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Related Experiment Video

Updated: Jul 14, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

An effort to use qualitative data analysis software for analysing think aloud data.

Katarina E Göransson¹, Anna Ehrenberg, Margareta Ehnfors

¹Department of Health Sciences, Orebro University, Orebro, Sweden. katarina.goransson@karolinska.se

International Journal of Medical Informatics

|June 23, 2007

Summary

This study used qualitative data analysis software to analyze emergency nurses' reasoning during triage. The software helped identify information nurses used for decision-making in emergency triage.

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Last Updated: Jul 14, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

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Published on: December 9, 2022

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

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Published on: April 18, 2017

Area of Science:

Informatics
Nursing Research
Qualitative Research Methodology

Background:

Emergency department triage is a critical decision-making process.
Understanding nurses' reasoning during triage is essential for improving patient care.
Qualitative methods, like think-aloud protocols, can provide in-depth insights into complex cognitive processes.

Purpose of the Study:

To describe the application of qualitative data analysis software (QSR NVivo) in supporting a three-step protocol analysis.
To examine emergency nurses' reasoning processes during triage using think-aloud data.
To guide future informatics research employing similar methodologies.

Main Methods:

Employed a three-step protocol analysis of think-aloud data.
Utilized QSR NVivo software for managing and analyzing qualitative data.
Collected data from 16 triage nurses to identify information focus and decision-making structures.

Main Results:

QSR NVivo facilitated the identification of key information utilized by nurses during triage.
The software aided in describing how nurses structured this information to arrive at triage decisions.
The study successfully managed and supported the protocol analysis of complex think-aloud data.

Conclusions:

Qualitative data analysis software, specifically QSR NVivo, can effectively support protocol analysis of think-aloud data in nursing research.
Detailed methodological descriptions can guide future informatics research in similar domains.
The study provides insights into the cognitive processes of emergency nurses during triage.