D o 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 ID: 710036
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What Can Qualitative Software Do for My Research?November 5, 2013APHA ConferenceSlide2
Outline of SessionOverall Goal: Understand how qualitative data analysis software can improve the rigor of your public health researchShort introduction to qualitative analysis and computer-assisted qualitative data analysis software (CAQDAS)Introduction to coding and coding exercise
NVivo demonstration and explorationSlide3
A Brief History of CAQDAS1981: Lyn and Tom Richards develop NUD*IST, the precursor to NVivo1994: Miles and Huberman discuss the use of software in qualitative analysis in their widely cited text2007: 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 todayToday at APHA 2013: Over 30 presentations mention using
NVivo in their abstracts (see handout)Slide4
How can Software Help Improve the Rigor of Qualitative Analysis?
X
Y
Z
Transparency
Saturation
MethodologySlide5
Considerations in Choosing to Use SoftwareSample size and multiplicity of data sourcesEmphasis on replicability, rigor and transparencyLikelihood that there will be future opportunities to perform secondary analyses on the same datasetDesire to publish in peer-reviewed journals
Interest in merging close-ended attributes into the qualitative datasetBuilding capacity of analysis team including training time and costsBudgetary parameters and software investmentSlide6
Promoting Reliability and Validity in AnalysisDocument the process of analysis including what is the statement of a respondent and what is interpretation by a researcherInvolve 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 well-defined themes. Refine again and again.
In analysis, check inter-rater reliabilityDevelop conventions for transcribing data so that transcripts are comparable across data source
Develop saturation guidelinesSlide7
Future Directions in Qualitative AnalysisMixed methods tools, such as the capacity to work with datasets containing both fixed response and open-ended materialWeb-based data, including social media and online discussion boardsCapacity for larger samples, especially large quantities of text (qualitative studies are no longer small)More tools for comparing coding by researcher, theme, and participant groupSlide8
A Future Look at Mixed Methods with NVivo
Descriptive Statistics
Inferential Statistics
Meta-Analysis
Coding of Text
Audio,
Video and
Image Data
Open-Ended Survey and Interview Responses
Transcribing tools for Audio and
Video
Import/Export from Excel, text and database files
Open-Ended and Fixed Response Questions
Within and Between Group Analysis of Coding
Text Analysis
Kappa Coefficient
Cluster Analysis of Word and Coding
Similarity
Qualitative
Quantitative
NVivoSlide9
Coding ExerciseSlide10
Brief Coding Exercise: PurposeWe will code a short transcript manuallyGiven the short timeframe we will not do this thoroughlyWe will talk about what we found and how we might begin to refine our codesWe will discuss how we would use qualitative software to accomplish the same stepsSlide11
CodingAny 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)Slide12
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)Slide13
EXAMPLE: Focus Group on Treating Chronic Fatigue PatientsPhysician Participant“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.”CodeTrends in Diagnoses OR
Physician training ORChronic fatigue syndrome familiaritySlide14
Coding processInitial codes will be defined, redefined, collapsed as more and more data are codedAnalysts will develop definitions, inclusion and exclusion criteria for each codeSlide15
Analysis of Codes/ThemesCodes/themes are analyzed for patterns, e.g. frequency, similarity and differences across respondent types, meaning, sequence, associations with other codes, causation, etc.Slide16
Brief Coding Exercise - InstructionsRead the interview with Thomas – 10 minutesRemember 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 minutesSlide17
Brief Coding Exercise – ThemesWhat themes did you come up with?Slide18
Brief Coding Exercise – DiscussionWhat 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?Slide19
Brief Coding Exercise – SummaryWhat works manually with a small amount of qualitative research becomes more complicated as the number of qualitative sources increaseDefining, redefining, merging, and separating codes is easier to do and easier to keep track of with qualitative softwareDocumenting the analysis process systematically is a benefit of the software; replicability is possibleSlide20
NVivo
Demonstration and ExplorationSlide21
Let’s explore NVivo in practice
How does NVivo
store data?Sources
may be text, audio, video, pictures, categorical or social media dataHow do I code in NVivo
?Select data and assign to one or more
NodesHow 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.Slide22
Systematic, Rigorous, QuickIncrease accessibility of data and transparency of analysis
Node content, memos, annotations, coding stripes, event log
Identify and test ideas about emerging patterns and themesText Search Query, Matrix Coding Query
Utilize open-ended text and non-text dataTranscripts, audio, video, pictures, survey and other categorical data, social media
Generate output for reporting
Query results, node exports, visualizations
Support team-based analysis
View team members’ coding, calculate Kappa coefficientSlide23
Utilizing Non-text DataClassification (First Cell)
PersonGenderAge RangeYears in Down East
Primary ResidenceBarbaraFemale40-4940
YesCharlesMale60-6972
YesDorthyFemale
20-3940Yes
HelenMale70-79
N/AYes
Attributes (First Row)
Nodes (First Column
)Slide24
Questions and Comments?