“Protective Bubble” or “Risky Bubble”: How Does the Social Media Identity Bubble Affect Adolescents’ Mental Health?

CHEN Zonghai, PAN Xiaole, JIANG Qiaolei, WU Yibo

Chinese Journal of Journalism & Communication ›› 2025, Vol. 47 ›› Issue (12) : 105-126.

PDF(1697 KB)
PDF(1697 KB)
Chinese Journal of Journalism & Communication ›› 2025, Vol. 47 ›› Issue (12) : 105-126.
Research Articles

“Protective Bubble” or “Risky Bubble”: How Does the Social Media Identity Bubble Affect Adolescents’ Mental Health?

Author information +
History +

Abstract

This study, based on a nationwide survey of psychology and behavior investigation of Chinese residents (PBICR), explores the impact of social media identity bubble on loneliness, depression and anxiety of Chinese adolescents, and examines the mechanism of perceived social support (PSS) and problematic Internet use (PIU) between identity bubble and mental health, as well as group differences. The results indicate that the impact of identity bubble on adolescents’ mental health is multifaceted, exhibiting a double-edged sword effect. Identity bubble can not only improve mental health through the mediating effect of PSS, but also lead to PIU and become a risk factor of mental health. The multi-group analysis shows significant differences in the risk mechanism of identity bubbles on adolescents’ mental health across gender, residence, and schooling stage. Female, urban, or high school and above adolescents are more susceptible to PIU triggered by identity bubbles, which in turn exacerbates their mental health problems. In addition, identity bubble directly reduces depressive emotions in female adolescents, but this positive effect is suppressed by PIU. With the popularity of online social interaction, being involved in identity bubble can either build a fortress for adolescents’ self-identity or become a hotbed of mental health risks. These findings provide new insights to the impact of online social interaction on adolescents’ mental health.

Key words

Adolescents / social media identity bubble / mental health / double-edged sword effect / multi-group analysis

Cite this article

Download Citations
CHEN Zonghai , PAN Xiaole , JIANG Qiaolei , et al. “Protective Bubble” or “Risky Bubble”: How Does the Social Media Identity Bubble Affect Adolescents’ Mental Health?[J]. Chinese Journal of Journalism & Communication. 2025, 47(12): 105-126

References

[1]
陈昌凤, 仇筠茜(2020). “信息茧房”在西方:似是而非的概念与算法的“破茧”求解. 《新闻大学》,(1),1-14+124.
[2]
共青团中央维护青少年权益部, 中国互联网络信息中心, 中国青少年新媒体协会(2023年12月23日). 第5次全国未成年人互联网使用情况调查报告. https://mp.weixin.qq.com/s/B5kTHTBLBv0qnVPMt2GutA.
[3]
黄含韵, 夏晓草(2023). 社会心理、角色与情绪:中国居民社交媒体使用与沉迷. 《现代传播》,(11),141-153.
[4]
季为民, 杨子函(2024). 2024年未成年人互联网运用调查报告. 载方勇,季为民, 沈杰(主编),《青少年蓝皮书: 中国未成年人互联网运用报告(2024)》(第15-39页).社会科学文献出版社.
[5]
蒋俏蕾, 童淑婷, 陈宗海(2020). 青少年互联网依赖与风险应对. 《青年探索》,(6),37-46.
[6]
姜永志(2020). 《青少年社交媒体使用与社会心理发展》. 江苏大学出版社.
[7]
彭海云, 盛靓, 王金睿, 周姿言, 辛素飞(2023). 2001-2019 年我国青少年孤独感的变迁:横断历史研究的视角. 《心理发展与教育》,(3),449-456.
[8]
邱依雯, 娄熠雪, 雷怡(2021). 青少年抑郁:基于社会支持的视角. 《心理发展与教育》,(2),288-297.
[9]
王东梅, 张立新, 张镇(2017). 问题性网络使用与幸福感、社交焦虑、抑郁关系的纵向研究. 《心理与行为研究》,(4),569-576.
[10]
温忠麟, 叶宝娟(2014). 中介效应分析:方法和模型发展. 《心理科学进展》,(5),731-745.
[11]
吴明隆(2010). 《结构方程模型——AMOS的操作与应用》(第2版). 重庆大学出版社.
[12]
伊莱·帕里泽(2011/2020). 《过滤泡: 互联网对我们的隐秘操纵》(方师师,杨媛译). 中国人民大学出版社.
[13]
约翰·桑特洛克(2007/2013). 《青少年心理学》(寇彧等译)(第11版). 人民邮电出版社.
[14]
张明新, 刘于思(2013). 社会交互式传播技术与青少年的同辈关系网——基于社会网络分析的经验研究. 《国际新闻界》,(7),37-50.
[15]
郑佳雯(2012). 中国“数码不平等”调查——互联网使用的社会与人口学特征. 《新闻大学》,(6),10-19+72.
[16]
周迎楠, 王俊秀(2023). 使用社交媒体发布动态的频率对青年群体主观幸福感的影响:基本心理需要满足的中介作用. 《心理科学》,(6),1454-1461.
[17]
Ang, C. S. (2017). Internet habit strength and online communication: Exploring gender differences. Computers in Human Behavior, 66, 1-6.
[18]
Ball-Rokeach, S. J. (1985). The origins of individual media-system dependency: A sociological framework. Communication Research, 12(4), 485-510.
Abstract
Prior theory and research that has demonstrated the consequences of individuals' media-system dependencies upon selective exposure and message effects has not, however, addressed the equally important question of the determinants of individuals' media-system dependencies. The aim of this article is to present a sociological framework for the analysis of the macro and micro determinants of those media-system dependencies. The configuration of determinants that constitute this framework includes structural dependencies between the media and other social systems, characteristics of the social environs, media-system activity, interpersonal discourse networks, the sociostructural location of individuals, and personal goals.
[19]
Caldiroli, A., Serati, M., & Buoli, M. (2018). Is Internet addiction a clinical symptom or a psychiatric disorder? A comparison with bipolar disorder. The Journal of Nervous and Mental Disease, 206(8), 644-656.
[20]
Caplan, S. E. (2010). Theory and measurement of generalized problematic Internet use: A two-step approach. Computers in Human Behavior, 26(5), 1089-1097.
[21]
Cohen, S., & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310.
[22]
de Carvalho, N. A., & Veiga, F. H. (2022). Psychosocial development research in adolescence: A scoping review. Trends in Psychology, 30(4), 640-669.
[23]
Demetrovics, Z., Király, O., Koronczai, B., Griffiths, Mark D., Nagygyörgy, K., Elekes, Z., Tamás, D., Kun, B., Kökönyei, G., & Urbán, R. (2016). Psychometric properties of the Problematic Internet Use Questionnaire Short-Form (PIUQ-SF-6) in a nationally representative sample of adolescents. PLoS One, 11(8), e0159409.
[24]
Flanagin, A. J. (2017). Online social influence and the convergence of mass and interpersonal communication. Human Communication Research, 43(4), 450-463.
[25]
Flanagin, A. J., Hocevar, K. P., & Samahito, S. N. (2013). Connecting with the user-generated Web: How group identification impacts online information sharing and evaluation. Information, Communication & Society, 17(6), 683-694.
[26]
Gottlieb, B. H., & Bergen, A. E. (2010). Social support concepts and measures. Journal of Psychosomatic Research, 69(5), 511-520.
Distinctions among concepts and approaches to assessing social support are made, and published generic and specialized measures of social support are reviewed. Depending on study aims, investigators may be interested in assessing perceived or received support from the perspective of the provider, the recipient, or both. Whereas some measures inquire about the availability or mobilization of several kinds of supportive resources, others seek supplemental information about the membership and structural properties of the social network as well. Observational and self-reported measures of support are presented, along with brief and extensive measures. A final set of three support measures is highlighted, including their psychometric properties.Copyright © 2010 Elsevier Inc. All rights reserved.
[27]
Griffiths, M. (2005). A ‘components’ model of addiction within a biopsychosocial framework. Journal of Substance Use, 10(4), 191-197.
[28]
Guo, T. C., & Li, X. (2016). Positive relationship between individuality and social identity in virtual communities: Self-categorization and social identification as distinct forms of social identity. Cyberpsychology, Behavior, and Social Networking, 19(11), 680-685.
[29]
Helgeson, V. S. (1993). Two important distinctions in social support: Kind of support and perceived versus received. Journal of Applied Social Psychology, 23(10), 825-845.
[30]
Hughes, M. E., Waite, L. J., Hawkley, L. C., & Cacioppo, J. T. (2004). A short scale for measuring loneliness in large surveys: Results from two population-based studies. Research on Aging, 26(6), 655-672.
Most studies of social relationships in later life focus on the amount of social contact, not on individuals' perceptions of social isolation. However, loneliness is likely to be an important aspect of aging. A major limiting factor in studying loneliness has been the lack of a measure suitable for large-scale social surveys. This article describes a short loneliness scale developed specifically for use on a telephone survey. The scale has three items and a simplified set of response categories but appears to measure overall loneliness quite well. The authors also document the relationship between loneliness and several commonly used measures of objective social isolation. As expected, they find that objective and subjective isolation are related. However, the relationship is relatively modest, indicating that the quantitative and qualitative aspects of social relationships are distinct. This result suggests the importance of studying both dimensions of social relationships in the aging process.
[31]
Hunt, M. G., Marx, R., Lipson, C., & Young, J. (2018). No more FOMO: Limiting social media decreases loneliness and depression. Journal of Social and Clinical Psychology, 37(10), 751-768.
[32]
Hussain, Z., Wegmann, E., Yang, H., & Montag, C. (2020). Social networks use disorder and associations with depression and anxiety symptoms: A systematic review of recent research in China. Frontiers in Psychology, 11, 211.
An increasing number of studies have investigated Social Networks Use Disorder (SNUD) among Western samples. In this context, the investigation of SNUD in Asia and especially in China has been much neglected. This poses a gap in the literature; it has been estimated that more than one billion Chinese people are using Chinese social networking sites (SNSs). Of note, many of these Chinese SNSs are rather unknown to researchers in Western countries. The primary objective of the present systematic review was to identify and evaluate studies that investigated Chinese SNS use and associations between SNUD and depression and anxiety symptoms. A comprehensive search strategy identified relevant studies in PsycINFO, PsycARTICLES, Psychology and Behavioral Sciences Collection, MEDLINE, ProQuest, Web of Science, PubMed, Google Scholar, and the Chinese National Knowledge Infrastructure database (CNKI). The search strategy identified 35 potential studies, 13 studies were identified after shortlisting and full-text reviews of the studies, and finally 10 studies were included in the full review. Associations between SNUD, depression, and anxiety were reported in 10 studies. In eight (of the 10) studies, symptom severity of SNUD was associated with depression. Four studies reported associations between SNUD and anxiety. Most studies had utilized cross-sectional survey designs. Most associations were found between SNUD and depression symptoms, but effect sizes were higher between SNUD and anxiety symptoms. The results have the potential to inform prevention and interventions on SNUD in Eastern cultures, although we explicitly state that our work focuses on China, the transfer of the present observations to other Asian countries (and their cultures) still needs to be established.Copyright © 2020 Hussain, Wegmann, Yang and Montag.
[33]
Kaakinen, M., Sirola, A., Savolainen, I., & Oksanen, A. (2020). Shared identity and shared information in social media: Development and validation of the identity bubble reinforcement scale. Media Psychology, 23(1), 25-51.
[34]
Kang, J., & Chung, D. Y. (2017). Homophily in an anonymous online community: Sociodemographic versus personality traits. Cyberpsychology, Behavior, and Social Networking, 20(6), 376-381.
[35]
Karacic, S., & Oreskovic, S. (2017). Internet addiction through the phase of adolescence: A questionnaire study. JMIR mental health, 4(2), e5537.
[36]
Keipi, T., Näsi, M., Oksanen, A., & Räsänen, P. (2017). Online hate and harmful content: Cross-national perspectives. Routledge.
[37]
Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukopadhyay, T., & Scherlis, W. (1998). Internet paradox: A social technology that reduces social involvement and psychological well-being?. American Psychologist, 53(9), 1017-1031.
The Internet could change the lives of average citizens as much as did the telephone in the early part of the 20th century and television in the 1950s and 1960s. Researchers and social critics are debating whether the Internet is improving or harming participation in community life and social relationships. This research examined the social and psychological impact of the Internet on 169 people in 73 households during their first 1 to 2 years on-line. We used longitudinal data to examine the effects of the Internet on social involvement and psychological well-being. In this sample, the Internet was used extensively for communication. Nonetheless, greater use of the Internet was associated with declines in participants' communication with family members in the household, declines in the size of their social circle, and increases in their depression and loneliness. These findings have implications for research, for public policy and for the design of technology.
[38]
Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ - 9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606-613.
While considerable attention has focused on improving the detection of depression, assessment of severity is also important in guiding treatment decisions. Therefore, we examined the validity of a brief, new measure of depression severity.The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as "0" (not at all) to "3" (nearly every day). The PHQ-9 was completed by 6,000 patients in 8 primary care clinics and 7 obstetrics-gynecology clinics. Construct validity was assessed using the 20-item Short-Form General Health Survey, self-reported sick days and clinic visits, and symptom-related difficulty. Criterion validity was assessed against an independent structured mental health professional (MHP) interview in a sample of 580 patients.As PHQ-9 depression severity increased, there was a substantial decrease in functional status on all 6 SF-20 subscales. Also, symptom-related difficulty, sick days, and health care utilization increased. Using the MHP reinterview as the criterion standard, a PHQ-9 score > or =10 had a sensitivity of 88% and a specificity of 88% for major depression. PHQ-9 scores of 5, 10, 15, and 20 represented mild, moderate, moderately severe, and severe depression, respectively. Results were similar in the primary care and obstetrics-gynecology samples.In addition to making criteria-based diagnoses of depressive disorders, the PHQ-9 is also a reliable and valid measure of depression severity. These characteristics plus its brevity make the PHQ-9 a useful clinical and research tool.
[39]
Lakey, B., & Orehek, E. (2011). Relational regulation theory: A new approach to explain the link between perceived social support and mental health. Psychological Review, 118(3), 482-495.
Perceived support is consistently linked to good mental health, which is typically explained as resulting from objectively supportive actions that buffer stress. Yet this explanation has difficulty accounting for the often-observed main effects between support and mental health. Relational regulation theory (RRT) hypothesizes that main effects occur when people regulate their affect, thought, and action through ordinary yet affectively consequential conversations and shared activities, rather than through conversations about how to cope with stress. This regulation is primarily relational in that the types of people and social interactions that regulate recipients are mostly a matter of personal taste. RRT operationally defines relationships quantitatively, permitting the clean distinction between relationships and recipient personality. RRT makes a number of new predictions about social support, including new approaches to intervention.
[40]
Latikka, R., Koivula, A., Oksa, R., Savela, N., & Oksanen, A. (2022). Loneliness and psychological distress before and during the COVID-19 pandemic: Relationships with social media identity bubbles. Social Science & Medicine, 293, 114674.
[41]
Lehdonvirta, V., & Räsänen, P. (2011). How do young people identify with online and offline peer groups? A comparison between UK, Spain and Japan. Journal of Youth Studies, 14(1), 91-108.
[42]
Leung, L. (2011). Loneliness, social support, and preference for online social interaction: The mediating effects of identity experimentation online among children and adolescents. Chinese Journal of Communication, 4(4), 381-399.
[43]
Mitchell, M. E., Lebow, J. R., Uribe, R., Grathouse, H., & Shoger, W. (2011). Internet use, happiness, social support and introversion: A more fine grained analysis of person variables and Internet activity. Computers in Human Behavior, 27(5), 1857-1861.
[44]
Politte-Corn, M., Nick, E. A., & Kujawa, A. (2023). Age-related differences in social media use, online social support, and depressive symptoms in adolescents and emerging adults. Child and Adolescent Mental Health, 28(4), 497-503.
Despite growing concerns about the impact of social media use on the developing brain and associated mental health impacts, whether susceptibility to the benefits and harms of social media use changes across adolescence and young adulthood has yet to be empirically tested.Using a cross-sectional sample of participants aged 14-22 years (N = 254), we examined (a) linear and non-linear age-related changes in social media use and online social support and (b) age-related differences in the effects of social media use and online social support on depressive symptoms.We found age differences in social media use, but not online social support, such that social media use increased across adolescence and peaked around age 20, followed by stable use into young adulthood. Age moderated the effect of online social support, but not overall social media use, on depressive symptoms, such that online social support was negatively associated with depressive symptoms for adolescents (age < 16.98), but the opposite pattern emerged for young adults (age > 19.04).Results suggest overall developmental changes in social media use and that adolescents may be more susceptible than emerging adults to the beneficial effects of positive online interactions on mental health.© 2023 Association for Child and Adolescent Mental Health.
[45]
Qazi, A., Hasan, N., Abayomi-Alli, O., Hardaker, G., Scherer, R., Sarker, Y., Kumar Paul, S., & Maitama, J.Z. (2022). Gender differences in information and communication technology use & skills: A systematic review and meta-analysis. Education and Information Technologies, 27(3), 4225-4258.
[46]
Qiao, J., Wang, Y., Li, X., Jiang, F., Zhang, Y., Ma, J., Song, Y., Ma, J., Fu, W., Pang, R., Zhu, Z., Zhang, J., Qian, X., Wang, L., Wu, J., Chang, H. M., Leung, P. C. K., Mao, M., Ma, D.,... & Hesketh, T. (2021). A Lancet Commission on 70 years of women’s reproductive, maternal, newborn, child, and adolescent health in China. The Lancet, 397(10293), 2497-2536.
[47]
Rosen, A. O., Holmes, A. L., Balluerka, N., Hidalgo, M. D., Gorostiaga, A., Gómez-Benito, J., & Huedo-Medina, T. B. (2022). Is social media a new type of social support? Social media use in Spain during the COVID-19 pandemic: A mixed methods study. International Journal of Environmental Research and Public Health, 19(7), 3952.
[48]
Seo, M., Kim, J., & Yang, H. (2016). Frequent interaction and fast feedback predict perceived social support: Using crawled and self-reported data of Facebook users. Journal of Computer-Mediated Communication, 21(4), 282-297.
[49]
Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092-1097.
[50]
Tokunaga, R. S. (2017). A meta-analysis of the relationships between psychosocial problems and internet habits: Synthesizing Internet addiction, problematic Internet use, and deficient self-regulation research. Communication Monographs, 84(4), 423-446.
[51]
Turel, O. (2015). An empirical examination of the “vicious cycle” of Facebook addiction. Journal of Computer Information Systems, 55(3), 83-91.
[52]
Turel, O., & Osatuyi, B. (2017). A peer-influence perspective on compulsive social networking site use: Trait mindfulness as a double-edged sword. Computers in Human Behavior, 77, 47-53.
[53]
United Nations International Children’s Emergency Fund (UNICEF). (2019, November 7-9). Leading Minds 2019 conference on child and adolescent mental health concludes.
[54]
Vannucci, A., Flannery, K. M., & Ohannessian, C. M. (2017). Social media use and anxiety in emerging adults. Journal of Affective Disorders, 207, 163-166.
Social media use is central to the lives of emerging adults, but the implications of social media use on psychological adjustment are not well understood. The current study aimed to examine the impact of time spent using social media on anxiety symptoms and severity in emerging adults.Using a web-based recruitment technique, we collected survey information on social media use and anxiety symptoms and related impairment in a nationally representative sample of 563 emerging adults from the U.S. (18-22 years-old; 50.2% female; 63.3% Non-Hispanic White). Participants self-reported the amount of time they spent using various social media sites on an average day, and responded to anxiety questionnaires RESULTS: Hierarchical regression revealed that more time spent using social media was significantly associated with greater symptoms of dispositional anxiety (B=0.74, 95% CI=0.59-0.90, p<0.001), but was unrelated to recent anxiety-related impairment (B=0.06, 95% CI=0.00-0.12, p=0.051), controlling for age, gender, race/ethnicity, and education level. Logistic regression also revealed that more daily social media use was significantly associated with a greater likelihood of participants scoring above the anxiety severity clinical cut-off indicating a probable anxiety disorder (AOR=1.032, 95% CI=1.004-1.062, p=0.028).Study limitations include the cross-sectional design and reliance on self-report questionnaires.Given the ubiquity of social media among emerging adults, who are also at high risk for anxiety disorders, the positive association between social media use and anxiety has important implications for clinicians. Gaining a more nuanced understanding of this relationship will help to inform novel approaches to anxiety treatment.Copyright © 2016 Elsevier B.V. All rights reserved.
[55]
Yang, C. C. (2016). Instagram use, loneliness, and social comparison orientation: Interact and browse on social media, but don’t compare. Cyberpsychology, Behavior, and Social Networking, 19(12), 703-708.
[56]
Young, K. S. (1996). Psychology of computer use: XL. addictive use of the Internet: A case that breaks the stereotype. Psychological Reports, 79(3), 899-902.
This case involves a homemaker 43 years of age who is addicted to using the Internet. This case was selected as it demonstrates that a nontechnologically oriented woman with a reportedly content home life and no prior addiction or psychiatric history abused the Internet which resulted in significant impairment to her family life. This paper defines addictive use of the Internet, outlines the subject's progression of addictive on-line use, and discusses the implications of such addictive behavior on the new market of Internet consumers.
[57]
Zerback, T., & Fawzi, N. (2017). Can online exemplars trigger a spiral of silence? Examining the effects of exemplar opinions on perceptions of public opinion and speaking out. New Media & Society, 19(7), 1034-1051.
In modern media environments, social media have fundamentally altered the way how individual opinions find their way into the public sphere. We link spiral of silence theory to exemplification research and investigate the effects of online opinions on peoples’ perceptions of public opinion and willingness to speak out. In an experiment, we can show that a relatively low number of online exemplars considerably influence perceived public support for the eviction of violent immigrants. Moreover, supporters of eviction were less willing to speak out on the issue online and offline when confronted with exemplars contradicting their opinion.
[58]
Zhang, B., Gao, Q., Fokkema, M., Alterman, V., & Liu, Q. (2015). Adolescent interpersonal relationships, social support and loneliness in high schools: Mediation effect and gender differences. Social Science Research, 53, 104-117.
The purpose of this study was to explore the associations between the qualities of different types of relationships in school, social support and loneliness in adolescence. Using a sample (N=1674) of adolescent students randomly selected from middle schools, we found boys' loneliness was influenced by the qualities of opposite-sex, teacher-student and same-sex relationships, whereas girls' loneliness was only influenced by same-sex relationships. Additionally, social support mediated the association between same-sex relationships and teacher-student relationships, and loneliness. Further, the quality of same-sex relationships showed stronger association with boys' loneliness than girls'. Finally, the quality of same-sex relationships showed the strongest association with boys' loneliness comparing with opposite-sex relationships and teacher-student relationships. These findings are discussed to illuminate the possible mechanisms by which interpersonal relationships could influence loneliness. In future research, causal relationships and other influencing factors on loneliness should be examined. Copyright © 2015 Elsevier Inc. All rights reserved.
[59]
Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The multidimensional scale of perceived social support. Journal of Personality Assessment, 52(1), 30-41.
[60]
Zych, I., Kaakinen, M., Savolainen, I., Sirola, A., Paek, H. J., & Oksanen, A. (2023). The role of impulsivity, social relations online and offline, and compulsive Internet use in cyberaggression: A four-country study. New Media & Society, 25(1), 181-198.
Cyberaggression is a harmful behavior, but cross-national studies on cyberaggression including relations among its individual and social predictors are limited. This study aimed to discover the direct and indirect relations among individual and social predictors of cyberaggression in socio-demographically balanced survey data set of 4816 15–25-year-old participants from Finland ( n = 1200, 50.0% female), South Korea ( n = 1192, 50.34% female), Spain ( n = 1212, 48.76% female), and the United States ( n = 1212, 50.17% female). Both, impulsivity and involvement in online cliques (i.e., identity bubbles) were related to more cyberaggression in the four countries. The relation between impulsivity and cyberaggression was partially mediated by compulsive Internet use in Finland, Spain, and the United States, but not in South Korea. The relation between identity bubble involvement and cyberaggression was mediated via compulsive Internet use only in the Spanish sample. Findings of this study can be used for policy and practice against cyberaggression.

Footnotes

1. 本文以12岁至17岁的青少年为研究对象,涉及小学、初中、高中、大学四个学段,小学生和大学生数量少。根据年龄推演,小学生就读于高年级,大学生则刚刚步入大学。在多群组分析时,将在小学和初中就读的青少年合并成“初中及以下”组,将在高中和大学就读的青少年合并成“高中及以上”组。

2. 多群组分析用于评估一个适配于某一样本群体的模型,是否也适配于其他样本群体。6个相互嵌套的模型分别为无限制模型、测量权重模型、结构权重模型、结构协方差模型、结构残差模型、测量残差模型。在多群组分析中,这些模型通过逐步约束参数跨组一致性形成嵌套关系。

Funding

General Project of National Social Science Fund “The Impact of Smartphones on the Development of Adolescents’ Well-being and the Mechanism of Collaborative Governance”(20BXW127)
TSJC Computing Communication and Intelligent Media Laboratory Research Support Grant(2026TSJCLAB001)
PDF(1697 KB)

Accesses

Citation

Detail

Sections
Recommended

/