Qualitative Data Analysis

Transcription

1 Qualitative Data Analysis APPROACHES AND TECHNIQUES COPYRIGHT 2018 KAREN O REILLY. THESE SLIDES/MATERIALS ARE SUBJECT TO COPYRIGHT. THEY ARE NOT TO BE COPIED, REPRODUCED, OR REDISTRIBUTED WITHOUT THE OWNER S WRITTEN PERMISSION.

2 Objectives By the end of the workshop, participants will have Knowledge and critical awareness of diverse types of qualitative data analysis A critical appreciation of what thematic analysis is and how it fits as an approach to analyzing qualitative data Practical knowledge of the process of thematic analysis Discursive knowledge of the role of thematic analysis in generating rigorous and valid reports Practical knowledge of (some of) the steps in data management, coding and preparation Topics The iterative-inductive nature of qualitative analysis A quick overview of different types of qualitative data analysis: thematic, discourse, content, grounded theory, narrative and ethnographic analysis Data management and storage (including, briefly, computer software) Coding: open, inductive, deductive and focused coding The role of theory in coding and analysis Memo-writing or diagramming Identifying themes and categories (processes, actions, stories, personas, or typologies)

3 The iterative-inductive nature of qualitative analysis

4 The broad nature of qualitative research qualitative methods entail and manifest the assumptions of the interpretive paradigm, the grounds of which lie in the need to grasp the meaning of social action in the context of the life-world and from the actors' perspective. (Vasilachs de Gialdino 2009)

5 attempts to capture or study data which are detailed, rich and complex concerned with meanings The data of qualitative research data mainly in form of words / ideas / themes / patterns / processes rather than numbers sets data in context explanations at the level of meaning or in terms of intentions, norms, opportunities, barriers or micro-social processes rather than context free causal laws

6 mainly inductive rather than deductive analytical process The broad nature of qualitative research emergent categories and theoretical ideas in addition to / rather than a priori concepts committed to retaining diversity and complexity in analysis respect for uniqueness of individual cases as well as comparative themes and pattern uses flexible, non standardised methods Seeks useful results rather then numerically generalisable

7 Key Idea Qualitative research is usually iterative-inductive This is a practice of doing research, informed by a sophisticated inductivism, in which data collection, analysis, and writing are not discrete phases but inextricably linked.

8 A quick overview of different types of qualitative data analysis: thematic, narrative, discourse, content, grounded theory, narrative and ethnographic analysis

9 Discourse Analysis

10 Philosophy Wittgenstein, Barthes, Derrida, Foucault, (Garfinkel, de Saussure) a particular set of linguistic categories relating to an object and the ways of depicting it frame the way we comprehend that object (Bryman 2012, p. 528) Discourse analysis - origins EG the medical discourse, holistic medicine, mental illness, migration, tourism Discourses justify power of practitioners to exclude, define, act For research this means we don t see people as having fixed attitudes but ideas shaped by language Discourse analysis is a way of conceptualising and analysing language (McMullen in Wertz et. al. 2011, p205) Discourse analysts thus view meaning as constructed, situated, and negotiated. They are likely to see many objects as text, not just talk

11 Potter and Wetherell (key ref) Anti-realist here we are not taking what people say at face value nor trying to achieve a privileged understanding as researchers Constructionist A particular view of reality is put forward by interviewees (others are possible) DA is more concerned with what is being said, by whom, to what ends Texts are studied as an insight into how meaning is made, not what meaning is Interviews as conversational encounters (Potter and Wetherell, 1987) People seem to accomplish things when they talk (Bryman 2012, 529)

12 Discourse analysis in action McMullen (in Wertz et al, 2011) Read all the texts, undirected way, no notes 1 week later read them all again, with notes in margins Notes were paraphrases, key words, descriptions Later readings were more directed, drawing on analytic concepts such as Positioning of oneself Interpretative repertoires Patterns Stepped back from analysis and thought about how terms such as resilience, coping, and recovery were framing the discourse Back to data, back to analysis, to and fro

13 Charmaz s response The discourse analyst remains outside the research participant s experience and looks at it from multiple vantage points as to how the performance is given and what it accomplishes. (Charmaz in Wertz, et. al. 2011, p. 298) In other words the emphasis is on how meanings are made not on how the participant feels or thinks, on expression and framing rather than on experience The analyst seems to start with what is most significant for her rather than what is most significant for the participants Charmaz then describes her iterative approach to data collection, and that she would go and collect more information on friendships and experiences

14 Narrative analysis

15 Narrative analysis Very diverse with different influences depending on the discipline What they share in common is the hermeneutic tradition (the interpretation of texts), the interpretation of culture, researchers use narrative analysis to understand how various people including those marginalized by the hypothetic-deductive model construct their lives (Wertz et al. 2011, p. 66) The emphasis is on how stories are told, in the context of biographies All knowledge is understood to be perspectival, local, and inter-subjective

16 Narrative methods of analysis No given set of techniques or procedures A way of thinking, a way of asking questions, a way of interrogating the voices, in context Josselson (in Wertz et. al, 2011) Read the texts overall for sense of structure and general themes Multiple readings to identify different voices of the self and how they relate Iterative readings seeking themes that cover contradictions and reach overall coherence Draws on wider theoretical literature in order to remain sensitive to nuances of meaning, how they are expressed and in what context. Also see Stanley (2013)

17 Charmaz s response (in Wertz et. al) Narrative analysis examines the texts in parts as well as a whole (using the hermeneutic circle) Narrative pays attention to the temporal dimensions in understanding and experiences Narrative, like phenomenology, believe participants are able to express the meaningful, temporal unfolding of life (p. 286) There is quite a heavy use of psychological theories, such as of identity In the end the emphasis is on identity as articulated in life story rather than as lived Both, she says, conducted thematic analysis. But they came up with different themes.

18 Ethnographic analysis

19 What is ethnography? Ethnography is a flexible mixed-methods approach that combines participant observation and conversation with other methods such as interviews and sometimes survey work. Crucially ethnography involves direct and sustained contact with human beings, in the context of their daily lives, over a prolonged period of time; respects the complexity of the social world; and aims to produce rich, sensitive, and credible stories. (O Reilly 2012)

20 Ethnographic Analysis Key Idea. Iterative-Inductive and Reflexive Hypothesis formulation, theory construction, coding, interpretation, (even data collection) are inextricably bound up with one another Analysis begins in the field Coding begins as you write field notes It is an iterative process of sorting emergent themes into categories and arguments that make sense of the data in the context of the participants lives It usually seeks meanings and understandings rather than laws or patterns

21 Content Analysis

22 Qualitative content analysis Exists on a continuum from intepretivism to positivism, quantitative to qualitative from counting occurrences of words or phrases (quantitative content analysis) to iterative understanding (qualitative or interpretive content analysis) It tends to be used more for the analysis of texts and documents than for interview data or field notes. The data tend to pre-exist the data collector Typical study seems to be of newspapers, but any documents, texts, visual data, or online data can be used (even field notes)

23 Methods of analysis Use predetermined codes or look for codes inductively Or use a combination of both For some, like Mayring (2000) the approach is quite linear 600 open-ended transcripts on consequences of unemployment, needed systematic (more positivist) approach For others, like Altheide (2013), the approach is more iterative and interpretive Analysing diverse texts that represent and shape culture. He suggests constantly refining codes, collecting more data, narrowing the focus over time, and looking at who produced texts and how. More interpretivist

24 Grounded theory

25 Glaser and Strauss Glaser Quantitative background Influence of Positivism Empiricist Rigorous Middle-range theories Strauss Chicago School Actor-oriented Ethnography Studied meanings and processes Grounded theories, then, attempt to explain observed processes

26 Grounded theories Grounded theories tend to be substantive They address given problems in specific situations Can be generalised to broader situations Commonly used in medical, educational and criminological settings

27 Data collection and analysis go hand in hand Codes, concepts and categories to sort the data come from the data Discovery of Grounded Theory Analysis proceeds in stages with constant comparisons Theory is developed in stages Memos are used to elaborate codes Sampling is for theory construction not representativeness The literature review comes later

28 Glaser and Strauss and later developments Glaser and Strauss diverged Glaser defends classic grounded theory Strauss worked with Juliet Corbin They trained Kathy Charmaz (and others) These are influenced by Symbolic Interactionism, Interpretivism, and pragmatism

29 Charmaz s approach Kathy Charmaz (2014) calls herself constructivist Theories are not discovered but constructed through our engagement with the world Theory offers an interpretation of the world not a picture So, grounded theory approaches are constantly adapted But there are commonalities in their techniques

30 Research problems, opening questions Data collection, initial coding Memos and raising codes to categories Overlapping stages Data collection, focussed coding Advanced memos, refining categories Theoretical sampling and directed data collection Adopting categories as theoretical concepts, further memos Sorting memos Integrating memos, diagram of concepts Writing

31 Thematic analysis

32 A generic term for the procedures that are common to most of the approaches discussed. Looking for themes in the data and combining them to achieve a coherent interpretation Thematic analysis In qualitative research thematic analysis is iterative (but this might not include data collection) In qualitative research inductive coding comes before deductive Researchers vary in the extent to which they use existing theories, but arguable they should all earn their way Some thematic analysis is used to develop grounded theories You may be interested in how the story is told, in what story is being told, in how it is framed, or in the experiences and feelings described Thematic analysis is theoretically flexible (Braun and Clarke 2006)

33 Thematic analysis goals to grasp the meaning of social action in the context of the life-world and from the actors' perspective explanations at the level of meaning or in terms of intentions, norms, opportunities, barriers, psychological or micro-social processes, rather than context free causal laws Remember your original research questions or puzzles what did you want to know? What will count as evidence? What are we aiming to produce?

34 Workshop In small groups, discuss What are your main aims and objectives? What sort of report do you aim to produce? Eg. articles, PhD, book, short report. Who for? What will count as evidence of what you are exploring? What sorts of outcomes are you looking for?

35 Data management and storage (including, briefly, computer software)

36 Dealing with data Analysis is a reflexive process of making sense of all or parts of the data for a specific reader/user Data will be moved from chronological order into themes, categories, areas Sorting therefore means dividing, moving, classifying Computers can help you sort but not analyse the data Documents, recordings, diaries, memory etc. are unlikely to be computerised/coded in the same way

37 Sorting and coding Data can be assigned to categories but should also remain within the rest of the data. Be fully inclusive but not mutually exclusive Categorise to meet your own demands - and be prepared to change - institutions, people, groups, themes, concepts all count as categories or classifications Today we focus on themes and concepts Data can be coded within the whole text or can be split up - but avoid divorcing from context You may need various forms of organisation eg excel sheets, database, word docs

38 Text: interviews, field notes, documents Forms of data Visual: photographs, film, cartoons, room layout Audio: recordings that can be transcribed, other sounds? Memory, smells, emotions

39 A note on recording and transcriptions Record if you can Transcribe if you can But you can identify themes in recordings, memory, etc. You do not have to be comprehensive in your coding, selection is essential Ask permissions Store safely and securely

40 A note on software Computer Assisted Qualitative Data AnalysiS (CAQDAS) is a term, introduced by Fielding and Lee in 1991, that refers to the wide range of software now available that supports a variety of analytic styles in qualitative work. Software does not do the analysis Main facilities: coding, searching, reporting, retrieving, images, modeling, video and variable type data Use one that is supported by your institution (or one you know colleagues use) Beware reification Beware losing the context

41 Analysis common steps Overview: Read everything through (or look) Avoid preconceptions: Keep an open mind Open Code: Make some notes (inductively) Focused or Selective Code: Re-read, make more notes Write memos: Look at the developing themes or categories Re-code, sort codes: Take them to the data (deductively) Bring in theories or concepts: Consider extant theories Open code: Take a step back from time to time to avoid forcing data into preconceived categories Write: Gradually reduce data to a few themes, personas, theories, arguments

42 Break

43 Coding: open, inductive, deductive and focused coding

44 Open Coding Step One - Open Coding Is first attempt to capture meanings, intentions (or whatever you are interested in) Ask questions of the data Remain open, enable surprise, but look closely Delve into not apparent Is provisional Works very well in teams Leads to more analysis (and perhaps data collection)

45 Open Coding Labelling segments of text with short phrases Code actions, processes, or themes Try using gerunds (Strauss and Corbin 1998) Have the rest of the data in mind (constant comparisons in GT) Stay close to the data Listen to the data, hear the arguments (insider perspectives) Keep codes simple and precise at this stage (you can elaborate later) Move quickly Construct codes

46 Open Coding Line by line; word by word; incident by incident Depends on quality of data Field notes are already quite selective So are visual data (try to remember why you collected material) Explore implicit and explicit Look for In-vivo codes (participants own terms) What are you coding? Different approaches will look for different things psychological processes, social processes, meanings, narratives, discourses, experiences, understandings, broad themes A realist analysis is looking for what is really going on. A constructivist approach will interact with the data to construct an interpretation But also move beyond the descriptive

47 Workshop Open Coding as individuals; discuss the process Gibbs video on line by line coding (6.5 mins) Shared coding of a section of interview transcript

48 LUNCH

49 Focused or selective coding Next stage in coding is focused coding This is directive, selective, conceptual It involves identifying the strong analytic directions And determining their adequacy for large segments of data Focused coding is iterative, not linear (ie you may need to do more open coding) It is comparative It also involves refining codes, defining them, and unpacking them (and starting to write memos) And developing categories (or clusters of codes)

50 Axial Coding Feeling free Axial coding is used by Strauss and Corbin (1998) to formalise the linking of categories into a framework Axial coding specifies the properties and dimensions of a category It also relates categories to subcategories Escaping Britain Crime weather Enjoying Spain Playing outdoors Warmth drinking Sharing pleasures Axial coding is a tool you can use

51 Workshop Focused coding in small groups of same section of transcript Shared coding of same Discussion Have we used extant theory? Have we used axial coding?

52 The role of theory in coding and analysis

53 Theoretical coding Theoretical codes are one more step in the analytical story (Charmaz 2014) They are labels/names that draw on theoretical concepts They may link/associate/relate focused/selective codes They relate codes or processes to theoretical ideas Theoretical codes are tools and should be used consciously, explicitly and reflexively. Avoid forcing data into preconceived categories

54 Examples of theoretical codes Stigma Empowerment Alienation Institutional racism Normalising Ie ideas that come with conceptual baggage/literature/

55 Dealing with preconceptions Achieving intimate familiarity Thorough data gathering Initial open coding Make sure all concepts earn their place in the data Treat all ideas as problematic Collect copious notes and transcripts Collect observations and thoughts as well as interviews Remain reflexive Finally: coding should be fun, and creative.

56 Memo-writing or diagramming

57 Memo Writing Memos can be jottings, ramblings thoughts, diagrams, and more systematically worked through arguments and schema. They are the pivotal intermediate step between coding and writing They mark the beginning of theorising as opposed to description They help you develop ideas and may also direct data gathering

58 How to create memos Begin early, but do not let this narrow your focus too soon Have a title to help you focus Use your codes and follow them through, compare with others and with other data Follow leads, dig beneath the surface, but also consider context and structure Work quickly so that you do not have time to panic, and so that you are more creative Just write, sketch, record in whatever way suits you best Ask what is going on here, what is being assumed Remember your research questions (re-write them)

59 How to create memos Do not try to structure too much at first Move between ideas, data, coding, to and fro Include data as examples so that you avoid abstracting away from the data Memos should be informal They are for personal use and can be firm or conjectural Can be short and stilted or long and free-flowing Enjoy - they are tools to use

60 Advanced memos Memos are work in progress As time goes along your memos will become more elaborate Memo writing is your space to stand back, think, explore, Memos may Define a code or category, or question it Detail processes Make comparisons Use concrete examples Offer conjectures Identify gaps in analysis

61 Workshop Write a memo together in a small group that pulls together a few ideas/processes you have seen in the data Consider using a theoretical code Have a title My memo on same transcript Have we coded processes, stories, discourses, actions? Is it theoretical or descriptive? Does it use axial coding?

62 BREAK

63 Identifying themes and categories processes, actions, stories, personas, or typologies

64 Workshop Identifying what sorts of things we have coded: Inductive Themes/Patterns Deductive themes Processes Actions Theoretical codes Latent themes Are they interpretive or descriptive? Is the aim to develop A thematic overview A focus on an area/theme? A theoretical argument A grounded theory (of processes) Personas Typologies Understandings (insider) Thematic analysis helps us sort our data, into patterns or types, but also usually involves us making sense of it for a specific purpose.

65 Developing insights The goal of qualitative analysis is to create insights that explain people s behavior in the context of their life, experiences, or culture or explain how policies or actions are practiced To do this we tend to relate our themes into a coherent story This often involves making some interpretations We may combine processes into a theory, move from themes to interpretive analysis (drawing on external theories), we may locate our understandings in the context of a life as lived, or we may look for (or construct) types or personas

66 Grounded theory (or describing processes) Making friends Seeing college as social Seeing social class differences Dressing up Grouping or forming a clique Distancing from others Receiving bad news, telling news, experiencing a disruption of self, loss of self facing loss. regaining a valued sense of self (Charmaz in Wertz et. al. 2011)

67 Moving from themes to interpretive analysis Themes Escape Freedom Language Bad Britain/good Spain Informal economy Volunteering Theoretical interpretation (grounded?) Attempting to escape Making constant comparisons with home Embracing free movement Interpreting freedom as linked to lack of control Seeing Spain as representing a better way of life Constructing a better way of life (O Reilly 2000)

68 Giving depth through stories (or interpreting narratives) Nella Last s diary Housewife, 49 Stories of sadness, of routine, of morality, In diaries generally, stories elucidate a point the diarist wants to make at the time of writing, and are modulated to a kind of model reader (Salter, in Stanley 2013, p. 101) Tues I went as usual to Hospital Supply Ms Wood, a tall majestic type always held the theory that when we win the war it is our duty to stamp out the German race, they are a menace I said ah no, Woody, I must push away all hurtful, negative thoughts and try and send my poor lad comfort and love and healing ones (Mrs Last)

69 Personas One common technique for summarizing a body of research is Personas These are archetypes, or ideal types (but be wary of stereotypes) Key characteristics pertaining to relevant stakeholders traditionally based on observed behaviour patterns, psychological traits, goals and motivations which tell a cohesive real world story about the fundamental characteristics of a type of person or group of people. They are designed to elicit empathy in a way that designers and others can relate and design to. LEEDR

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71 Typologies British in Spain full residents, peripatetic migrants, seasonal visitors, winter returners Attitudes towards settlement, and making a home (O Reilly 2000) Types of illness and time Illnesses like diabetes that demand daily monitoring Illnesses that have episodes Illnesses that progress rapidly Illness that means changing one s life (eg avoiding the sun) Ways of experiencing time and immersion in illness (Charmaz 2014)

72 Published examples Policy Academic

73 Conclusion We have covered: The iterative-inductive nature of qualitative analysis A quick overview of different types of qualitative data analysis: thematic, discourse, content, grounded theory, narrative and ethnographic analysis Data management and storage (including, briefly, computer software) Coding: open, inductive, deductive and focused coding Thematic analysis is a generic term for the practicalities of doing analysis Once you know what you are trying to achieve with your analysis And who for You can draw on techniques from different approaches But generally qualitative analysis is inductive and iterative The role of theory in coding and analysis Memo-writing or diagramming ENJOY Identifying themes and categories (processes, actions, stories, personas, or typologies)