In some cases, the research questions or circumstances of the research settings require that the data collection be essentially concurrent, often referred to as “embedding” one strand in another, typically with one strand dominating (Figure 11.1). For concurrent designs, less emphasis is placed on how one strand informs the next, and more on making inferences or drawing conclusions from the concurrent strands. In a design in which the quantitative methods are primary, participants might undergo extensive structured assessments using standard assessment instruments (e.g., behavioral change measures), but some participants might be selected for more detailed evaluation (e.g., what a participant who received an intervention experienced), to understand processes in intervention implementation (e.g., what practitioners really do) or to study mediation (e.g., through the use of selected case studies to understand causal pathways; Weller & Barnes, 2014). Iloabachie and colleagues (2011) examined the effectiveness of an Internet-based intervention for depression among adolescents and concurrently collected quantitative survey and qualitative interview data. Over time, the authors were able to assess quantitative outcomes (helpfulness and attitude change) along with qualitative themes reflecting adolescent experience. Embedded designs in which the qualitative methods are the primary method of data collection can also be envisioned. An example would be assessing personal characteristics (e.g., age) or outcomes (e.g., response to an intervention) in a study employing primarily qualitative interview methods. Doing so might be important for investigators who want to compare themes or ideas across groups defined by the quantitative characteristics (i.e., comparing men and women, or persons at different levels of functional impairment).