Login / Signup

Social, Emotional, and Behavioral Skills: Age and Gender Differences at 12 to 19 Years Old.

Tommaso FeracoChiara Meneghetti
Published in: Journal of Intelligence (2023)
Individuals use social, emotional, and behavioral (SEB) skills to build and maintain social relationships, regulate emotions, and manage goal-directed behaviors. A promising integrative framework of SEB skills was recently proposed, showing that they matter for positive outcomes during adolescence. Nothing is known about how and whether they differ between 12 and 19 years old and whether such differences depend on gender (males or females). Uncovering their age trajectories is fundamental because SEB skills are highly needed during this period of life. Educators, psychologists, and policymakers need to understand when, why, and how interventions concerning SEB skills should be proposed, potentially considering male and female profiles. To cover this gap, we cross-sectionally analyzed data from 4106 participants (2215 females, 12-19 years old). We highlighted age and gender differences in the five domains of SEB skills (self-management, innovation, cooperation, social engagement, and emotional resilience). Our results show that each SEB skill follows a specific age trend: emotional resilience and cooperation skills increase naturally between 12 and 19 years old, while innovation, social engagement, and self-management skills decline, especially between 12 and 16 years old, and grow later. The trajectories of self-management, social engagement, and emotional resilience skills also differ between males and females. Importantly, we detected declines in SEB skills (especially for social engagement and innovation skills) that can inform policies and interventions to sustain SEB skills in youths to favor their well-being and success in this crucial period.
Keyphrases
  • medical students
  • mental health
  • healthcare
  • depressive symptoms
  • public health
  • type diabetes
  • metabolic syndrome
  • social support
  • skeletal muscle
  • machine learning
  • insulin resistance