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Clinical Research on Dyspnea
Author Bios
What is Dyspnea?
What Provokes Dyspnea?
The Nature of Dyspnea
Language of Dyspnea
Clinical Application
Research Application
Variability in Sensations
Challenges in Study
Mechanical Loads and Sense of Effort
Chemoreceptors
Mechanoreceptors
Neuro-Mechanical Dissociation
Phase of Respiration and Dyspnea
Physiology of Dyspnea
Respiratory System
Cardiovascular System
Measuring Dyspnea
Scaling Issues
Qualitative Aspects
Reliability and Validity Overview
Reliability and Validity
Sensitivity and Specificity
Scales
Sensation vs. Perception vs. Symptom
Treating Dyspnea
Why Measure?
Currently selected section: Cluster Analysis
Statistical vs. Clinical Significance
Standard Error of Measurement
Measuring Fatigue
Measuring Depression
Measuring Anxiety and Hyperventilation
Measuring Quality of Life
Conclusion

 

Chapter 23: Dyspnea: More on Scaling: Cluster Analysis
        

Question 27.2

The linkages near the bottom of the dendogram suggest that ratings of similarity likely varied as a function of:

Selection A number of letters in the words
Selection B typical habitat
Selection Ctype (i.e. class) of animal

A technical problem with uncovering the underlying structure of ratings involves the general lack of criteria for determining the optimum number of clusters (i.e. a stopping rule). Comparisons between cluster solutions obtained in patients and in healthy adults suggest that between 8 and 10 categories of sensory experience serve to adequately differentiate among various states of breathing discomfort.

Figure 27.2 Hierarchical Clustering Solution for Dissimilarity Judgments (n=100) Obtained between Pairs of Descriptors of Breathlessness
Comparisons between cluster solutions obtained in patients and in healthy adults, described in text.
Reprinted by permission of Chest. http://www.chestjournal.org

Work will likely continue to elucidate the precise set of phrases and combinations that best reveal patient experiences of breathing discomfort. Future applications of clustering algorithms to explore not only the sensory but also the affective, evaluative, and temporal characteristics of descriptors may affect the number of clusters in any final solution.

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