Facial Emotion Recognition Across Various Age Groups in a Healthy Egyptian Population.

Background: The world’s population is significantly increasing in populations of all age groups, including older adults. Social cognition deficits are common in various neuropsychiatric illnesses in all age groups, particularly the older adult population, who commonly experience cognitive impairment. However, social cognition assessment remains an underexplored area of research in Egypt. So, the current study aims to obtain normative data for the Arabic version of the Faces Emotion Recognition test for the Egyptian population, as a reference for future clinical and research use in the older adult population in Egypt. Methodology: A cross-sectional study was conducted involving 241 community-dwelling Egyptian adults aged over 20. Participants were requested to complete an online survey comprising demographic information questions, patient health questionnaire 2 (PHQ2) questions, instructions for completing the Faces Test, and the 20 test items. Results: The mean score of the Faces test is 17.42 (SD = 1.59), with a range from 10 to 20 and a median of 18. Most of the faces achieved optimal recognition percentages by study participants; however, regarding faces 8 (distress) and 18 (interested), only 49.4% and 62.2% of participants, respectively, recognised those two faces correctly. Performance on the Faces test varies significantly, with younger participants achieving higher mean scores compared to older adult individuals. Conclusion: Facial emotional recognition varies across different age groups. Participants of all age groups in our study had lower item recognition rates than anticipated compared to prior normative data.

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Publication Details

Journal
Egyptian Journal of Geriatrics and Gerontology
Published
2024-10-01
DOI
https://doi.org/10.21608/ejgg.2024.427639
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
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article

Facial Emotion Recognition Across Various Age Groups in a Healthy Egyptian Population.

H. Ibrahim, Abeer Hassan, Ahmed Mohammedin, Heba Shaltoot et al.
Egyptian Journal of Geriatrics and Gerontology
Face recognition and analysis
article

Facial Emotion Recognition Across Various Age Groups in a Healthy Egyptian Population.

H. Ibrahim, Abeer Hassan, Ahmed Mohammedin, Heba Shaltoot, Hamouda Mohamed Saber, Enas R. Mohamed, Doha Rasheedy, Heba M. Tawfik, Shaimaa Nabil Rohaiem, M H Aly, Nesma Gamal, Marwa Abdelazeem
article en

Abstract

Background: The world’s population is significantly increasing in populations of all age groups, including older adults. Social cognition deficits are common in various neuropsychiatric illnesses in all age groups, particularly the older adult population, who commonly experience cognitive impairment. However, social cognition assessment remains an underexplored area of research in Egypt. So, the current study aims to obtain normative data for the Arabic version of the Faces Emotion Recognition test for the Egyptian population, as a reference for future clinical and research use in the older adult population in Egypt. Methodology: A cross-sectional study was conducted involving 241 community-dwelling Egyptian adults aged over 20. Participants were requested to complete an online survey comprising demographic information questions, patient health questionnaire 2 (PHQ2) questions, instructions for completing the Faces Test, and the 20 test items. Results: The mean score of the Faces test is 17.42 (SD = 1.59), with a range from 10 to 20 and a median of 18. Most of the faces achieved optimal recognition percentages by study participants; however, regarding faces 8 (distress) and 18 (interested), only 49.4% and 62.2% of participants, respectively, recognised those two faces correctly. Performance on the Faces test varies significantly, with younger participants achieving higher mean scores compared to older adult individuals. Conclusion: Facial emotional recognition varies across different age groups. Participants of all age groups in our study had lower item recognition rates than anticipated compared to prior normative data.

Egyptian Journal of Geriatrics and GerontologyVol. 11(2)
Ain Shams University (EG)
Gender equality
Openalex Percentile: Top 70%
Face recognition and analysis
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