Development of mixed method study framework

Literature for mixed method studies is diverse, and can be confusing and contradictory. This effect is further increased by apparent prejudices towards research firmly defined as

quantitative or qualitative (Bazeley, 2009). This leads to the need to set out the underlying theory clearly. Then, by explicitly grounding the mixed method design within this theory, much of the confusion can be avoided.

The purpose of the study was to expand the inquiry into what aspects of locality influence ACS outcome and why. Expansion is the use of multiple methods, within different phases of the study to increase the scope of what the study discovers. Within the diverse and broad nature of the research objectives, this approach enables exploration without restriction, expanding on previous literature theories and the information resulting from each phase of the study. The aim was to develop each stage throughout the study, based on the previous literature and data collected and analysed during the previous phase, creating layers across the study that build upon each other. The method aims to increase the validity of constructs and inquiry results by capitalising on inherent method strategies. As information emerges from this study regarding what place influences exist and their effect, it can be returned to the study agenda and built upon. A sequential approach was the natural choice to fulfil these aims, where each phase of the study leads to the formation of the questions, data collection and analysis for the next phase. Sequencing enabled exploration and development of each stage of the study, working towards a more rounded evidence base.

There is large diversity in mixed method approaches available, for example, the use of interviews and summary statistics. Collins, Onwuegbuzie and Sutton (2006) put forward five mixed method constructs that can be built up around the research objectives to form a design that is either concurrent or sequential. This study is sequential, iteratively moving from quantitative research into qualitative:

Qualitative follow-up interaction analysis involves using qualitative data analysis techniques to further investigate statistically significant interactions that emerge from inferential analyses. (Collins, Onwuegbuzie and Sutton, 2006, p.86) For the instigation of a mixed method design, the 13 steps of the conceptualised process of Collins, Onwuegbuzie and Sutton (2006) were used as a structure (Figure 3.2 on page 55); inspiration was also taken from the Maxwell and Loomis (2003) theory-based interactive model. This presents a logically ordered research process that is open to robust iterative stages, giving proficient guidance on how to accomplish a successful mixed method study. The first five steps are linear, making up the formulation stage discussed within this chapter and the previous one, building to the planning stage in steps six and seven. This conceptualising of rationale and

purpose determined how the mixed approach runs throughout the study frameworks and informs the entirety of the study.

This study is sequential, where quantitative and qualitative components focus on different people, but are drawn from the same sample. Thus, the same influences can be examined from different paradigms, looking to answer a range of diverse questions. The final stage is the

implementation stage from steps eight to eleven. The integration of data within this structure is

undertaken by a flexible approach across five areas: collection of data, analysis of data, re- evaluation of research, validation of data and interpretation data. Integration is flexible and iterative, encouraging interlinking conclusions to be formed. This model was useful as it allowed each stage to be revisited more than once, helping the research to evolve, according to the new information uncovered, whilst the analysis was being undertaken throughout the research.

3.5.1

Terminology for mixed method studies

For mixed method research, distinctly clarified terminology is essential, with the same word having different meanings according to the paradigm from which it is considered. For example, the meaning of the word outcome from a quantitative perspective is likely to be interpreted in terms of survival, whereas it is interpreted as the perspective of the person experiencing his or her own personal recovery, when taking a qualitative approach. In this study, the term survival is used when referring to the outcome from a quantitative approach, recovery from a qualitative perspective and outcome when looking at the overall effect.

The differences in methodological approaches lead to clear differences in the way place is defined. With quantitative analysis, there is a necessary constraint in that uniform fixed boundaries are defined, which will be referred to as the local area. Lower super output areas (LSOAs) are used within this study – boundaries that were built around homogeneous

population density. Within a qualitative approach, the neighbourhood is defined by individual connections. The differences in interpretations of place are explored throughout this thesis. A topic recently of interest within public health and epidemiology is defined by Cattell (2001) as the norms of trust, reciprocity and the concern for the wellbeing of one's community. The word

neighbourhood is used to refer to where there is a personal connection to the place a person

lives, where the boundaries of the place are self-defined and include the social environment. It is important to note that neighbourhoods also have structural characteristics that will

contribute to people’s perceptions of them. This perception and the personal history of the person living there will indicate the preference to reside locally. Within this study,

neighbourhoods are mainly explored using a qualitative approach. These distinctions encourage multiple aspects to be considered, forming multiple views.

3.5.2

Empiricist framework

The empiricist framework developed from the research objectives guides the study design, resulting in a sequential design following the structure displayed in Figure 3.3, with the

following typology (Greene, Caracelli and Graham, 1989). It started with the quantitative phase to gain an overview of what place influences existed, followed by a mixed questionnaire and qualitative phase to determine perceptions of these influences, forming why these influences affect people.

Methods: referring to the similarity (or differences) of research methods in terms of data

collection, analysis, form, assumptions, strengths and limitations. Diverse research techniques within two phases are used in this study to encourage combination of strengths, building up insight at each phase, and to reduce weaknesses and biases, such as clarifying theory developed in previous phases.

Phenomena: this study falls into a mid-range phenomenon, positioned within different and

overlapping methods, capitalising on the strengths as well as allowing separate research objectives to be addressed.

Implementation: the research objectives, methods, and interpretation are considered both

separately and data synthesis. Using sequential timing is especially useful, due to the broad nature of the research objective, refined as the study progresses.

Status: Equal emphasis is put on the quantitative and qualitative aspects; in Morse’s (1991)

terms: QUANT=QUAL.

Phase 1: Secondary data analysis

The use of large datasets relating to ACS patients across Yorkshire and Humber enabled exploration of the relationship between patients’ personal/clinical characteristics, place differences and survival at six months. The datasets facilitated the search for patterns and trends across an overview of people from different backgrounds and with ACS health problems, identifying local area influences.

This phase aimed to elicit an overview of how local area relates to ACS survival at six months, what local area aspects had influence and how personal characteristics that may affect outcome related to place differences; for example, ‘is it beneficial to live in a local area close to facilities such as food shops?’. This approach was taken owing to the broad nature of the research objectives: by examining many people at once, generalisable trends within this sample population were uncovered. By basing this phase on pre-collected data, analysis began immediately with little financial implication, but was limited to the variables within datasets already collected and the quality of the data. Insightful results were formed in this phase, though further clarification about the meaning behind the results was needed, leading to smaller, more in-depth study phases.

Phase 2: Questionnaires and qualitative study

Phase 2 focuses on perceptions of place influences and recovery: ‘what within the

neighbourhood is seen as supportive?’, ‘What is the meaning of recovery?’ and ‘What are the characteristics of neighbourhoods perceived as important to recovery?’

This phase consists of a questionnaire study at two time points, looking at initial and follow-up recovery, and a qualitative study employing in-depth interviews and community mapping. Insight was gained into what neighbourhood aspects were important to recovery and how these varied across place differences, severities of ACS and personal motivations.

Examining initial recovery and follow up at six months gave the opportunity to look at perceived recovery over two time points, by looking at the experiences of first coming out of hospital, and then changes in experience and what was valued within the place of residence six months later. Employing two points in time offered insight into experiences and perception of local social support, deprivation and the effect of local facilities on how the participant felt they had recovered. The questionnaires were limited by a set number and type of question that could be asked and the inability to gain further in-depth information.

Phase 3: Data synthesis

Phase 3 concentrates on bringing together the conceptual findings and data formed within Phases 1 and 2, aiming to answer the research objectives formed in section 2.6, and hence shed some light on the research aim.

The phase uses a variety of methods centred on seeing the information available as a whole, determining the contributions of exploring the phenomena from multiple angles. This is both enhanced and limited by differences in the origin of the information and the types of questions being asked – the main difficulty of data synthesis.

The final part of data synthesis, and the last iteration conducted in this study, was the revision of the latent class regression models developed within the first phase. The model building strategies were based on the conceptual locality influences, formed during data synthesis. This aimed to bring together perceptions of experiences, and aspects of locality that were associated with six-month survival, comparing what was perceived to have an effect on recovery and determining whether it was actually associated with survival. This is an integrated look at locality influences, with the power to generalise to the wider population and form a link between data formats.

It is however limited by how well quantified variables can represent conceptual ideas, and the relevance of survival as the outcome from ACS.