Integrative Mixed Methods Methodology

Introduction: The application of mixed methods approaches may aid in obtaining a deep-structure understanding of affective and coping responses, as precursors of resilience outcomes. The Integrative Mixed Methods (IMM) methodology offers rigorous mixed methods procedures that aim to yield the best of qualitative and quantitative forms of data analyses. 

Methods: The IMM methodology is conducted in seven steps: (1) developing well-specified focus questions; (2) collecting response narratives for each of several focus questions; (3) from transcribed text narratives, generating response codes, which constitutes specific answers to each focus question; (4) inductively “bundling” functionally-equivalent response codes into thematic categories; (5) scale coding response codes within a thematic category, to convert these into quantitative thematic variables; (6) conducting planned multivariate model data analyses; and (7) conducting re-contextualization and storylines.

Results: Focus questions regarding a most difficult life problem were presented to a diverse total sample of 303 research participants, to elicit cognitive, affective, behavioral, and reflective ways of coping with this difficult life problem. These analyses were utilized under two approaches: (a) an etc, “top-down,” theoretically based approach, and (b) an emic, “bottom-up,” inductive approach. Using independent coders and “roundtable analyses,” we identified response code matches.  Accepted respond codes were then “bundled” using the Atlas.ti qualitative analysis software program.  Then for each case, scale coding  added an “intensity of emphasis” value of: 1= tangential mention, 2= solid mention, 3= emphatic mention, was used to encode this emphasis within-category. Here, zero referred to “no mention” for a given thematic category.  This procedure populated 12 theoretically-based thematic categories

Conclusions:  The IMM methodology generated 27 thematic variables that established the mixed methods database for conducing planned and hypothesis driven multiple regression model analyses.  Our discussant will provide analyses and commentaries regarding this mixed methods approach for hypothesis testing using multiple regression models.