SAGE journal articles and other additional readings have been carefully selected by the author to accompany each chapter. Click on the following links. Please note these will open in a new window.

Article 11.1

Hennink, M., Kaiser, B., & Marconi, V. (2017). Code saturation versus meaning saturation: How many interviews are enough? Qualitative Health Research, 27, 591-608.

Abstract:
Saturation is a core guiding principle to determine sample sizes in qualitative research, yet little methodological research exists on parameters that influence saturation. Our study compared two approaches to assessing saturation: code saturation and meaning saturation. We examined sample sizes needed to reach saturation in each approach, what saturation meant, and how to assess saturation. Examining 25 in-depth interviews, we found that code saturation was reached at nine interviews, whereby the range of thematic issues was identified. However, 16–24 interviews were needed to reach meaning saturation where we developed a richly textured understanding of issues. Thus, code saturation may indicate when researchers have “heard it all,” but meaning saturation is needed to “understand it all.” We used our results to develop parameters that influence saturation, which may be used to estimate sample sizes for qualitative research proposals or to document in publications the grounds on which saturation was achieved.

Article 11.2

La Pelle, N. (2004). Simplifying qualitative data analysis using general purpose software tools. Field Methods, 16, 85-108.

Abstract:
This paper shows how clever but simple use of word processing functions can provide many features of special-purpose software designed for analyzing text. For many qualitative research projects, and for students who are learning computer-assisted analysis of text, the Microsoft Word functions outlined in this paper may be all that are required. Examples are given showing how Microsoft Word can be used for coding and retrieving, semi-automated coding and inspection, creating hierarchies of code categories via indexing, global editing of theme codes, coding of “face-sheet” data, exploring relationships between face-sheet codes and conceptual codes, quantifying the frequency of code instances, and annotating text. The techniques outlined can be used for analyzing and managing many kinds of data, including key informant interviews, focus groups, document and literature reviews, and open-ended survey questions.

Article 11.3

Morse, J. (2004). Constructing qualitatively derived theory: Concepts construction and concept typologies. Qualitative Health Research, 14, 1387-1395.

Abstract:
Although concepts differ in scope, specificity, and function within qualitatively derived theory, and the organization and integration of concepts is essential for the attainment of theoretical integrity, this topic has not been discussed previously in literature. In this presentation, the author discusses the derivation and kinds of concepts that qualitative inquiry generates. She examines the various positioning of certain types of concepts in emerging theoretical schemes and how the contribution of those concepts to completed theory varies according to the researchers’ agenda and the various roles assumed by different types of concepts.