Relationship between Emotional Intelligence, Internet Addiction, and Sociodemographic Factors among University Students: A Cross-sectional Study

INTRODUCTION WITH OBJECTIVES

In the current scientific era, the Internet has revolutionized our lives through advanced discoveries. It has become a crucial tool for education, entertainment, weather news, and communication. With the development of technology, the Internet has brought the world to our fingertips, and in the past decade, its usage has significantly changed, leading to an increase in Internet users. The easy availability of the internet has increased dependence, making it an addictive factor among youth.¹ Internet Addiction (IA) refers to uncontrolled obsessions, impulses, and behaviors that are excessive or poorly managed and cause distress or impairment.² The Internet is crucial in the Information Sharing Society, providing email, chatting, discussion groups, social entertainment, shopping, and information search, offering relief, depression management, and emotional release for teens.^3,4 Individuals develop an IA when disconnected from their real lives, where the online realm dominates reality and serves as a replacement or escape, allowing them to indulge in fantasies and conflicts.⁵

Connections have been identified between addictions and the regulation of emotions, stating that addictions are linked to a lack of ability to control emotions and where the term “Emotional Intelligence” (EI) comes from.⁶ EI is the skill of identifying both personal and others’ emotions and managing them effectively.⁷ Emotion regulation encompasses the control of all emotionally charged circumstances related to emotions, stress, and both positive and negative impacts.⁸

An analysis of research in the pertinent literature suggests that different indicators of mental health are linked to people’s strategies for regulating their emotions, including psychopathological issues such as depression, psychosomatic symptoms, and anxiety.^9-11 On the other hand, it was discovered that issues with emotion regulation were significantly correlated with substance use and loneliness.^12,13 Children who struggle to control their emotions often behave in hostile, unpleasant, vulnerable, introverted, lonely, and overly cautious ways toward others.

Studies have demonstrated the link between EI, IA, and mental health issues, underscoring the need for further research on how EI influences social aspects and academic performance among students. The findings of the study conducted by Caplan identify EI as the strongest predictor of IA.¹⁴ Multiple studies also highlight the significant increase in internet use among students, highlighting the potential impact of EI on this trend. Studies indicate a correlation between IA and EI, with individuals who struggle to manage their emotions being more susceptible to IA.^15-17 Facebook addiction is linked to depression, sleep issues, domestic violence, and relationship failure. Longitudinal designs should be used to identify determinants among Bangladeshi university students and their risk of developing the disorder.¹⁸ Another study finds that approximately 65.7% of medical students are involved in IA, which quite a bit can affect the field of EI. However, this can be minimized if appropriate measures are taken.¹⁹

Internet usage is increasing in Bangladesh, which is in line with the global trend. According to a research survey, the number of Internet users in Bangladesh is about 141.28 million.²⁰ A study in Bangladesh found that 96% of university students use the internet for various purposes, with 5% browsing for <1 h, 12.2% using 2 h, 18.75% spending 2–3 h, and 40.3% wasting time 4–6 h.²¹ Another study revealed that undergraduate medical students spend 5–6 h browsing the internet.²² These studies show that students spend significant time on the Internet, leading to long-term physical and mental effects, including disturbed eating habits and sleep patterns.

University students are a vulnerable age group as they are in a transitional phase of life, often lacking the knowledge and skills to regulate their emotions effectively. This age group is particularly susceptible to the pressures and uncertainties of academic and social environments, making them more prone to emotional dysregulation. As a result, they may struggle to manage their internet use, leading to higher risks of IA.

Despite the increasing body of research on IA and its relationship with EI globally, there is a significant research gap regarding these issues among Bangladeshi students. The cultural, educational, and social context of Bangladesh is unique and may influence how students experience and cope with IA and manage their emotions. Given the rapid rise in internet usage in Bangladesh, especially among university students, it is crucial to understand how this trend affects their emotional and mental well-being. This study aims to fill this gap by investigating the relationship between EI and IA among university students in urban Bangladesh and examining the associated factors that influence EI and IA. Understanding these dynamics will provide valuable insights for developing targeted interventions to promote healthier internet habits and enhance emotional well-being in this population.

MATERIAL AND METHODS

RESULTS

The Shapiro–Wilk test revealed that all variables followed a normal distribution for EI, IA, and demographic variables at the P < 0.001 level, which justified the use of parametric tests. Among the 300 participants, 114 (38%) were male and 186 (62%) were female. The majority of participants were Honors 1^st Year students (53.7%). In addition, the majority of the participants were from the Dhaka division (69.3%) and resided in urban areas (77.7%) [Table 1].

The mean age (±SD) of the participants was 21.81 (±2.19), with an age range of 18–26 years, whereas the mean age (±SD) of the male and female participants was 22.16 (±2.11) and 21.44 (±1.81), respectively. The mean IA score (±SD) of male participants was 39.53 (±15.61), and the mean EI score (±SD) of male participants was 123.74 (±13.29). The mean IA score (±SD) of female participants was 37.80 (±15.52), and the mean EI score (±SD) of female participants was 124.18 (±13.43) [Table 2]. The highest IA score recorded was 85, while 11 was the lowest. The EI score ranged from 170 to 69. A Pearson correlation coefficient (r = −0.463) indicated a significant (P < 0.001) moderate negative correlation between EI and IA, suggesting that higher EI scores were associated with lower IA scores.

The regression analysis assessed the predictive capability of IA on EI. The beta coefficient of −0.397 indicated a significant negative relationship between IA and EI. This suggested that higher IA scores were associated with lower EI scores. The R-squared (R2) value of 0.214 indicated that about 21.4% of the variance in EI (R² = 0.214) was explained by IA. The overall regression model was statistically significant, as evidenced by the F-value of 81.164 (P < 0.001). A regression analysis aimed to predict IA based on multiple independent variables. The results illustrated that the combined predictor variable comprising RA, Age, Number of Family Members (NF), Gender, SES, RD, and EQ did not significantly explain variance in the dependent variable, IA Score (Sig. F = 15.385). A multiple linear regression analysis was done to predict IA based on age, gender, EQ, SES, NF, RD, and RA [Table 3]. Data revealed that none of the independent variables were statistically significant predictors of IA except SES (P < 0.05). Regression assumptions, including normality, linearity, and homoscedasticity, were satisfied, ensuring model validity.

A regression analysis was measured to predict EI on various independent variables [Table 4]. The predictor variables, i.e., RA, Age, FM, gender, SES, RD, EQ, did not show significant variance in explaining the dependent variable, EI Score (Sig. F = 13.312). A multiple regression analysis was done to predict EI based on age, gender, EQ, SES, NF, RD, and RA [Table 4]. The analysis revealed that none of the independent variables were statistically significant predictors of EI except EQ (P < 0.05).

The analysis revealed that none of the examined factors, i.e., Age, Gender, EQ, SES, Family Members, RD, and RA, demonstrated a statistically significant association with IA scores among university students [Table 5]. All F-values were non-significant (P > 0.05), indicating that these variables did not significantly contribute to the variation in IA levels observed in this student population. The statistical analysis indicated that Age, Gender, EQ, SES, Family Members, RD, and RA did not exhibit a statistically significant association with EI scores among university students. All calculated F-values were non-significant (P > 0.05), indicating that these variables did not significantly contribute to the variation observed in EI levels within this student population.

DISCUSSION

The findings from this study indicated a significant negative correlation between EI and IA, suggesting that students with higher EI were less likely to experience IA. This relationship was crucial as it highlighted the protective role of EI in mitigating IA, which is a growing concern among youth. In this study, the average age (±SD) of the participants was 21.81 (±2.19) years, indicating a fairly uniform age range that allowed for a more focused understanding of developmental similarities within this demographic. The average IA score (±SD) of 38.46 (±15.55) indicated a moderate degree of IA among participants, reflecting varying levels of Internet usage habits. The analysis revealed that females exhibited higher average EI scores and lower average IA scores, whereas males demonstrated lower average EI scores and higher average IA scores. These findings suggested a potential inverse relationship between EI and IA, indicating that individuals with lower EI may be more prone to IA.

Regression analysis revealed a negative relationship between IA and EI, with the beta coefficient indicating that higher levels of EI were associated with lower levels of IA. This finding was consistent with previous studies that showed a similar trend. For instance, Ahmed et al. and Nadeem et al. found that students with moderate levels of IA tended to have slightly lower EI scores.^15,29 In addition, research from Asian countries linked excessive Internet use, particularly Facebook addiction, with adverse outcomes such as depression, poor sleep quality, domestic violence, and relationship failures.¹⁸

The results of the present study aligned with Datta et al., who observed the widespread use of mobile devices and internet facilities in Bangladesh, a nation rapidly becoming tech-savvy.²² This increased internet usage was linked to higher rates of depression among users, as seen in Uddin et al.³⁰ In addition, Parvathy and Smitha found that extensive internet use among medical students in Kerala significantly impacted their EI, demonstrating the strong influence of digital devices on the emotional and mental health of young adults.¹⁹ Understanding the inverse relationship between EI and IA during this critical developmental stage highlighted the importance of emotional skills in promoting healthy internet usage habits. These findings also suggested that interventions targeting IA could potentially enhance EI, thereby reducing IA and improving emotional and social well-being.

Therefore, it can be said that individuals with higher EI possess better emotional regulation skills, enabling them to manage their internet use more effectively and avoid the compulsive behaviors associated with IA. Higher EI might equip individuals with the ability to recognize and address emotional distress without resorting to excessive internet use as a coping mechanism. Furthermore, students with higher EI were likely to have stronger interpersonal relationships and support networks, reducing their need for online interactions that could lead to addiction.

The current study also examined the relationship between EI and various demographic factors such as age, gender, education level, socio-economic status, family size, housing type, and residential location. Multiple regression analysis showed that among the independent variables examined, only SES and Education Qualification were statistically significant predictors of IA and EI, respectively. SES was identified as a significant predictor of IA, whereas Education Qualification emerged as a significant predictor of EI. No other studies have been conducted to see the relationship between different demographic factors and EI. The results from the one-way ANOVA suggested that Age, Gender, EQ, SES, NF, RD, and RA did not show significant contributions to the observed variation in IA and EI levels among this student population.

Despite these significant findings, several aspects require further consideration. The sample size of this study was limited to university students, which may not be representative of the broader population. This restriction makes it challenging to generalize the findings to individuals of different age groups and educational backgrounds. In addition, due to the unresponsiveness of male participants, their number was significantly low, which might have skewed the results and limited the generalizability of the findings concerning gender differences.

CONCLUSION

This study underscores a significant inverse relationship between EI and IA among urban university students in Bangladesh, highlighting that higher EI levels correspond with lower IA tendencies. Females showed higher average EI scores and lower average IA scores, while males exhibited lower average EI scores and higher average IA scores. SES emerged as a notable predictor of IA, whereas Education Qualification was identified as a significant predictor of EI. Other factors, including Age, Gender, EQ, NF, RD, and RA, did not contribute significantly to the variation in IA and EI levels observed in this student population. Future research should prioritize longitudinal studies to track EI and IA dynamics over time, implement and evaluate EI-focused interventions to mitigate IA risks and explore cultural influences on digital behaviors. To enhance generalizability, future studies should include more diverse samples. In addition, developing interventions that bolster EI to reduce IA could be pivotal, focusing on emotional regulation, coping strategies, and fostering healthier internet usage habits through strengthened interpersonal relationships. These efforts could lead to more effective strategies for addressing IA among university students in Bangladesh and beyond.