Explanatory Sequential Designs
An alternative to the exploratory sequential design is the explanatory sequential design in which the quantitative data collection comes first, followed by qualitative data collection (Figure 11.1). Investigators who select this design often do so because there is some need for an explanation of the quantitative findings from study participants. An example of the use of an explanatory sequential design would be interviewing persons who did not seem to benefit from the intervention (based on the quantitative assessments typically used in a trial) to find out how the intervention could be modified. Participants may have useful feedback about aspects of the intervention that were helpful, or aspects that they found unhelpful or would not use. This information can be used to refine an intervention for the next phase of intervention testing or implementation (e.g., to understand the concepts of depression that are important to older adults) (Barg et al., 2010).
In an explanatory sequential design, it is important to carefully select participants to maximize the information specific to the research question. For example, participants who were enthusiastic users of an intervention or, on the other hand, who engaged only minimally with the intervention may provide more critical information on their responses to the intervention than a random sample of participants. Perhaps the purposive sampling might include both participants who did and who did not engage in the intervention to understand the reasons behind their decisions. In the explanatory sequential design, emphasis is placed on understanding not only whether an intervention works, but for whom, under what circumstances, and why an intervention did (or did not) have the desired effects—all questions for which mixed methods approaches are well suited.