Cited by 472Face Recognition and PerceptionPediatric Pain Management TechniquesPain Mechanisms and Treatments

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The structure, reliability and validity of pain expression: Evidence from patients with shoulder pain

Prkachin, Kenneth M., Solomon, Patricia E.·2008·Pain

DOI 10.1016/j.pain.2008.04.010

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Abstract

The present study examined psychometric properties of facial expressions of pain. A diverse sample of 129 people suffering from shoulder pain underwent a battery of active and passive range-of-motion tests to their affected and unaffected limbs. The same tests were repeated on a second occasion. Participants rated the maximum pain induced by each test on three self-report scales. Facial actions were measured with the Facial Action Coding System. Several facial actions discriminated painful from non-painful movements; however, brow-lowering, orbit tightening, levator contraction and eye closing appeared to constitute a distinct, unitary action. An index of pain expression based on these actions demonstrated test-retest reliability and concurrent validity with self-reports of pain. The findings support the concept of a core pain expression with desirable psychometric properties. They are also consistent with the suggestion of individual differences in pain expressiveness. Reasons for varying reports of relations between pain expression and self-reports in previous studies are discussed.

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Handbook of pain assessment
Williams, A. C. D. C. (1995) · Journal of Psychosomatic Research · doi:10.1016/0022-3999(95)90016-0 · Cited by 1,472
Handbook of emotions, 2nd ed.
Lewis, M. D., Haviland-Jones, J. M., & Barrett, L. F. (2000) · Cited by 1,304
The relationship of gender to pain, pain behavior, and disability in osteoarthritis patients: the role of catastrophizing
Keefe, F. J., Lefebvre, J. C., Egert, J. R., Affleck, G., Sullivan, M. J., & Caldwell, D. S. (2000) · Pain · doi:10.1016/s0304-3959(00)00296-7 · Cited by 735
Facial expression of pain: An evolutionary account
Williams, A. C. D. C. (2002) · Behavioral and Brain Sciences · doi:10.1017/s0140525x02000080 · Cited by 612
Facial Expression Of Emotion
Keltner, D. J., Ekman, P., Gonzaga, G. C., & Beer, J. S. (2002) · doi:10.1093/oso/9780195126013.003.0022 · Cited by 555
The consistency of facial expressions of pain: a comparison across modalities
Prkachin, K. M. (1992) · Pain · doi:10.1016/0304-3959(92)90213-u · Cited by 553
Self-citation
The facial expression of pain in patients with dementia
Miriam Kunz, A., Scharmann, S., Hemmeter, U., Schepelmann, K., & Lautenbacher, S. (2007) · Pain · doi:10.1016/j.pain.2007.09.007 · Cited by 290
Gender Differences in Pain and Pain Behavior: The Role of Catastrophizing
Sullivan, M. J. L., Tripp, D. A., & Santor, D. (2000) · Cognitive Therapy and Research · doi:10.1023/a:1005459110063 · Cited by 285
Handbook of pain assessment, 2nd ed.
Turk, D. C., & Melzack, R. (2001) · Cited by 259
The facial expression of pain.
Craig, K. D., Prkachin, K. M., & GRUNAU, R. E. (2001) · Cited by 259
Self-citation

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Show all 31 references

Research works printed but not linked: 2

Hadjistavropoulos, 1997, Toward a research outcome measure of pain in frail elderly in chronic care., Pain Clinic, 10, 71
Prkachin, 2007, The underestimation of pain among health-care providers., Can J Nurs Res, 39, 88

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Self-citation
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Self-citation
Weakly Supervised Dual Learning for Facial Action Unit Recognition
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Personalized Federated Deep Learning for Pain Estimation From Face ImagesPreprint
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Authors: Prkachin, K. M., & Solomon, P. E.
Affiliations: University of Northern British Columbia (CA)
McMaster University (CA)
Corresponding author: Prkachin, Kenneth M.
ORCID: Solomon, Patricia E.
Venue: Pain
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2008-10-15
Volume: 139
Issue: 2
Pages: 267-274
ISSN: 0304-3959 (ISSN-L)
DOI: 10.1016/j.pain.2008.04.010
OpenAlex: W2106043670
Cited by: 472
References: 31
Citations by year: 2026: 29 · 2025: 27 · 2024: 39 · 2023: 27 · 2022: 29 · 2021: 44 · 2020: 40 · 2019: 37 · 2018: 41 · 2017: 21 · 2016: 33 · 2015: 32 · 2014: 24 · 2013: 16 · 2012: 7
FWCI: 4.32
Type: journal article
Language: en
Open access: closed
Locations: Pain (publishedVersion)
PubMed (publishedVersion)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pediatric Pain Management Techniques
Health Sciences › Medicine › Physiology (medical) › Pain Mechanisms and Treatments
Keywords: pain expression, facial expressions of pain, shoulder pain, facial action units, facial action coding system, test-retest reliability, concurrent validity, self-reported pain, range of motion
MeSH terms: Facial Expression, Female, Humans, Male, Middle Aged, Pain Measurement, Psychometrics, Sensitivity and Specificity, Reproducibility of Results, Expressed Emotion, Evidence-Based Medicine, Shoulder Pain

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The structure, reliability and validity of pain expression: Evidence from patients with shoulder pain

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