Beyond the Coding Process: A Review of Margrit Schreier’s Qualitative Content Analysis in Practice

The ways in which individuals communicate today are rapidly changing and new forms of data are constantly emerging, especially in written form, thanks to the advent of the internet and social media. In Qualitative Content Analysis in Practice, Margrit Schreier (2012) explores the ways in which undergraduate students, graduate students, and researchers can make sense of written content. With this text, individuals at varying points in their academic or professional careers can utilize specific or overarching information regarding the process of qualitative content analysis (QCA). The chapters in Schreier (2012) are set up in a way that the book may be read in its entirety or each chapter can stand alone as specific reference guide. As a second year Ph.D. student in my final semester of classes and very new to qualitative research, I found this book particularly helpful in furthering my understandings of the specific tasks required when entertaining the idea of and implementing QCA. This proves to be useful and is a key reason why I would recommend this book for anyone in the beginning stages of their research journey. This book consists of twelve chapters, which, for the purpose of this review, I divided into three parts: Background Information, Coding, and Getting to Work. Part 1 (Chapters 1-3) Background Information For students new to qualitative research or for individuals who are wondering if their data set would be best analyzed using content analysis, chapters 1 through 3 of Schreier (2012) provide a solid background about what QCA is, where it came from, and if it will work for a specific set of data. Chapter 1 explores the origin of QCA and situates this methodology in the historical timeline of ever-developing qualitative analysis. The information provided in chapter 2 helps to delineate the differences in quantitative and qualitative research. I would recommend this chapter for individuals making the switch from quantitative to qualitative or for those more comfortable with the quantitative tradition. This chapter is a quick guide to what qualitative inquiry is and how it can be helpful for research. That being said, I believe chapter 3 is the most important of the three beginning chapters. This chapter helps the reader decide if QCA is the preferred method of data analysis for their project. Through her many examples of appropriate data and easy to follow tables, this chapter will be the most beneficial for individuals who are not sure if this is the methodology they want to use. Part 2 (Chapters 4-8) Coding For researchers who already understand QCA and have decided that they are going to use this analytical method, I would recommend starting at chapter 4. This chapter is particularly useful for anyone adopting coding, regardless if using QCA or not. The most useful part of this chapter is the way Schreier explains the logic behind coding and the step-by-step guide to create a good coding frame. Chapters 5-8 introduce quite possibly the most helpful sections of this book which are the 'Beginner's Mistakes' sections. These are short explanations of many of the mistakes novice coders make and how to avoid them. While chapters 5 and 6 set up the bases for what a coding frame is, chapter 7 exemplifies the ways in which a researcher would transform their data into significant segments which are necessary when using QCA for analysis. Again, through the use of examples, discussion of common mistakes and frequently asked questions, these chapters become the backbone of successful organization of codes and possible themes. Chapter 8 discusses the process of testing out a data-coding frame before using it in a research project. This chapter explains the process of analyzing data to ensure the information being extracted is congruent with the focus of the research. Additionally, Schreier discusses how to navigate this process when working with a partner; a useful tool for anyone new to collaboration. …