Analyzing Qualitative Data with Computer Software

Health Services Research, Dec, 1999 by Eben A. Weitzman

Objective. To provide health services researchers with an overview of the qualitative data analysis process and the role of software within it; to provide a principled approach to choosing among software packages to support qualitative data analysis; to alert researchers to the potential benefits and limitations of such software; and to provide an overview of the developments to be expected in the field in the near future. Data Sources, Study Design, Methods. This article does not include reports of empirical research.

Conclusions. Software for qualitative data analysis can benefit the researcher in terms of speed, consistency, rigor, and access to analytic methods not available by hand. Software, however, is not a replacement for methodological training.

Key Words. Qualitative research, qualitative data analysis, software, CAQDAS, mixed-methods research

As health services researchers increasingly turn to qualitative and mixed (qualitative and quantitative) research methods, there is increasing interest in finding and using new tools and methods for the analysis of qualitative data. As recently as the mid-1980s, most qualitative researchers were carrying out the mechanics of their analyses by hand: typing up field notes and interviews, photocopying them, marking them up with markers or pencils, cutting and pasting the marked segments onto file cards, sorting and shuffling the cards, and typing up their analyses. Some were beginning to use word processors for the typing work, and just a few were beginning to experiment with database programs for storing and accessing their text. Most qualitative methods textbooks at the time (e.g., Bogdan and Biklen 1982; Goetz and LeCompte 1984; Lofland and Lofland 1984; Miles and Huberman 1984) made little, if any, reference to the use of computers. A couple of programs designed specifically for the analyses of qualitative d ata were just beginning to appear (Drass 1980; Seidel and Clark 1984; Shelly and Sibert 1985).

But the landscape has changed dramatically. There has been an out-pouring of journal articles, a series of international conferences on computers and qualitative methodology, thoughtful books on the topic (Fielding and Lee 1991, 1998; Kelle 1995; Tesch 1990; Weitzman and Miles 1995b), and special journal issues (Mangabeira 1996; Tesch 1991). At the time the late Matt Miles and I wrote Computer Programs for Qualitative Data Analysis (Weitzman and Miles 1995b), we reviewed no fewer than 24 different programs that were useful for analyzing qualitative data. Half of those programs had been developed specifically for the analysis of qualitative data, while the other half had been developed for more general-purpose applications such as text search and storage. Since then, the field has continued to grow rapidly. Programs are being revised at a regular rate, and new programs appear on the scene at the rate of one or two a year. Yet the software varies widely, and it remains very much the case that there is no one b est program.

In this context, a researcher needs to be able to make a principled choice of software: one that matches the capabilities of the software to the specific needs of the researcher and the project. To that end, this article provides an overview of the range of uses of computer software in qualitative research; describes the major types of software available; provides an approach to needs assessment that can match software choice to specific researchers and projects; addresses some common questions about whether and why researchers should use software; and lays out some of the future developments that are either hoped for or clearly on the horizon.

THE ROLE OF COMPUTERS IN QUALITATIVE RESEARCH

In order to be able to discuss the role of computers in qualitative research, it will be helpful to identify the major steps in the analysis process. The model in Figure 1, and the description that follows, are intended as a general representation of those steps, one that sees many and wide variations in practice, and not as any sort of prescriptive model.

THE ANALYSIS PROCESS: FROM RESEARCH QUESTIONS TO CONCLUSIONS

In general, researchers begin with a set of research questions and move toward reaching conclusions. Data are collected in order to answer the research questions, and in qualitative studies the data are often voluminous. The researcher then faces the task of somehow reducing the data into a form in which it can be examined for patterns and relationships.

In most approaches, the researcher will go about this through developing some sort of coding scheme: a set of tags or labels representing the conceptual categories into which to sort the data. These may be developed either a priori from the conceptual framework driving the study, inductively as the analysis proceeds and the analyst begins to identify issues in the data, or by some combination of the two. Segments of the data are marked with relevant codes (coded). In many cases, researchers write memos as they code, recording emerging ideas and early conclusions about both theory and methods. As insights accrue, it often becomes useful to search back through the data for places where specific words or phrases are used, and to locate related phenomena in the text, in order to both code these new chunks and check the validity of emerging conclusions. It may sometimes be useful to create pointers (or links) between different places in the text where the same issues arise, as, for example, when in one interview a patient describes an episode that is elsewhere also described by his or her caregiver. This whole process will in many cases give rise to modification of any a priori coding scheme, and many researchers follow an iterative process, making repeated coding passes through the data.