Abstract
Purpose
This descriptive study aimed to identify the factors affecting adolescents’ emotional intelligence during the COVID-19 (coronavirus disease 2019) pandemic.
Methods
We utilized the 4th-year data from the 2018 Korean Children and Youth Panel Survey, which comprise 1,852 adolescents living with both parents. The determinants of adolescents’ emotional intelligence were analyzed through stepwise multiple regression, considering parental, family, and school factors.
Results
Parental factors, such as parents’ grit and emotional intelligence, were found to enhance adolescents’ emotional intelligence. Family factors, including parents’ positive parenting attitude and the average time spent with parents, also significantly enhance adolescents’ emotional intelligence. School factors, such as the number of remote class days during the previous semester, influenced adolescents’ emotional intelligence.
Conclusion
Parental and family factors enhanced emotional intelligence, whereas school factors, particularly remote learning, negatively impacted it. The model explained 67.5% of variance, with parents' emotional intelligence being the strongest predictor. Interventions should prioritize enhancing parental emotional competence and maintaining meaningful parent-child interactions, especially during educational disruptions.
Keywords: Adolescent, Emotional intelligence, Korea, Psychology recognition
INTRODUCTION
In 2023, the obligation to wear a mask in schools was relaxed in South Korea. However, many adolescents continue to wear them. This choice is not solely for illness prevention purposes but also owing to psychological and social factors that emerged during the coronavirus disease 2019 (COVID-19) pandemic [1]. For some adolescents, masks have become a way to hide their expressions [1]. Due to prolonged remote schooling, adolescents have become more accustomed to online communication. As a result, they often struggle to express their feelings and thoughts, and their ability to interpret non-verbal expressions has diminished, leading to a greater tendency to misread others’ emotions [2]. Particularly, adolescents face unprecedented challenges and stress, as they have to gauge and understand the emotions of others through the movement of their eyes and eyebrows while their mouth is covered by a mask [3]. Adolescence refers to the transitional period between childhood and adulthood, during which physical, psychological, emotional, and social changes become prominent [4]. This phase is particularly unstable due to intense emotional experiences, making accurate emotion recognition and expression critical for effective emotion regulation and the development of interpersonal relationships [5]. Accordingly, several experts have emphasized the importance of early intervention during this period to mitigate long-term risks [6].
Emotional perception refers to the ability to recognize one’s own emotions in affective, cognitive, and physical states [7]. Additionally, one can also recognize the emotions and psychological states of others and respond appropriately. This ability is called emotional intelligence [8]. Those able to perceive their emotions have higher levels of autonomy, clearer self-boundaries, and are psychologically healthier and more adaptable [9], given that they experience fewer emotional conflicts and can initiate effective coping strategies in challenging situations [10]. Therefore, emotional intelligence serves as a key factor in forming positive social relationships; it involves having a clear understanding of oneself and others and being able to adapt to social situations. Consequently, emotional intelligence is a core competency that is essential in the current era [3].
Adolescence is a period marked by multidimensional changes in emotional intelligence [11,12]. During this period, the ability to recognize and appropriately respond to the emotions and psychological states of others is a key skill and indicator of one’s role as a member of society [3]. According to previous studies, emotional intelligence supports individuals’ positive functioning, thereby enhancing life’s meaning and satisfaction, as well as psychological well-being [13]. Therefore, strengthening emotional intelligence in adolescents is essential for overall development and social, academic, and professional success.
Emotions are conveyed via verbal expressions and various non-verbal elements such as facial expressions, tone/volume of voice, and gestures [14]. It is particularly important to understand the emotions behind others’ facial expressions and respond appropriately to nurture effective interpersonal relationships [15]. Given the widespread school closures and transition to remote learning during the COVID-19 pandemic, the importance of emotional intelligence in adolescents has gained increased attention [16]. As mask-wearing has become a part of everyday life, facial expressions serve as a crucial lens through which adolescents’ emotional intelligence can be better understood [3]. Since facial expressions are among the most immediate and powerful cues for recognizing others’ emotions, the ability to accurately interpret these cues is a fundamental component of emotional intelligence, enabling individuals to respond appropriately in social interactions [3,14-16]. However, previous studies on emotional intelligence have focused only on self-awareness of emotions and verbal expression [17]. They have not identified and investigated the environmental changes caused by the pandemic—including the need to wear masks.
To address this gap, the present study examined adolescents’ ability to recognize the emotions and psychological states of others and analyzed the parent, family, and school factors affecting this ability. According to the ecological perspective [18], which emphasizes that individual behavior is greatly influenced by the environment and requires a multifaceted approach, adolescence is a critical period where environmental factors are especially important and can be considered in terms of family and school environments. Against this backdrop, this study analyzes adolescents’ emotional intelligence from an ecological perspective, considering the personal and environmental characteristics of the family and school domains. Specifically, it examined adolescents’ emotional intelligence amid the social changes following the COVID-19 pandemic, especially in 2021, which marked the transition from online education to in-person classes.
This study aimed to determine the parental, family, and school factors that affected the emotional intelligence of adolescents who experienced a period of limited social interaction owing to the COVID-19 pandemic, particularly after their return to face-to-face learning.
METHODS
Ethical statements: This study was approved by the Institutional Review Board of Baekseok University (IRB No. BUIRB-202407-HR-045). It utilized the second set of data released to the public through the Korean Children and Youth Panel Survey, obtained from the National Youth Policy Institute.
1. Research Design
This descriptive, cross-sectional secondary data analysis utilized the Korean Children and Youth Panel Survey (KCYPS) data from the National Youth Policy Institute (NYPI) to identify the factors affecting emotional intelligence among adolescents. This paper was composed according to the guidelines outlined in the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines [19].
2. Study Setting and Sample
We utilized the 2018 KCYPS data from the NYPI, which dynamically examined Korean adolescents’ health behaviors and changing patterns. To systematically and multidimensionally examine the complex patterns of changes in the growth and development of children and adolescents, the KCYPS conducted a 7-year follow-up study, which began in 2018, with first-year middle school students and continued to 2024, when the participants reached their first year of university [20]. This study’s sample was drawn from first-year middle school students. Considering the subjective value system of parents and the socio-economic aspects that affect the growth and development of adolescents, a simultaneous survey was conducted with parents and children. Adolescents were surveyed regarding their personal development and developmental environment, whereas their parents or guardians were individually interviewed about various background variables (e.g., education, occupation, and income level), their characteristics, and their adolescents’ developmental background [20].
The survey population for the 2018 KCYPS was established using the 2017 Education Statistics provided by the Ministry of Education. A multi-stage stratified cluster sampling method was employed, targeting first-year middle school students across 17 metropolitan cities and provinces nationwide [20]. First, regions and city size were selected as factors affecting adolescents’ development, according to which the status of the population was identified. By determining the number of students in each of the 17 metropolitan cities and provinces, according to the proportion of the total number of students, a minimum sample size of two or more schools was determined. Regarding each stratum, the number of students was determined by probability-proportional-to-size sampling, allocating the number of classes based on the size of the region, living environment, and educational conditions. To be eligible as a sample school, the school had to have at least two classes and a minimum of 50 students. If these conditions were not met, the school was replaced with a neighboring school. Classes were randomly selected, one per school, and all students in the selected classes were surveyed. The survey data were collected using tablet PCs and individual face-to-face interviews. Weights were applied to reflect the differences in the sampling rate, response rate, and the changed population that might have occurred owing to the survey [20].
We targeted adolescents who were in their third year of middle school in 2020, when the COVID-19 outbreak became a pandemic, and who became first-year high school students in 2021. In total, 2,265 first-year middle school students were included; the KCYPS data from their fourth year—when entering their first year of high school—were used. Subsequently, this study matched these data with the adolescents’ guardian data to obtain a final sample of 1,852 adolescents who were living with both parents. This sample comprised 81.8% of the original 2,265 students in the fourth year of the panel of first-year middle school students who participated in the survey.
3. Variables and Measurements
1) Parental factors
Parents’ grit and emotional intelligence were included as parental factors that may affect adolescents’ emotional intelligence. To examine parents’ grit, KCYPS used the instrument originally developed by Duckworth [21] and subsequently adapted to a Korean version [22]. This tool comprises eight questions scored on a 4-point Likert scale ranging from 1=“strongly disagree” to 4=“strongly agree.” Four questions are reverse-coded and scores range between 8 and 32, with higher scores indicating higher grit. The Cronbach’s α in the study by Kim and Hwang [22] was 0.71, and 0.62 in this study. Parents’ emotional intelligence was measured using 28 questions from the Reading the Mind in the Eyes Test (RMET), which was used in the 20th Korea Labor and Income Panel Study, based on Baron-Cohen et al. [23]. This tool assesses the ability to recognize others’ emotions by making the individual choose one of four words that describe the emotions or thoughts from the eyes and facial expressions of others; the more words selected correctly, the higher the individual’s ability to understand others’ emotions. The Cronbach’s α in this study was 0.69.
2) Family factors
Parents’ positive attitudes, average time spent with parents per day, family income level, and the presence of siblings were included as family factors that may affect adolescents’ emotional intelligence. The KCYPS examined parenting attitude, as perceived by adolescents, using the Parents as Social Context Questionnaire for Korean Adolescents [24]. This study used the domains corresponding to “warmth, support for autonomy, and provision of structure” and conducted a confirmatory factor analysis using AMOS to determine whether the three factors explained parents’ positive parenting attitudes. Consequently, the following values were obtained: χ2=380.12 (degrees of freedom=51, p<.001), Tucker-Lewis index=0.962, comparative fit index=0.970, root mean square error of approximation=0.059 (90% confidence interval, .05–.07), and standardized root mean square residual=0.032, indicating that the model was appropriate for measuring positive parenting attitude. Each of the three factors constituting a positive parenting attitude—warmth, autonomy support, and structure provision—was evaluated using four questions, for a total of 12 questions. The scores ranged from 1=“strongly disagree” to 4=“strongly disagree,” with higher scores indicating a more positive parenting attitude, as perceived by the adolescent. The Cronbach’s α for parents’ positive parenting attitude was 0.91 in the current study and that of Kim et al. [25].
The average time spent with parents per day, in hours and minutes, was calculated using the following formula: [(5×average time spent with parents on weekdays)+(2×average time spent with parents on weekends)]/7. Data on family income level were obtained from the adolescents’ parents using a survey. The subjective family income level was classified into five categories, from the lowest to the highest, and further classified into three categories: high, middle, and low. The presence of siblings, including the respondent, was indicated using a dummy variable (“no” if the number of siblings was one, and “yes” if the number was two or more).
3) School factors
The high school type, the size of the city where the school is located, and the number of remote class days were included as school factors that may affect adolescents’ emotional intelligence. The school types were first classified as regular, autonomous, or special-purpose high schools. Subsequently, they were reclassified as regular high school or other. The size of the city where the school was located was classified into three categories: large city, small- or medium-sized city, and town or township. The number of remote class days was determined based on how many days, on average, the school had remote classes during the first semester of 2021.
4) Emotional intelligence of adolescents
To measure adolescents’ emotional intelligence, this study used 28 questions from the RMET, which was used in the 20th Korea Labor and Income Panel Study, based on Baron-Cohen et al. [23]. The RMET measures the respondent’s ability to guess the emotions of others from observing their eyes and facial expressions. The scores ranged from 0 to 28, with a higher score indicating a higher level of emotional intelligence. The Cronbach’s α for the RMET was 0.72 in this study and that of the study by Kim et al. [26].
4. Data Analysis
The data were analyzed using IBM SPSS ver. 25.0 (IBM Corp.), and all statistical assessments utilized a two-tailed test with a significance level of .05. Descriptive statistics and a frequency analysis were used to identify participants’ general characteristics. Using independent t-tests and one-way analysis of variance, we determined the differences in adolescents’ emotional intelligence based on individual, family, and school factors. Furthermore, post hoc analyses were conducted using Scheffe’s test. Using Pearson’s correlation coefficients, we determined the correlation of adolescents’ emotional intelligence with parental, family, and school factors. The influence of parental, family, and school factors on adolescents’ emotional intelligence was examined using multiple regression analysis, in which variables were entered sequentially by factor group. Before implementing the regression analysis, the variance inflation factor index was used to determine the correlations among the independent variables. It indicated a value ≤2.22, suggesting the absence of multicollinearity [27]. The Durbin-Watson test provided a value of 2.03, indicating the absence of autocorrelation between the independent variables [28].
RESULTS
1. Participants’ General Characteristics
The adolescent participants comprised 984 males (53.1%) and 868 females (46.9%), and 87.9% of the participants had siblings. The average time spent with parents per day was 3.45±2.43 hours. Regarding the family income level of these adolescents, 201 (10.9%) of their parents believed theirs was “high,” while 1,442 (77.9%) and 209 (11.3%) believed theirs was “medium” and “low,” respectively. Most participants attended regular high schools (81.0%), while 351 (19.0%) attended autonomous, special purpose, or specialized vocational high schools. Regarding the size of the city where the school was located, 819 adolescents (44.4%) attended schools in large cities, 748 (40.5%) attended schools in small- or medium-sized cities, and 278 (15.1%) attended schools in towns or townships. The mean number of remote class days per week in the previous semester (2021) was 1.6±1.22 days (Table 1).
Table 1.
General characteristics of participants (N=1,852)
| Characteristic | Value |
|---|---|
| Gender | |
| Male | 984 (53.1) |
| Female | 868 (46.9) |
| Presence of siblings | |
| No | 225 (12.1) |
| Yes | 1,627 (87.9) |
| Average time spent with parents per day (hr) | 3.45±2.43 |
| Family income level | |
| High | 201 (10.8) |
| Middle | 1,442 (77.9) |
| Low | 209 (11.3) |
| Type of high school | |
| Regular high school | 1,494 (81.0) |
| Other | 351 (19.0) |
| Size of the city where the school is located | |
| Large city | 819 (44.4) |
| Small- or medium-sized city | 748 (40.5) |
| Town or township | 278 (15.1) |
| No. of remote class days per week in the previous semester | 1.60±1.22 |
Values are presented as number (%) or mean±standard deviation.
2. Differences in Adolescents’ Emotional Intelligence Based on General Characteristics
Table 2 presents the differences in adolescents’ emotional intelligence based on their general characteristics. No differences were found in adolescents’ emotional intelligence by gender (t=–0.47, p=.641) or sibling status (t=–1.31, p=.191). Adolescents with a “low” family income level had higher emotional intelligence than those with a “medium” family income level (F=6.23, p=.002), whereas the group attending other schools had higher emotional intelligence than the group attending regular high schools (t=–5.17, p<.001). Moreover, adolescents who attended high school in small- or medium-sized cities and those attending high school in towns or townships had higher emotional intelligence than those attending high school in large cities (F=6.04, p=.002).
Table 2.
Differences in adolescents’ emotional intelligence based on general characteristics (N=1,852)
| Characteristic | Emotional intelligence | ||
|---|---|---|---|
| Mean±SD | t/F | p | |
| Gender | |||
| Male | 15.22±5.95 | –0.47 | .641 |
| Female | 15.36±6.18 | ||
| Presence of siblings | |||
| No | 14.79±5.99 | –1.31 | .191 |
| Yes | 15.35±6.06 | ||
| Family income level | |||
| Higha | 15.80±5.94 | 6.23 | .002 |
| Middleb | 15.04±6.11 | (b<c) | |
| Lowc | 16.51±5.65 | ||
| Type of high school | |||
| Regular high school | 14.96±6.17 | –5.17 | <.001 |
| Other | 16.65±5.35 | ||
| Size of the city where the school is located | |||
| Large citya | 14.77±6.23 | 6.04 | .002 |
| Small- or medium-sized cityb | 15.54±5.98 | (a<b,c) | |
| Town or townshipc | 16.07±5.60 | ||
SD, standard deviation.
3. Correlation of Adolescents’ Emotional Intelligence with Parental, Family, and School Factors
Table 3 presents the correlation of adolescents’ emotional intelligence with parental, family, and school factors. Regarding parental factors, parents’ grit increased as adolescents’ emotional intelligence increased, exhibiting a positive correlation (r=.15, p<.001). Additionally, the parents’ emotional intelligence exhibited a positive correlation with that of adolescents (r=.82, p<.001). Regarding family factors, parents’ positive parenting attitude (r=0.23, p<.001) and average time spent with the parents per day (r=.26, p<.001) were positively correlated with adolescents’ emotional intelligence. Conversely, the mean number of remote class days per week in the previous semester was negatively correlated with adolescents’ emotional intelligence (r=–.27, p<.001).
Table 3.
Correlation of adolescents’ emotional intelligence with parental, family, and school factors (N=1,852)
| Parental | Family | School | Adolescents’ emotional intelligence | |||
|---|---|---|---|---|---|---|
| Parents’ grit | Parents’ emotional intelligence | Positive parenting attitude | Average time spent with parents per day | No. of remote class days per week in the previous semester | ||
| Parental | ||||||
| Parents’ grit | 1 | .13 (<.001) | .16 (<.001) | .10 (<.001) | –.13 (<.001) | .15 (<.001) |
| Parents’ emotional intelligence | .13 (<.001) | 1 | .22 (<.001) | .25 (<.001) | –.28 (<.001) | .82 (<.001) |
| Family | ||||||
| Positive parenting attitude | .16 (<.001) | .22 (<.001) | 1 | .30 (<.001) | –.14 (<.001) | .23 (<.001) |
| Average time spent with parents per day | .10 (<.001) | .25 (<.001) | .30 (<.001) | 1 | –.14 (<.001) | .26 (<.001) |
| School | ||||||
| No. of remote class days per week in the previous semester | –.13 (<.001) | –.28 (<.001) | –.14 (<.001) | –.14 (<.001) | 1 | –.27 (<.001) |
| Adolescents’ emotional intelligence | .15 (<.001) | .82 (<.001) | .23 (<.001) | .26 (<.001) | –.27 (<.001) | 1 |
Values are presented as r (p).
4. Effects of Parental, Family, and School Factors on Adolescents’ Emotional Intelligence
To determine how parental, family, and school factors affected adolescents’ emotional intelligence, a stepwise multiple regression analysis was performed using significant variables from the mean comparison and correlation analyses. The significance test indicated that all models for emotional intelligence were significant. The explanatory powers were 67.0% for model 1 (F=1,867.64, p<.001), 67.3% for model 2 (ΔR2=.005; F=643.58, p<.001), and 67.5% for model 3 (ΔR2=.002; F=383.17, p<.001) (Table 4).
Table 4.
Effect of parental, family, and school factors on adolescents’ emotional intelligence (N=1,852)
| Type of factor | Factor | Model 1 | Model 2 | Model 3 | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| B | SE | β | t | p | B | SE | β | t | p | B | SE | β | t | p | ||
| (Constant) | 0.95 | 0.66 | 1.43 | .153 | –0.26 | 0.82 | –0.31 | .753 | 0.77 | 0.88 | 0.87 | .385 | ||||
| Parental | Parents’ grit | 0.10 | 0.03 | .04 | 3.27 | .001 | 0.08 | 0.03 | .04 | 2.67 | .008 | 0.08 | 0.03 | .03 | 2.45 | .015 |
| Parents’ emotional intelligence | 0.78 | 0.01 | .81 | 60.09 | <.001 | 0.76 | 0.01 | .79 | 56.44 | <.001 | 0.75 | 0.01 | .78 | 53.83 | <.001 | |
| Family | Positive parenting attitude | 0.04 | 0.02 | .04 | 2.55 | .011 | 0.04 | 0.02 | .03 | 2.37 | .018 | |||||
| Average time spent with parents per day | 0.13 | 0.04 | .05 | 3.54 | <.001 | 0.12 | 0.04 | .05 | 3.36 | .001 | ||||||
| Family income level (middle: 1) | –0.14 | 0.26 | –.01 | –0.54 | .593 | –0.12 | 0.26 | –.01 | –0.45 | .651 | ||||||
| Family income level (high: 1) | –0.02 | 0.35 | –.01 | –0.05 | .957 | 0.01 | 0.35 | .01 | 0.02 | .985 | ||||||
| School | Type of high school (other: 1) | 0.01 | 0.21 | .01 | 0.06 | .956 | ||||||||||
| Size of the city where the school is located (small- or medium-sized city: 1) | –0.32 | 0.24 | –.03 | –1.32 | .187 | |||||||||||
| Size of the city where the school is located (large city: 1) | –0.44 | 0.24 | –.04 | –1.84 | .067 | |||||||||||
| No. of remote class days per week in the previous semester | –0.18 | 0.07 | –.04 | –2.57 | .010 | |||||||||||
| F (p) | 1,867.64 (<.001) | 634.58 (<.001) | 383.17 (<.001) | |||||||||||||
| R2 | .670 | .674 | .676 | |||||||||||||
| Adjusted R2 | .669 | .673 | .675 | |||||||||||||
| ΔR² | .005 | .002 | ||||||||||||||
Model 1: adjusted for parental factors; model 2: model 1+adjusted for family factors; and model 3: model 2+adjusted for school factors.
SE, standard error.
Model 1, which included the parental factors, indicated that parents’ grit and emotional intelligence significantly affect adolescents’ emotional intelligence. Greater levels of parental grit were associated with higher emotional intelligence among adolescents (β=.04, p=.001), and higher parental emotional intelligence positively affected adolescents’ emotional intelligence (β=.81, p<.001).
In model 2, which included parental and family factors, parents’ grit (β=.04, p=.008) and emotional intelligence (β=.79, p<.001) affected adolescents’ emotional intelligence. Moreover, positive parenting attitudes were associated with higher levels of emotional intelligence among adolescents (β=.04, p=.011). Similarly, spending more time with their parents was associated with higher emotional intelligence among adolescents (β=.05, p<.001). Notably, the subjective income level of the family had no significant effect on adolescents’ emotional intelligence.
In model 3, which incorporated parental, family, and school factors, parents’ grit (β=.03, p=.015) and emotional intelligence (β=.78, p<.001) affected adolescents’ emotional intelligence. Regarding family factors, positive parenting attitude, as perceived by adolescents (β=.03, p=.018), and the average time spent with their parents (β=.05, p=.001) positively affected adolescents’ emotional intelligence. Regarding school factors, an increase in the number of remote class days in the previous semester negatively impacted adolescents’ emotional intelligence (β=–.04, p=.010), whereas the type of high school and the size of the city where the school was located exhibited no significant effects on adolescents’ emotional intelligence (β=–.04, p=.067).
DISCUSSION
This study analyzed the factors that influenced the emotional intelligence of adolescents whose social relationships were affected by social distancing and remote classes during the COVID-19 pandemic. KCYPS data were used for third-year middle school students who experienced social isolation in 2020 owing to the COVID-19 pandemic and who became first-year high school students in 2021.
Regarding parental factors, parents’ grit and emotional intelligence positively affected adolescents’ emotional intelligence. Those with high grit tended to focus on their goals for longer periods, maintain perseverance, even in challenging situations, and not give up easily [29]. Their perseverance was especially evident in their relationships with their children and the continuous fulfillment of their responsibilities to support their children’s growth. According to Yoon and Choi [30], parental grit goes beyond enduring difficulties, requiring parents to consistently show commitment and patience in daily interactions with their children, which in turn positively influences the children’s emotional development. To successfully raise their children, parents must constantly exercise patience to overcome the difficulties encountered during the process. Additionally, parents are required to change their roles as their children grow, which means that they need to develop new roles and abilities as their children grow. A 6-year longitudinal study demonstrated that parents who maintain consistent emotional warmth and adapt their control strategies flexibly create optimal conditions for children’s psychological flexibility and emotional development, which forms the foundation for enhanced emotional intelligence [31]. This assists children in learning to overcome challenges and difficulties, thereby strengthening their emotional empathy and ability to understand others’ emotions, ultimately improving their emotional intelligence.
Parents’ emotional intelligence strongly influences that of adolescents, indicating that parents’ emotional intelligence affects the development of their children’s emotional recognition. Moreover, parents’ emotional intelligence has a modeling effect on their children, becoming a learning tool for them [32]. Children consciously and unconsciously learn and imitate, resulting in the modeling of emotional interactions as well as emotional expressions and coping. Those adolescents who can recognize and internalize their emotions are more likely to accurately understand and empathize with others’ emotions [33]. Furthermore, recognition of one’s own emotions leads to better emotion regulation and fewer emotional conflicts during adolescence [34]. Therefore, an elevated level of emotional intelligence in parents positively affects the development of adolescents’ emotional intelligence. The survey was conducted in 2021, when social isolation began owing to the COVID-19 pandemic and continued until 2021. During this period, the time spent at home increased dramatically, suggesting that the relationship with parents was the most significant factor affecting adolescents’ emotional development. This finding emphasizes the importance of developing educational programs for parents, to improve their emotional intelligence and promote emotional interactions with their children. This must be developed while considering the unique Korean culture, which emphasizes interdependence and bonding and values emotional closeness, in contrast to Western culture, which focuses on individuality and independence [35].
Regarding family factors, adolescents’ emotional intelligence increased as they perceived their parents’ parenting attitude more positively. This was consistent with previous studies reporting that a positive parenting attitude is a significant factor in adolescents’ emotional development [36,37], indicating that positive interactions with parents play a key role in children’s emotional development. Several previous studies have reported that the parent–child relationship is a key factor in the formation and maintenance of a child’s healthy self-image and interpersonal relationships and that the parenting quality provided by parents is closely related to the mental health of children [36-38]. Therefore, a positive parenting experience received from parents can enhance adolescents’ emotional intelligence [38]. This means that programs that positively improve parents’ parenting attitudes can be an important foundation for adolescents’ emotional intelligence.
Additionally, more time spent with parents positively affected adolescents’ emotional intelligence. This was consistent with the results of a study in the United Kingdom [39], which found that adolescents with relatively high mental health problems before the pandemic improved on all subscales of mental health during the pandemic. This was attributed to enhanced parent–child interactions owing to increased time spent at home during the pandemic. Notably, although this study examined the quantity of time spent with parents, not the quality, it found a positive impact on adolescents’ emotional intelligence. This suggests that parents should not feel burdened by focusing too much on the quality of emotional interactions, given that the hours that parents and children spend together daily can provide a sense of security and emotional development among children. Accordingly, social efforts are required to increase the time that parents and children spend together at home and to establish family-friendly policies that allow parents and children to naturally engage in emotional exchanges in their daily lives, even if the interactions are not special or deep.
In the present study, the subjective family income level had no significant effect on adolescents’ emotional intelligence, suggesting that emotional intelligence is closely related to the emotional environment rather than the economic environment. This finding differs from that of previous studies [39]. Dissimilar to previous studies, this study examined the family’s income level based on the subjective perception of the parents rather than objective indicators, which may have led to this discrepancy. Moreover, economic factors can operate in a complex manner, not only concerning income levels, but also in conjunction with numerous factors such as a country’s social support system, welfare levels, and cultural background [40]. Therefore, future studies should conduct a more in-depth analysis of the impact of economic factors on adolescents’ emotional intelligence, including objective economic indicators.
Regarding school factors, an increase in the number of remote class days negatively influenced adolescents’ emotional intelligence. This is consistent with previous studies showing that remote classes negatively impacted adolescents’ psychosocial development during the pandemic [41]. These results suggest that the absence of face-to-face interactions and the resulting isolation might have hindered adolescents’ emotional development. Conversely, the type and region of school had no significant effect on adolescents’ emotional intelligence. This suggests that changes in educational methods had a greater impact on emotional intelligence than school type and regional differences, emphasizing the necessity of developing integrated programs that promote effective peer interactions and emotional exchanges by improving the remote education environment in crises such as pandemics. These findings are in line with previous research indicating that the lack of in-person interaction during remote learning can impede adolescents’ emotional and social growth [42,43]. Interpreting these results in the context of prior studies, it becomes clear that targeted interventions within the school environment are crucial to mitigating the negative effects of social isolation during crises. Particularly, in such crises, adolescents’ emotional development should be enhanced through video-based small group activities, online mentoring, and virtual counseling services, emphasizing the role of school nurses and teachers.
Despite its contributions, this study has some limitations. First, it did not consider the adolescent participants’ characteristics, given that it focused on environmental factors that affected emotional intelligence. Future studies should examine individual factors that affect emotional intelligence from multiple perspectives. Second, this study was a cross-sectional examination; thus, the identification of causal relationships between variables is limited. In the future, longitudinal studies should be conducted to determine how the emotional intelligence of adolescents who had experienced the pandemic changed over time. Third, family income level was assessed solely on parents’ perceived subjective household economic status. Future research should incorporate multiple indicators to provide a more comprehensive analysis. Fourth, this study did not consider the interactive effects of various interpersonal and community factors such as peer relationships, community, and school health policies. Follow-up studies should include these factors to explore emotional intelligence from a broader perspective. Despite these limitations, the contributions of this study are significant, given that it targeted adolescents who experienced the COVID-19 pandemic and comprehensively analyzed their parental, family, and school factors.
CONCLUSION
This study examined the factors that affected adolescents’ emotional intelligence during the COVID-19 pandemic. The results indicated that positive parental and family environments significantly enhanced adolescents’ emotional intelligence, while certain school-related experiences, such as prolonged remote learning, impacted it negatively. The results of this study provide valuable insights for policymakers, researchers, and practitioners to minimize emotional distress among adolescents and support their healthy development during crises, such as pandemics. Based on the findings, this study proposes a multidimensional approach that considers all three factors—parental, family, and school—to improve adolescents’ emotional intelligence.
Regarding parental factors, parental education programs should be developed to improve parents’ grit and emotional intelligence. Importantly, training programs that strengthen emotional expression, understanding, and regulation ability should be included to improve parents’ emotional intelligence. Future research should empirically evaluate the effectiveness of these parent-focused programs in enhancing adolescent outcomes.
Regarding family factors, parent counseling or coaching programs should be established to promote positive parenting attitudes. Moreover, programs to strengthen family activities and emotional bonds should be expanded to ensure that parents and children spend sufficient time together. Community health nurses and school nurses should provide family-centered assessments and guide parents in implementing emotional support strategies that enhance parent-child interactions. In particular, high-quality interaction time between parents and children should be guaranteed through policies that support parents’ work–life balance. Future research could contribute to such programs by investigating which types of family activities and policies most effectively foster emotional intelligence in adolescents.
Finally, regarding school factors, an emotional support system in remote class environments should be established. To ensure active emotional interactions between teachers and students and between students in a non-face-to-face environment, classes focused on interactions should be designed and an online counseling system should be established. School nurses should lead the implementation of emotional intelligence screening programs, provide immediate crisis intervention for students showing emotional distress, and collaborate closely with teachers to identify and support students at risk during remote learning periods. It is recommended that future studies assess the impact of such school-based interventions on students’ emotional intelligence and well-being, especially in digital or hybrid learning environments.
From a nursing practice perspective, adolescent care nurses should be equipped with emotional intelligence assessment tools and evidence-based intervention strategies. In addition, training programs for school nurses and community health nurses should focus on recognizing signs of emotional difficulties, implementing preventive measures, and providing continuity of care during educational disruptions such as pandemics. Such a multidimensional approach should be achieved through cooperation between parents, families, and schools, particularly during crises, such as pandemics.
Footnotes
Authors' contribution
Conceptualization: KL, HC. Methodology: KL, HC. Formal analysis: HC. Investigation: KL, HC. Data curation: HC. Writing: KL, HC. All authors have read and agreed to the published version of the manuscript.
Conflict of interest
No existing or potential conflict of interest relevant to this article was reported.
Funding
None.
Data availability
The data used in this study are available from the National Youth Policy Institute at http://www.nypi.re.kr/archive. Data access procedures and documentation are in Korean.
Acknowledgements
The authors thank the National Youth Policy Institute for giving them access to their databases for this study.
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