Front. PsychiatryFrontiers in PsychiatryFront. Psychiatry1664-0640Frontiers Media S.A.10.3389/fpsyt.2023.1243619PsychiatryOriginal ResearchEffects of internet addiction and academic satisfaction on mental health among college students after the lifting of COVID-19 restrictions in ChinaDengAi-Ping12WangCong13CaiJia1DengZhong-Yue13MuYun-Fei13SongHong-Jun2MengYa-Jing1MengXian-Dong1HuangXue-Hua1ZhangLan1HuangYi1ZhangWei1ChenJin4RanMao-Sheng13*1Mental Health Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China2West China School of Nursing, Sichuan University, Chengdu, Sichuan, China3Psychiatric Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan, China4Department of Clinical Epidemiology and Evidence-Based Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China
Edited by: Gregor E. Berger, Psychiatric University Hospital Zurich, Switzerland
Reviewed by: Stefania Mancone, University of Cassino, Italy; Francisco Manuel Morales, University of Granada, Spain
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Background
Internet addiction (IA) among students, worsened by Coronavirus disease 2019 (COVID-19) pandemic, has become a social problem with the digitalization of school learning and many aspects of daily life. However, few studies on IA have been conducted among students after the lifting of COVID-19 restrictions in China.
Method
This large-sample, cross-sectional, online survey was conducted to explore the characteristics of IA and the association among IA, academic satisfaction, and mental health problems from December 14, 2022 to February 28, 2023 in Sichuan, China. All participants (N = 22,605) were students in colleges and universities, recruited via their teachers and professors.
Results
Of all the participants, 14,921 (66.0%) participants had IA. Participants with IA were more likely to have depression symptom, anxiety symptom, insomnia, and lifetime suicidal ideation. In addition, participants with severe IA had significantly higher rates of mental health problems (e.g., depression, anxiety, insomnia, and suicidal ideation) than those with mild IA. A significant IA-by-academic satisfactory-interaction on mental health was identified: participants with higher level of IA showed particularly severe symptom of depression, anxiety and insomnia when affected by low satisfactory of academy (p < 0.001).
Conclusion
This study reveals that IA has a significantly negative impact on mental health among college students after the lifting of COVID-19 restrictions in China. IA and academic satisfaction have interactive impacts on mental health problems among students. Further educational and health policies and psychosocial interventions should be developed to reduce IA and enhance academic satisfaction for improving students’ mental health.
academic satisfactoryChinainternet addictionmental healthstudents136220012West China Hospital10.13039/501100013365section-at-acceptanceAdolescent and Young Adult PsychiatryIntroduction
Internet use has snowballed with its gravity (essentiality and availability) in the lives of modern students. While older adults are also utilizing the internet more frequently, the majority of internet users are adolescents and young people, particularly among the digital generation (1–4). Research indicates that an imbalance between internet use and sleep will directly impact academic performance and long-term physical and mental health (5, 6).
The prevalence of internet addiction (IA) varies among different populations. Previous studies have reported the prevalence of IA ranging from 0.5 to 84% (7–10). In China, the prevalence of IA was found to be between 0.9 and 37.9% among adolescents and young adults (7, 9, 11, 12). Medical students exhibited a relatively higher rate of IA, reaching 41.9% (10). During the Coronavirus Disease 2019 (COVID-19) pandemic, evidence showed that 32.4% of Chinese students displayed a tendency towards IA (13). However, the prevalence of IA and its influencing factors among college students after the lifting of COVID-19 restrictions in China remains unknown.
Previous studies have showed the associations among IA, sleep problems, and mental health problems (14–17). A meta-analysis conducted in 2019, comprising 23 observational studies with 35,684 participants, revealed that individuals with IA had a pooled odds ratio of 2.2 for experiencing sleep problems and a 24% reduction in sleep duration compared to normal internet users (6). Furthermore, IA has been highly correlated with depression and anxiety (18–21), as well as poor academic performance (22, 23). However, further research is needed to explore the relationship between IA, academic performance, and mental health problems, particularly among college students after the lifting of COVID-19 restrictions in China.
Therefore, this study aimed to (1) investigate the prevalence of IA and (2) examine the association between IA, academic satisfaction, and mental health problems among college students in Sichuan, China, after the lifting of COVID-19 restrictions.
MethodsStudy design and participants
This cross-sectional online study was conducted among college students from December 14, 2022, to February 28, 2023, in the period immediately after the lifting of COVID-9 related restrictions in Sichuan, China. The study was approved by the Biomedical Research Ethics Committee of West China Hospital, Sichuan University (No: 2022-1790). Written informed consent was obtained online before the survey.
A self-designed online survey was released via a platform of Wenjuanxing. In order to ensure the quality of the study, the survey information was firstly sent to the teachers and professors in colleges and universities in Sichuan province, China. Then, it was disseminated from teachers and professors directly to their students. The confidentiality of all data was ensured. The inclusion criteria of participants: (1) Students studying at a university or college in Sichuan Province and (2) Voluntarily agree to participate in this survey. The exclusion criteria: (1) Students in other Province other than Sichuan and (2) Do not agree to participate in this survey. A total of 22,605 university and college students provided informed consents and completed the questionnaires.
Measurements
The questionnaire had 4 parts, taking approximately 20 min to complete. The first part included demographic and general information of the participants, such as sex, ethnicity, monthly family income, history of psychotic disorders, etc. The second part collected the information related to the COVID-19 pandemic, including the COVID-19 infection, quarantine experience, and psychological stress level. The third part inquired the participants’ daily habits and behaviors. The fourth part investigated current mental health problems, including symptoms of depression, anxiety, insomnia, internet addiction and social support.
The Patient Health Questionnaire (PHQ-9) was used to assess the level of depressive symptoms in the past 2 weeks (24). The total score of greater than 5 indicating depression symptoms (25). The good reliability and validity have been established for the Chinese versions of PHQ-9, which has been commonly used for Chinese general population (25, 26).
The Generalized Anxiety Disorder-7 (GAD-7) was used to assess symptoms of anxiety (27), with a total score of greater than 5 indicating symptoms of anxiety (27). The Chinese versions of GAD-7 has good reliability and validity among Chinese people (28).
The Insomnia Severity Index (ISI) was used to assess insomnia (29), with a total score of greater than 8 indicating insomnia. The Chinese versions of ISI has good reliability and validity among Chinese people (30).
The Internet Addiction Test (IAT) was used to assess internet addiction (31), which comprises 20 items and each item is scored on a five-point scale. An IA level was classified as mild, moderate, or severe according to the total score of IAT. The cut off score of 40 was used to categorize as average usage group (<40), and problematic usage group (≥40). The good reliability and validity have been established for the Chinese version of IAT among Chinese adolescents (32).
The Social Support Rating Scale (SSRS) was adopted in the current study to measure social support (33), which includes 10 items with three dimensions: objective support, subjective support, and support utilization. A higher total score indicates a higher level of social support for the participants. The Chinese version of SSRS has good reliability and validity among Chinese people (33).
Statistical analysis
Chi-square test and two-sample t-test were used to compare demographic variables and scales for categorical and continuous variables as appropriate between the 2 groups. Two sample t-test and Chi-square test were performed to compare the score of PHQ-9, GAD-7, ISI, and SSRS, and the percentage of lifetime suicidal ideation between the 2 groups. Linear regression models with IA as a dependent variable and academic satisfactory as an independent variable was performed to examine the main effects of IA and academic satisfactory as well as their interaction on mental health problems (depression, anxiety and insomnia). All analyses controlled for demographic (i.e., age, sex, nationality, household registered residence, single child, family income, educational level of father/mother, smoking, drinking, family history of psychosis, history of psychotic disorder, marital status of parents, and parenting style) in order to adjust for potential variation in study variables attributed to these characteristics. SPSS (version 22.0) was used for data analysis. The threshold for statistical significance was set at 2-sided, p < 0.05.
ResultDemographic information
There were 22,605 college students finished the survey in total, which includes 7,684 participants (34%, age = 19.14 ± 1.224, Female = 64.9%) in the without IA group, and 11,969 participants (66%, age = 19.09 ± 1.198, Female = 64.9%) in the with IA group (Table 1). Compared with participants in the without IA group, participants in the with IA group had significantly higher percentage of Han nationality (87.8% vs. 89.3%), smoking (6.8% vs. 7.6%), drinking (15.4% vs. 20.1%), family history of psychosis (0.6% vs. 1.1%), history of psychotic disorder (4.1% vs. 6.9%), infection of COVID-19 (33.1% vs. 38.2%), and quarantine experience (34.8% vs. 38.7%) (p < 0.001). Participants in the with IA group had significantly lower percentage of progress (22% VS 15.7%) and higher retrogression (33.1% VS 50.8%) in academic performance and high percentage of academy unsatisfaction than those in the without IA group (7.1% VS 15.6%) (p < 0.001).
Demographic characteristics of the participants.
Total (N = 22,605)
Without internet addiction (N = 7,684)
With internet addiction (N = 14,921)
p
Age
19.1 ± 1.207
19.14 ± 1.224
19.09 ± 1.198
<0.05
Sex
>0.05
Male (%)
7,927 (35.1)
2,688 (35.0)
5,239 (35.1)
Female (%)
14,678 (64.9)
4,996 (65.0)
9,682 (64.9)
Grade
>0.05
Grade 1 (%)
13,958 (61.7)
4,710 (61.3)
9,248 (62.0)
Grade 2 (%)
6,493 (28.7)
2,245 (29.2)
4,248 (28.5)
Grade 3 (%)
1,845 (8.2)
631 (8.2)
1,214 (8.1)
Grade 4 and 5 (%)
309 (1.4)
98 (1.3)
211 (1.4)
Nationality
<0.001
Han (%)
20,078 (88.8)
6,750 (87.8)
13,328 (89.3)
Other (%)
2,527 (11.2)
934 (12.2)
1,593 (10.7)
Registered residence
>0.05
Rural (%)
17,921 (79.3)
6,108 (79.5)
11,813 (79.2)
Urban (%)
4,684 (20.7)
1,576 (20.5)
3,108 (20.8)
Single-child
>0.05
Yes (%)
5,455 (24.1)
1,885 (24.5)
3,570 (23.9)
No (%)
17,150 (75.9)
5,799 (75.5)
11,351 (76.1)
Romantic relationship status
>0.05
Single (%)
16,535 (73.1)
5,615 (73.1)
10,920 (73.2)
Have a lover (%)
6,070 (26.9)
2,069 (26.9)
4,001 (26.8)
Family income (monthly)
>0.05
<2040 RMB (%)
5,271 (23.3)
1,824 (23.7)
3,447 (23.1)
2040–4,999 RMB (%)
8,931 (39.5)
3,096 (40.3)
5,835 (39.1)
5,000–9,999 RMB (%)
5,572 (24.6)
1,843 (24.0)
3,729 (25.0)
>10,000 RMB (%)
2,831 (12.5)
921 (12.0)
1,910 (12.8)
Education level of Father
<0.05
Primary school and below (%)
7,729 (34.2)
2,687 (35.0)
5,042 (33.8)
Middle school (%)
9,313 (41.2)
3,124 (40.7)
6,189 (41.5)
High school (%)
3,638 (16.1)
1,262 (16.3)
2,376 (15.9)
College and above (%)
1,925 (8.5)
611 (8.0)
1,314 (8.8)
Education level of Mother
>0.05
Primary school and below (%)
10,110 (44.7)
3,465 (45.1)
6,645 (44.5)
Middle school (%)
8,228 (36.4)
2,768 (36.0)
5,460 (36.6)
High school (%)
2,943 (13.0)
1,002 (13.0)
1,941 (13.0)
College and above (%)
1,324 (5.9)
449 (5.8)
875 (5.9)
Smoking
<0.001
Yes (%)
1,654 (7.3)
523 (6.8)
1,131 (7.6)
No (%)
20,951 (92.7)
7,161 (93.2)
13,790 (92.4)
Drinking
<0.001
Yes (%)
4,177 (18.5)
1,180 (15.4)
2,997 (20.1)
No (%)
18,428 (81.5)
6,504 (84.6)
11,924 (79.9)
Family history of psychosis
<0.001
Positive (%)
217 (1.0)
46 (0.6)
171 (1.1)
Negative (%)
22,388 (99.0)
7,638 (99.4)
14,750 (98.9)
History of psychotic disorder
<0.001
Positive (%)
1,352 (6.0)
317 (4.1)
1,035 (6.9)
Negative (%)
21,253 (94.0)
7,367 (95.9)
13,886 (93.1)
Marital status of parents
>0.05
Unmarried (%)
381 (1.7)
113 (1.5)
268 (1.8)
Married (%)
18,544 (82.0)
6,333 (82.4)
12,211 (81.8)
Divorced (%)
1,929 (8.5)
649 (8.4)
1,280 (8.6)
Remarried (%)
1,313 (5.8)
444 (5.8)
869 (5.8)
Other (%)
438 (1.9)
145 (1.9)
293 (2.0)
Parenting style
<0.001
Authoritative (%)
10,913 (48.3)
4,296 (55.9)
6,617 (44.3)
Autocratic (%)
4,921 (21.8)
1,454 (18.9)
3,467 (23.2)
Ignorant (%)
2,534 (11.2)
650 (8.5)
1,884 (12.6)
Submissive (%)
4,237 (18.7)
1,284 (16.7)
2,953 (19.8)
Infection of COVID-19
<0.001
Yes (%)
8,241 (36.5)
2,542 (33.1)
5,699 (38.2)
No (%)
14,364 (63.5)
5,142 (66.9)
9,222 (61.8)
Quarantine experience
<0.001
Yes (%)
8,446 (37.4)
2,676 (34.8)
5,770 (38.7)
No (%)
14,159 (62.6)
5,008 (65.2)
9,151 (61.3)
Academic achievement
<0.001
Progress
4,032 (17.8)
1,687 (22.0)
2,345 (15.7)
Unaffected
8,456 (37.4)
3,456 (45.0)
5,000 (33.5)
Retrogression
10,117 (44.8)
2,541 (33.1)
7,576 (50.8)
Academic satisfaction
<0.001
Exceptional
1,561 (6.9)
744 (9.7)
817 (5.5)
Good
4,310 (19.1)
2,044 (26.6)
2,266 (15.2)
Satisfactory
13,282 (58.8)
4,267 (55.5)
9,015 (60.4)
Unsatisfactory
2,871 (12.7)
542 (7.1)
2,329 (15.6)
Very unsatisfactory
581 (2.6)
87 (1.1)
494 (3.3)
Comparison of mental health problems between the two groups
As shown in Table 2, compared with participants with IA group, participants without IA group had significantly lower mean scores of PHQ-9 (T = −53.336, p < 0.001), GAD-7 (T = −48.479, p < 0.001), and ISI (T = −48.309, p < 0.001), higher mean scores of SSRS (T = 29.402, p < 0.001), and lower percentage of lifetime suicidal ideation (χ2 = 504.815, p < 0.001). As shown in Figure 1, the higher the level of IA, the severe the depression symptom, anxiety symptom and sleep problem the participants reported, and the lower level of social support they received (p < 0.05).
Comparison of mental health problems between the two groups.
Total (N = 22,605)
Without IA (N = 7,684)
With IA (N = 14,921)
T/χ2
PHQ-9
4.45 ± 5.7
1.79 ± 3.569
5.82 ± 6.095
−53.336a***
GAD-7
3.06 ± 4.591
1.1 ± 4.07
4.07 ± 4.99
−48.479a***
ISI
6.11 ± 6.169
3.48 ± 4.795
7.46 ± 6.358
−48.309a***
SSRS
35.98 ± 7.624
38.02 ± 7.845
34.93 ± 7.288
29.402a***
Suicidal ideation
5,741 (25.4)
1,255 (16.3)
4,486 (30.1)
504.815b***
IA, internet addiction; ***, p < 0.001.
Two-sample t test.
Chi-square test.
Comparison of mental health among different level of internet addiction. The figure showed that the higher the level of IA, the severe the depression symptom, anxiety symptom and sleep problem the participants reported, and the lower level of social support they received (p < 0.05).
Interacting effects of IA and academic satisfaction on mental health
As shown in Figure 2, an effect of IA was found on depression (t = 12.85, p < 0.001, B = 0.077, 95% CI: 0.065–0.089), anxiety (t = 11.1, p < 0.001, B = 0.05, 95% CI: 0.045–0.064) and insomnia (t = 15.46, p < 0.001, B = 0.1, 95% CI: 0.09–0.12). Participants with higher score of IA had more serious mental health problem. Furthermore, an effect of academic satisfactory was found on anxiety (t = −2.81, p = 0.005, B = -0.25, 95% CI: −0.450–0.760) and insomnia (t = 3.96, p < 0.001, B = 0.48, 95% CI: 0.240–0.710). Participants with lower level of academic satisfactory had more serious symptom of anxiety and insomnia. However, there was no effect of academic satisfactory on symptoms of depression. There was significant interaction between IA and academic satisfactory on symptoms of depression (t = 10.27, p < 0.001, B = 0.021, 95% CI: 0.017–0.025), anxiety (t = 10.22, p < 0.001, B = 0.017, 95% CI: 0.014–0.02) and insomnia (t = 3.93, p < 0.001, B = 0.008, 95% CI: 0.004–0.013).
The interact impact of internet addiction and academic satisfactory on mental health problems. (A) An effect of IA on depression (t = 12.85, p < 0.001, B = 0.077, 95% CI: 0.065; 0.089), and a significant interaction between IA and academic satisfactory on depression (t = 10.27, p < 0.001, B = 0.021, 95% CI: 0.017; 0.025). (B) An effect of IA on anxiety (t = 11.1, p < 0.001, B = 0.05, 95% CI: 0.045; 0.064) and an effect of academic satisfactory on anxiety (t = −2.81, p = 0.005, B = −0.25, 95% CI: −0.45; −0.76). Significant interaction between IA and academic satisfactory on anxiety (t = 10.22, p < 0.001, B = 0.017, 95% CI: 0.014; 0.02). (C) An effect of IA on insomnia (t = 15.46, p < 0.001, B = 0.1, 95% CI: 0.09; 0.12) and an effect of academic satisfactory on insomnia (t = 3.96, p < 0.001, B = 0.48, 95% CI: 0.24; 0.71). Significant interaction between IA and academic satisfactory on insomnia (t = 3.93, p < 0.001, B = 0.008, 95% CI: 0.004; 0.013). AS, academic satisfactory.
Discussion
This study investigated the relationship between IA and mental health problems in college students after the lifting of COVID-19 restrictions in Sichuan, China. The study showed that college students with IA were more likely to have depression symptom, anxiety symptom, insomnia, and lifetime suicidal ideation than those without IA. Importantly, participants with higher level of IA would experience more severe mental health problems (e.g., depression, anxiety, insomnia, and suicidal ideation) and receive fewer social support. Further, the study revealed that participants with higher level of IA, combining with lower level of academic satisfaction were more likely to have depression symptom, anxiety symptom and insomnia.
Compared with those without IA, participants with IA were more likely to have depression symptom, anxiety symptom, insomnia, and lifetime suicidal ideation, which is consistent with previous studies (23, 29, 34). Evidence shows that IA is often comorbid with various mental health problems such as suicidal ideation (34), sleep problems (35, 36), depression, and anxiety (23, 37). Previous studies also reveal that IA, specifically addictive gaming, may be linked to diminished sleep quality and reduced sleep duration, subsequently leading to the sleep-related issues (38). Cognitive-behavioral model of IA (34) and the theory for problematic internet use (38) illustrate that individuals suffering from psychological distress (such as depression) may be more likely to be frustrated in real life, and they would choose turn to the internet to make them feel safe and comfortable. Thus, it is important to prevent IA and reduce psychological distress after the COVID-19 pandemic for maintaining normal social activities and functioning among college students.
The results of this study showed that college students with IA had significantly higher rate of family history of psychosis than those without IA, which is consistent with previous study (34). Evidence suggests that there is a significant association between parental depression and IA in young people (39). Compared to young people with mild IA or without IA, those with moderate to severe IA have three times higher risks of parents with moderate to severe depression (40). Parental depression may contribute to adolescent stress, which in turn can lead to adolescent internet addiction (40). Moreover, parent with IA may have a significant negative effect on their offspring (41, 42). Therefore, characteristics and mental health problems of parents should also be considered and addressed for education and psychosocial interventions for reducing IA and improving mental health of college students.
This study revealed that participants with higher level of IA would experience more severe mental health problems, which might be explained by the mechanism of IA. IA, a behavioral addiction, shares several similar traits with gambling disorder (33), and more importantly, it also shares the similar addictive patterns in neurobiology (43–45). Evidence has shown that IA would contribute to a release of dopamine at a rapid rate, which may lead to immediate gratification and the potential for a repetitive response, including compulsive behaviors and increased tolerance (46). In fMRI studies, dysregulated reward processing and diminished impulse control were found in people with IA (47). Thus, more serious IA might imply the development of organic pathologies, so youth with IA needs to early intervention and prevention in advance.
This is the first study to reveal the interaction between IA and academic satisfaction on mental health problems. The study showed that the higher degree of IA, combining with the lower academic satisfaction would contribute to mental health problems such as depression, anxiety, and insomnia. Previous studies indicated that IA could be seen as a maladaptive coping strategy to deal with problematic conditions of students (48). Those problematic conditions could include challenges in interpersonal interactions, such as difficulties in establishing and maintaining friendships (48) and dysfunctional familial relationships (18). And in this study, students with IA had higher level of academic unsatisfaction. Evidence shows that escapism by means of immersion has the strongest association with addictive behaviors (49). Therefore, this study suggests that students with IA may not only escape from the problematic relationships, but also from the failure of academic performance. On the other hand, IA has also impaired students’ academic satisfaction (18). IA and academic satisfaction might create a vicious cycle: IA might lead to the decrease of cognitive function (22) and academic procrastination (50, 51), and it would further lead to poor academic performance, which in turn lead to the escapism. Thus, to break this vicious cycle, it is necessary to prevent IA and improve students’ academic studies. More importantly, it is important to address the problems that cause the IA to escape into internet world, which means that the educational institutes, schools and parents need to help students with their academic performance.
Strengths and limitations
To our knowledge, this is the first study to explore the college students’ IA and the mental health problems after the lifting of COVID-19 restrictions in China. Also, this study has a large sample size of students in different colleges and universities from freshmen to senior students in Sichuan, China. The response rate of the survey was very high (92.0%). Moreover, the questionnaire of the survey was released to students directly through their teachers and professors, which may improve the quality of data collection.
This study also has a few limitations. This study was conducted only in Sichuan province, China, which may not generalize the results of college students to other areas of China. This study is a cross-sectional design, and no causal associations should be inferred. Further long-term follow-up studies on IA and mental health among college students should be conducted.
Conclusion
This initial study aimed to investigate the college students’ IA and the mental health problems during and after the COVID-19 pandemic. The results of this study showed that IA had a significant negative impact on the mental health problems among Chinese college students. The college students with IA were more likely to have depression, anxiety, insomnia, and suicidal ideation. And college students with serious IA would have more severe mental health problems (e.g., depression, anxiety, insomnia, and suicidal ideation) and lower level of social support. The study also firstly shows that IA and academic satisfactory have interact impacts on mental health problems among college students. Further educational and health policies and psychosocial interventions should be developed to reduce IA and enhance academic satisfaction for improving students’ mental health. Longitudinal studies should be conducted in the future to further clarify the causal relationship among IA, academic satisfaction and mental health problems.
Data availability statement
The original contributions presented in the study are included in the article/supplementary materials, further inquiries can be directed to the corresponding author.
Ethics statement
The studies involving humans were approved by Biomedical Research Ethics Committee of West China Hospital, Sichuan University (No: 2022-1790). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants’ legal guardians/next of kin.
Author contributions
M-SR designed this study. M-SR, A-PD, JaC, Z-YD, CW, Y-FM, H-JS, YH, and WZ conducted this study. A-PD, CW, JaC, M-SR, and Z-YD conducted data analysis. A-PD, CW, JaC, and M-SR wrote the first draft of the paper. A-PD, CW, JaC, Z-YD, Y-FM, H-JS, Y-JM, X-DM, X-HH, LZ, YH, WZ, JnC, and M-SR participated in the data collection and made contributions to critical revision of the manuscript. All authors contributed to the article and approved the submitted version.
Funding
Initial Research Fund, West China Hospital (WCH, No: 136220012, PI: M-SR). The funder had no role in the design and conduct of the study, collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
We thank all participants and their teachers and professors for their help and willingness to participate in the study and the time that they devoted to the study.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
ReferencesEditorial. Social media, screen time, and young people’s mental health. Lancet. (2019) 393:611. doi: 10.1016/S0140-6736(19)30358-7RubinR. Too much screen time for young children, experts say. JAMA. (2020) 323:300. doi: 10.1001/jama.2019.21854, PMID: 31990299GuoWTaoYLiXLinXMengYYangX. Associations of internet addiction severity with psychopathology, serious mental illness, and suicidality: large-sample cross-sectional study. J Med Internet Res. (2020) 22:e17560. doi: 10.2196/17560, PMID: 32780029FinebergNAMenchónJMHallNDell’OssoBBrandMPotenzaMN. Advances in problematic usage of the internet research – a narrative review by experts from the European network for problematic usage of the internet. Compr Psychiatry. (2022) 118:152346. doi: 10.1016/j.comppsych.2022.152346, PMID: 36029549AlshammariTAlserayeSRogowskaAAlrasheedNAlshammariM. Examining the indirect effect of online gaming on depression via sleep inequality and anxiety-a serial and parallel mediation analysis. J Clin Med. (2022) 11:7293. doi: 10.3390/jcm11247293, PMID: 36555910AlimoradiZLinCYBroströmABülowPHBajalanZGriffithsMD. Internet addiction and sleep problems: a systematic review and meta-analysis. Sleep Med Rev. (2019) 47:51–61. doi: 10.1016/j.smrv.2019.06.004, PMID: 31336284MengSQChengJLLiYYYangXQZhengJWChangXW. Global prevalence of digital addiction in general population: a systematic review and meta-analysis. Clin Psychol Rev. (2022) 92:102128. doi: 10.1016/j.cpr.2022.102128, PMID: 35150965DiotaiutiPGirelliLManconeSCorradoSValenteGCavicchioloE. Impulsivity and depressive brooding in internet addiction: a study with a sample of Italian adolescents during COVID-19 lockdown. Front Psych. (2022) 13:941313. doi: 10.3389/fpsyt.2022.941313, PMID: 35898621HaoQHPengWWangJTuYLiHZhuTM. The correlation between internet addiction and interpersonal relationship among teenagers and college students based on Pearson’s correlation coefficient: a systematic review and meta-analysis. Front Psych. (2022) 13:818494. doi: 10.3389/fpsyt.2022.818494, PMID: 35356718TatenoMTeoARShiraishiMTayamaMKawanishiCKatoTA. Prevalence rate of internet addiction among Japanese college students: two cross-sectional studies and reconsideration of cut-off points of Young’s internet addiction test in Japan. Psychiatry Clin Neurosci. (2018) 72:723–30. doi: 10.1111/pcn.12686, PMID: 29845676YangJFuXLiaoXLiY. Association of problematic smartphone use with poor sleep quality, depression, and anxiety: a systematic review and meta-analysis. Psychiatry Res. (2020) 284:112686. doi: 10.1016/j.psychres.2019.112686, PMID: 31757638ChungJSChoiELeeARKimSYLeeKKimBN. The difference in sleep, depression, anxiety, and internet addiction between Korean adolescents with different circadian preference. Indian J Psychiatry. (2020) 62:524–30. doi: 10.4103/psychiatry.IndianJPsychiatry_254_19, PMID: 33678833SunYLiYBaoYMengSSunYSchumannG. Brief report: increased addictive internet and substance use behavior during the COVID-19 pandemic in China. Am J Addict. (2020) 29:268–70. doi: 10.1111/ajad.13066, PMID: 32500608ZhongYMaHLiangYFLiaoCJZhangCCJiangWJ. Prevalence of smartphone addiction among Asian medical students: a meta-analysis of multinational observational studies. Int J Soc Psychiatry. (2022) 68:1171–83. doi: 10.1177/00207640221089535, PMID: 35422151LiLWangYYWangSBZhangLLiLXuDD. Prevalence of sleep disturbances in Chinese university students: a comprehensive meta-analysis. J Sleep Res. (2018) 27:e12648. doi: 10.1111/jsr.12648, PMID: 29383787WangHLuoWHuangWXiangHChenSLinW. How sleep duration mediated childhood trauma and internet addiction of the vocational college population in urban areas of South China. Front Psych. (2023) 13:1088172. doi: 10.3389/fpsyt.2022.1088172, PMID: 36713913TereshchenkoSKasparovESmolnikovaMShubinaMGorbachevaNMoskalenkoO. Internet addiction and sleep problems among Russian adolescents: a field school-based study. Int J Environ Res Public Health. (2021) 18:10397. doi: 10.3390/ijerph181910397, PMID: 34639694DouDShekDTL. Predictive effect of internet addiction and academic values on satisfaction with academic performance among high school students in mainland China. Front Psychol. (2021) 12:797906. doi: 10.3389/fpsyg.2021.797906, PMID: 35069391TaylorSPattara-AngkoonSSiriratSWoodsD. The theoretical underpinnings of internet addiction and its association with psychopathology in adolescence. Int J Adolesc Med Health. (2017) 31:20170046. doi: 10.1515/ijamh-2017-0046, PMID: 28682784TanYChenYLuYLiL. Exploring associations between problematic internet use, depressive symptoms and sleep disturbance among southern Chinese adolescents. Int J Environ Res Public Health. (2016) 13:313. doi: 10.3390/ijerph13030313, PMID: 26985900RainaGBhattS. Effect of internet addiction on mental health of adolescent boys and girls. Indian J Ment Health. (2021) 8:218–30.SetyaningsihILeksonoABBMuhrodjiPEdyantoASVidyantiAN. Adolescents with internet gaming disorder are more likely to have lower score of cognitive function: a cross-sectional study among junior high school students in Yogyakarta, Indonesia. Open Access Maced J Med Sci. (2021) 9:1111–6. doi: 10.3889/oamjms.2021.6858DouDShekDTL. Concurrent and longitudinal relationships between positive youth development attributes and adolescent internet addiction symptoms in Chinese mainland high school students. Int J Environ Res Public Health. (2021) 18:1937. doi: 10.3390/ijerph18041937, PMID: 33671277KroenkeKSpitzerRLWilliamsJB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. (2001) 16:606–13. doi: 10.1046/j.1525-1497.2001.016009606.x, PMID: 11556941ShiLLuZAQueJYHuangXLLiuLRanMS. Prevalence of and risk factors associated with mental health symptoms among the general population in China during the coronavirus disease 2019 pandemic. JAMA Netw Open. (2020) 3:e2014053. doi: 10.1001/jamanetworkopen.2020.14053, PMID: 32609353SongHJMuYFWangCCaiJDengZYDengAP. Academic performance and mental health among Chinese middle and high school students after the lifting of COVID-19 restrictions. Front Psych. (2023) 14:1248541. doi: 10.3389/fpsyt.2023.1248541, PMID: 37645634SpitzerRLKroenkeKWilliamsJBLöweB. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. (2006) 166:1092–7. doi: 10.1001/archinte.166.10.1092HeXLiCQianJCuiHSWuWY. Reliability and validity of a generalized anxiety disorder scale in general hospital outpatients. Shanghai Arch Psychiatry. (2010) 22:200–3. doi: 10.3969/j.issn.1002-0892.2010.04.002BastienCHVallièresAMorinCM. Validation of the insomnia severity index as an outcome measure for insomnia research. Sleep Med. (2001) 2:297–307. doi: 10.1016/S1389-9457(00)00065-4LiYYSunYMengSQBaoYPChengJLChangXW. Internet addiction increases in the general population during COVID-19: evidence from China. Am J Addict. (2021) 30:389–97. doi: 10.1111/ajad.13156, PMID: 33738888MoonSJHwangJSKimJYShinALBaeSMKimJW. Psychometric properties of the internet addiction test: a systematic review and meta-analysis. Cyberpsychol Behav Soc Netw. (2018) 21:473–84. doi: 10.1089/cyber.2018.0154, PMID: 30110200LaiCMMakKKWatanabeHAngRPPangJSHoRC. Psychometric properties of the internet addiction test in Chinese adolescents. J Pediatr Psychol. (2013) 38:794–807. doi: 10.1093/jpepsy/jst022, PMID: 23671059HuangYLuoDChenXZhangDHuangZXiaoS. HIV-related stress experienced by newly diagnosed people living with HIV in China: a 1-year longitudinal study. Int J Environ Res Public Health. (2020) 17:2681. doi: 10.3390/ijerph17082681, PMID: 32295107ShenYMengFXuHLiXZhangYHuangC. Internet addiction among college students in a Chinese population: prevalence, correlates, and its relationship with suicide attempts. Depress Anxiety. (2020) 37:812–21. doi: 10.1002/da.23036BenerAYildirimETorunPÇatanFBolatEAlıçS. Internet addiction, fatigue, and sleep problems among adolescent students: a large-scale study. Int J Ment Heal Addict. (2019) 17:959–69. doi: 10.1007/s11469-018-9937-1JainASharmaRGaurKLYadavNSharmaPSharmaN. Study of internet addiction and its association with depression and insomnia in university students. J Family Med Prim Care. (2020) 9:1700–6. doi: 10.4103/jfmpc.jfmpc_1178_19, PMID: 32509675GaoTQinZHuYFeiJCaoRLiangL. Trajectories of depression and anxiety in Chinese high school freshmen: associations with internet addiction. J Affect Disord. (2021) 286:180–6. doi: 10.1016/j.jad.2021.02.074LamLT. Internet gaming addiction, problematic use of the internet, and sleep problems: a systematic review. Curr Psychiatry Rep. (2014) 16:444. doi: 10.1007/s11920-014-0444-1, PMID: 24619594LamLT. Parental mental health and internet addiction in adolescents. Addict Behav. (2015) 42:20–3. doi: 10.1016/j.addbeh.2014.10.033LamLT. The roles of parent-and-child mental health and parental internet addiction in adolescent internet addiction: does a parent-and-child gender match matter?Front Public Health. (2020) 8:142. doi: 10.3389/fpubh.2020.00142, PMID: 32500052LamLTWongEMY. Stress moderates the relationship between problematic internet use by parents and problematic internet use by adolescents. J Adolesc Health. (2015) 56:300–6. doi: 10.1016/j.jadohealth.2014.10.263, PMID: 25703319LuLLiuMGeBBaiZLiuZ. Adolescent addiction to short video applications in the mobile internet era. Front Psychol. (2022) 13:893599. doi: 10.3389/fpsyg.2022.893599, PMID: 35619797CaiHZhaoYJHeFLiSYLiZLZhangWY. Internet addiction and residual depressive symptoms among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic: a network analysis perspective. Transl Psychiatry. (2023) 13:186. doi: 10.1038/s41398-023-02468-5, PMID: 37270593KussDJ. Internet gaming addiction: current perspectives. Psychol Res Behav Manag. (2013) 6:125–37. doi: 10.2147/PRBM.S39476SpekmanMLCKonijnEARoelofsmaPHMPGriffithsMD. Gaming addiction, definition and measurement: a large-scale empirical study. Comput Hum Behav. (2013) 29:2150–5. doi: 10.1016/j.chb.2013.05.015SussmanCJHarperJMStahlJLWeigleP. Internet and video game addictions: diagnosis, epidemiology, and neurobiology. Child Adolesc Psychiatr Clin N Am. (2018) 27:307–26. doi: 10.1016/j.chc.2017.11.015Fauth-BühlerMMannK. Neurobiological correlates of internet gaming disorder: similarities to pathological gambling. Addict Behav. (2017) 64:349–56. doi: 10.1016/j.addbeh.2015.11.004, PMID: 26621112FontanaABenziIMACipressoP. Problematic internet use as a moderator between personality dimensions and internalizing and externalizing symptoms in adolescence. Curr Psychol. (2023) 42:19419–28. doi: 10.1007/s12144-021-02409-9, PMID: 35068906HussainZGriffithsMDBaguleyT. Online gaming addiction: classification, prediction and associated risk factors. Addict Res Theory. (2012) 20:359–71. doi: 10.3109/16066359.2011.640442TiZZhangLYanJ. Analysis and management of academic procrastination behavior of students with internet addiction. Adv Soc Sci Educ Humanit Res. (2022) 635:381–4. doi: 10.2991/assehr.k.220107.074Aznar-DíazIRomero-RodriguezJMGarcia-GonzalezARamirez-MontoyaMS. Mexican and Spanish university students’ internet addiction and academic procrastination: correlation and potential factors. PLoS One. (2020) 15:e0233655. doi: 10.1371/journal.pome.0233655, PMID: 32442238