Applied Mathematics

Volume 5, Issue 11 (June 2014)

ISSN Print: 2152-7385   ISSN Online: 2152-7393

Google-based Impact Factor: 0.96  Citations  

Sub-Grouping Healthy Subjects’ Sensitivity to Pain and Its Relationship to Personality Traits: Results of a Cluster Analysis

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DOI: 10.4236/am.2014.511163    3,143 Downloads   4,281 Views  Citations

ABSTRACT

Objective: Individual differences in the sensitivity to pain and the factors that may contribute to these differences are well studied. Nevertheless, there is no single test that can reliably classify subjects as being sensitive or insensitive to pain. Methods: In the present study, hierarchical clustering and K-means cluster analysis was used to identify subgroups among 191 healthy subjects (105 females, 86 males) according to their sensitivity to pain. Group determination was based on the subjects’ response to experimental noxious stimuli of heat (pain intensity), cold (cold pain threshold, tolerance, and intensity), and conditioned pain modulation (CPM, tested by co-administering repeated short painful heat stimuli and a conditioning tonic cold pain stimulation). In addition, in order to determine if the subjects in these subgroups differed on personality traits scores on Cloninger’s Tridimensional Personality Questionnaire (TPQ, outcome measure) for the three dimensions of personality: Novelty Seeking (NS); Harm Avoidance (HA); and Reward Dependence (RD) were calculated. Results: Based on pain scores, subjects were grouped as low pain (57%) with a low level of sensitivity in pain parameters, or high pain (43%) cluster members. The high pain had significant higher scores of HA (p = 0.05) and RD (p = 0.05) than the low pain group. Conclusions: This method of sub-grouping may be useful for identifying the mechanisms underlying individual variability in the sensitivity to pain and may point to groups at risk for experiencing high levels of clinical pain.

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Pud, D. , Treister, R. and Eisenberg, E. (2014) Sub-Grouping Healthy Subjects’ Sensitivity to Pain and Its Relationship to Personality Traits: Results of a Cluster Analysis. Applied Mathematics, 5, 1705-1712. doi: 10.4236/am.2014.511163.

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