5 Qual data 2

Question 1

Q: What is the primary goal of qualitative data analysis?

Answer 1

A: It is a systematic process of meaning-making, identifying patterns, and describing and interpreting data to understand variations in experiences and consider complexity.

Question 2

Q: What is required from the researcher during qualitative data analysis?

Answer 2

A: Active engagement with the data.

Question 3

Q: What are some complex forms of transcription, and what do they account for?

Answer 3

A: Complex forms, such as the Jefferson system, account for prosody (phonetics), paralinguistics (non-phonemic), and extralinguistic (non-linguistic) aspects.

Question 4

Q: What is content analysis in qualitative research?

Answer 4

A: A method that uses qualitative data to examine patterns in communication in a replicable and systematic manner, allowing for statistical analysis of non-numeric data, though it is not typically considered qualitative.

Question 5

Q: What is grounded theory?

Answer 5

A: A method used to generate theories of social phenomena through systematic data analysis, involving both inductive and deductive stages.

Question 6

Q: What is the focus of discourse/conversation analysis?

Answer 6

A: To identify rules of conversational organization by studying recorded, natural talk-in-interaction to discover how participants understand and respond to one another.

Question 7

Q: What does interpretative phenomenological analysis (IPA) aim to do?

Answer 7

A: To offer insights into how a given person, in a given context, makes sense of a given phenomenon, typically relating to experiences of personal significance, using small homogeneous samples.

Question 8

Q: What is thematic analysis?

Answer 8

A: A method for identifying, analyzing, and reporting patterns within data, organizing and describing it, and interpreting aspects of the research topic.

Question 9

Q: What are some advantages of thematic analysis?

Answer 9

A: It is flexible, easy and quick to learn, accessible to novice researchers, summarizes key features of large data sets, highlights similarities and differences across data sets, generates unanticipated insights, provides social and psychological interpretations of data, and results are accessible to the educated public.

Question 10

Q: What type of analysis is typically inductive but can also be deductive?

Answer 10

A: Qualitative data analysis.

Question 11

Q: What is the first phase of thematic analysis?

Answer 11

A: Data familiarisation, which involves reading and re-reading the data.

Question 12

Q: What is the second phase of thematic analysis?

Answer 12

A: Generating codes by labeling ideas relevant to the research question.

Question 13

Q: What is the third phase of thematic analysis?

Answer 13

A: Searching for themes by grouping related codes into candidate themes.

Question 14

Q: What is the fourth phase of thematic analysis?

Answer 14

A: Reviewing themes to check if they fit the data and address the research question.

Question 15

Q: What is the fifth phase of thematic analysis?

Answer 15

A: Defining and naming themes by describing them and selecting data extracts.

Question 16

Q: What is the sixth phase of thematic analysis?

Answer 16

A: Producing the report or paper.

Question 17

Q: What is important about the orientation phase in thematic analysis?

Answer 17

A: Being clear about assumptions and the theoretical framework, such as using a critical realist perspective that recognizes the socially constructed nature of reality and the role of language in shaping meaning.

Question 18

Q: What approach is typically used in thematic analysis to derive codes and themes?

Answer 18

A: An inductive approach, focusing on the experiences of participants rather than using a pre-defined set of concepts and assumptions.

Question 19

Q: What does familiarisation involve in the context of thematic analysis?

Answer 19

A: Reading and re-reading the data, keeping the research question in mind, making initial notes on first impressions, and aiming for data immersion rather than analysis.

Question 20

Q: What is the temptation to avoid during the familiarisation phase?

Answer 20

A: Rushing to turn initial impressions into themes, which can lead to anecdotal findings.

Question 21

Q: What is coding in qualitative data analysis?

Answer 21

A: Identifying features of the data that appear interesting to the analyst and referring to the most basic segments or elements of the raw data that can be assessed meaningfully regarding the phenomenon.

Question 22

Q: What are 1st order codes in thematic analysis?

Answer 22

A: Descriptive or semantic codes that describe the idea of the data in the researcher’s own words.

Question 23

Q: What are 2nd order codes in thematic analysis?

Answer 23

A: Abstract, latent, or interpretative codes that capture the underlying meaning of an idea in the data.

Question 24

Q: What should be the approach towards coding in thematic analysis?

Answer 24

A: Shifting toward systematic engagement with the data, recognizing that codes don’t simply ‘emerge’ but are created by the researcher based on data and their knowledge and skills.

Question 25

Q: Why might a researcher code and recode data multiple times?

Answer 25

A: Because the researcher’s understanding of the data develops over time, leading to a more plausible and coherent set of codes.

Question 26

Q: What does a theme capture in relation to qualitative research?

Answer 26

A: A theme captures something important about the data in relation to the research question and represents a patterned response or meaning within the data set.

Question 27

Q: What is the central organizing concept of a theme?

Answer 27

A: It is the core idea that brings related codes together into a coherent theme.

Question 28

Q: What is involved in the active, constructive phase of searching for themes?

Answer 28

A: Shaping codes into a coherent story that makes sense of the data by grouping codes into categories or candidate themes.

Question 29

Q: What are candidate themes?

Answer 29

A: Tentative, temporary themes that are refined as the analysis progresses.

Question 30

Q: What questions should be considered when reviewing and writing themes according to Braun et al. (2014)?

Answer 30

A: - Is this candidate theme evident across more than one or two data items, or just a description of specific interviewees?

Does each theme have a centrally organizing concept, or is there overlap between the themes?
Do the themes answer the research question?
Do the themes capture all/most of the codes?
Is there a clear fit between the themes and the data?

Question 31

Q: Why is qualitative analysis considered an iterative process?

Answer 31

A: Because making progress can involve returning to earlier phases of the analysis.

Question 32

Q: What should theme names be according to Braun and Clarke (2012)?

Answer 32

A: Concise, informative, and catchy.

Question 33

Q: How can thematic maps help in the analysis process?

Answer 33

A: They help see the overall structure of the analysis, showing how distinct themes form an overall story.

Question 34

Q: What should theme writing determine?

Answer 34

A: The exact story told by each theme and the overall narrative.

Question 35

Q: What is the purpose of the analytic narrative in theme writing?

Answer 35

A: To tell the reader what the researcher thinks is going on in the data, why it is important for the research question, and why the reader should care.

Question 36

Q: How should data extracts be selected for theme writing?

Answer 36

A: They should provide clear and compelling illustrations of the points demonstrated in the analysis and be drawn from across the data set to provide evidence of a pattern.

Question 37

Q: What must also be provided along with data extracts in theme writing?

Answer 37

A: An interpretation of the data.

Question 38

Q: What is important to do when naming themes?

Answer 38

A: Create names that signal the focus and scope of the theme, aiming to be concise, informative, and catchy.