Related Experiment Video
Updated: Mar 17, 2026

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective
Published on: July 1, 2015
Critical ethnography: An under-used research methodology in neuroscience nursing
Abstract:
Critical ethnography is a qualitative research method that endeavours to explore and understand dominant discourses that are seen as being the 'right' way to think, see, talk about or enact a particular 'action' or situation in society and recommend ways to re-dress social power inequities. In health care, vulnerable populations, including many individuals who have experienced neurological illnesses or injuries that leave them susceptible to the influence of others, would be suitable groups for study using critical ethnography methodology. Critical ethnography has also been used to study workplace culture. While ethnography has been effectively used to underpin other phenomena of interest to neuroscience nurses, only one example of the use of critical ethnography exists in the published literature related to neuroscience nursing. In our "Research Corner" in this issue of the Canadian Journal of Neuroscience Nursing (CJNN) our guest editors, Dr. Cheryl Ross and Dr. Cath Rogers will briefly highlight the origins of qualitative research, ethnography, and critical ethnography and describe how they are used and, as the third author, I will discuss the relevance of critical ethnography findings for neuroscience nurses.
More Related Videos
08:10Neuroimaging Field Methods Using Functional Near Infrared Spectroscopy NIRS Neuroimaging to Study Global Child Development: Rural Sub-Saharan Africa
Published on: February 2, 2018
05:26Enactive Phenomenological Approach to the Trier Social Stress Test: A Mixed Methods Point of View
Published on: January 7, 2019
Related Concept Videos
The Scientific Method in Nursing Process
When using research findings to change practice, one must understand the process used to guide a study. The scientific method is a systematic, step-by-step process that supports the data's validity, reliability, and generalizability. As a result, findings can be...
Naturalistic Observations
Case Studies
Data Collection II