Integration Through Connecting in Explanatory Sequential Mixed Method Studies. (December 2020)

• Record Type: Journal Article
• Authors: Draucker, Claire Burke; Rawl, Susan M.; Vode, Emilee; Carter-Harris, Lisa
• Is Part Of: Western journal of nursing research. Volume 42:Number 12(2020)
• Page Start: 1137
• Page End: 1147
• Publication Date: 2020-12
• Subjects: mixed methods -- explanatory sequential designs -- connecting -- interview guides; Nursing -- Research -- Periodicals; Nursing -- Periodicals; Nursing -- Research -- West (U.S.) -- Periodicals; Nursing -- West (U.S.) -- Periodicals; Nursing -- Periodicals; Nursing Research -- Periodicals; Soins infirmiers -- Recherche -- Périodiques; Soins infirmiers -- Périodiques; Soins infirmiers -- Recherche -- États-Unis (Ouest) -- Périodiques; Soins infirmiers -- États-Unis (Ouest) -- Périodiques; Soins infirmiers; Recherche; États-Unis (Ouest); Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 610.730702
• DOI: 10.1177/0193945920914647
• Languages: English
• ISSNs: 0193-9459

Abstract

The purposes of this methods article are to (a) discuss how integration can occur through a connecting approach in explanatory sequential mixed methods studies, (b) describe a connecting strategy developed for a study testing a conceptual model to predict lung cancer screening, and (c) describe three analytic products developed by subsequent integration procedures enabled by the connecting strategy. Connecting occurs when numeric data from a quantitative strand of a study are used to select a sample to be interviewed for a subsequent qualitative strand. Because researchers often do not fully exploit numeric data for this purpose, we developed a multi-step systematic sampling strategy that produced an interview sample of eight subgroups of five persons ( n = 40) whose profiles converged with or diverged from the conceptual model in specified ways. The subgroups facilitated the development of tailored interview guides, in-depth narrative summaries, and exemplar case studies to expand the quantitative findings.