CHAPTER 3. METHODOLOGY
3.4 RESEARCH METHODS
The researcher used mixed methods to collect the data. According to Carayon et al (Carayon, Kianfar, Li, Xie, Alyousef & Wooldridge, 2015:291) ‘Mixed methods research is the type of study in which an investigator or team of investigators combines components of qualitative and quantitative research approaches for the wider purposes of breadth and depth of understanding and validation.’ This is done purposefully to enable a multi-faceted understanding of a phenomenon (Chiang-Hanisko, Newman, Dyess, Piyakong & Liehr, 2016:1). The mixed methods design employed in this study was purposely meant to abduct a different dimension of the phenomenon and not only for cross validation
~ 65 ~
(Fielding, 2012:124). This involved integrating quantitative and qualitative methods within a single research design.
According to Zou, Sunindijo and Dainty, this need not essentially refer to the combination of research methods associated with one research methodology, but could comprise the combination of methods that transcend different methodologies. According to their study, many researchers believe that both methods complement instead of rival each other, and thus, qualitative research can compensate for the weaknesses of quantitative research and vice versa (Zou, Sunindijo & Dainty, 2014:320). Mixed methods systematically integrate quantitative and qualitative approaches to research to answer and analyse multiple research questions (Fielding, 2012:124). Quantitative research follows a post- positivist worldview and is predominantly interested in collecting and analysing numerical data with structured methods. Qualitative research follows a more constructivist worldview and is predominantly interested in collecting and analysing narrative data using open-ended holistic procedures. Mixed-methods research therefore collects both narrative and numerical data, employs both structured and emergent designs, uses both statistical and thematic analysis, and makes meta-inferences to answer the research questions by integrating the inferences gathered from their qualitative and quantitative findings (Tashakkori & Newman, 2010:514).
Mixed Methods have also been combined to conduct exploratory and confirmatory research, for instance, a researcher might first employ a qualitative method to explore a phenomenon and generate a relevant conceptual model and hypotheses, and then use a quantitative method to test the hypotheses to confirm the validity of the model (Albright, Gechter & Kempe, 2013:402). There is also evidence that mixed methods approach can help to compensate for the constraints of one set of methods (Albright et al., 2013:402).
This is because what succeeds in one context or setting may fail in another, and without an understanding of the ‘why’ behind success or failure, the effect of context cannot be understood (Albright et al., 2013:402). Therefore, mixed methods can allow examination of both the content and context of an intervention, with quantitative methods typically used to measure aspects of the content, and qualitative methods classically used to understand
~ 66 ~
the context (Ozawa & Pongpirul, 2014:323). Understanding the context of a specific intervention’s implementation is crucial, as the settings in which a particular research study occurs are complex and likely to vary significantly. Hence the use of mixed methods, and specifically of at least one quantitative method with at least one qualitative method, characteristically provides a better insight into a topic of interest than does the use of only one method (Albright et al., 2013:402).
However, contemplating mixed methods with the lens of the purist, even though mixed methods research may appear to offer a solution to the deficiencies of individual research paradigms, it is also a subject of criticism. Critics argue that mixed methods carry different epistemological commitments that may not be merged. Some also say that quantitative and qualitative methods are rooted in separate paradigms, and so could be considered as incompatible (Zou et al., 2014:320). Despite these criticisms, the notion of research methods carrying fixed philosophical assumptions is difficult to sustain, because each method could be used in a wide variety of tasks in both qualitative and quantitative research (Zou et al., 2014:320).
Mixed methods have been argued to be important in health systems research because it allows researchers to view problems from multiple perspectives, to contextualize information, develop a more complete understanding of a problem, triangulate results, and quantify hard-to-measure constructs. It also provides illustrations of context for trends, examines processes/experiences along with outcomes and captures a macro picture of a system (Ozawa & Pongpirul, 2014:323; Creswell, Klassen, Plano Clark &
Smith, 2011:2094).
Van Griensven, Moore and Hall contend that compared with a single method approaches, MMR may be viewed as providing a more complete and deeper understanding of the subject under investigation, and having greater scope to realize the full potential of the approach. MMR investigators ensure that the strengths of the qualitative and quantitative strands of their study overlap, while their weaknesses offset each other.
Different methods may be used to answer the same or related questions. When methods are engaged to answer the same question, it is known as convergence, whereas it is termed complementarity when qualitative and quantitative methods are used to answer
~ 67 ~
related questions evaluation or explanation. The concurrent convergent parallel design that was used in this study involved the simultaneous collection of both quantitative and qualitative data, then reviewing the two types together after analysis (Albright et al., 2013:402).Table 3.2: below shows mixed methods typologies.
Table 3. 2 Mixed Methods Design typology
Mixed Methods Design
Typologies Timing Priority
Convergent parallel design Simultaneous collection of quantitative and qualitative data.
Data merged after analysis. both
Explanatory sequential design
Quantitative data collection, followed by qualitative data
collection. Qualitative data used to explain quantitative data. Quantitative Exploratory sequential
design
Qualitative data collection, followed by quantitative data
collection. Quantitative data used to explain qualitative data. Qualitative Embedded design One form of data is embedded within the other. Data
collection may be sequential or concurrent.
Quantitative or qualitative
Multiphase design
A series of separate studies or phases using a combination of sequential and/or concurrent methods of qualitative and/or quantitative data collection.
Equal
3.4.1 The Mixed Methods Design Data Framework
In the parallel convergent mixed methods approach used for this research, data collection, analysis, and inference generation occur side-by-side to address the research objectives (Creswell, 2013:269; Tashakkori & Newman, 2010:515). At least two inferences, two qualitative and one quantitative, was reported, after which they were synthesised at the interpretive point of the boundary to address the research objectives (Chiang-Hanisko et al., 2016:1). This made the phenomenon clearer as compared to using one method.
~ 68 ~
Each datum was analysed separately, after which the results were synthesised for convergent validation. According to Van Griensven et al, the researcher can decide to keep the study's strands separate, in the parallel convergent mixed methods design, integration is suspended until the results from both are ready to be interpreted and convergent validations are then done (Van Griensven, Moore & Hall, 2014:367). Figure 3.2, shows the data collection framework that the researcher used as a guide adapted from (Chiang-Hanisko et al., 2016:4).
Figure 3.2 The framework of Mixed Methods Design