Emotional Granularity as a Predictor of Working Memory Capacity: A Cognitive Processing Perspective
DOI:
https://doi.org/10.63468/sshrr.367Keywords:
Emotional granularity, working memory capacity, cognitive processing, emotion–cognition interaction, executive functioningAbstract
Background: Emotional granularity is the capacity to distinguish and label emotional experiences, as well as to do so with precision and has been associated with emotional regulation as well as psychological well-being. Nevertheless, its contribution to cognitive performance, especially the working memory capacity, has not been adequately researched as part of the emotion-cognition studies.
Aim: The current research was intended to investigate the emotional granularity as a predictor of working memory capacity through the prism of cognitive processing.
Method: The cross-sectional correlational design was used quantitatively based on the sample of 220 young adults. Experience based emotion differentiation indices were used to test emotional granularity whereas standardized computerized working memory tests were used to test working memory capacity. The Pearson correlation and hierarchical regression analysis were made with controlling of the age and emotional intensity.
Findings: Emotional granularity was found to be positively related significantly to the working memory capacity. The hierarchical regression analysis showed that emotional granularity was a significant predictor of working memory capacity in relation to the influence of age and emotional intensity that explained unique variance in cognitive performance.
Conclusion: The results indicate that emotional granularity is an effective cognitive processing factor that facilitates working memory capacity. The study contributes to emotion-cognition relationships and demonstrates that emotional representational accuracy is a key attribute of executive functioning by proposing emotional differentiation as a predictor of cognitive efficiency.
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Copyright (c) 2026 Muhammad Waqas , Muhammad Muaavia Khalid, Huda Afzal
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