ANALYSING

QUALITATIVE DATA

Dr Lesley Pugsley

ASME RME November 2015

The Qualitative Paradigm

Acknowledges and accepts the

existence of multiple versions of

reality, because reality is multi-

layered.

All accounts are partial

Aim of Qualitative Research

To form a map of the relevant

characteristics of a population

rather than a mirror of the

number of people with those

characteristics

Features of Qualitative Research -1

– People act intentionally and make meanings in and through their activities (Blumer 1969)

– People actively construct their social worlds- they are not ‘cultural dupes’ (Becker, 1970, Garfinkel, 1967)

– Situations are fluid, richly affected by context – ‘situated activities’

Features of Qualitative Research-2

–Events and individuals are unique and largely non- generalisable

–Social worlds should be studied in their natural states (Hammersley and Atkinson, 1997)

–There are multiple interpretations of and perspectives on single events

–Need to examine situations through the eyes of the participants

Qualitative research is

Interpretive

Meaning rather than frequency

–What, why & when

NOT

–How many

Qualitative Research

Must Be:

Rigorous

Reflexive

Triangulated or validated

Transparent

Data Analysis

Qualitative data are ‘sexy’

Qualitative Data are unstructured and

unwieldy

Researchers need to apply structure and

coherence - to ‘make sense’ of their data

Good qualitative analysis

Systematic

Accessible to others

Dynamic – open to change

Comprehensive

Allows between and cross case analysis

Grounded / iterative

Enables easy retrieval

Coding

Transcripts coded by a paragraph of speech

Unlike survey questionnaires when code is by question - not case (greater consistency)

Sort into categories

Continue to code & sort until no new categories are generated

Categorisng Data

Need to develop categories for coding

These can come from:

Theory

Intuition

Data

Coding Down

Where the research is designed to test

an hypothesis

Categories are derived from the

theoretical framework and then data

are sought to match the categories

Coding Up

Where the aim is to describe the data, code and classify it in order to identify themes or generate theory

This demands a constant interrogation of the data until no new thematic categories are generated

Theories are then sought from the extant literature to provide explanations

Open Coding

Data sorted into 1st level concepts

Date generated concepts or categories

Data sorted into different files

Indexing- Comprehensive data catalogue

Think widely – categories can be collated

Axial Coding

Shift is from a focus on the text

More directed approach - uses concepts and categories to re-read data to confirm:-

Accuracy of categories to data

Explore the relationships

Creating a coding List or TreeGrantley, M. (1999:14) Data from a London Educational Initiative Project

(I). And how did you decide what you wanted to do?

(GP). There were certain things that we were doing, one was fund holding, we are going inti this and we had the meetings, loads and loads of meetings.

(I). Did you have a plan of what education you wanted to do?

(GP). No it was basically the courses, as and when they came we chose which we wanted to do and which we didn’t want to do.

(I). What has the funding enabled you to do?

(GP). To do the courses and get paid at the same time.

Concepts List

o Decision making

o Fund Holding

oMeetings

o Courses

oGetting Paid

Coding Tree-

potential to expand

GP Educational

Initiative

Decision making

Who What / why

Fundholding Meetings

Format

Courses

Curriculum

Getting Paid

Barriers

Implications

Task

Working Individually :-

Read the handout – an extract from a

focus group transcript and code the data

into categories that are meaningful to you

Coding

1. Passing as normal

2. Symbols of disability

3. Stigma

4. Misunderstandings

5. Embarrassment

6. Aids for coping

7. Problems

8. Impact of problems

9. Coping strategies

Coding

Ann: The problem is that we all look, well, normal.

It’s not like were carrying white sticks or anything.

Passing as normal

Symbols of disability

Bertha: No and even if you are being guided you

could just be with a friend or something.

Passing as normal

Coding

Connie: I’ve got a white stick but usually it’s in my handbag – I hate using it people stare at you and you get offered seats in the bus, - you get more attention, more than I want anyway.

Passing as normal

Stigma

Ann: well that's the problem – it’s embarrassing, people who don’t know assume that if you are using a white stick then you can’t see anything, so they look, quite openly, staring thinking that you can’t see them staring.

Misunderstandings

Embarrassment

Coding

Interviewer: So do you prefer looking ‘normal’?

Bertha: Well I feel pretty normal, mostly.

Connie: With the white stick, it’s meant for car drivers really so that they can see you if you jump in the road-but I do feel very conscious when I’m carrying it, people jump out of the way like you’ve got the plague or something

Passing as normal

Aids for coping,

Stigma

Embarrassment

Coding

Donna: I use one when I’m out on my own, when

my sister is not with me and {it’s mainly for dealing

with stairs} - I have real problems with steps not

being able to see with depth perception.

Aids for coping

Problems

CODING

Ann: Oh, me too.

Donna: And contrasts you know coming into a dark

room, or outside, can’t see a thing then.

Problems

Bertha: Oh god, lifts are the worst! I just can’t see

anything when I step into a lift

Impact of Problems

Coding

Connie: Because it’s all dark! – I know you just have

to hope that someone else comes in to press the

buttons

Problems

Strategies for coping

Ann: That’s why I wear dark glasses outside – it

makes the contrast less.

Strategies for coping

Generating Categories

Inclusive rather than exclusive codes

– Interlink the units of data

– Try to assign two or more codes to each segment of data

Let codes emerge - read & re-read

– develop a systematic approach, Classify data & create typologies- link the codes

Change and refine the categories as you proceed.

Refining Categories

Be thorough - consider all the categories you can

Some will be discarded because they fail to resonate

with other data

Some will collapse together

The aim is to make links and determine patterns in

the data - and to identify contrasts and highlight

paradox.

KEY POINTS

There are no short cuts

Never let the data accumulate

Read & re-read and keep notes – analytic memos

-to track your thought process

KEY POINTS -2

– Merely describing / reporting what happened is

Journalism not Research

– The analytical concepts generated determine the

strength of the piece

– Data need to be integrated with established

theories and concepts with referenced literatures

to support & strengthen your case

Caveat:Do you really want to do

qualitative research?

Qualitative Research is not the easy option!

It is hard work - exhaustingly hard work.

“It is only suitable for people who care about it, take it

seriously and are prepared for commitment. It must be done

properly or not at all so unless you are fired with zeal, don’t

do it!” (Delamont, 2002:ix). Fieldwork in Educational Settings.

London: Routledge.

But - it is exhilarating, informative and addictive !