A Sequential Exploratory-Confirmative Mixed Methods Grounded Theory

3.2.5.1 Developing an innovative research design. Johnson et al. (2010) introduced some of the grounded theory studies that had utilized mixed methods in one-way or another.

Nevertheless, the authors identified that there had been no existing MM-GT research that had used qualitative and quantitative method in equal status, meaning there is no existing design framework that I could employ for my research. Subsequentially, I carefully reviewed mixed methods research designs that had been categorized by several mixed methods experts. However, none of the existing designs seemed to be a good fit for my research question. As I was struggling to make my study to fit into one of the existing study designs, Dr. Burke Johnson provided me with an eye-opening perspective and suggestion during a consultation session. His advice was to

“not to try to pick what is already written in the menu, but to create a new recipe that is unique and is best fitting to your study” (personal communication, September 7, 2012). Tashakkori and Teddlie (2009), in their discussion about the seven-step process for selecting an appropriate mixed methods design, also emphasize that,

You want to select the best available MM research design for your study, but you realize that you may have to eventually generate your own . . . . You may have to combine existing designs . . . . or develop a new MM design, using flexibility and creativity because no one best design exists for your research project, either when it starts or as it evolves (p. 163-164).

Inspired and empowered by the new perspective and with the consultation and guidance from the MM-GT research expert Dr. Johnson, I developed a new MM-GT design based on existing MM frameworks, in which both an exploratory and confirmatory intent, both qualitative and quantitative data collection operation, and both qualitative and statistical analysis and inference are combined (Johnson et al., 2010) .

Various design factors were considered during the development of this new design.

According to Greene (2007),

The design of a mixed methods study follows directly from the identified purpose for mixing, because different purposes call for different mixes of methods, different

priorities or weights allocated to the different methods, different interactions among the methods during the course of the study, and different sequences of implementation (p.

112).

Based on these principles, Greene (2007) proposed several design options to consider when a researcher is constructing his or her own design. She suggested seven design dimensions, namely paradigms, phenomena, methods, status, implementation: independence, implementation:

timing, and study. Besides Greene’s seven dimensions, additional important design typologies have been proposed by other MM thinkers, including “number of strands or phases” (Teddlie &

Tashakkori, 2006). The table below displays the list of the design dimensions as proposed by Green and Teddlie & Tashakkori, with their definition and their application to this study.

Table 1. Design dimensions of the study

Dimension What it concerns The dimension used in this study

Paradigms

“The degree to which the different method types are implemented within the same or different paradigms”

(p.118)

The whole set of methods is designed and implemented with the same paradigmatic framework: pragmatism.

Phenomena

The degree to which the qual and quan methods are intended to assess totally different or exactly same phenomenon

Quantitative and qualitative methods in this study are assessing the same phenomenon - building a DMT model of resilience- using Integrated design with a purpose of Iteration.

Methods

The degree to which the qual and quan methods are similar to or different from one another in form,

assumptions, strength, and limitations or biases

The study uses two different methods, qual and quan, but with an assumption that each method has its unique strengths thereby compensating the limitation or weakness of the other method.

Status

The relative weight - or dominance in Creswell’s (2011) typology - and influence of the qual and quan methods in regard to their frequency and centrality to study objectives

More weight on qual in regard to the frequency yet equal weight and importance in regard to the centrality

Implementation The degree to which the The implementation of qual and quan

-Independence implementation of qual and quan methods are done interactively or independently

methods is intentionally interactive during the course of the study.

Implementation - Timing

Whether the different methods are implemented concurrently or sequentially

Sequential as a whole yet includes a partial concurrent phase

Study Whether the mixing takes place in one

study or across a set of studies Mixing occurs across a set of studies

Number of strands or phases

Whether the study involves one phase or multiple phases –Mono

strand/multistrand

Multiple strands - qual + quan Multiple phases – three phases

3.2.5.2 Developing the design. Based on the pragmatic paradigm, multiple data sources and data collection/analysis techniques were employed in order to ask how and why the

phenomenon of resilience building through DMT intervention operates (Greene, 2007). Namely the literature, clinical observation and experience, numeric scores from standardized instruments, verbal data from interviews, and nonverbal data from video recordings. In this study, grounded theory was construed as an approach, rather than a method (Johnson, McGowan, & Turner, 2010b) as several methods such as meta-modeling from literature and clinical observation, interviews, clinical experiment, quantitative measurement, and visual analysis were employed and inter-woven together into the overall methodological design in order to “bring about a balance of theory generation and theory testing” (Gasson, 2003).

A sequential structure with three phases was employed since the overall process of model generation and testing would take place consecutively. Each phase informed the next phase, contributing to build up towards the final model construction. The three phases were: 1)

exploratory phase: model generation, 2) confirmatory phase: intervention and model testing and refinement, and 3) model completion phase. Below is a brief overview of each phase.

Phase I. I began with a broad concept and seek to gain a deeper understanding of the