Making Sense of Qualitative Data Together
Eligibility Criteria
This programme is open to people and organisations based in the North East and North Cumbria, as well as those from the following organisations:
- NIHR Biomedical Research Centre (BRC)
- NIHR Applied Research Collaboration (ARC)
- NIHR Innovation Observatory (IO)
- NIHR Research Support Service (RSS)
- NIHR Policy Research Unit (PRU)
- NIHR Research Delivery Network (RDN)
- NIHR HRC in Diagnostic and Technology Evaluation (HRC)
Course Description
This session explores how patient and public involvement and engagement (PPIE) can enhance the analysis and interpretation of research data. Co-delivered by a public contributor experienced in co-producing research, the session begins with a case study of a co-produced meta-synthesis of qualitative literature. This example highlights the involvement of lay contributors across two different analytical methods—framework analysis (deductive, i.e., theory-driven) and meta-ethnography (inductive, i.e., data-driven)—and showcases the training and adaptations used to make these methods more accessible.
Participants will then take part in a hands-on exercise, where they will:
- Apply both inductive and deductive analytical approaches to a short qualitative text.
- Reflect on their perspectives and expertise in shaping interpretation.
To close, participants will discuss which stakeholders should be involved in analysis, and what adaptations may support more inclusive and meaningful involvement.
No prior experience in qualitative analysis is required.
Learning Outcomes
By the end of this session, participants will be able to:
- Understand how public contributors can be meaningfully involved in the analysis and interpretation of qualitative research data.
- Apply and compare inductive and deductive analysis methods to a qualitative text and reflect on differing perspectives.
- Inclusion of diverse stakeholders in research analysis and interpretation.
- Identify key challenges and solutions in the inclusion of lay people in the analysis and interpretation of research data.
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