Title |
Children Facial Expression Production: Influence of Age, Gender, Emotion Subtype, Elicitation Condition and Culture
|
---|---|
Published in |
Frontiers in Psychology, April 2018
|
DOI | 10.3389/fpsyg.2018.00446 |
Pubmed ID | |
Authors |
Charline Grossard, Laurence Chaby, Stéphanie Hun, Hugues Pellerin, Jérémy Bourgeois, Arnaud Dapogny, Huaxiong Ding, Sylvie Serret, Pierre Foulon, Mohamed Chetouani, Liming Chen, Kevin Bailly, Ouriel Grynszpan, David Cohen |
Abstract |
The production of facial expressions (FEs) is an important skill that allows children to share and adapt emotions with their relatives and peers during social interactions. These skills are impaired in children with Autism Spectrum Disorder. However, the way in which typical children develop and master their production of FEs has still not been clearly assessed. This study aimed to explore factors that could influence the production of FEs in childhood such as age, gender, emotion subtype (sadness, anger, joy, and neutral), elicitation task (on request, imitation), area of recruitment (French Riviera and Parisian) and emotion multimodality. A total of one hundred fifty-seven children aged 6-11 years were enrolled in Nice and Paris, France. We asked them to produce FEs in two different tasks: imitation with an avatar model and production on request without a model. Results from a multivariate analysis revealed that: (1) children performed better with age. (2) Positive emotions were easier to produce than negative emotions. (3) Children produced better FE on request (as opposed to imitation); and (4) Riviera children performed better than Parisian children suggesting regional influences on emotion production. We conclude that facial emotion production is a complex developmental process influenced by several factors that needs to be acknowledged in future research. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 9 | 23% |
France | 2 | 5% |
United Kingdom | 2 | 5% |
Switzerland | 1 | 3% |
Canada | 1 | 3% |
Russia | 1 | 3% |
Guam | 1 | 3% |
Unknown | 23 | 57% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 37 | 93% |
Scientists | 3 | 8% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 86 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 13 | 15% |
Student > Bachelor | 7 | 8% |
Student > Doctoral Student | 6 | 7% |
Researcher | 5 | 6% |
Student > Master | 4 | 5% |
Other | 16 | 19% |
Unknown | 35 | 41% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 16 | 19% |
Computer Science | 7 | 8% |
Nursing and Health Professions | 5 | 6% |
Medicine and Dentistry | 4 | 5% |
Social Sciences | 3 | 3% |
Other | 14 | 16% |
Unknown | 37 | 43% |