Emotional Intelligence: Emotional Expression and Emotional Regulation for Intrinsic and Extrinsic Emotional Satisfaction

Purpose: Theorists have constructed emotional intelligence differently, based on which the literature reveals different diversified scales to measure emotional intelligence. These scales are quite lengthy to respond and have been criticized for producing varying results. The current paper projects the findings of 3 consecutive studies carried out to summarize and simplify the existing models of emotional intelligence and to produce a brief measure in this regard. Methods: Based on the review of the earlier models of emotional intelligence, emotional intelligence was comprehended as an “ability to express and regulate emotions for intrinsic and extrinsic emotional satisfaction”. “Emotional Intelligence Scale (EIS)”, comprising 12 items in English, was developed and validated through principal component analysis, exploratory factor analysis, and confirmatory factor analysis through a series of 3 consecutive studies which involved 1894 participants from Pakistan. The validity of EIS was tested step by step for its face, content, factorial, convergent, and discriminant validity. The reliability was measured through internal consistency and item-total and item-scale correlations. Results: EIS was revealed to be a valid and reliable scale to measure emotional intelligence through 4 core factors, ie, emotional expression, emotional regulation, intrinsic emotional satisfaction, and extrinsic emotional satisfaction. The additional findings revealed significantly higher levels of emotional intelligence among men as compared to women; significantly positive correlation of emotional intelligence with social intelligence, positive emotional effects, age, and education; and a significantly inverse correlation between emotional intelligence and the negative emotional effects. Conclusion: The current paper reported the development and validation of a new scale on emotional intelligence by comprehending and summarizing the earlier models of