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ORIGINAL RESEARCH article

Front. Psychiatry, 16 September 2021
Sec. Public Mental Health
This article is part of the Research Topic Impact of Excessive Internet Use on Children and Adolescents’ Mental Health View all 5 articles

Prevalence of Internet Addiction Disorder and Its Correlates Among Clinically Stable Adolescents With Psychiatric Disorders in China During the COVID-19 Outbreak

\nZong-Lei Li&#x;Zong-Lei Li1Rui Liu&#x;Rui Liu2Fan He&#x;Fan He2Shu-Ying Li&#x;Shu-Ying Li3Yan-Jie Zhao,,&#x;Yan-Jie Zhao4,5,6Wu-Yang ZhangWu-Yang Zhang3Yao ZhangYao Zhang3Teris CheungTeris Cheung7Todd JacksonTodd Jackson8Yi-Lang Tang,
Yi-Lang Tang9,10*Yu-Tao Xiang,,
Yu-Tao Xiang4,5,6*
  • 1Department of Psychiatry, Xiamen Xianyue Hospital, Xiamen, China
  • 2Beijing Key Laboratory of Mental Disorders Beijing Anding Hospital, The Advanced Innovation Center for Human Brain Protection, The National Clinical Research Center for Mental Disorders, School of Mental Health, Capital Medical University, Beijing, China
  • 3Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
  • 4Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, Macao SAR, China
  • 5Centre for Cognitive and Brain Sciences, University of Macau, Macao, Macao SAR, China
  • 6Institute of Advanced Studies in Humanities and Social Sciences, University of Macau, Macao, Macao SAR, China
  • 7School of Nursing, Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China
  • 8Department of Psychology, University of Macau, Macao, Macao SAR, China
  • 9Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
  • 10Mental Health Service Line, Atlanta VA Medical Center, Decatur, GA, United States

Background: Since the Coronavirus disease 2019 (COVID-19) pandemic emerged, Internet usage has increased among adolescents. Due to this trend, the prevalence of Internet addiction disorder (IAD) may have increased within this group. This study examined the prevalence of IAD and its correlates among clinically stable adolescents with psychiatric disorders in China during the COVID-19 outbreak.

Method: A multi-center, cross-sectional study was carried out between April 29 and June 9, 2020 in three major tertiary mental health centers in China. IAD and depressive symptoms were assessed using the Internet Addiction Test (IAT) and the 9-item Patient Health Questionnaire (PHQ-9), respectively.

Results: A total of 1,454 adolescent psychiatric patients were included in final analyses. The prevalence of IAD was 31.2% (95% CI: 28.8–33.6%) during the COVID-19 pandemic. A multiple logistic regression analysis revealed that poor relationships with parents (P < 0.001, OR = 2.34, 95%CI: 1.49–3.68) and elevated total PHQ-9 scores (P < 0.001, OR = 1.19, 95%CI: 1.16–1.21) were significantly associated with higher risk for IAD while longer daily physical exercise durations (P = 0.04, OR = 0.67, 95%CI: 0.46–0.98) and rural residence (P = 0.003, OR = 0.62, 95%CI: 0.46–0.85) were significant correlates of lower risk for IAD.

Conclusions: IAD was common among adolescent patients with clinically stable psychiatric disorders during the COVID-19 pandemic; regular physical exercise, healthy relationships with parents and fewer symptoms of depression were associated with lower risk within this population.

Introduction

The Coronavirus disease 2019 (COVID-19) pandemic is an international public health emergency that has negatively impacted many aspects of human life worldwide (1, 2). Because COVID-19 is highly contagious, a range of emergency public health measures has been adopted such as universal masking, social distancing, lockdowns, school closures, and public transportation suspension, all of which might have effects on the mental health and behavior of affected people, including adolescents (38). For instance, large-scale social quarantine/isolation during the pandemic with “forced” overexposure to the Internet may increase the risk for Internet addiction disorder (IAD) (9); additionally, adolescents typically spent more time on the Internet to study, play games, and chat with friends during the pandemic (10); these experiences have received growing attention as influences on IAD in adolescents during the COVID-19 pandemic.

IAD is among the most common mental health problems in adolescents (11). A previous study reported that the prevalence of IAD was 19.8% among mainland Chinese adolescents based on the Young's Internet Addiction Test (IAT) (12). A meta-analysis found the pooled prevalence of IAD was 11.3% in Chinese university students (13). A recent study on IAD during the COVID-19 epidemic found the prevalence of IAD was 2.68% based on the IAT while the corresponding figure for problematic internet use was 33.37% in a sample of 2,050 school-age children and adolescents in China (10). In another study on IAD among 1,060 junior high school students in Taiwan during the COVID-19 outbreak, the prevalence of IAD was 24.4% based on the Chen Internet Addiction Scale (14).

Regarding correlates of IAD, psychiatric disturbances including major depressive disorder (MDD), bipolar disorder (BD), insomnia, and attention-deficit hyperactivity disorder (ADHD) are common comorbid diagnoses (1518). Prior studies have reported the prevalence of IAD that among child and adolescent psychiatric patients ranged from 11.3 to 24.1% (17, 19, 20). To date, however, little is known about rates of IAD in clinically stable adolescents with psychiatric disorders during the COVID-19 pandemic.

The Internet has been used widely among patients with psychiatric disorder via computers, smartphones or other devices (2124). The internet offers non-traditional options for access to information and communication, and has been linked to reduced stress, anxiety and/or depressive symptoms in select studies (21, 25, 26). For many clinically stable adolescent patients with psychiatric disorders, maintenance pharmacotherapy is required. On the one hand, during the COVID-19 pandemic, these adolescents have limited access to mental health services, and the internet has been used as a helpful alternative resource (27) that could prolong time on the internet. On the other hand, overuse of the internet without effective control measures could result in IAD and contribute to exacerbations in disturbances among adolescents with psychiatric disorders (28). Previous studies have found that excessive internet use in the form of an addiction is related to the perpetuation of social anxiety, exacerbations in emotional distress and increased interference with daily functioning (29).

In order to reduce potential negative consequences of IAD for daily life and academic performance of psychiatrically vulnerable adolescents living through a pandemic, it is important to understand its frequency and correlates. Therefore, we conducted this study to examine the prevalence of IAD and its associated factors in clinically stable mainland Chinese adolescents with psychiatric disorders during the COVID-19 outbreak.

Methods

Patients and Study Sites

A multi-center, cross-sectional study was carried out between April 29 and June 9, 2020 in three major tertiary mental health centers for children and adolescents, located in the northern (Beijing), southern (Fujian province), and central regions of China (Hunan province, Hubei province). These hospitals represent a range of clinical settings in China. Due to the risk of transmission, traditional face-to-face interviews could not be conducted. Instead, following other studies (12, 27) data were collected using the WeChat-based Questionnaire Star application (Changsha Renxing Science and Technology, Shanghai, China). WeChat is a widely used social communication app with more than 1 billion users in China. To be eligible, participants were (1) aged between 10 and 17 years (the age range of adolescents used in participating hospitals), (2) outpatients receiving maintenance treatment for psychiatric disorders, and (3) “clinically stable” based on (i) judgments of treating psychiatrists and (ii) changes in psychotropic medication dosages of <50% during the past 3 months following previous operationalizations in the literature (30, 31), and (4) enrolled after providing personal verbal assent accompanied by guardians' written informed consent. Participants' principal psychiatric disorder according to International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10; (32) were recorded in an electronic medical record system and confirmed by their treating psychiatrists. This study was approved by research ethics committees of the respective hospitals.

Measurements

A pre-designed data form was used to collect information about basic socio-demographic background and clinical characteristics, including age, gender, household (urban/rural), status as only child, guardians' personal income, major medical conditions, principal psychiatric diagnosis (i.e., major depressive disorder (MDD)/bipolar disorder (BD)/ attention deficit hyperactivity disorder (ADHD)/ other diagnoses), perceived academic pressure, relationship with parents, concern about COVID-19, daily physical exercise, mass media use, difficulty seeing psychiatrists, treatment adherence and illness relapse during the COVID-19 outbreak. Treatment adherence was evaluated by a standardized question (“Degree to which the adolescent insisted on taking medicine during the COVID-19 outbreak?”), with options of “poor,” “fair,” and “good.” Illness relapse was assessed by a standardized question (“Degree to which the adolescent has had a relapse during the COVID-19 outbreak?”), with options of “No,” “Symptom worsening, but no relapse”, and “relapse.” Responses to questions on treatment adherence and illness relapse were confirmed by treating psychiatrists. Based on the results of a pilot study, those with assessment time s of less than 2 min were removed as a measure of quality control.

Internet addiction was assessed using the Chinese version of the Internet Addiction Test (IAT) (33, 34). The IAT comprises 20 items, each of which includes response options ranging from 1 (“rarely”) to 5 (“always”). This scale has been validated and widely used to screen internet addiction in Chinese adolescents (34, 35). IAT total scores of ≥50 are considered to reflect “IAD” (35, 36). Severity of depressive symptoms was assessed using the Chinese version of 9-item Patient Health Questionnaire (PHQ-9) (37, 38). Total PHQ-9 scores range from 0 to 27, with higher scores indicating more severe depressive symptoms (3941). The PHQ-9 has satisfactory psychometric properties among adolescents (39, 41). In the current sample Cronbach's alpha value of PHQ-9 was 0.93.

Data Analysis

Data were analyzed using SPSS software, version 24.0. Comparisons of social-demographic and clinical characteristics between patients with vs. patients without IAD were performed using chi-square tests, independent samples t-tests, or Mann-Whitney U tests, as appropriate. A multiple logistic regression analysis with the “enter” method was conducted to explore independent correlates of IAD status. All measures with significant differences in univariate analyses were entered as independent variables, and IAD was the dependent variable. The significance level was set as 0.05 (two-tailed).

Results

A total of 1,570 adolescent patients were invited; of these, 1,454 met all inclusion criteria; their data were subjected to analyses. On the basis of setting, 381 patients (26.2%) were recruited from in Beijing Anding Hospital (Beijing), 576 (39.6%) from the First Affiliated Hospital of Zhengzhou University (Henan province), 243 (16.7%) from Xiamen Xianyue Hospital (Fujian province), and 254 (17.5%) from other parts of China. The prevalence of IAD was 31.2% (95% CI: 28.8–33.6%) in the current sample. Socio-demographic information and clinical characteristics of respondents are presented in Table 1.

TABLE 1
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Table 1. Socio-demographic and clinical characteristics of adolescent patients.

Univariate analyses indicated gender, residence, principal psychiatric diagnosis, PHQ-9 total scores, perceived academic pressure, relationship with parents, concern of COVID-19, daily physical exercise, difficulty seeing psychiatrists, treatment adherence and illness relapse during the COVID-19 outbreak significantly differed between adolescent patients with IAD and those without IAD (all P-values < 0.05).

A multiple logistic regression analysis revealed that poor relationship with parents (P < 0.001, OR = 2.34, 95%CI: 1.49–3.68) and higher PHQ-9 total scores (P < 0.001, OR = 1.19, 95%CI: 1.16–1.21) were significant correlates of higher risk for IAD while longer daily physical exercise durations (P = 0.04, OR = 0.67, 95%CI: 0.46–0.98) and rural residence (P = 0.003, OR = 0.62, 95%CI: 0.46–0.85) were associated with significantly lower risk of IAD (Table 2).

TABLE 2
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Table 2. Independent correlates of IAD by multiple logistic regression analysis.

Discussion

To the best of our knowledge, this is the first study to examine the prevalence and correlates of IAD among clinically stable adolescents with psychiatric disorders in China during the COVID-19 outbreak. We found the prevalence of IAD in this sample was 31.2% (95% CI: 33.6–28.8%). This rate is higher than figures from previous studies using the IAT. For example, the prevalence of IAD was 10.4% among 1,059 Chinese adolescents in Anhui province (42), 26.5% for 6,468 adolescents in Guangzhou (43), and 23.7% (95% CI: 22.1–25.2%) among 2,892 adolescents in a multicenter survey of China (12). Additionally, the prevalence of IAD in this study was higher than rates reported for adolescents with psychiatric disorders. For example, the prevalence of IAD was 20.7% using the Compulsive Internet Use Scale in 111 adolescents receiving inpatient psychiatric care in Austria (17), 24.1% using the IAT among psychiatric adolescent patients in Turkey (20), 11.3% using a standardized instrument for internet addiction in adolescent psychiatric inpatients from Germany (19), and 12.9% (95% CI: 7.6–19.7%) using the IAT in 132 adolescent outpatients with autism spectrum disorder and/or attention-deficit hyperactivity disorder in Japan (44).

Apart from the influence of differences in study sites, sample sizes, measurement tools and/or timeframes of performed research, there are several potential reasons for the relatively high prevalence of IAD in our sample. First, similar to substance use disorders (45), the risk to develop IAD is associated with amount of exposure. Compared to pre-pandemic eras, adolescents, particularly those with psychiatric disorders, may have had more exposure to the internet in active (e.g., playing games, and communications with friends) or passive (e.g., doing homework, and taking online classes) forms during the COVID-19 pandemic. In line with this contention, recent studies have found school-age children spent significantly longer time on the Internet during the pandemic (10, 46). Second, particular residual psychiatric symptoms including lack of confidence, poor self-esteem, and lack of social skills in daily life may contribute to an increased likelihood of excessive Internet use or the development of IAD (35, 47). Some studies have found that certain psychiatric disorders in adolescents (e.g., ADHD, MDD, anxiety disorders) correlate with increased risk of IAD (15, 16, 48, 49). Previous studies on coping have also suggested that the Internet is a common way to release emotions and escape from or avoid real-life problems; such strategies may lead to excessive internet usage, resulting in IAD among adolescents with psychiatric disorders (29, 35, 50).

Similar to previous findings (13, 51, 52), we found that the adolescents in rural areas had a lower risk of IAD. Compared with adolescents living in rural areas, adolescents living in urban areas have greater ease in accessing the Internet through smartphones and computers (13, 53). Furthermore, adolescents living in rural areas more often engaged in housework or farming activities in order to relieve family burdens (54); these experiences can reduce available free time, potentially contributing to less computer exposure (13, 53).

In our multivariate analysis, having 30–60 min/day of physical exercise emerged as a significant correlate of lower risk for IAD among adolescent psychiatric patients during the COVID-19 pandemic. This finding dovetails with a number of studies that underscore regular physical activity and exercise as protective factors against excessive internet use, stress, and negative emotions within general adolescent samples (11, 5557). Coupled with these results, our findings provide foundations for the hypothesis that regular daily physical exercise helps adolescent psychiatric patients to reduce stress, anxiety and fear of the COVID-19 pandemic, and functions as a protective factor against IAD.

Logistic regression analysis results also indicated adolescent psychiatric patients who had poor relationships with their parents were at significantly higher risk for IAD. This finding converges with other evidence linking IAD with family conflict, an overprotective parenting style, reduced parental supervision, and less family communication (5860). Conversely, more harmonious parent-adolescent relationships have positive associations with emotion regulation capacities that serve as a developmental resource that lessens problem behaviors of children (61). In the context of the COVID-19 outbreak, poor parent-adolescent relationships may not have buffering effects against loneliness and insecure feelings of adolescent psychiatric patients (3) who are cut-off from direct personal contact with others and more prone to excessive Internet use and IAD.

Finally, the multivariate model identified more severe depressive symptoms as a correlate of significantly higher risk for IAD among adolescents with psychiatric disorders. This finding is also consistent with other studies (21, 35, 62). Due to fear, helplessness, and stress resulting from the COVID-19 pandemic and a range of preventive measures (e.g., mass lockdowns, home quarantine, prolonged school closure and public transportation suspension) (3) that foster physical isolation between people, adolescents who have more depressive symptoms may use the Internet to obtain social support, enhance self-esteem, and/or distract themselves from negative affect or other stressors in their lives, potentially increasing their risk for IAD. Notably, however, previous studies have documented bidirectional relationships between depression and IAD. On one hand, IAD alone is a risk factor for certain psychiatric disorders (63, 64). On the other hand, the occurrence of psychiatric disorders could increase the likelihood of IAD (65).

Several limitations of this study should be noted. First, as alluded to above, the cross-sectional study design precludes the capacity to make causal statements about the status of IAD as a cause or consequence of associated experiences. Second, for ethical reasons, this study included clinically stable patients, limiting the generalizability of findings to currently less stable patients, a group for whom appropriate clinical care is a priority relative to completing a research study. Third, due to lack of widely accepted diagnostic criteria for IAD, various tools have been used in different studies. Consequently, direct comparisons of IAD patterns between studies and conclusions about prevalence in this literature must be made with caution. Fourth, severity of psychiatric disorders (e.g., BD, ADHD, and others) which may be associated with Internet use behaviors among adolescents and certain potentially relevant correlates of IAD (e.g., residual psychiatric symptoms, social support, sleep quality, physical health, social distancing, duration of lockdowns, time spent on internet for study purposes), were not measured in light of the heavier response burdens that would have been incurred upon unpaid research participants.

In conclusion, this study indicated IAD is common among clinically stable adolescent psychiatric patients during the COVID-19 pandemic. However, within the sample, regular daily physical activity and better perceived relationships with parents emerged as significant behavioral correlates of reduced risk for IAD while elevations in depressive symptoms were correlated with significantly increased risk for IAT. Considering the negative consequences of IAD on daily life and academic performance of adolescents with psychiatric disorders, preventive measures, routine screening, and timely treatments should be undertaken for those at risk during the COVID-19 pandemic. Furthermore, findings are potentially useful for health authorities and mental health professionals toward developing guidelines, designing preventive programs and implementing policies that help clinically stable adolescents with psychiatric disorders to prevent IAD. For example, prevalence data provide useful foundations for policies that may aid in curbing excessive internet use among adolescent psychiatric patients. As well, apart from medication treatment for residual psychiatric symptoms, certain psychosocial interventions such as cognitive behavior therapy and family counseling to improve adolescent-parent relationships could be offered to adolescents at risk for IAD in rehabilitation programs (66). Finally, mental health professionals should be funded to develop appropriate online services to help clinically stable patients reduce feelings of shame, stress and loneliness related to IAD and regulate their internet usage (6).

Data Availability Statement

The Research Ethics Committees of participating hospitals that approved the study prohibits the authors from making the research dataset of clinical studies publicly available. Readers and all interested researchers may contact Dr. Yu-Tao Xiang (Email address: xyutly@gmail.com) for details. Dr. Xiang will apply to the Research Ethics Committee of participating hospitals for the release of the data.

Ethics Statement

The studies involving human participants were reviewed and approved by Beijing Anding Hospital, Xiamen Xianyue Hospital, and First Affiliated Hospital of Zhengzhou University. Participants provided personal verbal assent accompanied by guardians' written informed consent.

Author Contributions

Study design: Z-LL and Y-TX. Data collection, analysis, and interpretation: Z-LL, FH, S-YL, Y-JZ, W-YZ, YZ, and TC. Drafting of the manuscript: RL, Y-TX, and Y-LT. Critical revision of the manuscript: TJ. All authors approved the final version for publication.

Funding

This study was supported by the Beijing Municipal Science & Technology Commission (Z181100001718124), the Beijing Talents Foundation (Grant No.: 2017000021469G222), the University of Macau (MYRG2019-00066-FHS), the Suzhou Key Medical Center for Psychiatric Diseases (Szzx201509), and the Health and Family Planning Key Talents Training Project of Fujian Province (2017-ZQN-93).

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.

References

1. Xiang Y-T, Yang Y, Li W, Zhang L, Zhang Q, Cheung T, et al. Timely mental health care for the 2019 novel coronavirus outbreak is urgently needed. Lancet Psychiatry. (2020) 7:228–9. doi: 10.1016/S2215-0366(20)30046-8

PubMed Abstract | CrossRef Full Text | Google Scholar

2. World Health Organization. (2020). 2019-nCoV Outbreak is an Emergency of International Concern. Avaialbe online at: https://wwweurowhoint/en/health-topics/health-emergencies/coronavirus-covid-19/news/news/2020/01/2019-ncov-outbreak-is-an-emergency-of-international-concern (accessed January 31, 2020).

3. Guessoum SB, Lachal J, Radjack R, Carretier E, Minassian S, Benoit L, et al. Adolescent psychiatric disorders during the COVID-19 pandemic and lockdown. Psychiatry Res. (2020) 291:113264. doi: 10.1016/j.psychres.2020.113264

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Qi H, Liu R, Chen X, Yuan XF, Li YQ, Huang HH, et al. Prevalence of anxiety and associated factors for Chinese adolescents during the COVID-19 outbreak. Psychiatry Clin Neurosci. (2020) 74:555–7. doi: 10.1111/pcn.13102

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Zhou J, Yuan X, Qi H, Liu R, Li Y, Huang H, et al. Prevalence of depression and its correlative factors among female adolescents in China during the coronavirus disease 2019 outbreak. Global Health. (2020) 16:69. doi: 10.1186/s12992-020-00601-3

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Király O, Potenza MN, Stein DJ, King DL, Hodgins DC, Saunders JB, et al. Preventing problematic internet use during the COVID-19 pandemic: consensus guidance. Compr Psychiatry. (2020) 100:152180. doi: 10.1016/j.comppsych.2020.152180

PubMed Abstract | CrossRef Full Text | Google Scholar

7. Kilincel S, Kilincel O, Muratdagi G, Aydin A, Usta MB. Factors affecting the anxiety levels of adolescents in home-quarantine during COVID-19 pandemic in Turkey. Asia Pac Psychiatry. (2021) 13:e12406. doi: 10.1111/appy.12406

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Wasserman D, Carli V, Iosue M, Javed A, Herrman H. Suicide prevention in childhood and adolescence: a narrative review of current knowledge on risk and protective factors and effectiveness of interventions. Asia Pac Psychiatry. (2021):e12452. doi: 10.1111/appy.12452

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Alheneidi H, AlSumait L, AlSumait D, Smith AP. Loneliness and problematic internet use during COVID-19 lock-down. Behav Sci. (2021) 11:5. doi: 10.3390/bs11010005

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Dong H, Yang F, Lu X, Hao W. Internet addiction and related psychological factors among children and adolescents in china during the coronavirus disease 2019 (COVID-19) epidemic. Front Psychiatry. (2020) 11:00751. doi: 10.3389/fpsyt.2020.00751

PubMed Abstract | CrossRef Full Text

11. Masih J, Rajkumar R. Internet addiction disorder and mental health in adolescents. Depress Anxiety. (2019) S13:002. doi: 10.4172/2167-1044.S13-002

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Xu D-D, Lok K-I, Liu H-Z, Cao X-L, An F-R, Hall BJ, et al. Internet addiction among adolescents in Macau and mainland China: prevalence, demographics and quality of life. Sci Rep. (2020) 10:16222. doi: 10.1038/s41598-020-73023-1

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Li L, Xu DD, Chai JX, Wang D, Li L, Zhang L, et al. Prevalence of Internet addiction disorder in Chinese university students: a comprehensive meta-analysis of observational studies. J Behav Addict. (2018) 7:610–23. doi: 10.1556/2006.7.2018.53

PubMed Abstract | CrossRef Full Text | Google Scholar

14. Lin MP. Prevalence of internet addiction during the COVID-19 outbreak and its risk factors among junior high school students in Taiwan. Int J Environ Res Public Health. (2020) 17:8547. doi: 10.3390/ijerph17228547

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Bielefeld M, Drews M, Putzig I, Bottel L, Steinbüchel T, Dieris-Hirche J, et al. Comorbidity of Internet use disorder and attention deficit hyperactivity disorder: two adult case-control studies. J Behav Addict. (2017) 6:490–504. doi: 10.1556/2006.6.2017.073

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Floros G, Siomos K, Stogiannidou A, Giouzepas I, Garyfallos G. Comorbidity of psychiatric disorders with Internet addiction in a clinical sample: the effect of personality, defense style and psychopathology. Addict Behav. (2014) 39:1839–45. doi: 10.1016/j.addbeh.2014.07.031

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Fuchs M, Riedl D, Bock A, Rumpold G, Sevecke K. Pathological internet use—an important comorbidity in child and adolescent psychiatry: prevalence and correlation patterns in a naturalistic sample of adolescent inpatients. BioMed Res Int. (2018) 2018:1629147. doi: 10.1155/2018/1629147

PubMed Abstract | CrossRef Full Text | Google Scholar

18. Kawabe K, Horiuchi F, Ochi M, Oka Y, Ueno S. Internet addiction: prevalence and relation with mental states in adolescents. Psychiatry Clin Neurosci. (2016) 70:405–12. doi: 10.1111/pcn.12402

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Müller KW, Ammerschläger M, Freisleder FJ, Beutel ME, Wölfling K. [Addictive internet use as a comorbid disorder among clients of an adolescent psychiatry—prevalence and psychopathological symptoms]. Z Kinder Jugendpsychiatr Psychother. (2012) 40:331–7; quiz 8–9. doi: 10.1024/1422-4917/a000190

PubMed Abstract | CrossRef Full Text | Google Scholar

20. Yar A, Gündogdu Ö Y, Tural Ü, Memik N. The prevalence of internet addiction in turkish adolescents with psychiatric disorders. Noro Psikiyatr Ars. (2019) 56:200–4. doi: 10.29399/npa.23045

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Kalckreuth S, Trefflich F, Rummel-Kluge C. Mental health related Internet use among psychiatric patients: a cross-sectional analysis. BMC Psychiatry. (2014) 14:368. doi: 10.1186/s12888-014-0368-7

PubMed Abstract | CrossRef Full Text | Google Scholar

22. Morris NP. Internet access for patients on psychiatric units. J Am Acad Psychiatry Law. (2018) 46:224–31. doi: 10.29158/JAAPL.003760-18

PubMed Abstract | CrossRef Full Text | Google Scholar

23. Wong KTG, Liu D, Balzan R, King D, Galletly C. Smartphone and internet access and utilization by people with schizophrenia in south australia: quantitative survey study. JMIR Ment Health. (2020) 7:e11551. doi: 10.2196/11551

PubMed Abstract | CrossRef Full Text | Google Scholar

24. Firth J, Cotter J, Torous J, Bucci S, Firth JA, Yung AR. Mobile phone ownership and endorsement of “mhealth” among people with psychosis: a meta-analysis of cross-sectional studies. Schizophr Bull. (2016) 42:448–55. doi: 10.1093/schbul/sbv132

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Chi X, Liu X, Guo T, Wu M, Chen X. Internet addiction and depression in chinese adolescents: a moderated mediation model. Front Psychiatry. (2019) 10:816. doi: 10.3389/fpsyt.2019.00816

PubMed Abstract | CrossRef Full Text | Google Scholar

26. Shaw LH, Gant LM. In defense of the internet: the relationship between Internet communication and depression, loneliness, self-esteem, and perceived social support. Cyberpsychol Behav. (2002) 5:157–71. doi: 10.1089/109493102753770552

PubMed Abstract | CrossRef Full Text

27. Liu S, Yang L, Zhang C, Xiang Y-T, Liu Z, Hu S, et al. Online mental health services in China during the COVID-19 outbreak. Lancet Psychiatry. (2020) 7:e17–e8. doi: 10.1016/S2215-0366(20)30077-8

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Ko CH, Yen JY, Yen CF, Chen CS, Chen CC. The association between Internet addiction and psychiatric disorder: a review of the literature. Eur Psychiatry. (2012) 27:1–8. doi: 10.1016/j.eurpsy.2010.04.011

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Kuss DJ, Lopez-Fernandez O. Internet addiction and problematic Internet use: a systematic review of clinical research. World J Psychiatry. (2016) 6:143–76. doi: 10.5498/wjp.v6.i1.143

PubMed Abstract | CrossRef Full Text | Google Scholar

30. Xiang Y-T, Weng Y-Z, Leung C-M, Tang W-K, Ungvari GS, Gerevich J. Clinical and social determinants of psychotropic drug prescription for schizophrenia outpatients in China. Prog Neuro Psychopharmacol Biol Psychiatry. (2007) 31:756–60. doi: 10.1016/j.pnpbp.2007.01.013

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Lobana A, Mattoo SK, Basu D, Gupta N. Quality of life in schizophrenia in India: comparison of three approaches. Acta Psychiatr Scand. (2001) 104:51–5. doi: 10.1034/j.1600-0447.2001.104001051.x

PubMed Abstract | CrossRef Full Text | Google Scholar

32. World Health Organization. The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. Geneva: World Health Organization (1992).

Google Scholar

33. Young KS. Internet addiction: the emergence of a new clinical disorder. Cyberpsychol Behav. (1998) 1:237–44.

34. Lai CM, Mak KK, Watanabe H, Ang RP, Pang JS, Ho RC. Psychometric properties of the internet addiction test in Chinese adolescents. J Pediatr Psychol. (2013) 38:794–807. doi: 10.1093/jpepsy/jst022

PubMed Abstract | CrossRef Full Text | Google Scholar

35. Li G, Hou G, Yang D, Jian H, Wang W. Relationship between anxiety, depression, sex, obesity, and internet addiction in Chinese adolescents: a short-term longitudinal study. Addict Behav. (2019) 90:421–7. doi: 10.1016/j.addbeh.2018.12.009

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Chaudhari B, Menon P, Saldanha D, Tewari A, Bhattacharya L. Internet addiction and its determinants among medical students. Ind Psychiatry J. (2015) 24:158–62. doi: 10.4103/0972-6748.181729

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Kroenke K, Spitzer RL, Williams JB. 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

PubMed Abstract | CrossRef Full Text | Google Scholar

38. Wang W, Bian Q, Zhao Y, Li X, Wang W, Du J, et al. Reliability and validity of the Chinese version of the Patient Health Questionnaire (PHQ-9) in the general population. Gen Hosp Psychiatry. (2014) 36:539–44. doi: 10.1016/j.genhosppsych.2014.05.021

PubMed Abstract | CrossRef Full Text | Google Scholar

39. Tsai FJ, Huang YH, Liu HC, Huang KY, Huang YH, Liu SI. Patient health questionnaire for school-based depression screening among Chinese adolescents. Pediatrics. (2014) 133:e402–9. doi: 10.1542/peds.2013-0204

PubMed Abstract | CrossRef Full Text | Google Scholar

40. Zhang YL, Liang W, Chen ZM, Zhang HM, Zhang JH, Weng XQ, et al. Validity and reliability of patient health questionnaire-9 and patient health questionnaire-2 to screen for depression among college students in China. Asia Pac Psychiatry. (2013) 5:268–75. doi: 10.1111/appy.12103

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Leung DY, Mak YW, Leung SF, Chiang VC, Loke AY. Measurement invariances of the PHQ-9 across gender and age groups in Chinese adolescents. Asia-Pacific Psychiatry. (2020):e12381. doi: 10.1111/appy.12381

PubMed Abstract | CrossRef Full Text | Google Scholar

42. Wu XS, Zhang ZH, Zhao F, Wang WJ, Li YF, Bi L, et al. Prevalence of Internet addiction and its association with social support and other related factors among adolescents in China. J Adolesc. (2016) 52:103–11. doi: 10.1016/j.adolescence.2016.07.012

PubMed Abstract | CrossRef Full Text | Google Scholar

43. Xin M, Xing J, Pengfei W, Houru L, Mengcheng W, Hong Z. Online activities, prevalence of Internet addiction and risk factors related to family and school among adolescents in China. Addict Behav Rep. (2018) 7:14–8. doi: 10.1016/j.abrep.2017.10.003

PubMed Abstract | CrossRef Full Text | Google Scholar

44. So R, Makino K, Fujiwara M, Hirota T, Ohcho K, Ikeda S, et al. The prevalence of internet addiction among a japanese adolescent psychiatric clinic sample with autism spectrum disorder and/or attention-deficit hyperactivity disorder: a cross-sectional study. J Autism Dev Disord. (2017) 47:2217–24. doi: 10.1007/s10803-017-3148-7

PubMed Abstract | CrossRef Full Text | Google Scholar

45. Witkiewitz K, Litten RZ, Leggio L. Advances in the science and treatment of alcohol use disorder. Sci Adv. (2019) 5:eaax4043. doi: 10.1126/sciadv.aax4043

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Duan L, Shao X, Wang Y, Huang Y, Miao J, Yang X, et al. An investigation of mental health status of children and adolescents in china during the outbreak of COVID-19. J Affect Disord. (2020) 275:112–8. doi: 10.1016/j.jad.2020.06.029

PubMed Abstract | CrossRef Full Text | Google Scholar

47. Pantic I. Online social networking and mental health. Cyberpsychol Behav Soc Netw. (2014) 17:652–7. doi: 10.1089/cyber.2014.0070

PubMed Abstract | CrossRef Full Text | Google Scholar

48. Tang J, Yu Y, Du Y, Ma Y, Zhang D, Wang J. Prevalence of internet addiction and its association with stressful life events and psychological symptoms among adolescent internet users. Addict Behav. (2014) 39:744–7. doi: 10.1016/j.addbeh.2013.12.010

PubMed Abstract | CrossRef Full Text | Google Scholar

49. Bozkurt H, Coskun M, Ayaydin H, Adak I, Zoroglu SS. Prevalence and patterns of psychiatric disorders in referred adolescents with Internet addiction. Psychiatry Clin Neurosci. (2013) 67:352–9. doi: 10.1111/pcn.12065

PubMed Abstract | CrossRef Full Text | Google Scholar

50. Kuss DJ, Louws J, Wiers RW. Online gaming addiction? Motives predict addictive play behavior in massively multiplayer online role-playing games. Cyberpsychol Behav Soc Netw. (2012) 15:480–5. doi: 10.1089/cyber.2012.0034

PubMed Abstract | CrossRef Full Text | Google Scholar

51. Sowndarya T, Pattar M. Pattern of internet addiction among urban and rural school students, Mangaluru, India: a comparative cross-sectional study. Int J Contemp Pediatr. (2018) 5:1750. doi: 10.18203/2349-3291.ijcp20183005

CrossRef Full Text

52. Hamza A, Sharma MK, Anand N, Marimuthu P, Thamilselvan P, Thakur PC, et al. Urban and rural pattern of Internet use among youth and its association with mood state. J Family Med Prim Care. (2019) 8:2602–6. doi: 10.4103/jfmpc.jfmpc_428_19

PubMed Abstract | CrossRef Full Text | Google Scholar

53. Regis MF, Oliveira LM, Santos AR, Leonidio AD, Diniz PR, Freitas CM. Urban versus rural lifestyle in adolescents: associations between environment, physical activity levels and sedentary behavior. Einstein. (2016) 14:461–7. doi: 10.1590/s1679-45082016ao3788

PubMed Abstract | CrossRef Full Text | Google Scholar

54. Ren Y, Yang J, Liu L. Social anxiety and internet addiction among rural left-behind children: the mediating effect of loneliness. Iran J Public Health. (2017) 46:1659–68.

PubMed Abstract | Google Scholar

55. Mamun MA, Hossain MS, Siddique AB, Sikder MT, Kuss DJ, Griffiths MD. Problematic internet use in Bangladeshi students: the role of socio-demographic factors, depression, anxiety, and stress. Asian J Psychiatry. (2019) 44:48–54. doi: 10.1016/j.ajp.2019.07.005

PubMed Abstract | CrossRef Full Text | Google Scholar

56. Park S. Associations of physical activity with sleep satisfaction, perceived stress, and problematic Internet use in Korean adolescents. BMC Public Health. (2014) 14:1143. doi: 10.1186/1471-2458-14-1143

PubMed Abstract | CrossRef Full Text | Google Scholar

57. Bener A, Yildirim E, Torun P, Çatan F, Bolat E, Aliç S, et al. Internet addiction, fatigue, and sleep problems among adolescent students: a large-scale study. Int J Ment Health Addict. (2019) 17:959–69. doi: 10.1007/s11469-018-9937-1

CrossRef Full Text | Google Scholar

58. Liu Q-X, Fang X-Y, Deng L-Y, Zhang J-T. Parent–adolescent communication, parental Internet use and Internet-specific norms and pathological internet use among Chinese adolescents. Comput Hum Behav. (2012) 28:1269–75. doi: 10.1016/j.chb.2012.02.010

CrossRef Full Text | Google Scholar

59. Faltýnková A, Blinka L, Ševčíková A, Husarova D. The associations between family-related factors and excessive internet use in adolescents. Int J Environ Res Public Health. (2020) 17:1754. doi: 10.3390/ijerph17051754

PubMed Abstract | CrossRef Full Text | Google Scholar

60. Martins MV, Formiga A, Santos C, Sousa D, Resende C, Campos R, et al. Adolescent internet addiction—role of parental control and adolescent behaviours. Int J Pediatr Adolesc Med. (2020) 7:116–20. doi: 10.1016/j.ijpam.2019.12.003

PubMed Abstract | CrossRef Full Text | Google Scholar

61. Wang W, Li D, Li X, Wang Y, Sun W, Zhao L, et al. Parent-adolescent relationship and adolescent internet addiction: a moderated mediation model. Addict Behav. (2018) 84:171–7. doi: 10.1016/j.addbeh.2018.04.015

PubMed Abstract | CrossRef Full Text | Google Scholar

62. Elhai JD, Levine JC, Hall BJ. The relationship between anxiety symptom severity and problematic smartphone use: a review of the literature and conceptual frameworks. J Anxiety Disord. (2019) 62:45–52. doi: 10.1016/j.janxdis.2018.11.005

PubMed Abstract | CrossRef Full Text | Google Scholar

63. Lin Y-J, Hsiao RC, Liu T-L, Yen C-F. Bidirectional relationships of psychiatric symptoms with internet addiction in college students: a prospective study. J Formos Med Assoc. (2020) 119:1093–100. doi: 10.1016/j.jfma.2019.10.006

PubMed Abstract | CrossRef Full Text | Google Scholar

64. Lau JTF, Walden DL, Wu AMS, Cheng KM, Lau MCM, Mo PKH. Bidirectional predictions between Internet addiction and probable depression among Chinese adolescents. J Behav Addict. (2018) 7:633–43. doi: 10.1556/2006.7.2018.87

PubMed Abstract | CrossRef Full Text | Google Scholar

65. Ho RC, Zhang MW, Tsang TY, Toh AH, Pan F, Lu Y, et al. The association between internet addiction and psychiatric co-morbidity: a meta-analysis. BMC Psychiatry. (2014) 14:183. doi: 10.1186/1471-244X-14-183

PubMed Abstract | CrossRef Full Text | Google Scholar

66. Meng S, Dong P, Sun Y, Li Y, Chang X, Sun G, et al. Guidelines for prevention and treatment of internet addiction in adolescents during home quarantine for the COVID-19 pandemic. Heart Mind. (2020) 4:95–9. doi: 10.4103/hm.hm_36_20

CrossRef Full Text | Google Scholar

Keywords: adolescent patients, COVID-19, internet addiction, psychiatric disorder, Chinese

Citation: Li Z-L, Liu R, He F, Li S-Y, Zhao Y-J, Zhang W-Y, Zhang Y, Cheung T, Jackson T, Tang Y-L and Xiang Y-T (2021) Prevalence of Internet Addiction Disorder and Its Correlates Among Clinically Stable Adolescents With Psychiatric Disorders in China During the COVID-19 Outbreak. Front. Psychiatry 12:686177. doi: 10.3389/fpsyt.2021.686177

Received: 26 March 2021; Accepted: 12 August 2021;
Published: 16 September 2021.

Edited by:

Saeed Farooq, Keele University, United Kingdom

Reviewed by:

Jitendra Rohilla, All India Institute of Medical Sciences, Rishikesh, India
Yong Zhang, Tianjin Anding Hospital, China

Copyright © 2021 Li, Liu, He, Li, Zhao, Zhang, Zhang, Cheung, Jackson, Tang and Xiang. 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.

*Correspondence: Yi-Lang Tang, ytang5@emory.edu; Yu-Tao Xiang, xyutly@gmail.com

These authors have contributed equally to this work

Disclaimer: 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.