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J Korean Acad Soc Nurs Educ > Volume 31(4); 2025 > Article
코로나19 대유행 상황에서 대학생의 대면시간, 디지털 번아웃, 사회지능과 외로움의 관계

Abstract

Purpose:

The coronavirus disease 2019 pandemic has led to significant societal changes such as a rapid shift toward online learning, including college classes moving to virtual platforms. This study investigated the relationship between face-to-face communication time, digital burnout, social intelligence, and loneliness among college students during the pandemic.

Methods:

This descriptive correlation study was conducted with 172 college students who participated in an online survey from July 1 to July 9, 2022. Face-to-face communication time, digital burnout, social intelligence, and loneliness were measured. Descriptive statistics, independent t-test, one-way ANOVA, Pearson’s correlation, and regression analysis were used to analyze the collected data.

Results:

Digital burnout (β= -.21, p=.011) and loneliness (β= -.46, p<.001) were significantly associated with social intelligence (F=15.04, p<.001), whereas face-to-face communication time did not show a significant association with social intelligence (β= -.01, p=.922). Digital burnout (β=.41, p<.001) and social intelligence (β= -.33, p<.001) were significantly associated with loneliness (F=18.34, p<.001); however, face-to-face communication was not significantly associated with loneliness (β= -.06, p=.314).

Conclusion:

These findings suggest that digital burnout is significantly associated with both social intelligence and loneliness. This study emphasizes the need for interventions to address digital burnout and promote healthy online habits to improve the social well-being of college students.

Introduction

Our society has undergone rapid changes in daily life since the coronavirus disease 2019 (COVID-19) outbreak [1]. Owing to social distancing, most classes were switched online, and face-to-face interaction decreased among college students [2]. Conversely, online activities including social networking services (SNSs), online shopping, media viewing, and internet search have increased [2]. The increase in physical and mental fatigue and stress due to excessive online and digital device use compared with that during the pre-COVID-19 period is referred to as digital burnout, a newly coined term, and is becoming a social problem [3]. Sleep deprivation, stress, and psychological fatigue are the effects of digital burnout [3]. Continuing only non-face-to-face exchanges in virtual space reduces social relations required in the real world and negatively affects interpersonal relationship formation [4], and excessive online learning using digital devices degrade social intelligence and increase loneliness [5]. Therefore, identifying the factors associated with social intelligence and loneliness is essential to understanding how digital burnout and reduced face-to-face interaction contribute to emotional well-being.
Social intelligence refers to the ability to perceive and interact with others in social comprehension [5]. As social intelligence is exerted by interpreting relationships between individuals, building emotional connections, and using social interaction skills [6], it affects not only social adaptation and interpersonal relationships but also professional abilities, acting as an essential factor in work and school [7]. Understanding the factors associated with social intelligence is critical to addressing its decline and ensuring the development of necessary social skills, particularly in online learning environments. Meanwhile, loneliness refers to the emotional experience of a mismatch between one’s ideal social interactions and the reality of their current relationships [8]. Loneliness is a significant issue that negatively impacts not only an individual’s health but also the overall well-being of society [8]. Therefore, thoroughly exploring its associated factors is an essential process for developing effective solutions. Reduced social relationships due to decreased social intelligence induce social isolation, thereby increasing loneliness [9]. As online relationship formation lacks nonverbal elements and cannot completely replace face-to-face communication [10], the lack of interaction through face-to-face dialogues can increase loneliness, a psychological deficiency [11]. Therefore, understanding how the decline in social intelligence contributes to loneliness can guide efforts to promote healthier social environments and better emotional support for individuals.
Identifying the associating factors of social intelligence and loneliness is crucial for developing strategies to improve social interaction skills and emotional connections, especially in a digital age. College students fall into the transition period from adolescence to adulthood and are vulnerable to mental health problems [12]. Moreover, the younger the age group, the more likely they are to be stressed by the constraints of daily life because of infectious diseases [13]; therefore, they will be significantly affected by social distancing. Social intelligence and social life can be negatively affected by the reduction of interaction in the online learning environment experienced by college students [14]. A deeper understanding of how online learning impacts both social intelligence and loneliness can provide valuable insights into improving students’ overall well-being. Previous studies have explored topics such as digital burnout [3], loneliness [9,14,15], and the relationship between interaction types and mental health [16] related to the pandemic. Additionally, research has been conducted on the relationship between social intelligence and loneliness [5,7]. However, there has been no study that comprehensively examines the relationship between interaction types, digital burnout, social intelligence, and loneliness specifically among university students. Although the COVID-19 global health emergency is over, online usage time is expected to continue to increase because of digital technology development and telecommuting system activation. Here, understanding the relationship between face-to-face communication time, digital burnout, social intelligence, and loneliness for social emotional support among college students is necessary. Therefore, this study aimed to understand the relationship between face-to-face communication time, digital burnout, social intelligence, and loneliness to suggest the direction in which online use should proceed.

Methods

Study design

This is a descriptive correlation study to analyze the relationship between face-to-face communication time, digital burnout, social intelligence, and loneliness perceived by college students and understand their correlation to broaden their understanding of proper online use and digital burnout prevention for healthy emotions.

Setting and samples

The participants of this study were selected from among college students 19 years and older, enrolled in universities in Korea, who comprehended the objectives of the study and willingly consented to take part. The required sample size of 135 was calculated by setting the moderate effect size to .15, significance level to .05, and power to 80%; using the G*Power program, 14 predictors (10 items for general characteristics, time for face-to-face communication, digital burnout, social intelligence or loneliness) were required for linear regression analysis. Taking into account the high dropout rate in online surveys, a questionnaire was distributed to 179 respondents with about 25% dropout expected. Data from 172 respondents were analyzed, with seven responses excluded due to inappropriate answers.

Measurement

● General characteristics

The general characteristics comprised 10 questions on sex, age, grade, major, preferred communication methods, changes in relationships after the pandemic, time spent online, major uses of the internet, satisfaction with online learning, and computer license or education.

● Time for face-to-face communications

Face-to-face communication time was assessed by asking, “How much time do you spend talking face-to-face with others each week?”, with responses recorded as whole numbers representing hours.

● Digital burnout

The Digital Burnout Scale (DBS), which was developed by Erten and Özdemir [17], was used for measuring digital burnout. The DBS was translated into Korean and then back-translated to verify the items, after which three nursing professors evaluated its appropriateness. The DBS comprises three domains (digital aging, digital deprivation, and emotional exhaustion) with 24 items. Each question is measured on a 5-point Likert scale from 1 to 5; the higher the total score, the more severe the digital burnout level. Cronbach’s α of the DBS was .94 [17]; in this study, the reliability was .91.

● Social intelligence

The Tromsø Social Intelligence Scale (TSIS), which was developed by Silvera et al. [18] and translated in Korean by Park [19], was used for measuring social intelligence. The TSIS comprises three domains (social skills, social awareness, and social information processing) with 21 items. Each question is measured on a 7-point Likert scale from 1 to 7; the higher the total score, the higher the social intelligence level. Cronbach’s α of the TSIS was approximately .79 to .86 [18]; in this study, the reliability was .84.

● Loneliness

The UCLA Loneliness Scale (Version 3) developed by Russell [20] was used to assess the degree of loneliness among college students. The scale was first translated into Korean and then back-translated to ensure the accuracy of the items by three nursing professors. This scale has 20 questions, with each question measured on a 4-point Likert scale from 1 to 4; the higher the score, the higher the loneliness level. At the time of development, the reliability of Cronbach’s α was approximately .89 to .94 [20]; in this study, Cronbach’s α was .93.

Data collection

Data collection was conducted for 9 days from July 1 to July 9, 2022. Advertisements for research participants’ recruitment were uploaded to SNSs (Instagram of the nursing department), which included the purpose and procedure of this study, confidentiality of personal information, withdrawal of participation at any time, and explaining in detail that the survey contents were used only for this study. Considering the epidemic of infectious diseases caused by COVID-19, the distribution and collection of questionnaires were conducted non-face-to-face using an online platform. A consent statement for the study was attached on the first page of the questionnaire, and the questionnaire was set to begin when the participant selected ‘I agree’.

Data analysis

IBM SPSS version 29.0 (IBM Corp.) was used for data analysis. The significance levels of all analyses were set at p<.05. The general characteristics and study variables of the participants were calculated using descriptive statistics and frequency analysis, including mean, standard deviation, frequency, and percentage. The independent t-test and one-way ANOVA were used to analyze the difference between social intelligence and loneliness according to general characteristics, and post hoc comparison was performed using the Scheffé test. Pearson’s correlation coefficient was employed to analyze the relationship between the study variables, and multiple regression was performed to analyze factors associating social intelligence and loneliness.

Ethical consideration

This study was carried out after obtaining approval by the Institutional Review Board of the University of Ulsan (IRB No. 2022R0010). The study information and consent forms outlined the purpose of the research, the procedures involved, details regarding anonymity and confidentiality, the researcher’s contact information, participants’ right to withdraw from the study at any point, and assured that personal information and responses to the questionnaire would remain confidential. The data collected only minimal personal information (sex and age) and encrypted and stored on a computer accessible only to the lead researcher. It was explained that the data will be stored for 3 years for data confirmation during the publication process after study completion and subsequently completely discarded. Participants are entitled to request access to, correction of, or deletion of their personal information at any time.

Results

Differences in social intelligence and loneliness according to general characteristics

The majority of the participants were female (76.7%) and male (23.3%), and the mean age was 21.69±2.14 years. Third year students comprised the largest group (36.6%), followed by second (22.1%) and fourth year students (22.7%). Regarding major courses, 39.0% and 29.1% were in the humanities and medicine, respectively. A combination of face-to-face and non-face-to-face communication was preferred by over half of the participants (52.3%). Those who preferred non-face-to-face communication reported significantly higher levels of loneliness than those who did not. When asked about changes in relationships after the pandemic, the most common response (54.1%) was experiencing fewer face-to-face encounters. Participants who reported difficulty making relationships showed significantly higher loneliness scores than those who reported fewer face-to-face encounters, less physical contact, or restricted social activities. The highest percentage of participants (43.0%) spent between 4 and 6 hours/day online. Regarding major uses of the internet, entertainment was the most frequent answer (46.5%). Of the participants, 42.4% were either very satisfied or somewhat satisfied with online education. Over half of the participants (64.0%) had a computer-related certification (Table 1).
Table 1
Differences in Social Intelligence and Loneliness according to the General Characteristics (N=172)
Characteristics Categories n (%) or mean±SD Social intelligence Loneliness

Mean±SD t/F p Mean±SD t/F p (post hoc*)
Sex Male 40 (23.3) 96.58±15.12 -0.80 .424 40.70±11.77 -0.92 .361
Female 132 (76.7) 98.64±14.06 42.51±10.67
Age (years) 21.69±2.14 - -
Grade Freshman 32 (18.6) 100.97±16.29 0.55 .648 40.50±11.78 0.56 .642
Sophomore 38 (22.1) 97.58±15.27 42.95±12.47
Junior 63 (36.6) 97.94±14.38 41.52±9.27
Senior 39 (22.7) 96.79±11.40 43.46±11.27
Major Liberal arts 67 (39.0) 95.46±13.78 1.40 .244 45.10±9.93 3.56 .015
Natural sciences 45 (26.1) 100.51±15.42 39.40±11.96
Medicine 50 (29.1) 99.14±14.06 41.50±10.43
Arts 10 (5.8) 100.80±12.59 36.90±10.84
Preferred communication methods Onlinea 16 (9.3) 93.19±15.56 1.30 .275 48.88±11.23 3.58 .030 (a>b)
Face-to-faceb 66 (38.4) 99.58±13.48 41.02±10.32
Both 90 (52.3) 98.01±14.61 41.67±10.99
Changes in relationship after the pandemic Difficult to make a relationshipa 47 (27.3) 92.28±13.17 3.27 .013 48.11±8.50 7.25 <.001 (a>b,c,d)
Fewer face-to-face encountersb 93 (54.1) 99.53±13.42 40.61±10.42
Less physical contactc 16 (9.3) 102.06±17.37 38.63±13.06
Restricted social activitiesd 12 (7.0) 104.25±12.91 33.50±8.13
More difficult to converse in face-to-face than online 4 (2.3) 101.75±22.41 45.25±16.32
Time spent online (per day) <2 hours 6 (3.5) 90.00±14.74 2.22 .088 46.83±11.92 2.22 .087
2~<4 hours 49 (28.5) 94.90±14.41 44.53±10.86
4~<6 hours 74 (43.0) 99.53±13.46 39.92±10.37
≥6 hours 43 (25.0) 100.67±14.93 42.37±11.36
Major uses of the internet Education 47 (27.3) 96.11±14.39 1.44 .233 41.79±9.81 0.47 .986
Watch news 4 (2.3) 99.50±19.35 42.50±10.47
Social networking 41 (23.9) 95.80±12.85 42.61±10.94
Entertainment 80 (46.5) 100.51±14.60 41.98±11.73
Satisfaction of online learning Very dissatisfied 9 (5.3) 96.44±23.17 1.32 .264 43.67±16.99 .328 .859
Somewhat dissatisfied 38 (22.1) 96.32±15.58 43.26±10.67
Neither satisfied or dissatisfied 52 (30.2) 97.48±13.57 41.65±10.47
Somewhat satisfied 59 (34.3) 98.32±12.27 42.02±10.46
Very satisfied 14 (8.1) 106.14±13.83 39.79±11.75
Computer-related license or education Yes 110 (64.0) 99.85±13.17 2.09 .038 41.63±10.93 -0.73 .464
No 62 (36.0) 95.16±15.78 42.90±10.95

SD=standard deviation

* Scheffé test

Level of time required for face-to-face communications, digital burnout, social intelligence, and loneliness

Participants had an average of 15.02±18.74 hours of face-to-face communications per week, with a maximum of 100 hours. The median score was 7.50 hours (interquartile range, 4.00~20.00). The total scores for digital burnout and social intelligence were 65.42±15.95 and 98.16±14.30, respectively. Participants reported an average loneliness score of 42.09±10.93 (Table 2).
Table 2
Face-to-Face Communication Time, Digital Burnout, Social Intelligence, and Loneliness (N=172)
Variables Mean±SD Range Min.~Max.
Face-to-face communication time (hours per week) 15.02±18.74 - 1~100
Digital burnout 65.42±15.95 24~120 24~103
Burnout aging 28.37±8.29 12~60 11~52
Burnout deprivation 18.66±5.03 6~30 6~30
Emotional exhaustion 15.38±4.94 6~30 6~27
Social intelligence 98.16±14.30 21~147 66~137
Social skills 31.15±7.58 7~49 10~49
Social awareness 31.31±5.55 7~49 18~44
Social information processing 35.71±5.05 7~49 20~49
Loneliness 42.09±10.93 20~80 21~68

Max.=maximum; Min.=minimum; SD=standard deviation

Correlations among the study variables

Social intelligence was positively correlated with face-to-face communication time (r=.17, p=.031) and negatively correlated with digital burnout (r= -.53, p<.001). Loneliness was negatively correlated with face-to-face communication time (r= -.24, p=.002) and social intelligence (r= -.61, p<.001) and positively correlated with digital burnout (r=.65, p<.001) (Table 3).
Table 3
Correlations among the Study Variables(N=172)
Variables Face-to-face communication time Digital burnout Social intelligence Loneliness

r (p)
Face-to-face communication time 1
Digital burnout -.22 (.004) 1
Social intelligence .17 (.031) -.53 (<.001) 1
Loneliness -.24 (.002) .65 (<.001) -.61 (<.001) 1

Factors associated with social intelligence and loneliness

First, upon checking the assumptions of the regression analysis, it was confirmed that there was no issue of autocorrelation, as evidenced by a Durbin-Watson statistic of 2.08. In addition, no multicollinearity was noted, with a variance inflation factor ranging from 1.03 to 1.90. Multiple regression analysis was performed with significant general characteristics, showed that lower digital burnout (β= -.21, p=.011), lower loneliness (β= -.46, p<.001), and having computer-related education or certification (β=.14, p=.024) were associated with higher social intelligence (F=15.04, p<.001).
Second, regression assumptions were examined. A Durbin-Watson statistic of 2.09 showed no evidence of autocorrelation, and variance inflation factors ranging from 1.07 to 4.79 indicated no multicollinearity. Higher digital burnout (β=.41, p<.001), lower social intelligence (β= -.33, p<.001), and being a humanities major compared with an arts major (β=.24, p=.036) were associated with higher loneliness levels (F=18.34, p<.001) (Table 4).
Table 4
Factors Associated with Social Intelligence and Loneliness (N=172)
Variables Categories Social intelligence Loneliness

B β t p B β t p
(Constant) 133.38 - 28.65 <.001 44.28 - 6.33 <.001
Face-to-face communication time -0.01 -.01 -0.10 .922 -0.03 -.06 -1.01 .314
Digital burnout -0.19 -.21 -2.57 .011 0.28 .41 6.20 <.001
Social intelligence - - - - -0.26 -.33 -5.46 <.001
Loneliness -0.61 -.46 -5.65 <.001 - - - -
Major (ref.=arts) Liberal arts - - - - 5.31 .24 2.11 .036
Natural sciences - - - - 3.36 .14 1.30 .195
Medicine - - - - 4.26 .18 1.67 .098
Preferred communication methods (ref.=both) Online - - - - 3.75 .10 1.79 .075
Face-to-face - - - - 0.38 .02 0.31 .760
Changes in relationship after the pandemic (ref.=fewer face-to-face encounters) Difficult to make a relationship -0.83 -.03 -0.40 .693 2.41 .10 1.72 .088
Less physical contact 1.05 .02 0.33 .740 0.67 .02 0.33 .745
Restricted social activities -0.37 -.01 -0.11 .915 -3.89 -.09 -1.70 .091
More difficult to converse in face-to-face than online 5.15 .05 0.90 .370 3.84 .05 0.98 .328
Computer-related certification or education (ref.=no) Yes 4.15 .14 2.28 .024 - - - -
F=15.04, p<.001, R2=.43, adjusted R2=.40 F=18.34, p<.001, R2=.58, adjusted R2=.55

ref.=reference

Discussion

This descriptive study was conducted to understand the effects of college students’ face-to-face communication time and digital burnout on their social intelligence and loneliness. In this study, college students reported a mean digital burnout score of 65.42±15.95, which corresponds to a moderate level of burnout. This score is lower than the mean of 72.78±18.92 reported by Turkish nursing students during the 2020~2021 academic year, when remote learning was widely implemented due to the early phase of the pandemic [3]. The relatively lower score in the present study, conducted in July 2022, may reflect a transitional period when digital demands began to recede. Nonetheless, these findings collectively indicate that digital burnout remains a significant concern among university students in the post-pandemic context. This study also revealed that the social intelligence score (98.16±14.30) was higher than that reported for Turkish nursing students in a previous study (74.15±9.98) [5]. Conversely, the loneliness score (42.09±10.93; mean item score: 2.10) was slightly higher than the previously reported score (mean item score: 1.74) [5]. This difference may be attributable to the timing of the studies, as Savci et al. [5] conducted their research in 2020, while the present study took place during the later stages of the COVID-19 pandemic. Since the onset of COVID-19, loneliness among adolescents has increased significantly compared to pre-pandemic levels, with variations observed based on sex, levels of social support, and perceived social impact of the pandemic [9]. Social intelligence, defined as the ability to communicate effectively and interact with others [7], is particularly important for university students, who need to cultivate the skills to form and sustain healthy, close relationships [7]. As university students are in a critical stage of interpersonal and developmental growth [9], it is essential to screen for and address loneliness within this population.
This study identified digital burnout, loneliness, and computer-related education and certifications as the factors associated with social intelligence. Both loneliness and digital burnout were found to negatively impact social intelligence, supporting existing research [7,21]. The finding on digital burnout aligns with previous studies suggesting that frequent use of and immersion in digital technology negatively affects social intelligence and increases social isolation [21]. In digital environments, communication often relies on elements like emoticons that can distort real emotions, making it difficult to fully understand others’ feelings. Additionally, the potential for constant connectivity can lead to fatigue, which may further hinder one’s ability to accurately perceive others’ intentions. Given that social intelligence is largely acquired and can be developed through diverse social experiences continues to mature throughout early adulthood [5,22], interventions aimed at enhancing it during this developmental stage may be particularly effective. Moreover, preventing digital burnout is anticipated to facilitate the development of social intelligence among college students. Loneliness was also identified as a factor that negatively affects social intelligence. During the COVID-19 pandemic, policies such as social distancing led to increased isolation, which reduced opportunities to engage in or learn from social interactions. In an attempt to compensate for loneliness, individuals may turn to excessive use of social media [23]; while this may enable temporary social connection, it limits meaningful emotional exchanges and may ultimately diminish social intelligence. Moreover, computer-related education and certifications were positively associated with social intelligence. This is consistent with previous studies on social intelligence and professional ability [7], suggesting that digital burnout and social intelligence are affected not only by the amount of digital device use but also by how these devices are used. Conversely, while face-to-face communication time showed a significant positive correlation with social intelligence; it was not found to be a significant predictor of social intelligence. Although face-to-face communication time has decreased since COVID-19, its association with social intelligence has relatively diminished, as online communication—including the use of non-face-to-face channels—has increased, and sociability has improved through the formation of online social relationships [2,5]. This trend may reflect the increased and widespread formation of social relationships through non-face-to-face communication following COVID-19. Therefore, future studies should examine social intelligence based on the quality and limitations of social interaction, rather than distinguishing between online and offline interactions.
Second, digital burnout, social intelligence, and being a liberal arts major were significant factors related to loneliness. Digital burnout, characterized by constant exposure to digital devices, can lead to emotional exhaustion and a sense of detachment from others [3]. Loneliness can increase more quickly as online use increases [15,23,24], especially for individuals who feel that their opportunities for social interaction are limited online [5]. When individuals are mentally drained from digital overload, they may find it harder to engage in meaningful social interactions, which can lead to feelings of loneliness. Online interactions often lack the depth and emotional connection that face-to-face interactions provide [25]. While digital communication offers convenience, it often fails to foster genuine, empathetic connections. This absence of authentic interaction can contribute to feelings of loneliness, as individuals may feel that their social needs are not being fully met. As loneliness is associated with social intelligence, it was also found that social intelligence has a relationship with loneliness, indicating a bidirectional relationship between the two. Social skills, a subfactor of social intelligence, refer to an individual’s ability to behave appropriately in interpersonal relationships [18]. Social awareness involves recognizing appropriate behaviors in social contexts, while social information processing includes understanding others’ emotions [18]. In other words, individuals with high social intelligence respond and behave appropriately in relationships and social environments, and their ability to understand others’ thoughts can predict lower levels of loneliness [7]. Individuals with higher social intelligence are generally better at forming and maintaining meaningful connections, which can protect them from loneliness [5]. Socially intelligent individuals are often more adept at navigating social networks, managing conflicts, and engaging with others, leading to greater social integration and less loneliness. However, face-to-face communication time was negatively correlated with loneliness, but it was not a significant influencing factor of loneliness. During the pandemic lockdown period, face-to-face communication showed a stronger correlation with mental health compared to digital communication [16]. However, studies on digital communication show mixed results. While voice calls [7] and text-based communication, such as e-mail or SMS, have been found to positively impact well-being and mental health, video chatting has been associated with negative effects [16]. It is possible that, in this study, the positive and negative effects of digital communication, apart from face-to-face conversation time, also played a role. However, since this study did not investigate digital text-based communication, this remains unconfirmed. This suggests that managing student mental health during periods of social restriction, such as pandemics, requires a nuanced approach to promoting interaction. The liberal arts major also acted as a significant factor associated with loneliness, suggesting that the degree of loneliness may vary depending on the participant’s major of study. While instructional methods may differ slightly across institutions, during the COVID-19 pandemic, approximately 70% of courses conducted face-to-face were laboratory, practicum, or performance-based classes. Therefore, it can be inferred that students in liberal arts majors, which typically involve fewer hands-on courses, experienced higher levels of loneliness compared to those in arts-related majors [26].
In summary, digital burnout was identified as a significant factor associated with both social intelligence and loneliness. Thus, a key strategy for improving college students’ social intelligence and reducing loneliness is preventing and managing digital burnout. Previously, it was believed that digital burnout and social intelligence could be affected by the way digital devices are used rather than merely their use. Therefore, helping college students prevent digital burnout by promoting healthy digital habits is critically important. Furthermore, cultivating healthy online social relationships could reduce loneliness and promote the development of social intelligence among college students. Digital burnout may be alleviated by promoting sleep hygiene practices and implementing organizational policies that provide mental health support [27]. The relationship between loneliness and social intelligence is dynamic and reciprocal. Social intelligence can act as a protective factor against loneliness by enhancing one’s ability to connect with others and engage in positive social interactions. Conversely, chronic loneliness can diminish one’s social intelligence by limiting opportunities for social practice and emotional learning. Thus, improving social intelligence could be a valuable approach in managing and reducing loneliness, especially in situations where social interactions are limited. This study is significant in that it examines digital burnout among college students in the aftermath of the COVID-19 pandemic and explores its associated factors, offering important implications for nursing education. Enhancing social intelligence may serve as an effective strategy to promote optimal mental well-being and prevent the onset of mental health disorders [28]. Therefore, integrating strategies derived from the findings of this study into nursing curricula could help support students’ mental health. Furthermore, incorporating structured opportunities for meaningful peer interaction and digital wellness education into nursing programs may strengthen interpersonal competence among nursing students. Additionally, fostering the formation of social relationships through the healthy use of digital technology may serve as a new countermeasure to loneliness among college students.
This study has several limitations. First, the small sample size limited the ability to represent the entire college student population and generalize the findings. Therefore, future research should examine loneliness in relation to individual tendencies to identify more precise contributing factors. Second, the sample consisted mainly of voluntary respondents from a specific region, which limits the representativeness of the sample and warrants caution when generalizing the results to the entire college student population. Third, the online learning experiences during the pandemic varied among participants. Some likely experienced online learning in both high school and university, while others only at the university level. This difference may have contributed to variations in the research results. Fourth, face-to-face communication time was measured using a single item, which may have been subjectively interpreted by respondents, potentially leading to inconsistent responses. Thus, more precise and validated measures are needed in future studies. Finally, participants may have enhanced their social intelligence by adapting to prolonged social distancing and online environments during the pandemic. Accordingly, future research should explore the relationships among study variables based on individuals’ levels of adaptation to non-face-to-face systems and digital environments.

Conclusion

This study was conducted to confirm the face-to-face communication time, digital burnout, social intelligence, and loneliness of college students and identify the factors affecting social intelligence and loneliness. The results confirmed that identifying the degree of digital burnout, cultivating ways to cope with it, and improving social intelligence can reduce loneliness among college students. Conversely, face-to-face conversation time was not identified as a factor that directly affects social intelligence and loneliness; however, it had a significant correlation. Therefore, further research is needed to consider other factors. Based on the results of this study, developing an intervention to prevent and overcome digital burnout to positively affect the social intelligence and loneliness of college students is necessary. Prior research has identified sleep hygiene—particularly limiting screen use before bedtime—as an effective strategy for mitigating digital burnout [27]. Building on the present findings, digital self-regulation through targeted educational programs may be beneficial, as students with computer-related training demonstrated higher social intelligence. Furthermore, promoting emotionally meaningful online interactions, such as small-group discussions, may enhance social connectedness and reduce loneliness in virtual environments. Finally, reducing excessive use of SNSs may help prevent maladaptive coping responses to digital fatigue and social isolation.

Notes

Author contributions

S Kim (Kim, Sohee): Conceptualization, Investigation, Data curation, Writing - original draft, Visualization. S Kim (Kim, Seongmin): Conceptualization, Investigation, Data curation, Writing - original draft, S Ko: Conceptualization, Methodology, Supervision, Formal analysis, Writing - original draft, Writing - review & editing, Project administration.

Conflict of interest

No potential conflict of interest relevant to this article was reported.

Funding

None

Acknowledgements

None

Supplementary materials

None

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