Literature DB >> 16298065

Characterizing individual differences in heat-pain sensitivity.

Christopher S Nielsen1, Donald D Price, Olav Vassend, Audun Stubhaug, Jennifer R Harris.   

Abstract

Heat induced pain has been shown to follow a positively accelerating power function for groups of subjects, yet the extent to which this applies to individual subjects is unknown. Statistical methods were developed for assessing the goodness of fit and reliability of the power function for data from individual subjects with the aim of using such functions for characterizing individual differences in heat-pain sensitivity. 175 subjects rated ascending and random series of contact heat stimuli with visual analogue scales for pain intensity (VAS-I) and unpleasantness (VAS-A). Curve fitting showed excellent model fit. Substitution of model estimates in place of observed VAS scores produced minimal bias in group means, about 0.3 VAS units in the ascending series and 1.0 in the random series, on a 0-100 scale. Individual power function exponents were considerably higher for the ascending than for the random series and somewhat higher for VAS-A than for VAS-I (means: ascending VAS-I=9.04, VAS-A=9.80; random VAS-I=4.95, VAS-A=5.67). The reliability of VAS estimates was high (>==.93), and for the ascending series it remained so when extrapolating 4 degrees C beyond the empirical range. Exponent reliability was high for the ascending series (VAS-I=.92; VAS-A=.91), but considerably lower for the random series (VAS-I=.69; VAS-A=.71). Individual differences constituted 60% of the total variance in pain ratings, whereas stimulus temperature accounted for only 40%. This finding underscores the importance of taking individual differences into account when performing pain studies.

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Year:  2005        PMID: 16298065     DOI: 10.1016/j.pain.2005.09.018

Source DB:  PubMed          Journal:  Pain        ISSN: 0304-3959            Impact factor:   6.961


  24 in total

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Authors:  Jeff Boissoneault; Landrew Sevel; Janelle Letzen; Michael Robinson; Roland Staud
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2.  Parsing pain perception between nociceptive representation and magnitude estimation.

Authors:  M N Baliki; P Y Geha; A V Apkarian
Journal:  J Neurophysiol       Date:  2008-12-10       Impact factor: 2.714

3.  Clinical and evoked pain, personality traits, and emotional states: can familial confounding explain the associations?

Authors:  Eric Strachan; Brian Poeschla; Elizabeth Dansie; Annemarie Succop; Laura Chopko; Niloofar Afari
Journal:  J Psychosom Res       Date:  2014-10-02       Impact factor: 3.006

Review 4.  Genetic basis of pain variability: recent advances.

Authors:  Erin E Young; William R Lariviere; Inna Belfer
Journal:  J Med Genet       Date:  2011-11-05       Impact factor: 6.318

5.  Psychological and sensory predictors of experimental thermal pain: a multifactorial model.

Authors:  Christopher J Starr; Timothy T Houle; Robert C Coghill
Journal:  J Pain       Date:  2010-06-08       Impact factor: 5.820

6.  Selective conversion of fibroblasts into peripheral sensory neurons.

Authors:  Joel W Blanchard; Kevin T Eade; Attila Szűcs; Valentina Lo Sardo; Rachel K Tsunemoto; Daniel Williams; Pietro Paolo Sanna; Kristin K Baldwin
Journal:  Nat Neurosci       Date:  2014-11-24       Impact factor: 24.884

7.  Do past pain events systematically impact pain ratings of healthy subjects or fibromyalgia patients?

Authors:  Roland Staud; Michael E Robinson; Donald D Price
Journal:  J Pain       Date:  2009-09-26       Impact factor: 5.820

8.  Tracking local anesthetic effects using a novel perceptual reference approach.

Authors:  Dominik A Ettlin; Nenad Lukic; Jetmir Abazi; Sonja Widmayer; Michael L Meier
Journal:  J Neurophysiol       Date:  2016-01-20       Impact factor: 2.714

Review 9.  Progress in genetic studies of pain and analgesia.

Authors:  Michael L Lacroix-Fralish; Jeffrey S Mogil
Journal:  Annu Rev Pharmacol Toxicol       Date:  2009       Impact factor: 13.820

10.  Ethnicity and OPRM variant independently predict pain perception and patient-controlled analgesia usage for post-operative pain.

Authors:  Ene-choo Tan; Eileen C P Lim; Yik-ying Teo; Yvonne Lim; Hai-yang Law; Alex T Sia
Journal:  Mol Pain       Date:  2009-06-23       Impact factor: 3.395

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