Qualitative Data Analysis

Transcription

1 Qualitative Data Analysis Sample Lecture Pack Code: REM050 Postgraduate Study in Educational and Social Research by Distance Learning This is an extract from a lecture pack for a module offered as part of the University of London International Programmes Master of Research (MRes) in Educational and Social Research. Materials for this degree programme are developed by academics at the Institute of Education of the University of London. For more information, see: University of London, 2014

2 Module 5 Qualitative Data Analysis Module introduction by Will Gibson Key reading Chapter 2 Description, analysis, and interpretation in qualitative enquiry, pp. 9 54, from Transforming Qualitative Data: Descriptions, analysis and interpretation by H. Wolcott Introduction In social research, analysis is often one of the most under-discussed parts of the research process. Although authors often include a quite elaborate account of the findings of their investigations, published research in books and journal articles rarely includes a detailed outline of the process of analysis. Authors may use general descriptive terms like grounded theory, CAQDAS (computer-assisted qualitative data analysis), discourse analysis, narrative analysis, and thematic analysis to describe their analytic work but, at best, these merely characterize very general approaches, commitments or tools and do not help to explain what might have been involved in any particular instance of their use. They are, in other words, general descriptions, rather like the term ethnography. Textbooks on analysis are usually much more explicit, but they can also be a little confusing. Compare, for example, Miles and Huberman s (1994) text Qualitative Data Analysis with Wolcott s (1994) Transforming Qualitative Data or Grbich s (2006) Qualitative Data Analysis and you will see three very different articulations of the process of analysis. If the experts cannot agree on what analysis is, how on earth are researchers new to the area supposed to know what to do? One of the aims of this module is to show the breadth of work that is done in the name of qualitative analysis, and to explain the various ways in which different authors, disciplines and focal areas have defined approaches to analysis. In this way, the module will produce a basic map of the field of analysis. You will look at grounded theory, discourse analysis, narrative analysis, and reflect on some of the issues implicated in these various domains of work. It is important to emphasize from the outset, though, that the field of qualitative analysis is far broader than the particular approaches that will be discussed here. Wolcott (1994) has pointed to more than 50 distinct types of analysis, and it would clearly be impossible to discuss all of those. My aim in this module then is to create a critical awareness of issues related to analysis, and to exemplify these in relation to some of the more common analytic forms. Researchers very often come to analysis with strong preferences for particular methods of data work. In providing a general overview of approaches, this module does not intend to suggest that these different approaches to analysis should be treated as something like a set of tools in a toolbox, or that researchers typically work by selecting the right tool for the appropriate analytic job. Of course, you cannot discount the idea that some researchers might work in that 2

3 fashion, but it is not typically the case, because professional expertise, disciplinary focus and theoretical commitments tend to lead researchers to specialize in one area rather than another. Rather, the purpose of the module is to give a sense of how such approaches function, why people who use those approaches do so, and the types of aims they typically have when they do so. A part of the process of development as a researcher involves creating your own expertise and preferences about the most appropriate forms of analysis. The process of analysis One of the most important points to make about analysis is that it is not best thought of as a stage in social research, but is better regarded as a form of research work that is informed by and informs all other aspects of research work. One of the commonest ways of portraying the social research process is as a linear move along the lines outlined below: formulate questions search literature design research collect data analyse data write up research. In some respects, this way of representing social research misrepresents every aspect of the process. Questions are not formulated only at the beginning of research but are iteratively worked out through the research process; literature is used to inform and position research interests not only prior to data collection, but in relation to every aspect of research work, including analysis, writing, and research design; research design is an evolving aspect of the research process that is informed by data analysis and by the types of data that are collected. In the abstract, a researcher may begin their research with any component of research work (excluding, perhaps, the writing up of findings) and move from there to any other component. For example, some researchers do begin their projects with the consideration of some data and use their analysis of it to formulate a problem. For example, in his work on the analysis of conversation Harvey Sacks (1992) frequently described the analysis of data as a means of developing a problematic that could subsequently be systematically explored in relation to a larger data set. Another model of research might involve a researcher beginning with a loose idea of a research interest, generating a preliminary idea of data that might be useful for exploring that interest, analysing their data and, from there, creating a more detailed view of both their question and of their research design (this is a common orientation in grounded theory, for example). Indeed, in many approaches, analysis is most effective when it has the possibility of informing the other features of research that is, where researchers are able to use their analysis to make adjustments to their research design, to think about other literature that might be relevant to their project, or to modify 3

4 their research question or even their research interest itself. This does not mean that there is no relevance to the linear model represented above, because it is typical for researchers to attempt to create some sort of forward movement in the research process (often represented in research timetables) that has some parity with the linear approach. It must be accepted, however, that it is something of an idealization, rather than an accurate representation of the actual process. Technology and analysis A very dominant discourse in the area of qualitative research concerns the role of computers in analysis. Programs such as Atlas.ti, NVivo, Qualrus, MAXQDA, and the Ethnograph are all forms of CAQDAS computer-assisted qualitative data analysis software. These types of software are, in some instances, very useful tools for helping researchers to organize their analytic work. They are typically useful in helping them to code their data (you will look in detail at the issue of coding in Unit 2), to explore their coding frameworks, to organize their analytic notes, and so on. These programs, in essence, provide databases that help researchers to manage their data and their analysis of it. Importantly, these sorts of software are not relevant to all forms of data work. While a researcher undertaking grounded theory might well use something like Atlas.ti to organize their work, someone undertaking critical discourse analysis may find that such a programme would be of little use to them, because they tend to work with much smaller segments of data. It is a common misunderstanding to think that all qualitative research should involve the use of software of this type: it is not the case. Nor is it the case that such software actually performs analysis; these programs are tools that help researchers organize their work. Generating and exploring data One way to think about social research design is in terms of the creation of a strategy for generating data. The use of the word generating rather than collecting is important here: to refer to the collection of data implies gathering up pre-existing or ready-made fragments or forms of evidence. In contrast, the notion of generating data emphasizes the role of the researcher in the creation of data; those data are an emergent property of a researcher working in a social setting in relation to a particular set of interests. One of the implications of thinking about research design as data design is that data are created for a purpose to deal with some problem or issue. This basic point helps to show that when researchers come to deal with their data they do not come to it cold, so to speak, but with distinct motivated interests. Researchers ask questions of data that are related to their research concerns they try to find things out that will help them to answer their research questions or gain clarity on some concern or other. However, analysis is not simply a matter of answering pre-specified questions: it is also often characterized by a process of generating new questions. Analysis is exploratory and, like all good explorations, full of surprises. It is very common for new interests and concerns to arise from the interrogation of data. This is precisely why it is so important to allow your analysis to inform your research design, because if it does not it may not be possible to empirically explore the interesting questions developed through the examination of the data. Data analysis should begin as soon as some data have been collected so that you can reflect on: how the emerging data relate to the research questions; whether or not 4

5 the specified design is actually working in terms of the production of interesting or relevant data; whether there are other interests that may need to be incorporated into the design of the generation of data; whether or not there are other interesting literary sources that need to be consulted. Forms of data The types of things that researchers might treat as data are extremely varied. Photographs, video recordings of activities, notes in books about things a researcher has seen, audio recordings of interviews or informal conversations, newspaper reports, minutes from meetings, diaries, books, web pages, blogs, films, television programmes, recordings of music, household objects all of these can be used as data to deal with a problem. The question what is data? can only really be answered in relation to a particular research issue because data is defined by the relevance of some thing to a particular research topic. Further, in any given project, there is likely to be a wide variety of possible data sources that could be used, and the purpose of the research design process is to narrow that down to very particular features. Structure of the module In this module you will be exploring all of the issues outlined above. You will be doing this through a combination of data analysis exercises, as well as through detailed reading of descriptions of approaches to analysis. The structure of the units to this module is as follows: Unit 1 Grounded theory Unit 2 Thematic analysis Unit 3 Discourse analysis Unit 4 Transcription Unit 5 Narrative analysis Learning outcomes By the end of the module you should be able to: explain the main principles of grounded theory and some of the key debates within the perspective undertake a thematic analysis of an interview transcript define, describe and apply different discourse analysis strategies transcribe audio recordings of talks using a variety of transcription approaches use and critique narrative analysis. 5

6 Reading The key reading for this module is included at the end of this lecture pack. However, if you would like to supplement your reading with other materials there are a lot of options available to you. There are not many books on qualitative data analysis that provide a very detailed overview of the entire field of approaches and issues. Usually, books tend to focus on one or other type of qualitative analysis. If you are thinking of buying a book it is perhaps most useful to think about what type of analysis you are most interested in and to purchase something that deals in a focused way with that. The references at the end of the various units of this module will give you an idea of some of the key texts in the various areas. References Grbich, C. (2006) Qualitative Data Analysis: An introduction. London, Sage Miles, M. and Huberman, A. (1994) Qualitative Data Analysis. Thousand Oaks, Sage Sacks, H. (1992) Lectures on Conversation, Volumes I and II. London, Blackwell Wolcott, H. (1994) Transforming Qualitative Data: Descriptions, analysis and interpretation. London, Sage 6

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8 Module 5 Qualitative Data Analysis Unit 1 Grounded theory by Will Gibson Learning objectives After studying this unit you should be able to: define grounded theory and explain its central procedures and elements explain the difference between the various articulations of grounded theory analytically evaluate the debates related to grounded theory, particularly the divergences within the work of Glaser and Strauss and the constructivist critiques of the approach. Key readings for this unit Grounded theory: objectivist and constructivist methods by C. Charmaz (2000) Introduction and Chapter 5 The constant comparative method of qualitative analysis from The Discovery of Grounded Theory by B. Glaser and A. Strauss (1967) Chapter 1 Introduction (pp.1 7) from Basics of Grounded Theory Analysis by B. Glaser (1992) Introduction A background to grounded theory Grounded theory (GT) is a very influential approach to working with data in qualitative research. Strictly speaking, the approach, as originally formulated by Glaser and Strauss, was not conceptualized as a solely qualitative approach, but it has had a bigger impact on qualitative than on quantitative researchers. Grounded theory originated from the collaborative work of Barney Glaser and Anselm Strauss. Both Glaser and Strauss were sociologists trained in the US, but of very different stock. Strauss had worked in the Symbolic Interactionist tradition at the University of Chicago. Much of Strauss s work, both prior and subsequent to his collaborations with Glaser, display similarities with that perspective. For example, his work on the sociology of work in healthcare settings shows a theoretical concern with the institutional organization of professionalized practice 8

9 a dominant theme in much interactionist work. Barney Glaser studied at the University of Colombia and his work shows some similarities to the functionalist sociology of Robert Merton and Paul Lazarfeld. The details of their backgrounds do not concern you here, but it is useful to bear them in mind because they offer a context for understanding the divergences that Glaser and Strauss took in their later work. It is also important to note that in their writings, particularly in their first grounded theory book, The Discovery of Grounded Theory (1967), the authors frequently refer to sociologists rather than social researchers. This is partly because of their own academic contexts of work, but it should be emphasized from the beginning that their audience is far wider than this restricted readership. One of their first collaborations was on an empirical study of the different levels of awareness that patients in a San Francisco hospital had of their own risks of death, and the ways in which these levels of awareness were interactionally managed by hospital staff. The study focused on the tactics used by nursing staff, family members and other hospital personnel to deal with the patients awareness (or lack of awareness) of their likelihood of dying. Glaser and Strauss were also concerned with the impact of these tactics on the patient, the staff, and the functioning of the institution. This study culminated in the book Awareness of Dying (1965), which formed an empirical basis for Glaser and Strauss s development of grounded theory. Their original articulation of grounded theory in The Discovery of Grounded Theory (which is often referred to as simply Discovery) drew heavily on the work Awareness of Dying. In the Introduction to Discovery, Glaser and Strauss described the main contribution of their new approach to social research work as providing an alternative to the development of theory prior to empirical work. In essence, the authors argued that the hypothetico-deductive model of scientific enquiry, where theoretical problems are specified and then verified through research, was of limited use in the social sciences. Theory, they suggested, was most effective where it helped researchers to understand an empirical context, and should be developed or generated in relation to an understanding of that context, rather than in advance of it. As the authors put it (1967: 3): Our basic position is that generating grounded theory is a way of arriving at theory suited to its supposed uses. We shall contrast this position with theory generated by logical deduction from a priori assumptions. This move to empirically situated or grounded theory development represented, they argued, a radical departure not only from quantitative approaches to social science, but also from qualitative ones. The distinction between the apriori theorizing and grounded theorizing can be demonstrated nicely through Glaser and Strauss s own study, Awareness of Dying. In their research at the San Francisco hospital, the authors did not begin with a theory of how patients awareness was interactionally managed, but developed their theory through detailed empirical work, consisting largely of interviews and observations. It is easy to imagine a different approach, in which they may have begun their study with a theoretical notion that, for example, different pre-specified personality types manage the matter of awareness of death in different ways. A researcher might use their pre-codified and defined personality categories as a means to classify the participants in the study, and to make comparisons between them. In Glaser and Strauss s approach, however, all categories, hypotheses and concepts need to be derived from the examination of data rather than developed prior to research. Theory should be an outcome of data analysis, not a precursor to it. The introduction to Discovery provides a 9

10 detailed description of this apriori/grounded theory distinction. In the remainder of Discovery, and in the various books that they produced afterwards, Glaser and Strauss outline a set of procedures or a methodology for producing theory from data and empirical work. In this respect, grounded theory is a methodology for creating theory through empirical work a methodology that is built on an assumption about how theory ought to function. Key components of grounded theory Constant comparative method The constant comparative method is a key aspect of grounded theory that involves formulating a number of stages to developing theory through data. In Chapter 5 of Discovery, the authors provide a detailed outline of the difference between this approach and other common approaches to qualitative data analysis. The distinction turns on the use of a systematic approach to generating theory through coding and other analytic apparatus, such as hypotheses, memos, theoretical sampling, triangulation, code properties, and so on. I will say something about each of these in turn below. The authors own description of the constant comparative method has become historically important in qualitative research, so rather than trying to summarize it I have provided it as a reading to accompany this unit. Theoretical sampling Theoretical sampling involves the creation of sampling strategies that relate to the emerging theories being created through the interrogation of data. The people included in the study (or the documents to be analysed, the sites of observation, the cases of inclusion) are selected on the basis of their potential relevance to an emerging theory. In their original articulation of grounded theory, a researcher begins a study with quite a loose idea of who to involve in the research, usually based on tacit and lay knowledge. The authors give the example of a study of a hospital, where the researcher uses their basic understanding of the division of labour in the hospital to decide to interview, doctors, nurses, and other key personnel. As the study progresses, and the researcher gains a more nuanced understanding of the hospital, the researcher creates different selection criteria: different concepts to guide the selection of people. The researcher may realize that some of the crude categories that were originally used are not used by the people in the organization (such as administrative staff ), or they may realize that there are more subtle ways in which the people in the organization distinguish between or label personnel that might be useful selection criteria. The implications of this approach to theoretical sensitivity is that analysis must be thoroughly integrated into the collection of data, and is by no means an afterthought. Analysis informs the construction of sampling procedures and of research design more broadly, including the selection of methods, the decisions about how many people to involve, and so on. Hypotheses The concept of hypotheses plays an important role in Glaser and Strauss's (1967) formulation of their approach. A hypothesis is a statement about a theoretical assumption that emerges from the examination of data. Hypotheses 10

11 are also mechanisms for driving the examination of data, for creating new sampling strategies or codes and categories. To give you an example, I am currently involved in an ethnography that is examining the training procedures in a trauma care ward in a London hospital. Trauma care involves close collaboration between specialized healthcare professionals such as anaesthetists, orthopaedic surgeons, nurses, pre-hospital care teams (like ambulance and helicopter crews) and so on. One of the problems that trauma care teams face is that very little formal training is offered on how teams ought to co-operate. Another problem is that participating in the trauma team is, in most cases, only a small part of the professional s role. For example, orthopaedic surgeons only spend about one-third of their time doing trauma work, the rest of their work being dedicated to longer-term care regimes. These two observations emerged quite quickly in our study, and raised a number of hypotheses for the research team. One hypothesis was that there may be a lack of professional commitment to trauma care in particular fields, and that mistakes in care provision may occur as a result of these politicized commitments. This hypothesis was used to select some participants for interview, including some of the personnel who had been mentioned as potentially difficult members of the trauma team. Not all hypotheses turn out to be correct, and it is a normal feature of grounded theory work that researchers may need to re-formulate their hypotheses and related concepts, sampling strategies, codes, and so on in the course of their research. Codes A code is a category that is used to describe some general feature across a data set. Codes are used to examine commonalities across the data set, differences across a data set, and relationships between commonalities and differences. By creating a category, a researcher provides a way of seeing the commonalities across a set of cases. In Chapter 5 of Discovery (1967: 105 6), the authors give an example from their Awareness of Dying study: the category of social loss of dying patients emerged quickly from comparisons of nurses responses to the potential deaths of their patients. Each relevant response involved the nurse s appraisal of the degree of loss that her patient would be in his family, his occupation, or society: He was so young, He was to be a doctor, She had a full life, or what will the children and her husband do without her? Each instance of data that is included in the category fits the description of the category. In the above example, this something in common involves an articulation of social loss. By generating a number of codes, researchers start to create patterns in relation to their data that categorize the data as of this type or of that type. In this way, the researcher specifies not only commonalities, but also differences between the cases in their research. A researcher may realize that some of the people in a given category (say, doctors ) are different from other people in that category because of some concept that has developed from their theory. In our trauma care study, there is clearly a difference between doctors who are highly committed to the trauma team and those who are not. These distinctions have emerged through the examination and coding of data. 11

12 Furthermore, as coding develops, researchers start to explore the relationships between their codes. For example, it is clear that some of our non-committed trauma doctors get their disinterest from the nature of the other teams that they participate in, some of which regard trauma care as uninteresting, not useful for professional development, and unsocial because of the uncertainty of the working hours. These differences emerge through using data codes for motivation, attitude to trauma care and trauma team specializations, and examining the relationship between these. For example, researchers can use qualitative analysis technology to search their codes to see the extent to which two or more codes occur at the same time. Using Boolean search terms (and, not, or, and/or), researchers can create simple and more complex searches of their data and codes and find out the relationships between their codes. The results of these searches can be used to create new codes and new hypotheses for further exploration. Much of the methodological discussion in the various texts associated with grounded theory involves examining the procedures of defining codes and relating them to each other. Properties The notion of properties makes a brief appearance in Discovery but is described in more detail in Strauss s later collaborations with Juliet Corbin. For example, Strauss and Corbin (1987) define a property as some aspect of a code that varies along a scale. The following extended quotation illustrates this idea nicely with reference to a study of drug taking: we might say that one of the properties that differentiates limited experimenting with drugs from hard-core use of drugs is frequency or the number of times a week the person is stoned. We dimensionalize the property frequency by saying that with limited use, the user is stoned only occasionally. If we wanted to qualify or explain the term limited experimenting even further, then we could say that the teen uses drugs and gets stoned only when at a party with other teens at which drugs are readily available and passed around, whereas we might say that the hard-core user is stoned very often, using drugs three to four times a week, either when alone or when with selected others, and seeking out drugs on his or her own rather than having them passed around at a party. This qualifying of a category by specifying its particular properties and dimensions is important because we can begin to formulate patterns along with their variations. For example, we might say, based on frequency of use and the type of drug used, that this situation can be classified into the pattern of limited experimenting with drugs. Perhaps if we do another interview and the patterns of drug use and getting stoned fit neither identified pattern, then the analyst can develop a third pattern such as the recreational use of drugs. Patterns are formed when groups of properties align themselves along various dimensions. (Strauss and Corbin, 1987: 117, original emphasis) Theoretical saturation and theory solidification Theoretical saturation and theory solidification are important aspects of grounded theory that refer to the ways in which a theory takes shape. Solidifying the theory entails the firming up of a theory and its constitutive components (categories, properties and hypotheses). Here, the analyst begins to discard nonrelevant properties and categories and to work with a more stable selection of 12

13 concepts and ideas. A fundamental aspect of this later stage of theory development is that of theory saturation, which refers to the point at which theoretical work (like applying a code category or defining a property) routinely produces the same results or conclusions. For example, where a researcher stops producing new categories, and stops modifying their categories in the light of new data (because the existing categories are well defined, sufficient, and suitable to new instances), then the researcher may be said to have reached theoretical saturation. Writing Glaser and Strauss s articulation of writing is quite distinct from other descriptions of the writing process in qualitative social research. In many constructivist approaches the writing process and writing up are very much intertwined. Writing is an aspect of the development of ideas, and there is no clear boundary between the working out of ideas on paper and writing up. Through writing, researchers may discover new theories and ideas. In principle, grounded theory accepts this premise, but suggests that all ideas should be very well developed and empirically worked through before writing up is undertaken. Writing up should be about simply putting the worked-out ideas on paper, and not about creating anything new. Debates and dilemmas in grounded theory As you have seen, one of the key and defining features of grounded theory is the emphasis on generating theory through research rather than prior to research. One of the strongest examples of this view in Glaser and Strauss s work (both in their early work and in their subsequent divergent writings) is in terms of the uses of literature. For example, Strauss and Corbin make a distinction between technical literature and non-technical literature, the former referring to published academic work like books and journal articles and the latter to diaries, documents, reports etc. As with Glaser and Strauss (1967) and Glaser (1978, 1992), Strauss and Corbin (1987) argue that for the purposes of grounded theory it is best to avoid using literature to generate theoretical or conceptual ideas that can be pursued in relation to the research. In a particularly telling statement (Strauss and Corbin, 1990: 49) they argue that: if you begin with a list of already identified variables (categories), they may and are indeed very likely to get in the way of discovery. Also, in grounded theory studies, you want to explain phenomena in light of the theoretical framework that evolves during the research itself; thus, you do not want to be constrained by having to adhere to a previously developed theory that may or may not apply to the area under investigation. However, both Glaser and Strauss (1967) and Strauss and Corbin (1987) also argue that it may be useful to use literature subsequently to compare the categories that the research has generated with other research in the field see Goulding (2002) on this point. In this respect then, literature may be a good way of generating ideas in subsequent analytic stages, but not in the first instance. A strong criticism that has been levelled at this aspect of grounded theory is that it represents something of a disingenuous view of how research typically proceeds. Goulding, for example, argues that Glaser and Strauss s characterization of their research as closed off from apriori formulation belies the 13

14 level of their research knowledge and their prior professional experience. Further, since the authors do not preclude the use of externally derived concepts at other stages of the research, their insistence on avoiding them at the earlier stages seems a little strange. If external ideas can drive research later, why not let it drive it earlier? Surely the effect is, in the end, the same? The charge of positivism This critique of a touch of disingenuousness in grounded theory is a part of a wider critique of the approach as representing some clear positivistic tendencies. The notions of discovering theory in some objective fashion, the aims of unbiased data collection, and of trying to find some external objective reality have been strongly problematized by those who have adopted more interpretivist stances in the qualitative social sciences, such as Charmaz (2000: 509). Glaser has responded in characteristically robust fashion in the open-access journal Forum Qualitative Sozialforschung (FQS) (Glaser, 2002), where he takes substantial issue with the constructivist position. The divergence between Glaser and Strauss As I noted in the introduction to this unit, Glaser and Strauss later parted company in quite a dramatic fashion. Strauss s collaborations with Juliet Corbin were interpreted by Glaser as involving a radical departure from the initial formulations of grounded theory. Glaser s vitriolic response to this perceived shift is a rare example of gloves-off discourse in academia and, because of this, I have included it as another short, key reading for this unit. This reading articulates a tough response to Strauss and Corbin s work, and one that outlines nicely some of the differences between the authors later work. Concluding remarks: grounded theory, grounded theory, and grounded theory It should be clear from the discussion you have read in this unit that grounded theory is far from a unified approach. The divergences between Glaser and Strauss own work, and the ways in which other grounded theory contributors have worked through these debates and their fit with other qualitative approaches, have created a complex network of articulations of the approach. Furthermore, the term grounded theory is, in some instances, used in a very imprecise way, and can refers to nothing much more than the undertaking of qualitative research. When some researchers refer to grounded theory they mean something like qualitative research or data analysis. This looseness and slippage of the term can make it very difficult for researchers to understand what grounded theory really is, both in general and in specific instances of its application. Through this unit and its associated readings, you should become knowledgeable of the subtle variations in approach, and equipped to make your own judgements about the particular claims being made when researchers refer to their work as involving grounded theory. 14

15 References Charmaz, C. (2000) Grounded theory: objectivist and constructivist methods in Denzin, N. and Lincoln, Y. Handbook of Qualitative Research (2nd edn), London, Sage. Glaser, B. (1978) Theoretical Sensitivity: Advances in the methodology of grounded theory. Mill Valley, CA, Sociology Press Glaser, B. (1992) Basics of Grounded Theory Analysis. Mill Valley, CA, Sociology Press Glaser, B.G. (2002) Constructivist grounded theory?, Forum Qualitative Sozialforschung/Forum: Qualitative Social Research 3(3), Art. 12. Available at: (accessed October 2008) Glaser, B. and Strauss, A. (1965) Awareness of Dying. Chicago, Aldine Glaser, B. and Strauss, A. (1967) The Discovery of Grounded Theory: Strategies for qualitative research. Mill Valley, CA, Sociology Press Goulding, C. (2002) Grounded Theory: A practical guide for management, business, and market research. London, Sage Strauss, A. and Corbin, J. (1987) Basics of Qualitative Research: Techniques and procedures for developing grounded theory. London, Sage Strauss, A. and Corbin, J. (1990) Basics of Qualitative Research: Grounded theory procedures and techniques. London, Sage 15