CBR 302CBR 302A Hands-On Approach to Qualitative Methods A Hands-On Approach to Qualitative Methods

and Analysisand Analysis

Introduction

About making the world a better place via Community Based Research (CBR) :

We’re all part of solution No one way Use dialogue Deep learning to get at root of problem

(Aha)

Learning Objectives

Upon completion of this workshop, you will be able to:

Describe qualitative research conceptsExplain some of the important terms associated with qualitative

research List misconceptions and limitations of ‘qualitative’ methodsFollow the steps to develop a research projectDifferentiate between Methods, Methodology and ResearchDevelop strategies and skill for gathering and managing 'good' data

(e.g. recording, transcribing, note-taking, qualitative software, etc)

Participate in the analysis of data and develop strategies for coding data

Learn effective approaches for presenting qualitative data 

Qualitative Research: Prevalent Concepts

“seek … how social experience is created and given meaning” (Denzin & Lincoln, 2000, p. 8)

Produce findings without statistical procedures or quantification

Accept different ways of making sense of the world

Seek participant interpretation

Emphasize participant more than researcher view

Qualitative Research: Prevalent Concepts

Researcher primary instrument

Focus on subjective (or lived) experience

Obtain descriptive, rich, in-depth accounts

Allow ‘from the ground up’ theory building

Can use open, exploratory, ‘unstructured’ means

One Definition of Qualitative Research

Understanding actions & meanings in their social context (or ‘natural settings’)

Focus on subjective (or lived) experience Descriptive, rich, in-depth Allows for ‘from the ground up’ theory

building Open ended, exploratory, ‘unstructured’

What is Qualitative Data?

Data in the form of wordsLanguage in the form of texts such as : interviews,

questionnaire responses & long textObservation of settings & events (researcher’s

notes)Personal document such as letter, diaries, etc

Aspects of QR Methods

Increases understanding of context, content

Increases understanding of what is affected & how

Analyzes why particular impacts are occurring

Assesses how policy can be improved

Qualitative Research: Common Misconceptions

Easier than quantitative research

Not methodologically rigorous

Doesn’t reveal anything about ‘populations’

Data more manageable

Only experts can do it

Only a first step (for survey development)

Limitations of Qualitative Methods

Can be difficult to focus (holistic)

Researcher may have difficulty reconciling differences in the data & assessing how representative they are

Cannot make predictions

Cannot be objective since objectivity rejected on principle

Cannot be replicated

Qualitative Research Stages

State Research Purpose and Problem

Design Research Project - Method

Conduct Research Project

Data Collection & Analysis

Disseminate Results

Exercise 1:

Define Qualitative Research in your own words & discuss its application in the context of your work?

Methods, Methodology & Research

Method: The practice of researchThe specific techniques that are employed in collecting, analyzing and disseminating the research

Methodology: The experience of researchThe situations, contexts and social factors that informs the researcher’s and participants’ involvement in the project

Method

A set of procedures and techniques for gathering and analyzing data (Strauss & Corbin, 1998, p. 3)

• Observation- Participant- Nonparticipant

• Interview• Focus Group• Case study• Short-answer Questionnaire• Case study• Life history, Narrative, • Document analysis

Methods, Methodology & Research

Methodology – Process issues that can significantly impact on the quality and validity of the research data

Relationships to the community Power and research Nature of the questions Role of prior knowledge in developing the

project and analyzing the data

Research Design and Methods

… there is no one design or method appropriate for all

Instead, each partnership has to decide what works best for its research question and intervention goal in its particular community context. P. 70

Reference: Minkler & Wallerstein, 2003

Data

Rich Description

Captures sufficient data (e.g., quotations) so reader can follow process, results, themes, conclusions Captures sufficient detail to capture themes or patterns to summarize essence of data

Method Exercise 1: Continued

Working with your table mates please discuss:

What factors should you consider when making the decision about which method to use to collect the data?

Be prepared to discuss your recommendations with the class.

Stages of Research

Identifying the Research Project – Collaborative Venture with community partners

Clearly identify the focus and objectives of the research project

Designing the Research Project – Method

Conducting the Research Project

Data Collection & Analysis

Dissemination of the Data

Develop Interview Guide Using Standard Open–Ended Questions

Sub-questions should help answer main research question

Ask only what you need to know

Ask easier questions first

Do not ask more than one question within a sentence

Seeking more than a yes or no answer

Use exploratory words e.g., “describe,” “tell me”, “how,” “where,” ‘imagine,” “think back”

Develop Interview Guide Using Standard Open–Ended Questions

Create dialogue, encouraging participant to talk

Ask factual before controversial ones Ask demographical questions as required

Last question for additional comments, interview impressions

No leading questions

Develop Interview Guide

Unstructured Open-Ended Interview

Ask one question and allow questions to emerge

Good for initial explorations of topic when not much known

Develop Interview Guide

Closed fixed questions

Participants choose from possible answers

Useful for non-practiced interviewers

Group Exercise 2:

Using the scenarios that you have been given, please identify the following:

1. A specific focus of the research project2. Two primary goals of the research

project3. The method that you would use to

conduct the research

4. Four research / interview questions

Be prepared to present your group’s results to the class

Considerations for Sampling

Exclusion:

Decide if, why, how will exclude certain members who want to be in the study

Collaboration:

Decide norms, decision process, how to make change, procedures to encourage follow principles (e.g., member checks; data collection/analysis personnel)

Data Analysis

The process through which data are organized so that comparisons can be made and conclusions drawn

Analyzing the Data

Manifest Content – the actual ideas that are present and observable in the data

Latent Content – the ideas and themes that emerge as you analyze and interpret the data

Data Analysis: Levels of Exploration

Reference: Hagland, (1997), see also Argyris, C. & SchÖn (1974)

Trends,Patterns

Themes/Structure (Forces/pressures at play)

Need to look below the surface

(Described from Interview)

Events

Group Exercise: Data Collection

Using a copy of the newspaper provided, please conduct a research analysis of the document and explore the following:

What messages does the media provide you about issues of gender? In what way are those messages evidenced? What are the potential benefits and drawbacks of providing those messages?

Record your findings and make notes of your observations and responses – verbal, non-verbal and emotional.

Data Analysis

Coding

a word or short phrase that serves to organize or categorize your data (community; equitable coverage; stereotyping)

Themes

clusters or patterns of codes that thematically ‘hang together’ (positive portrayal of women; equitable portrayal;)

Coding

Coding means going through your data systematically (i.e., read each transcript carefully)

Decide ahead of time how you are going to approach analyzing the data

You get to make up the names for the codes

Remember – not everything is important

Choose what is important to study by going back to your goals & objectives.

Categories

• Codes are grouped to see where patterns occur (observations over time causing event)

• From your exercise, examine both sets of data to see if there are any codes that could be grouped together to form a category

• Tip: look at definitions of codes as well E.g., some codes might be all about “process”

• Try to see if any other categories could be formed

Themes or Structure

After categories are formed ……….. look for themes or structure

(reasons why you might be getting the particular pattern or trend)

Exercise 3: Data Analysis

Using the data you have collected, try to develop a simple ‘coding scheme’ of main ideas (maximum 10 codes)

Pick 1 code to apply: Look for all the times that this idea is mentioned in your data.

Analyze your code: What are the range of experiences here? What patterns/themes do you see here? What does this mean?

Discussion Questions

What are the themes that emerged?

What are the factors that determined the choice of the particular themes?

How did your prior knowledge about the issue impact on the themes that you identified?

How would that knowledge impact on the analysis of the data?

Collaborative Data Analysis

Seeing the world through different eyes – Staff, clients & researchers all come with

different perspectives The more people you involve in developing

your coding scheme – the better.

Different eyes lends credibility to data analysis

Collaborative Data Analysis

Members of the team can examine specific parts of the data

E.g., stratified data: executive interviews by some members; low-income interviews coded by other team members

Some members may code only for a certain period of time due to their availability

Code because of knowledge and expertise of certain member

Code because of lack of knowledge and expertise of certain members

Advocacy

Look for those persistent patterns that block social change

Once you identify the patterns, you can start to do something about them

Analysis

QR and CBR seeks “authenticity” or ‘truthfulness”

Because of research rigor, results are credible, demonstrates authenticity, truthfulness, provides voice

Reference: Lincoln & Guba, 2000

Strategies for Optimizing Validity

Triangulation: - the process of using a variety of data sources and approaches to understanding a problem.

Thick description: Rich, thick descriptions of the participants allow readers to assess ‘transferability’ to other research settings and context.

Member checks: Asking participants to reflect on preliminary analyses and read rough drafts of chapters/reports to ensure accuracy. These “checks” can take place individually or in a group setting.

Clear audit trail: Keeping a complete and accurate record of the steps taken to come to the conclusions. This includes keeping organized notes, a clear and consistent coding scheme and a ‘transparent’ data analysis process in a reflective journal.

What about Software?

PROs: manages large amounts of

data, gives an ‘air’ of legitimacy, makes organization and retrieval easy, provides structure especially for teams not co-located

Helps easily look at various slices of the data

Helps track decisions over time

CONs steep learning curve

(may not be worth it), too much structure, expense

Remember...software manages ...YOU DO

ANALYSIS!

Types of Software

NUDIST- N6 NVivo Atlas.ti SPSS

Dissemination

Approaches for presenting qualitative data effectively

Predefine who your audience will be

How do they receive their communications now?

What will help them hear the message?

Write in a language that is easily understood

Can depict environment in which research took place

Critical Questions to Examine

Who owns the data?

What commitment have you made to share the findings/results with the community?

How do you ensure that the results are accessible to the community?

What role will the community play in dissemination, and any resulting action outcomes?

Presenting Your Data

Describe your methods – tell your audience exactly what it is that you did to come up with your results.

Be descriptive & analytical (so conclusions are accepted)

Use lots of quotes (as evidence, let people see them)

Consider tables, charts, figures, models & diagrams

Contextualize – where does this data come from, who does it apply to (particularity, applicability)...

Speak with confidence about your data

Final Phase

What are the future indications of your research?

Are there other areas that have been highlighted for future research?

Are there any other steps to be taken?

Workshop Reflections

Any surprises?

What are the most important learnings/messages that you will take away from today?

Is there anything that you will plan to do differently?

Learning Objectives

Having completed this workshop you should now be able to:

Describe qualitative research conceptsExplain some of the important terms associated with qualitative

research List misconceptions and limitations of ‘qualitative’ methodsFollow the steps to develop a research projectDifferentiate between Methods, Methodology and ResearchDevelop strategies and skill for gathering and managing 'good' data

(e.g. recording, transcribing, note-taking, qualitative software, etc)

Participate in the analysis of data and develop strategies for coding data

Learn effective approaches for presenting qualitative data 

CBR 302CBR 302A Hands-On Approach to Qualitative Methods A Hands-On Approach to Qualitative Methods

and Analysisand Analysis