Exploring the Application of Grounded Theory: A Systematic Review of Methodological Approaches
Year: 2024
Type: review
Study design: Systematic Review
Abstract: Grounded Theory (GT) has become a fundamental Qualitative research methodology for developing theories from empirical data. However, its application varies across disciplines, leading to methodological inconsistencies and debates regarding rigor, coding techniques, and researcher subjectivity. This systematic review examines methodological approaches in GT research, analyzing their implementation, strengths, challenges, and emerging trends. Following PRISMA guidelines, relevant studies were selected from academic databases, and a thematic synthesis was conducted to identify methodological patterns. The review highlights the prevalence of Classical, Straussian, and Constructivist GT approaches, each differing in coding strategies, theoretical sampling, and researcher involvement. Findings indicate that GT is widely used in sociology, psychology, healthcare, and software engineering, demonstrating its adaptability across diverse fields. Key strengths of GT include its iterative data collection process and deep contextual grounding, while challenges involve coding complexity, inter-rater reliability, and researcher bias. Emerging trends suggest increasing integration of GT with technological tools, such as Qualitative data analysis software and AI-assisted coding. Additionally, mixed-methods GT approaches are gaining traction to enhance theoretical robustness. This review underscores the need for standardized methodological guidelines to ensure consistency and rigor in GT studies. Future research should explore the intersection of GT with digital advancements and interdisciplinary applications to strengthen its methodological integrity. By synthesizing best practices and identifying methodological gaps, this study provides valuable insights for researchers seeking to apply GT effectively in Qualitative inquiry.
Author: David P Pascua Jr
Institution: Isabela State University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4407845271