TY - JOUR
T1 - Sub-grouping healthy subjects’ sensitivity to pain and its relationship to personality traits: results of a cluster analysis
AU - Pud, Dorit
AU - Treister, Roi
AU - Eisenberg, Elon
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
U2 - 10.4236/am.2014.511163
DO - 10.4236/am.2014.511163
M3 - Article
SN - 1005-1031
VL - 5
JO - Applied Mathematics
JF - Applied Mathematics
IS - 11
ER -