Ontogeny and phylogeny of facial expression of pain
Notice bibliographique
Résumé
1. Background Facial expression of pain offers an important opportunity for better understanding, assessing, and managing pain. Certain facial muscle movements are sensitive and specific predictors of the presence and severity of pain. The facial display of pain has been found to be relatively consistent across human development (from infancy to adulthood),11 and between humans and nonhuman animals (see below). 2. Facial expression of pain in humans Pain assessment in humans typically relies on self-report; facial expression can be used to quantify pain in individuals who are unable to express themselves verbally (eg, infants, young children, those with verbal or cognitive impairments). This approach was made possible by the Facial Action Coding System of Ekman and Friesen,3 which taxonomizes human facial muscle movements into “action units” (AUs). Certain constellations of these AUs reliably correspond to different human emotional states. The corresponding figure identifies the AUs most commonly associated with pain in infants (Figure A)4 and adults (Figure B).10 The study of facial expression of pain in infants, using the Neonatal Facial Coding System (NFCS),4 provided objective evidence at a time when many doubted the ability of infants to perceive pain. Facial expression of pain is largely a spontaneous reflexive reaction to noxious stimuli, but is, to a certain extent, subject to voluntary control; children as young as 8 years of age are capable of manipulating their facial expression of pain.8 3. Facial expression of pain in nonhuman animals A plethora of new measures of spontaneous pain have been recently developed in response to criticism that preclinical pain researchers were over-reliant on withdrawal responses.9 Given the similar nonverbal status of infants and nonhuman animals, facial expression of pain would seem to provide a solution, especially given Darwin‘s2 direct prediction of phylogenetic continuity of facial expression of emotions. Langford et al.7 adapted the human NFCS to the mouse to create the Mouse Grimace Scale, featuring similar AUs to humans plus 2 rodent-specific changes (in whisker and ear position) (Figure C). Grimace scales have subsequently been developed for the rat,12 rabbit,6 horse1 (Figure D), and cat.5 Quantifying pain through facial expression in these species has proven to have high accuracy and reliability, is useful for indicating both procedural and postoperative pain, and for assessing the efficacy of analgesics. The approach is being increasingly adopted in both veterinary research and care. 4. Conclusions The similarity of facial expression of pain in humans and other animals provides evidence for evolutionary psychological accounts of pain communication13 and represents an impressive example of cross-species translation in pain research. There is a movement towards automated computerized measurement of facial expression of pain, which should eliminate some of the time burden currently associated with its use. Clinical pain continues to be undermanaged in both humans and nonhuman animals. We believe that the study and use of facial expression of pain can effectively address both problems.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».