Definition:
Grounded Theory (GT) is a systematic, inductive qualitative research method aimed at developing a theory based on the data itself rather than testing an existing theory. It is widely used in social sciences, healthcare, and education to explore processes, behaviors, and interactions within real-world contexts.
Use GT when:
✅ You want to develop a new theory rather than apply or test an existing one.
✅ Your research question explores social processes, interactions, or patterns of behavior over time.
✅ There is limited existing research on your topic, requiring a fresh conceptual framework.
✅ You need a flexible, iterative approach where data collection and analysis happen simultaneously.
🔹 Examples:
Understanding how nurses adapt to AI in clinical settings.
Exploring how students develop professional identity in healthcare education.
Investigating how patients cope with chronic illness in different social environments.
Unlike traditional methods where analysis happens after data collection, GT follows a constant comparative method, meaning:
You collect data, analyze it, and then adjust your next data collection based on emerging insights.
Early data influences which participants to recruit next and which questions to ask.
Sampling is not pre-determined but evolves based on emerging findings.
New participants or sources are chosen because they help refine the emerging theory.
1️⃣ Open Coding – Identifying key themes, concepts, and patterns within the data.
2️⃣ Axial Coding – Connecting categories and subcategories to form relationships.
3️⃣ Selective Coding – Identifying the core category that ties everything together into a coherent theory.
Example:
Open coding: "Nurses express uncertainty about AI decisions."
Axial coding: "Uncertainty relates to lack of AI transparency and perceived threats to autonomy."
Selective coding: "Trust-building strategies are essential for successful AI adoption in healthcare."
Researchers write memos throughout the research process to track thoughts, insights, and theory development.
This helps avoid forcing data into pre-existing theories and ensures the theory is grounded in actual findings.
There are three main versions of GT, each with subtle differences:
Approach
Key Features
Leading Theorist(s)
Classic Grounded Theory (Glaserian GT)
Theory emerges from data with minimal pre-existing frameworks.
Barney Glaser & Anselm Strauss
Straussian Grounded Theory
More structured, using explicit coding and relationships.
Anselm Strauss & Juliet Corbin
Constructivist Grounded Theory
Emphasizes researcher’s role in theory construction, acknowledging subjectivity.
Kathy Charmaz
Which One Should You Choose?
If you want a purely inductive approach: Classic GT (Glaserian)
If you prefer structured coding and detailed categories: Straussian GT
If you acknowledge your role in shaping the theory: Constructivist GT
✔ Develops new theories in under-researched areas.
✔ Flexible and iterative, allowing data to guide the process.
✔ Captures complex social processes that evolve over time.
✔ Can be applied across disciplines (healthcare, education, business, social sciences).
❌ Time-consuming – Requires continuous data collection and analysis.
❌ Requires skill – Researchers must balance emerging insights without forcing a theory.
❌ Not easily replicable – Theories are highly context-dependent.
❌ Data overload – The iterative approach can lead to vast amounts of data, making synthesis difficult.
Example: How do healthcare professionals integrate AI into their clinical decision-making?
Methods: Interviews, focus groups, observations, documents, etc.
Use theoretical sampling (participants chosen based on emerging themes).
Read transcripts, identify patterns, and label emerging concepts.
Link categories together into a broader framework.
Identify the core category that ties everything together into a theory.
Stop data collection when no new themes emerge.
Use diagrams and conceptual models to illustrate key findings.
Research Question: How do medical professionals develop trust in AI-driven clinical decision-making?
Open Coding:
"Doctors hesitate to trust AI for complex cases."
"AI is seen as useful for routine decision-making."
Axial Coding:
AI trust is shaped by perceived accuracy, peer influence, and regulatory guidelines.
Selective Coding (Emerging Theory):
A theory of 'Trust Calibration' emerges, explaining that AI trust is built through exposure, reliability, and professional endorsement.
This new theory could guide future AI training and policy in healthcare.
Grounded Theory is an excellent approach when:
✔ You want to build theory from real-world data.
✔ You are exploring social processes and interactions.
✔ You need a flexible, iterative approach rather than a fixed hypothesis.
The three key authors for Grounded Theory methodology are:
1️⃣ Barney Glaser & Anselm Strauss – Discovery of Grounded Theory (1967)
They co-developed the original Grounded Theory approach.
Their work emphasized inductive, data-driven theory generation without preconceived hypotheses.
2️⃣ Juliet Corbin & Anselm Strauss – Basics of Qualitative Research (1990, 2015)
They refined Grounded Theory with structured coding (open, axial, and selective coding).
Their version is often called Straussian Grounded Theory and is more systematic than Glaser’s.
3️⃣ Kathy Charmaz – Constructing Grounded Theory (2006, 2014)
Developed Constructivist Grounded Theory, emphasizing researcher subjectivity and social construction of knowledge.
Introduced a more flexible, interpretive approach.
Each of these scholars has shaped Grounded Theory in unique ways—would you like a comparison table summarizing their contributions?