• Dr Harcharan Singh

Emotional intelligence (EI)—the constellation of abilities and self-perceived competencies that facilitate the perception, understanding, and regulation of affect—has long been associated with offline psychosocial adjustment, yet its buffering role in the algorithm-driven attention economy remains insufficiently quantified. Guided by the Interaction-of-Person–Affect–Cognition–Execution (I-PACE) framework, the present study investigates how trait EI relates to both quantitative usage metrics and qualitative engagement styles across five of India’s most popular social-media platforms (TikTok, Instagram, X, Facebook, and WhatsApp). A cross-sectional sample of 1 206 emerging adults (53 % women; M_age = 22.4 years, SD = 2.8) completed the 30-item Trait Emotional Intelligence Questionnaire–Short Form, the Bergen Social Media Addiction Scale, the Big-Five Inventory-44, and mental-health screeners (GAD-7; PHQ-9). Crucially, each participant also exported a seven-day Multi-Platform Activity Log from their smartphone’s screen-time dashboard, yielding device-logged indices of daily minutes, passive-to-active browsing ratios, nocturnal checking frequency, and prosocial content creation. Descriptive analyses revealed a mean daily exposure of 147 minutes and a passive-scrolling ratio of 0.61, mirroring global Gen-Z norms. Pearson and Spearman correlations demonstrated modest but consistent inverse associations between global EI and screen time (r = –.22, p < .001), passive scrolling (r = –.27, p < .001), and nocturnal checks (r = –.19, p < .001), while empathy showed a positive relation to prosocial posting (r = .24, p < .001). Hierarchical multiple regressions controlling for age, gender, conscientiousness, anxiety, and depression indicated that the emotion-regulation facet emerged as the single strongest negative predictor of problematic use (β = –.34, ΔR² = .09, p < .001). PROCESS Model 4 mediation confirmed that emotion-regulation carried 42 % of the anxiety → problematic-use pathway (indirect B = .13, 95 % CI [.09, .18]). Age moderated the EI–screen-time association (interaction p = .004), with the protective gradient steepest among 18- to 20-year-olds. Platform-specific regressions showed the EI–passive-scrolling slope was largest on short-video feeds (TikTok β = –.31) and smallest on private-messaging environments (WhatsApp β = –.10). Collectively, the findings refine EI theory by highlighting facet-level specificity and by demonstrating that self-regulatory competencies retain predictive power even after personality and mental-health covariates are parcelled out. Practically, they suggest three intervention levers: (1) embedding EI-training drills (e.g., cognitive-reappraisal micro-exercises) into digital-citizenship curricula, (2) integrating reflective-pause nudges at user-interface level to capitalise on EI principles, and (3) targeting low-EI individuals in clinical or campus counselling settings for early digital-hygiene support. Limitations include the cross-sectional design, potential under-capture of multitasking by operating-system dashboards, and cultural specificity to Indian emerging adults. Future longitudinal and experimental studies, augmented with physiological EI markers and passive sensing, are recommended to clarify causality and broaden generalisability.

emotional intelligence; social media; digital well-being; passive scrolling; emotion regulation; I-PACE model; emerging adults; India

"Correlation between emotional intelligence and social media usage patterns", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.91-101, April-2021, Available :http://www.jetir.org/papers/JETIR2104441.pdf

"Correlation between emotional intelligence and social media usage patterns", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp91-101, April-2021, Available at : http://www.jetir.org/papers/JETIR2104441.pdf