ delivery of screening and brief alcohol interventions, the results from both the quantitative phase (in which the data itself would be analysed) and the qualitative phase (which explored GPs’ own perspectives on their use of such data) were seen as carrying equal status in contributing to the overall research findings.
3.5.4 Approach to mixed-methods data integration and interpretation
Referring back to Burke Johnson and Onwuegbuzie’s definition of mixed-methods research, using this approach must entail some level of ‘mixing’ or ‘combining’ data (467). As such, a key element of fully mixed-methods research is effective data integration. Indeed, without an explicit and well-considered framework for data integration, it has been argued that many so-called mixed methods studies remain unable to “transcend the forced dichotomy of quantitative and qualitative methods and data”(440), and continue to present results as separate, disconnected data sets. Alternatively, ‘true’ integration relies on examining phenomena from multiple perspectives in order to gain a more rich and comprehensive understanding (511).
In this study, data integration took place at three broad levels. First, as emphasised above, a key function of the sequential research design was to integrate the findings
from one phase of the research directly within the following phase: thus the
development and refinement of the research as it progressed was directly supported by mixed-methods data integration. In particular, findings from Phases 1 and 2 (a systematic review of factors influencing recording of routine data by PCPs and
secondary data analysis of alcohol Read code data) informed the content and direction of the semi-structured interviews conducted in Phase 3 with North East GPs; as well as the selection of the GP participants themselves.
Second, data integration took place at the analysis stage, where both convergent and discordant data gained from each phase of the research were blended in order to generate a more comprehensive explanatory framework of the phenomenon under investigation (483). In terms of how this was operationalized within the research process, as both qualitative and quantitative data were available on a number of GP case study practices, the use of a mixed methods matrix (originally developed by Miles and Huberman (512)) was felt to be of value. Within a mixed methods matrix, the rows represent the cases for which there is both qualitative and quantitative data, and the columns display different data collected on each case (see Figure 5). This allows researchers to pay attention to surprises and paradoxes between types of data on a single case and then look for patterns across all cases (513) in a qualitative cross-case analysis (512). Therefore, results from each phase were summarised and displayed in a matrix once individual-level, single-method analysis had been carried out. This allowed the identification of both meta-inferences, i.e. overarching converging messages from all individual component inferences, at the same time as helping to highlight areas of divergence and discrepancy.
Third and finally, mixed-methods data integration occurred at the interpretation stage of the study. Specifically, the discussion section of this thesis sought to explore the emerging themes in more depth, and in turn, to situate these meta-inferences within the broader published literature in the field. As such, the conclusion sought to use fully integrated quantitative and qualitative data to answer to overarching research
question: can routine data help evaluate the implementation of alcohol screening and brief intervention?
3.6 Summary
This chapter has presented a justification and rationale for employing a mixed- methods approach to this research study. Specifically, the application of mixed- methods seeks: to support the development of a more in-depth contextualised understanding of the phenomenon under investigation; to address the acknowledged weaknesses of single method research designs; and to support the on-going
development of the actual study results. In terms of how this translates on an operational level for the research process itself, an equal weight sequential explanatory mixed-methods design was selected, incorporating elements of data integration throughout the study at multiple levels. Finally, the process and broad methodological approach are informed by a critical realist approach, reflecting the need to understand not just how individuals interact within a specific context, but additionally, the underlying generative mechanisms that have shaped that context. The following three chapters 4, 5 and 6, present the methods (or instruments) employed in the delivery of the research study itself, alongside the results from each respective research component.