1D Qualitative Methods

Question 1

Main methods of qual research

Answer 1

• Semi-structured/in depth interview
• Focus groups
• Observation
• Action research

Question 2

How can qual methods contribute to public health research and policy?

Answer 2

1. Formulating research questions or policy problems
   - Defining an issue
   - Creating contextual understanding
2. Developing methods and tools
   - What to ask in a questionnaire, how it is understand and how to interpret responses
   - This is how surveys are typically developed - qual research, then pilot with feedback, then further refining
3. Evaluating interventions
   - Explaining outcomes: why something did or did not work
   - How an intervention could be improved
   - Understanding unintended consequences

Question 3

Applications of the different qualitative methods

Answer 3

Interviews:
- Exploring accounts of experiences and beliefs

Focus groups
- Exploring shared experiences and beliefs
- Exploring how/if people come to a consensus

Observation:
- Exploring what people actually do (not what they say they do)
- Capturing the familiar/routine to allow things that may be understand to be made explicit

Action research:
- Participants also involved in the research
- Useful for understanding needs and evaluation

Question 4

What are the different types of qualitative analysis?

Answer 4

Grounded theory: you have a theory, data collection feeds into this cyclically until you have theoretical saturation

Thematic (content) analysis: not much is known as a starting point, keep going until you have saturation with no new themes

Framework analysis: developed by National Centre for Social Research, more applied approach, orientated towards policy, with clear aims and research questions - key themes identified early and reflect the policy question as well as emerging from the data

Question 5

How to improve the validity of qualitative analysis?

Answer 5

• Account for deviant data
• Develop a coding structure with other researchers
• Present to interviewees to ensure the material accurately represents what they thought
• Counting responses in themes
• Transparency e.g. provide quotes
• Provided detail info on process of analysis
• Comparing findings to other study methods and to other studies
• Reflexivity re the effect of researchers on the findings

Question 6

What are ethical issues in qualitative research?

Answer 6

1. Cost and time by participants
2. Psychological harm from
   - Disclosing sensitive information
   - Reaction from others

Question 7

How to manage ethical issues in qual research?

Answer 7

Before data collection:
- Ensure benefits outweigh costs
- Conduct literature review to check question has not already been answered
- Be clear about aims of research and participant role
- Obtain informed consent
- Have ground rules for focus groups

After data collection:
- Anonymise data
- Store data securely in line with IG
- Provide contact details so participants can report concerns

Question 8

What are problems that may be encountered in qualitative research and how can these be prevented?

Answer 8

Inadequate sample:
- Start recruitment early
- Remove barriers to participation e.g travel expenses, creche facilities, conduct research near to homes
- Consider interviews rather than focus groups (easier to organise)

Lack of credibility in data:
- For interview: sensitivity choice of location + conduct of interview
- Focus groups: emphasise no wrong answers, involve quieter participants, consider in analysis how/why views were expressed
- Observation (people change behaviour): do not draw attention to oneself, observe over long periods, reflect in analysis on how/why behaviour changes
- Analysis (poor quality): allow time and resources, be transparent about methods

Findings sidelined:
- Ensure timelines match decisions
- Understand policymakers’ agenda from outset
- Tailor finding to audience
- Plan dissemination strategy at the outset

Question 9

What are the strengths and weaknesses of qualitative research?

Answer 9

Strengths
- Depth of data
- Answers complex questions e.g. how/why
- Can generate hypothesis when much is unknown

Limitations
- Lack of generalisability
- Time and labour intensive
- Perceived as less credible by policymakers (may be due to positivist ideas about validity and reliability)