Stability analysis of clustering of Norris' visual analogue scale: Applying the consensus clustering approach.

Zheng Guan, X Gregory Chen, Justin Hay, Joop van Gerven, Jacobus Burggraaf, Marieke de Kam
Author Information
  1. Zheng Guan: Centre for Human Drug Research.
  2. X Gregory Chen: Leiden University Medical Center, The Netherlands.
  3. Justin Hay: Centre for Human Drug Research.
  4. Joop van Gerven: Centre for Human Drug Research.
  5. Jacobus Burggraaf: Centre for Human Drug Research.
  6. Marieke de Kam: Centre for Human Drug Research.

Abstract

ABSTRACT: Visual analogue scales are widely used to measure subjective responses. Norris' 16 visual analogue scales (N_VAS) measure subjective feelings of alertness and mood. Up to now, different scientists have clustered items of N_VAS into different ways and Bond and Lader's way has been the most frequently used in clinical research. However, there are concerns about the stability of this clustering over different subject samples and different drug classes. The aim of this study was to test whether Bond and Lader's clustering was stable in terms of subject samples and drug effects. Alternative clustering of N_VAS was tested.Data from studies with 3 types of drugs: cannabinoid receptor agonist (delta-9-tetrahydrocannabinol [THC]), muscarinic antagonist (scopolamine), and benzodiazepines (midazolam and lorazepam), collected between 2005 and 2012, were used for this analysis. Exploratory factor analysis (EFA) was used to test the clustering algorithm of Bond and Lader. Consensus clustering was performed to test the stability of clustering results over samples and over different drug types. Stability analysis was performed using a three-cluster assumption, and then on other alternative assumptions.Heat maps of the consensus matrix (CM) and density plots showed instability of the three-cluster hypothesis and suggested instability over the 3 drug classes. Two- and four-cluster hypothesis were also tested. Heat maps of the CM and density plots suggested that the two-cluster assumption was superior.In summary, the two-cluster assumption leads to a provably stable outcome over samples and the 3 drug types based on the data used.

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MeSH Term

Adult
Algorithms
Benzodiazepines
Cannabinoid Receptor Agonists
Cluster Analysis
Consensus
Cross-Over Studies
Data Interpretation, Statistical
Datasets as Topic
Double-Blind Method
Factor Analysis, Statistical
Humans
Male
Muscarinic Antagonists
Pain Measurement
Randomized Controlled Trials as Topic
Reproducibility of Results
Visual Analog Scale

Chemicals

Cannabinoid Receptor Agonists
Muscarinic Antagonists
Benzodiazepines

Word Cloud

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