Related Experiment Video
Updated: May 13, 2025

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences
Published on: September 4, 2019
The Art of Analysis: Crafting Credible and Authentic Qualitative Results
Adrianna Watson1, Debra Jackson2
1College of Nursing, Brigham Young University, Provo, Utah, USA.
Introduction:
Qualitative research offers unparalleled insights into complex human experiences. The rigour of qualitative data analysis is critical to ensuring credible and actionable findings.
Background:
Different qualitative methodologies offer unique lenses to explore human experiences. However, challenges such as context dependency and potential biases necessitate alignment between research aims, analytical strategies and ethical practices to preserve participant voices and ensure methodological rigour.
Data Sources:
This narrative review synthesises foundational qualitative methodologies and recent research, offering practical strategies to address challenges in data analysis within nursing and health-related research.
Discussion:
Robust qualitative analysis requires clear analytical aims, reflexivity and ethical integrity. We explore common pitfalls, such as superficial analyses and a lack of transparency, while emphasising the role of rigorous methodologies in ensuring validity, reliability and meaningful findings.
Implications For Nursing:
Rigour in qualitative analysis transforms research into actionable insights, informing culturally sensitive care, evidence-based interventions and nursing education. High-quality analysis strengthens the discipline and improves patient outcomes.
Conclusion:
Qualitative research demands meticulous and ethical analysis to unlock its full potential. Nurse researchers can deliver findings that drive impactful change in healthcare practice and policy by prioritising analytical rigour and transparency.
Patient Or Public Contribution:
No Patient or Public Contribution.
Related Concept Videos
Qualitative Analysis
There are two main approaches to qualitative analysis:...
Statistical Significance
Quality Control
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
Statistical Analysis: Overview
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
Data Validation
Key parameters for method validation include:
Naturalistic Observations

