Analysis of qualitative data

1. Analysis of qualitative data India FETP

2. Competency to be gained from this lecture Appreciate the complexity of the analysis of qualitative data

3. Outline • Principle of analysis of qualitative data • Analysis of focus groups • Enhancing the quality of the analysis • Writing the report

4. The interpretative nature of qualitative research • Critical issues • Self-as-instrument for data collection, analysis and reporting • Lack of guidelines for data analysis • Possible answers • Document biases, feelings and personal experience of the investigator • Explicit descriptions attesting the fidelity of implementation of recommended procedures Analysis principles

5. Main pitfall in qualitative data analysis • Temptation • Impressions on the basis of the initial review of notes and tapes • Quick move to written summary • Blur the distinction between • What was observed, heard or read (raw data) • Patterns and theme discerned (Interpretation ) Analysis principles

6. Activities in qualitative data analysis • Data reduction • Selecting, focusing, simplifying, abstracting and transforming data • Data display • Presenting data in an organized manner to help understand what is occurring • Conclusion drawing and verification • Noting regularities, patterns, explanations tested for plausibility, robustness and validity Analysis principles

7. Qualitative analysis plan • Lists research questions • Indicates which data collection technique provided relevant information Analysis principles

8. Example of a qualitative analysis plan Analysis principles

9. Focus group analysis • Overview of group data • Content analysis • Deviant case analysis Focus group analysis

10. Overview of group data • Table format • List the proportion of groups raising a subject or concern • Should not be mistaken for a quantitative analysis • Does not capture how much an issue was stressed • Does not specify the context • More in-depth analysis is needed Focus group analysis

11. Summarized overview of group data for FETP focus groups

12. Techniques in content analysis • Transcript analysis with coding • Group analysis with synthetic table Focus group analysis

13. Transcript analysis with coding • Reading of the notes / transcripts • Issues colour or letter coded • Notes or colours flag issues in the transcript • Blue, red, green • A, B, C • Sub-categories possible: A1, A2 etc… Focus group analysis

14. Group analysis with synthetic table • Use of a table format • Lines: • List of groups • Columns • Issues • Filling the table: • Summary of the conclusion of the interview • Meaning and intention of respondents Focus group analysis

15. Summarized example of table content analysis for FETP focus groups Focus group analysis

16. Advantage of synthetic table • Systematic • Stimulates collective discussion • Fast • Facilitates • Syntheses • Conclusions Focus group analysis

17. Reviewing content • Identify similarities • Spot differences • Find the causes for similarities and differences • Interpret in relation to the objectives of the study Focus group analysis

18. Ethnographic summary • Repeated open minded readings of the transcripts • Search for underlying meaning of emergent themes • Beyond count of occurrences Focus group analysis

19. Deviant case analysis • Identify deviants • Positive • Negative • Conduct in-depth interview Focus group analysis

20. Stages of use Note taking Transcribing Coding Content analyzing Data display Report writing Types of packages Text retrievers Textbase managers Code retrieve programmes Code base theory builders Conceptual network builders Computer software for qualitative data analysis Focus group analysis

21. Strengths Speed up tasks Allow more complex tasks Allow consistency and comprehensiveness Weaknesses Do not conduct the qualitative analysis Cannot be a substitute for training of the investigator Require new learning Pro and cons of qualitative data analysis computer software Focus group analysis

22. Enhancing the quality of the analysis • Testing rival explanations • Examining negative cases • May broaden, change or cast doubts on the rule • Triangulation Quality of analysis

23. Triangulation • Term taken from land surveying • No single method adequately solves the problem of rival explanations • Guard against systematic biases • Several triangulations • Methods • Sources • Analyst • Theory Quality of analysis

24. Triangulation of methods • Compare data collected using different methods • Qualitative • Quantitative • Focus on what is learned by the degree of convergence • Form of comparative analysis Quality of analysis

25. Triangulation of data sources • Possible sources of data to compare • Observations with interviews • What is said in public and in private • What is said over time • Perspective of different persons • Doctors, nurses, patients • The point is to understand the difference, not to achieve convergence Quality of analysis

26. Triangulation of analysts • Uses multiple observers / analysts • Use those who were studied to review the findings • Control for: • Selective perception • Interpretative bias Quality of analysis

27. Triangulation of theories • Use different interpretation framework: • Behaviours • Psycho-analytical • Understand how findings are affected by different: • Assumptions • Fundamental premises Quality of analysis

28. Adapting the report to the audience • Identify audiences • Health planners • Policy makers • Media • Funders • Population • Tailor the format of the report to the action you expect Report

29. The report • Concise • Summarizes main conclusions • Highlights differences and similarities • Contains examples and quotes • Addresses the objectives of the research • Includes an executive summary • Recommendations: • Identifies areas for further research • Spells out action points Report

30. Take home message • Systematic approaches may help address the subjective nature of qualitative data analysis • Code, display and formulate conclusions • Triangulate to check hypotheses • Adapt the report to the various audiences to promote recommendations