This is the second in a series of three articles 

Contrary to popular perception, qualitative research can produce vast amounts of data. These may include verbatim notes or transcribed recordings of interviews or focus groups, jotted notes and more detailed “fieldnotes” of observational research, a diary or chronological account, and the researcher's reflective notes made during the research. These data are not necessarily small scale: transcribing a typical single interview takes several hours and can generate 20–40 pages of single spaced text. Transcripts and notes are the raw data of the research. They provide a descriptive record of the research, but they cannot provide explanations. The researcher has to make sense of the data by sifting and interpreting them.

#### Summary points

Qualitative research produces large amounts of textual data in the form of transcripts and observational fieldnotes

The systematic and rigorous preparation and analysis of these data is time consuming and labour intensive

Data analysis often takes place alongside data collection to allow questions to be refined and new avenues of inquiry to develop

Textual data are typically explored inductively using content analysis to generate categories and explanations; software packages can help with analysis but should not be viewed as short cuts to rigorous and systematic analysis

High quality analysis of qualitative data depends on the skill, vision, and integrity of the researcher; it should not be left to the novice

In much qualitative research the analytical process begins during data collection as the data already gathered are analysed and shape the ongoing data collection. This sequential analysis1 or interim analysis2 has the advantage of allowing the researcher to go back and refine questions, develop hypotheses, and pursue emerging avenues of inquiry in further depth. Crucially, it also enables the researcher to look for deviant or negative cases; that is, …

https://faculty.washington.edu/jelmore/articles_online/Pope-QualResinHC-Ana.pdf

Analysing qualitative data

Qualitative case study methodology provides tools for researchers to study complex phenomena within their contexts. When the approach is applied correctly, it becomes a valuable method for health science research to develop theory, evaluate programs, and develop interventions. The purpose of this paper is to guide the novice researcher in identifying the key elements for designing and implementing qualitative case study research projects. An overview of the types of case study designs is provided along with general recommendations for writing the research questions, developing propositions, determining the “case” under study, binding the case and a discussion of data sources and triangulation. To facilitate application of these principles, clear examples of research questions, study propositions and the different types of case study designs

/pdf/qualitative-case-study-methodology-study-design-and-1k0cisnxrr.pdf

Qualitative Case Study Methodology: Study Design and Implementation for Novice Researchers

The growth in qualitative research is a well-noted and welcomed fact within the social sciences; however, there is a regrettable lack of tools available for the analysis of qualitative material. There is a need for greater disclosure in qualitative analysis, and for more sophisticated tools to facilitate such analyses. This article details a technique for conducting thematic analysis of qualitative material, presenting a step-by-step guide of the analytic process, with the aid of an empirical example. The analytic method presented employs established, well-known techniques; the article proposes that thematic analyses can be usefully aided by and presented as thematic networks. Thematic networks are web-like illustrations that summarize the main themes constituting a piece of text. The thematic networks technique is a robust and highly sensitive tool for the systematization and presentation of qualitative analyses.

Thematic networks: an analytic tool for qualitative research

Contrary to popular perception, qualitative research can produce vast amounts of data. These may include verbatim notes or transcribed recordings of interviews or focus groups, jotted notes and more detailed “fieldnotes” of observational research, a diary or chronological account, and the researcher’s reflective notes made during the research. These data are not necessarily small scale: transcribing a typical single interview takes several hours and can generate 20-40 pages of single spaced text. Transcripts and notes are the raw data of the research. They provide a descriptive record of the research, but they cannot provide explanations. The researcher has to make sense of the data by sifting and interpreting them.

Qualitative research in health care: analyzing qualitative data

This article distills the core principles of a phenomenological research design and, by means of a specific study, illustrates the phenomenological methodology. After a brief overview of the developments of phenomenology, the research paradigm of the specific study follows. Thereafter the location of the data, the data-gathering the data-storage methods are explained. Unstructured in-depth phenomenological interviews supplemented by memoing, essays by participants, a focus group discussion and field notes were used. The data explicitation, by means of a simplified version of Hycner's (1999) process, is further explained. The article finally contains commentary about the validity and truthfulness measures, as well as a synopsis of the findings of the study.

/pdf/a-phenomenological-research-design-illustrated-3jo4u6j5qi.pdf

A phenomenological research design illustrated

Using computers in qualitative research.

Introduction - Udo Kelle An Overview of Computer-Aided Methods in Qualitative Research PART ONE: GENERAL METHODOLOGICAL ISSUES Computer Use in Qualitative Research and Issues of Validity - Udo Kelle and Heather Laurie User Experiences of Qualitative Data Analysis Software - Raymond M Lee and Nigel G Fielding Grounded Theory as an Emerging Paradigm for Computer-Assisted Qualitative Data Analysis - Marrku Lonkila Different Functions of Coding in the Analysis of Textual Data - John Seidel and Udo Kelle PART TWO: COMPUTERS AND QUALITATIVE THEORY BUILDING Introduction: Using Linkages and Networks for Theory Building - Gerald Prein and Udo Kelle in discussion with Lyn Richards and Tom Richards Reducing Fragmentation in Qualitative Research - Ian Dey Using Hierarchical Categories in Qualitative Data Analysis - Tom Richards and Lyn Richards Designing and Refining Hierarchical Coding Frames - Luis Araujo PART THREE: COMPUTERS AND QUALITATIVE HYPOTHESIS EXAMINATION Introduction - Udo Kelle in discussion with Ernest Sibert, Anne Shelly, Sharlene Hesse-Biber and G[um]unter L Huber Hypothesis Examination in Qualitative Research Using Logic Programming for Hypothesis Generation and Refinement - Ernest Sibert and Anne Shelly Hypothesis Testing in Computer-Aided Qualitative Data Analysis - Sharlene Hesse-Biber and Paul Dupuis Qualitative Hypothesis Examination and Theory Building - G[um]unter L Huber PART FOUR: COMPUTERS AND TRIANGULATION Introduction - Gerald Prein and Udo Kuckartz in discussion with Edeltraud Roller, Charles C Ragin and Udo Kelle Between Quality and Quantity Case-Oriented Quantification - Udo Kuckartz Hermeneutic-Classificatory Content Analysis - Edeltraud Roller, Rainer Mathes and Thomas Eckert Using Qualitative Comparative Analysis to Study Configurations - Charles C Ragin An Overview of Software - Gerald Prein, Udo Kelle and Katherine Bird

Computer-Aided Qualitative Data Analysis: Theory, Methods and Practice

There are major discomforts in pioneering. Excitement, anticipation and
thrill of achievement are balanced against uncertainty, delay and sheer
inconvenience. When the frontier in question is methodological
development, discomforts include waste of time, even of data, and the
competition between demands for testing new methods and demands for full
and rigorous analysis of data. This chapter tells part of the story of a project
that pioneered changes in the methodology of qualitative analysis.

From filing cabinet to computer

Most computer approaches to qualitative data analysis have concentrated on coding and retrieval of text. This paper describes a research project which set out to support a range of methods for the analysis of unstructured data, with emphasis on the building and testing of grounded theory. It resulted in software whose innovations include: a) No limit to the number of coding categories and sub-categories, and no limit to the number of times a given text passage can be coded; b) The use of separate document and indexing databases, interrelated and of unlimited flexibility; c) Comprehensive hypermedia-like browsing tools for both document and indexing databases; d) Ability to search for words and lexical patterns occurring in text and to combine this with indexing of the text; e) Ability to handle off-line textual and non-textual data as well as on-line data; f) Ability to record textual comments in indexing categories — a memoing facility for emerging ideas and categories; g) Support and exploitation of hierarchical indexing systems; h) Mechanisms for creating new indexing categories out of existing ones, relating them to the data documents, and using them for further analyses. New goals of the project are to provide a number of artificial intelligence based information structuring and reasoning facilities which can be used to aid the organization and retrieval of qualitative data, and to extend the present capabilities of the software to express and test new ideas, concepts, generalizations and hypotheses about the data.

The NUDIST qualitative data analysis system

In all fields where qualitative data are important, and especially in fields where rigorous qualitative analysis is demanded, computers are remaking methodology. Demand for, and faith in, computing for qualitative analysis is now strongly influencing health research. In this article, the authors argue for an evaluation of the impact of computer techniques and an opening of debate among developers and users of programs to address the purposes, power, and potential of computing in qualitative research. As a contribution to such a debate, these authors explore the original goals, design, and implementation of one approach to qualitative computing: NUDIST, a newly developed program for the mainframe and the Macintosh™ is introduced. In light of this, the ways in which old goals were achieved and the means by which the new goals imposed by users and critics may be met are discussed.

Tom Richards

Papers

Using computers in qualitative research.

Computer-Aided Qualitative Data Analysis: Theory, Methods and Practice

From filing cabinet to computer

The NUDIST qualitative data analysis system

Computing in Qualitative Analysis: A Healthy Development?