What Can
Qualitative Software
Do for My
Research?
November 5, 2013
APHA Conference
Outline of Session
 Overall Goal: Understand how qualitative data
analysis software can improve the rigor of your public
health research
 Short introduction to qualitative analysis and
computer-assisted qualitative data analysis software
(CAQDAS)
 Introduction to coding and coding exercise
 NVivo demonstration and exploration
Abt Associates | pg 2
A Brief History of CAQDAS
 1981: Lyn and Tom Richards develop NUD*IST, the
precursor to NVivo
 1994: Miles and Huberman discuss the use of software in
qualitative analysis in their widely cited text
 2007: National Science Foundation publishes guidelines
for the use of software in qualitative data analysis
 2013: NVivo, AtlasTi, EZ-Text, ANSWR, MaxQDA,
HyperResearch and Dedoose are among the most
commonly used tools today
 Today at APHA 2013: Over 30 presentations mention
using NVivo in their abstracts (see handout)
Abt Associates | pg 3
How can Software Help Improve the
Rigor of Qualitative Analysis?
Methodology
GATHER
ORGANIZE
Existing Research
Data Sources
Coding Structure
Demographics
Literature Review
Current Information
Data Sources
ANALYZE
Coding
Queries
Memos
Visuals
VISUALIZE
RESULTS
Reports
Journal Articles
Dissertations
Study
Presentations
• Transparency
• Saturation
Abt Associates | pg 4
Considerations in Choosing
to Use Software
 Sample size and multiplicity of data sources
 Emphasis on replicability, rigor and transparency
 Likelihood that there will be future opportunities to
perform secondary analyses on the same dataset
 Desire to publish in peer-reviewed journals
 Interest in merging close-ended attributes into the
qualitative dataset
 Building capacity of analysis team including training
time and costs
 Budgetary parameters and software investment
Abt Associates | pg 5
Promoting Reliability and Validity
in Analysis
 Document the process of analysis including what is the
statement of a respondent and what is interpretation by a
researcher
 Involve multiple analysts to check biases
 Document in detail the process by which analytical themes or
codes are developed
 Train coders or analysts on coding structure and create welldefined themes. Refine again and again.
 In analysis, check inter-rater reliability
 Develop conventions for transcribing data so that transcripts are
comparable across data source
 Develop saturation guidelines
Abt Associates | pg 6
Future Directions in Qualitative
Analysis
 Mixed methods tools, such as the capacity to work
with datasets containing both fixed response and
open-ended material
 Web-based data, including social media and online
discussion boards
 Capacity for larger samples, especially large
quantities of text (qualitative studies are no longer
small)
 More tools for comparing coding by researcher,
theme, and participant group
Abt Associates | pg 7
A Future Look at Mixed Methods
with NVivo
Qualitative
Coding of Text
Audio, Video and
Image Data
Open-Ended Survey
and Interview
Responses
Transcribing tools
for Audio and Video
NVivo
Quantitative
Import/Export from
Excel, text and database
files
Open-Ended and Fixed
Response Questions
Within and Between
Group Analysis of Coding
Text Analysis
Descriptive
Statistics
Inferential
Statistics
Meta-Analysis
Kappa Coefficient
Cluster Analysis of Word
and Coding Similarity
Abt Associates | pg 8
Coding
Exercise
Abt Associates | pg 9
Brief Coding Exercise: Purpose
 We will code a short transcript manually
– Given the short timeframe we will not do this thoroughly
 We will talk about what we found and how we might
begin to refine our codes
 We will discuss how we would use qualitative
software to accomplish the same steps
Abt Associates | pg 10
Coding
Any researcher who wishes to become proficient at
doing qualitative analysis must learn to code well and
easily. The excellence of the research rests in large
part on the excellence of the coding.
(Anselm L. Strauss, Qualitative Analysis for Social
Scientists, 1987, p. 27)
Abt Associates | pg 11
What is Coding?
 Codes are short words or phrases that symbolize the
essence of a piece of text, visual image, or other
qualitative data.
 Codes reduce a large quantity of data into more
manageable “themes.”
 Interpret qualitative data into meaningful themes
(meaningful depends on the lens of the analyst)
Abt Associates | pg 12
EXAMPLE: Focus Group on Treating
Chronic Fatigue Patients
Physician Participant
Code
“There are also trends over times.
When I was in training, everybody
who we now consider chronic fatigue
or even chronic fibromyalgia was
largely looked into a group that they
called the hypochondriacal patients.
Now you hardly ever hear the
diagnosis hypochondriasis anymore.”

Trends in Diagnoses OR

Physician training OR

Chronic fatigue syndrome
familiarity
Abt Associates | pg 13
Coding process
 Initial codes will be defined, redefined, collapsed as
more and more data are coded
 Analysts will develop definitions, inclusion and
exclusion criteria for each code
Abt Associates | pg 14
Analysis of Codes/Themes
 Codes/themes are analyzed for patterns, e.g.
– frequency,
– similarity and differences across respondent types,
– meaning,
– sequence,
– associations with other codes,
– causation, etc.
Abt Associates | pg 15
Brief Coding Exercise - Instructions
 Read the interview with Thomas – 10 minutes
 Remember the purpose of the research. (Description
in packet.)
 Look for themes. Put parentheses around the text
and write the word/phrase that summarizes the text
next to it.
 Note questions or ideas that occur to you as you
read the interview.
 Report out and discussion – 10 minutes
Abt Associates | pg 16
Brief Coding Exercise – Themes
What themes did you come up with?
Abt Associates | pg 17
Brief Coding Exercise – Discussion
 What codes are similar to each other?
 How will we capture the changing definitions over
time?
 How will we merge codes?
 How will we assess inter-rater reliability?
 What questions or comments occurred to you as you
read the interview?
Abt Associates | pg 18
Brief Coding Exercise – Summary
 What works manually with a small amount of
qualitative research becomes more complicated as
the number of qualitative sources increase
 Defining, redefining, merging, and separating codes
is easier to do and easier to keep track of with
qualitative software
 Documenting the analysis process systematically is a
benefit of the software; replicability is possible
Abt Associates | pg 19
NVivo
Demonstration
and
Exploration
Abt Associates | pg 20
Let’s explore NVivo in practice
How does NVivo store data?
Sources may be text, audio, video, pictures,
categorical or social media data
How do I code in NVivo?
Select data and assign to one or more
Nodes
How can I see my coding in NVivo?
Turn on Coding Stripes, and open Nodes
Isn’t there more the software can
do?
Text Search and Word Frequency Queries
can help you code.
Matrix Coding Queries can reveal patterns
within and across themes or groups of
participants.
Abt Associates | pg 21
Systematic, Rigorous, Quick

Increase accessibility of data and transparency of analysis
o Node content, memos, annotations, coding stripes, event log

Identify and test ideas about emerging patterns and themes
o Text Search Query, Matrix Coding Query

Utilize open-ended text and non-text data
o Transcripts, audio, video, pictures, survey and other categorical data,
social media

Generate output for reporting
o Query results, node exports, visualizations

Support team-based analysis
o View team members’ coding, calculate Kappa coefficient
Abt Associates | pg 22
Utilizing Non-text Data
Classification
Attributes (First Row)
(First Cell)
Nodes
(First
Column)
Person
Gender
Age Range
Years in
Down East
Primary
Residence
Barbara
Female
40-49
40
Yes
Charles
Male
60-69
72
Yes
Dorthy
Female
20-39
40
Yes
Helen
Male
70-79
N/A
Yes
Abt Associates | pg 23
Questions and
Comments?
Abt Associates | pg 24
Contact Information
 Lisa LeRoy, MBA, PhD
Lisa_leroy@abtassoc.com
617-349-2723
 Ilana Ron, MSc
Ilana_ron@abtassoc.com
301-347-5339
 Cynthia Jacobs, EdD
C.Jacobs@qsrinternational.com
617-491-1850
Abt Associates | pg 25