Measurement of the Ability to Recognize Facial Emotions over the Adult Lifetime in a Supra-Normal Sample
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Notice bibliographique
Résumé
Background: Measuring the ability to recognize facial emotions has been the object of a growing number of studies. However, the heterogeneity of the measuring devices used and the images tested led to partial agreements and conflicting results in the scientific literature. The lack of agreed upon computerized measuring devices worsens the situation. Description of the study and methods used: This was a single blind, randomized, controlled study of parallel groups with no direct individual benefit for the volunteers. We used Method of Research Analysis of Emotional Integration (M.A.R.I.E.), which is “software,” meaning in this case a computerized measuring device that quantifies the process of facial emotional recognition. This tool and the methodology are amply illustrated in previously published articles by the same authors and by the principal author. We have established prescriptive parameters and standards for the recognition of anger, disgust, joy, fear, surprise, sadness, and neutrality on three faces from a control group of 204 subjects between the ages of 20 and 70 years, all White Caucasians from Northern France, whose cognitive functions were at an optimum level. Hence, the subjects in the study sample were described in this article as “supra-normal.” This study was conducted between April 2000 and April 2005 in Northern France in Lille City, home town of Duchenne de Boulogne (1806-1875) famous for Duchenne-smile. The Results: The results indicated that: 1) at whatever age of the subject, a) joy is the most recognized emotion, and b) anger is the most difficult to recognize; 2) aging of the subjects alters the ability to recognize emotion on a given face; 3) the recognition of a given emotion depends on the face on which it is expressed; 4) recognition of fear and disgust persists at the same level, despite aging of the subjects; 5) the recognition of joy improves with age; 6) the identity of a face is important in the recognition of emotions; 7) level of education does not affect the ability to recognize facial emotions, and; 8) 1% of the supra-normal population with even an optimum level of cognition has difficulty recognizing facial emotional expressions. Conclusions: The inborn potential to express and recognize facial emotions (RFE) typically manifests in infancy well before the acquisition of language and cultural influences. The study tracks this ability as a unique "Developmental Line" for a homogeneous adult sample using a special measuring tool. The quantitative analysis of the findings leads to a conclusion that we need to further refine our scientific definition of what constitutes “emotion” and identify innate complex neuropsychological and neurobiological processes in which a series of determinants ranging from inborn endowments to sociocultural influences interact in still poorly understood ways. In spite of that, it can be concluded that the conventional cultural wisdom or innate drives for survival of the species may be influencing the differences found in the ability to perceive, discern and label certain canonical emotions accurately and efficiently. Also, there are some definitive trends that can be inferred to guide clinical practice. For example, joy is universally recognized, and therefore, may be more relevant for building therapeutic relationship than the emotion-neutral expression of the therapist in most face to face therapeutic settings. There are also variations in this ability in the aging subjects, changing in positive and negative directions for different emotions for their expression and recognition through the life cycle. Some trends can be definitely identified as normal variations. This study on a culturally homogeneous small sample of white Caucasian French population opens many areas for future research, for replication in various other groups, clinical diagnostic studies, and early therapeutic interventions.
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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 | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 découle