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Staying theoretically sensitive when conducting grounded theory research.

Gudrun Reay1, Shelley Raffin Bouchal2, James A Rankin2

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Summary
This summary is machine-generated.

Grounded theory (GT) research emphasizes theoretical sensitivity, requiring researchers to remain open to data and avoid preconceptions. This approach facilitates the discovery of new theories by embracing emergence and constant comparison.

Keywords:
epistemologygrounded theorynurse researcherontologytheoretical sensitivitytheory developmenttriage

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Area of Science:

  • Social Sciences
  • Qualitative Research Methods

Background:

  • Grounded theory (GT) aims to discover and conceptualize underlying social patterns into theories.
  • Theoretical sensitivity is crucial for GT, requiring researchers to enter the field without preconceptions to remain open to data and emerging theories.
  • Understanding GT's historical context and epistemological foundations is key to grasping theoretical sensitivity.

Purpose of the Study:

  • To explore the concept of theoretical sensitivity within classical Grounded Theory.
  • To discuss the ontological and epistemological underpinnings of Grounded Theory.
  • To illustrate challenges and best practices for maintaining theoretical sensitivity in research.

Main Methods:

  • Exploration of classical Grounded Theory principles.
  • Discussion of theoretical sensitivity as a core methodological concept.
  • Analysis of research challenges, including maintaining openness to data and emergence.

Main Results:

  • Theoretical sensitivity is an underlying principle guiding GT research.
  • Adherence to GT methods, including theoretical sensitivity, aids in theory discovery.
  • Key GT concepts like delaying literature review, emergence, and constant comparative method are linked to theoretical sensitivity.

Conclusions:

  • Understanding theoretical sensitivity enhances comprehension of core GT concepts.
  • Theoretical sensitivity enables researchers to discover theories that bridge the gap between theory and practice.
  • Embracing emergence and constant data comparison are vital for effective GT research.