Social Media Use and Experiences of Cybervictimization: Links to Six Domains of Youth Well-Being

Abstract

Given the near ubiquitous use of social media among youth, understanding associations with adolescent development is critical. The present study investigated the relationship between social media use, well-being, and cybervictimization in a sample of young people from New Zealand. A sample of 332 youth aged between 7 and 18 years of age (64.2% female) completed online surveys assessing their social media use, experiences of cybervictimization, well-being, and the mobile phone regulations in place at their school. Youth who used social media reported lower well-being across three domains (physical well-being, emotional well-being, and functioning at school) and were also more likely to have experienced cybervictimization than youth who did not use social media. Examination of effects specific to each platform indicated a unique effect of TikTok on lower school functioning and a unique effect of Snapchat on higher cybervictimization. Finally, phone use at school was associated with a greater frequency of cybervictimization. The results indicate lower well-being and greater risk of cybervictimization among youth who use social media, with differential effects between social media platforms. Findings suggest that student well-being and experiences of cyberbullying could be mitigated through the implementation of regulations at the school-level, such as restricting phone use at school.

Keywords

social media wellbeing cybervictimization smartphones Snapchat TikTok

Introduction

Social media and social networking sites are embedded within the daily lives of young people today, with 95% of youth aged 13 to 17 partaking (Vogels et al., 2022). Social media applications (apps) regularly change in popularity, with TikTok gaining the most popular spot for teens, followed by Instagram and Snapchat in the United States (Vogels et al., 2022). In Aotearoa/New Zealand, the location of the present study, recent figures show that Snapchat (61%) is most frequently used by youth, followed by TikTok (60%), Instagram (49%), and YouTube (48%) (CensusAtSchool, 2023). Given the rapid integration of social media into young people’s daily lives and the growing time spent online, there is increasing concern regarding the implications for youth development (Bozzola et al., 2022). However, the extant literature examining links between social media use and well-being is mixed, with studies variously reporting positive, negative, and null associations (Odgers & Jensen, 2020).

Social Media and Adolescent Development

Adolescence is an important developmental stage, with marked biological, hormonal, and brain changes (Dahl et al., 2018). During this time, young people begin to develop their self-worth and navigate desires to “fit in” with their peers (Spies Shapiro & Margolin, 2014). This can lead to increased sensitivity to social pressures and means that adolescents may be more vulnerable to the dangers of social media, such as social comparison, adverse content exposure, inappropriate social contact, blackmail, and scams (Spies Shapiro & Margolin, 2014). A meta-analysis by Vannucci et al. (2020) found that the association between social media use and risky behaviors during adolescence was stronger in younger samples (mean age of 12 years) than older samples (mean age of 18 years). Further, Charmaraman and colleagues found that early social media initiation (use of social media platforms such as Instagram or Snapchat in children 10 years or younger) was significantly associated with problematic digital behavior outcomes, such as increased likelihood of online harassment and sexual harassment victimization (Charmaraman et al., 2022).

Overall, however, there remains debate about the beneficial versus harmful effects of social media during adolescence. Some research suggests that social media use is associated with adverse mental health outcomes in young people, such as anxiety and depression symptoms (Keles et al., 2020; Kelly et al., 2018; Riehm et al., 2019; Tsitsika et al., 2014) and poorer well-being (Boer et al., 2020; Booker et al., 2018; Twenge et al., 2018). Other research demonstrates that social media can enhance the quality of adolescents’ friendships, for example through encouraging self-disclosure (Subrahmanyam & Greenfield, 2008; Valkenburg & Peter, 2011). A meta-analysis by Meier and Reinecke (2021) suggests a small negative association between social media and mental health. However, an expanding body of research underscores the importance of person-specific effects, recognizing that the association between social media and mental health differs across individuals (Beyens et al., 2020, 2024; Pouwels et al., 2024).

Platform-Specific Effects

Social media apps vary in terms of their purposes, user interface aspects, and application features (Carter et al., 2022). And just as social media platforms vary in terms of their purposes and features, adolescents may differ in their reasons for using social media, including social connection, identity expression, escape, or entertainment (Sundar & Limperos, 2013). As social media use has become increasingly nuanced and user-specific (Beyens et al., 2020; Devito et al., 2018), Carter et al. (2022) suggest conceptualizing social media as a personal social media ecosystem, shaped by the unique social media environments and interactions that individuals create for themselves (Carter et al., 2022).

Given the varied and unique features of different social media platforms, it is critical to understand how different platforms may differ in their connections to mental health outcomes and negative online interactions such as cybervictimization. While most research tends to examine social media use across platforms, there is some evidence that specific social media platforms may have differential associations with mental health (Masciantonio et al., 2021; Moreno & Uhls, 2019; Pittman & Reich, 2016; Vannucci et al., 2018; Vannucci & McCauley Ohannessian, 2019). For instance, Facebook and Instagram have been linked to internalizing symptoms such as emotional symptoms and loneliness (Masciantonio et al., 2021; Pittman & Reich, 2016), Facebook, Snapchat, and TikTok have been associated with increased depressive symptoms (Perlis et al., 2021), Snapchat has been linked with externalizing symptoms such as substance use (Vannucci et al., 2018), and some research suggests TikTok may not be associated with any mental health outcomes (Masciantonio et al., 2021). However, previous research has focused on adults and very few studies have examined potential differential effects within adolescents (Vannucci & McCauley Ohannessian, 2019), therefore our understanding of how unique social media platforms influence youth well-being remains inconclusive.

The rapid evolution of social media platforms, technology and adolescent trends makes it difficult for research to keep pace. Platforms such as Snapchat have now integrated Artificial Intelligence (AI) into features such as filters and chatbots, where younger adolescents are more likely to use such features and perceive them as positive than their older counterparts (Vanhoffelen et al., 2025).

Cybervictimization

One mechanism through which social media may relate to adolescent well-being and development is through cybervictimization (Craig et al., 2020). Cybervictimization can be described as “any behaviour performed through electronic or digital media by individuals or groups that repeatedly communicates hostile or aggressive messages intended to inflict harm or discomfort on others” (Tokunaga, 2010, p. 278). When victimization occurs through social media, a single cyberbullying incident can cause victims repeated distress based on the utilized application features, interaction configurations, and accessibility of audiences (Farrington et al., 2023; Meier & Reinecke, 2021). Examples of cyberbullying include sending or posting hurtful, threatening, derogatory, sexually explicit or hateful messages, comments or posts to or about someone, sending hurtful or offensive images or videos of others without consent, spreading hate or rumors about an individual or group, creating offensive websites about others, and pretending to be someone else to hurt, embarrass, or gather personal information (Schonfeld et al., 2023). Experiences of cybervictimization can have lasting and devastating impacts, including loss of sleep, suicidal behavior, depression, and anxiety (Jose & Vierling, 2018; Nixon, 2014). Young victims and perpetrators of cyberbullying (under 25 years old) are at an increased risk of experiencing suicidal behaviors and suicidal ideation (John et al., 2018). Given the differing features and user interface aspects among social media platforms, some apps maybe be more likely to facilitate or enable cybervictimization than others. Furthermore, new technology advances such as AI can generate “deepfake” images, voices, and videos creating further risks to children of cyberbullying and exploitation (UNICEF, 2025).

Cybervictimization is further fuelled by the digital privacy concerns of social media platforms in their current form. Personal data can be inputted, shared, hacked, tracked, and more, often without an individual’s knowledge or permission (Niu et al., 2024). Compromised personal data can steer targeted harassment, cyberbullying, identity theft, exploitation, and many other harmful violations (Niu et al., 2024, 2025). Research by Niu and colleagues highlights the fact that negative online experiences can both generate psychological distress or interpersonal conflict, as well as prompt protective behaviors such as social media withdrawal or adjusting social media use (Niu et al., 2024, 2025).

Mobile Phone Use at School

The presence of mobile phones within schools and classrooms has increased rapidly over recent years, making it an important context to consider in relation to youth social media use and cybervictimization (Hatfield, 2024). Indeed, whole school policies related to health and well-being have been shown to reduce overall screen time and positively influence student well-being (Dix et al., 2012; Katapally et al., 2018; Kvardova et al., 2019). Thus, school policies relating to student smartphone use have the potential to positively impact youth well-being, by limiting the amount of time that youth have access to social media and through limits on the ways in which technology is used at school. For example, recent research from Norway suggests that banning smartphones in middle school significantly reduces the extent of psychological specialist care required by female students and decreases bullying in both males and females (Abrahamsson, 2024). Internationally, school regulations and bans on mobile phones at school are becoming more common (Tandon et al., 2020; UNESCO, 2023), and research is starting to emerge on how school smartphone bans might relate to student social media use and well-being outcomes. A recent rapid review by Böttger and Zierer (2024) found that there was an overall modest positive effect of school smartphone bans, in terms of effects on academic performance and social behavior, with larger effects seen in social well-being than in academic performance. The Böttger and Zierer review was able to identify only five studies with sufficient quantitative data, highlighting the need for more research in this area. Existing evidence, however, suggests that regulating youth mobile phone use at school could have beneficial effects on rates of cybervictimization and on well-being.

The Present Research

The present study investigated the relationship between social media use, well-being, and cybervictimization in a sample of young people from Aotearoa/New Zealand. Mental well-being is more than the absence of mental ill-being (C. L. Keyes, 2002; C. L. M. Keyes, 2005), therefore when examining youth mental health, it is important to consider positive outcomes (i.e., well-being) rather than focusing solely on clinical outcomes (i.e., anxiety and depression symptoms). In addition, as specific social media platforms may differentially relate to well-being, we distinguished between TikTok, Snapchat, Facebook, Instagram, and Twitter/X use. Finally, we accounted for school regulations on phone use, which may be a mitigating factor for the harmful effects of social media use in young people.

Research Aims

The specific research questions we aimed to answer in this research are as follows:

Is youth social media use associated with cybervictimization and well-being across six domains of functioning?

Do the associations between social media, cybervictimization, and well-being differ based on the social media platforms used?

Does the regulation of smartphone use at school mitigate associations between social media and cybervictimization and well-being?

Methods

Procedures

Data for this project were collected from youth in Aotearoa/New Zealand using anonymous online surveys through Qualtrics. Everyone who completed the survey was given the option to enter a draw to win one of ten NZD $100 gift cards. Participants were recruited through two methods: (a) email invitations sent to schools, and (b) paid social media advertising on Facebook aimed at parents of school-aged youth. Due to the online nature of the survey (participants simply clicked on a link to access the survey), we do not know the proportion of respondents that resulted from each recruitment method. See Gath et al. (2024) for further details about recruitment procedures. This study was approved by the University of Canterbury Human Research Ethics Committee (Ref: 2023/79). Parental consent and participant assent were obtained for all participants.

Sample

The analysis sample included 332 youth aged between 7 and 18 years of age (M = 13.9, SD = 2.0). Participants reported their gender as 64.2% female, 33.4% male, and 1.5% another gender. The ethnic distribution of participants (with multiple affiliations allowed) was 65.7% NZ European, 25.9% Asian, 13.0% Māori, 3.0% Pacific People, and 9.3% other.

Students primarily attended secondary school (70.0%) with smaller numbers from intermediate school (19.7%), primary school (6.4%), or other/not specified (3.9%). One-quarter of students (n = 90) chose not to report the names of the schools that they attended. The remaining sample of students came from across 43 different schools. The socioeconomic deprivation of these schools varied, ranging from decile 3 to decile 10 (M = 6.88, SD = 1.54) on the New Zealand Deprivation Index (Atkinson et al., 2019; 1 = lowest deprivation, 10 = highest deprivation). Participating students were spread across 10 of the 16 Regional Council areas in New Zealand, with the highest numbers from Canterbury (26.2%), Taranaki (13.0%), and Nelson (9.9%).

Measures

Social Media Use

Participants were asked “Do you use social media? (for example, TikTok or Snapchat)” and could respond either Yes or No. Those who responded Yes were then asked to indicate which social media platforms they used, with the options of: TikTok, Snapchat, Facebook, Instagram, Twitter/X, and Other.

School-Level Regulation of Mobile Phone Use

Participants were asked two questions related to the regulation of their mobile phone use at school. First, they were asked “Does your school have rules about using phones?” with response options of Yes, No, or I don’t know. Next, they were asked “Do you use your phone during class time?” with response options of Yes or No.

Youth Well-being

Well-being was assessed using the self-report version of the revised KINDL questionnaire designed for measuring health-related quality of life in children and adolescents (Ravens-Sieberer & Bullinger, 2000). We used the Kiddo-KINDL^R which is designed for youth aged 14 through 17 years of age, but used some of the wording from the Kid-KINDL^R (for ages 7- to 13-year-olds) where appropriate to ensure the questionnaire was appropriate across the full age range of our participants. The KINDL^R has demonstrated reliability and validity across a wide range of samples and across ages (Ravens-Sieberer & Bullinger, 2000). The KINDL^R is comprised of 6 subscales made up of 4 items each, for a total of 24 items. In the present study, each item was rated on a 5-point scale from 1 = Never to 5 = All the time. The 6 subscales were: Physical Wellbeing, Emotional Wellbeing, Self-Esteem, Family Wellbeing, Friendship Wellbeing, and Everyday Functioning at School. After reverse coding items as appropriate, sum scores were created for each subscale (out of a total of 20) as well as a total wellbeing score out of 120 by summing all subscales. Internal consistency for the scale was high (Cronbach’s alpha = 0.88).

Cybervictimization

Youth experiences of cyberbullying were assessed using four items from the Child Relationship Survey (CRS) (Wolke et al., 2023). Youth were asked “Thinking about this school year, how often have these things happened to you. . .” and the four items were: Had a private email, message or photo sent to someone else or put where others can see it; Had rumors spread about you online; Got mean or hurtful emails, instant messages or tweets; Had an embarrassing picture posted online without permission. Items were rated on a 4-point scale from 1 = Never to 4 = A lot. A total score representing the frequency of experiencing cybervictimization was computed as the sum across the 4 items (possible range of 4-16). Internal consistency for the 4 items was high (Cronbach’s alpha = 0.80).

Results

Data were available for 332 youth aged between 7 and 18 years of age. The majority of participants were between the ages of 11 and 16 years of age (inclusive), and variability in social media use was also observed primarily within this group (i.e., social media use was rare before 11 and ubiquitous after 16 in our sample). Figure 1 provides the distribution of social media use by age across the full sample. Given these variations in age and social media use, we focused our analysis for this paper on the 268 youth aged 11 through 16 years of age with data available on social media use. Of these 268 youth, 221 (82.5%) used social media.

Figure 1.

Distribution of participants and social media use by year of age.

Social Media Use and Well-being

To examine the associations between social media use and well-being, we used a multivariate analysis of variance (MANOVA) predicting all six domains of well-being simultaneously from age and social media use. The multivariate tests indicated significant effects of both age [F(6,247) = 3.33, p = .004] and social media use [F(6,247) = 2.94, p = .009] on well-being. Preliminary analyses indicated no significant interactions between age and well-being, so interaction effects were excluded from the final model.

Examination of the effects for each dependent variable indicated that age was only significantly predictive of school well-being, whereby school well-being decreased with increasing age [F(1,252) = 15.00, p < .001; η²_p = .06]. Social media use predicted well-being in three domains: physical [F(1,252) = 4.57, p = .03; η²_p = .02], emotional [F(1,252) = 8.58, p = .004; η²_p = .03], and school [F(1,252) = 5.68, p = .02; η²_p = .02]. In all cases, those who did not use social media reported higher well-being than those who did use social media. Table 1 provides the means and standard deviations for each well-being domain by social media use.

Table 1.

Mean Well-Being Scores Across Domains by Social Media Use.

Well-being domain	Social media use (n = 221)	No social media (n = )	p-value
Physical	12.38 (2.93)	13.70 (2.97)	.034
Emotional	13.49 (2.62)	14.87 (2.09)	.004
Self-esteem	12.57 (2.97)	13.50 (3.45)	.184
Family	15.33 (2.93)	15.59 (3.02)	.718
Friends	14.75 (2.68)	14.41 (3.23)	.583
School	11.97 (2.95)	13.72 (3.28)	.018

Social Media Use and Cybervictimization

We next used an analysis of variance (ANOVA) to predict cybervictimization scores from age and social media use. Again, preliminary analyses indicated no significant interaction between age and social media use so this interaction effect was excluded from the final model. The model was significant [F(6,251) = 2.51, p = .02]. While victimization was not significantly associated with age [F(5,251) = 1.45, p = .21], social media use was a significant predictor [F(1,251) = 7.80, p = .006]. Youth who used social media reported higher levels of cybervictimization (M = 6.08, SD = 2.43) than youth who did not use social media (M = 5.02, SD = 1.95).

Associations between Specific Social Media Platforms, Well-being, and Victimization

Figure 2 provides the percentage of youth using each social media platform (total as well as by age). Snapchat was the most commonly used platform, followed by Instagram and TikTok. Youth aged 14 to 16 were more likely to be using each platform than youth aged 11 to 13.

Figure 2.

Percentage of youth using each social media platform overall and by age group.

To understand whether certain social media platforms may be more closely associated with well-being and cyberbullying than others, we used linear regressions to predict our dependent variables (well-being and cybervictimization) from binomial variables indicating whether youth did (=1) or did not (=0) use each of the following social media platforms: TikTok, Facebook, Instagram, Twitter/X, and Snapchat. When examining associations with well-being, we focused on the three well-being domains found to be significantly associated with social media use above: physical, emotional, and social well-being. This analysis focused on only those youth who reported using social media (n = 221).

The linear regression models predicting physical well-being and emotional well-being were not significant [both F(5,205) < 1.01, p’s > .41], indicating that physical and emotional well-being were not differentially related to specific social media platforms. However, the model predicting school well-being was significant [F(5,203) = 2.66, p = .02]. The only significant predictor in the model was the use of TikTok [β = −1.21 (SE = 0.47), t = −2.55, p = .01]. Using TikTok was negatively associated with school well-being. After adjusting for the use of other platforms, those who used TikTok scored lower in school functioning (M = 10.95, SE = 0.43) than those who used social media but did not use TikTok (M = 12.16, SE = 0.46).

The linear regression model predicting cybervictimization was also significant [F(5,206) = 4.17, p = .001]. The only significant predictor in the model was the use of Snapchat [β = 1.28 (SE = 0.43), t = 2.99, p = .003]. Using Snapchat was associated with higher levels of cybervictimization. After adjusting for the use of other platforms, those who used Snapchat reported higher levels of victimization (M = 5.91, SE = 0.32) than those who used social media but did not use Snapchat (M = 4.63, SE = 0.42).

Use of Phones at School as a Mitigating Factor

Finally, we examined whether, for students who use social media, cyberbullying and well-being differed based on phone use at school. For this analysis, we focused on the 221 students aged 11 to 16 who reported using social media. The vast majority of students reported that their school had rules about using phones at school: 88.5% reported their school had rules, 3.3% said their school did not have rules, and 8.3% reported that they didn’t know if their school had rules. Thus, the moderating factor we examined was whether youth reported that they used their phone during class time, as this variable reflects “rules in practice” in terms of how strict or how well-enforced school regulations are around student phone use. Within the sample of students who used social media, 74.5% reported that they did not use their phones in class, whereas 25.5% reported that they did use their phones in class.

We used a MANOVA to predict all six well-being domain scores from phone use in class among students who used social media. The overall model was not significant [F(6,150) = 1.05, p = .40], indicating that well-being did not differ between those who used their phones in class and those who did not.

We used a one-way ANOVA to predict cybervictimization from phone use in class among students who used social media. This model was significant [F(1,194) = 3.67, p = .05]. Students who used their phones during class reported higher levels of cybervictimization (M = 6.69, SD = 2.85) than those who did not use their phones during class (M = 5.91, SD = 2.29).

Discussion

In this study, we examined social media use, well-being and cybervictimization within a sample of 332 youth aged between 7 and 18 years of age. Our findings indicate that from age 11 onwards, youth were more likely to be using social media than not. By age 17, all participating youth were using social media. The prevalence of social media use among the younger children in the sample is particularly noteworthy, given the current restrictions on social media accounts for those under 13 years of age. In 1998, the Children’s Online Privacy Protection Act 1998 was established in the US to ensure children under 13 years of age do not share their personal information on the internet without their parents’ permission (Federal Trade Commission, 2024). Since then, age limits for social media platforms have been based on this legal privacy parameter with no considerations for psychological development, capacity or well-being in relation to platform-specific risks and potential harms. Recently, Australia has implemented legislation introducing a mandatory minimum age of 16 years old to access social media platforms such as TikTok, Instagram, YouTube, Snapchat, and more. Currently, there are no laws in New Zealand governing the legal age for accessing social media platforms and this remains determined by the social media platform itself. Our results show that children are accessing social media platforms younger than 13 years of age and that youth up to age 16 may be experiencing negative consequences for their well-being.

In the present sample, youth who did not use social media reported higher well-being than those who used social media across three domains: physical well-being, emotional well-being, and functioning at school. While previous research has indicated links between social media use and clinical symptoms of depression and anxiety (Keles et al., 2020; Kelly et al., 2018; Riehm et al., 2019; Tsitsika et al., 2014), our analysis shows that sub-clinical measures of well-being similarly indicate differences based on social media use. Our results also show that youth who used social media were more likely to have been the victims of cyberbullying than those who did not use social media. A novel contribution of this research is the examination of individual social media platforms in relation to well-being and cyberbullying outcomes. Our results indicate that, in late 2023, New Zealand youth were most likely to be using Snapchat, and the use of this platform increased the risk of experiencing cyberbullying relative to other social media platforms.

Snapchat and Cybervictimization

The finding that use of Snapchat elevated risk of cybervictimization could be linked to its unique features, such as its disappearing content and primarily visual communication through photos and videos (Vuković et al., 2025). The perceived privacy and anonymity of Snapchat communication encourages users to share private or sensitive content instantaneously with limited oversight, which can increase the risk of inappropriate or risky behaviors (Vuković et al., 2025). The ephemeral design and misconception of young people regarding their privacy on Snapchat may encourage greater self-disclosure, provide a false sense of security, and enable false identities, increasing victimization such as exploitation, grooming, harassment, and more (Huie et al., 2024; Mandau, 2021). Screen-recordings can enable Snapchat content to be permanently saved and shared without consent, leading to further abuse and harm (Huie et al., 2024; Vuković et al., 2025). A qualitative study of adolescent girls highlighted the role of screenshots taken on Snapchat in image-based sexual abuse, with girls often blaming themselves for their own victimization (Mandau, 2021). Snapchat also allows for individuals’ locations to be shared with other users, inciting stalking and compromising physical safety (Huie et al., 2024). Research suggests parents are not sufficiently informed about the characteristics and risks of Snapchat, limiting their ability to implement privacy-protective measures or provide guidance to help reduce cyberbullying and victimization for their children (Vuković et al., 2025).

Further, the gamification of Snapchat through “streaks” increases daily exposure and peer pressure through reward-based mechanisms. During a Snapchat streak, users must send each other at least one picture every 24 hours to maintain their streak. A number is displayed next to the name of the friend to indicate the number of days in a row they have exchanged images, with research indicating that maintaining a streak is an important goal for adolescents (Hristova & Lieberoth, 2021). The increased touchpoints and “obligatory” exchanges resulting from Snapchat streaks can increase opportunities for conflict, coercion, and boundary violations (van Essen & Van Ouytsel, 2023). Thus, both the disappearing-message format and “streaks” inherent to Snapchat’s design may foster peer pressure and harassment and create opportunities for victimization.

TikTok and Well-being at School

We also found a unique effect of TikTok in predicting diminished well-being. This finding was specific to functioning at school, which included aspects of engagement with school, worries about the future, and finding schoolwork easy/difficult. Our results are in contrast to those of Masciantonio and colleagues who found no association between TikTok use and well-being in a sample of adults (Masciantonio et al., 2021). This discrepancy in findings points to potential differential effects of social media on the mental health and well-being of youth compared to adults and highlights the critical importance of examining the impacts of social media platforms within youth populations, as findings from adult samples cannot be extrapolated to the experiences and impacts for children and youth. Explanations for why lower functioning at school may be associated with the use of TikTok could include impacts on time displacement (e.g., taking time away from studying or sleeping) and impacts on attention and executive control. TikTok’s design makes it easy to keep scrolling, with short-form videos playing continuously, which may make it more difficult for adolescents to limit their use even when it interferes with their sleep and their academic work (Miedzobrodzka et al., 2024). Further, frequent use of short-form video apps like TikTok have been linked with reduced attentional and executive control and poorer cognitive and academic performance (Y. Gao et al., 2025; Xu et al., 2023; Yan et al., 2024). For example, Haliti-Sylaj and Sadiku (2024) found that greater exposure to short video reels was associated with reduced attention span and lower academic performance in a sample of university students. Impacts on attention and academic performance are likely to flow through to aspects of well-being, such as school engagement and worries about the future, potentially explaining the findings within the present sample.

Additionally, TikTok videos are generated by algorithms which may influence the content and frequency of information to users, where repeated exposure to harmful or developmentally inappropriate content can lead to negative consequences upon mental health (Woodward et al., 2025). How individuals respond to negative online experiences likely depends on the effectiveness of the coping strategies available to them, including technology or platform-based choices (Niu et al., 2024, 2025).

School-Level Regulations

Finally, we found that students who used their phones during class time were more likely to report experiencing cybervictimization. This could suggest that greater regulation of student mobile phone use at school, such as limiting phone use in the classroom, may be one effective approach to reducing cyberbullying (Abrahamsson, 2024). When students have access to their phones and social media at school, the opportunities for recording and sharing inappropriate or unconsented content are greatly increased, all while in close proximity to other students whom they might not have contact with outside of school (Gath et al., 2024). Further, existing interpersonal conflicts can be exacerbated, such as when an incident is filmed and distributed online (Gath et al., 2024). Thus, while research evaluating the effectiveness of mobile phone policies often focus on academic outcomes (Böttger & Zierer, 2024), it is equally important to consider potential benefits for youth well-being that could come from having phone-free time at school, including fewer opportunities for cybervictimization.

Starting in April 2024, students in New Zealand are now prohibited from using mobile phones during the school day unless specific or special circumstances are applied (a government mandate implemented subsequent to data collection for the present study). Preliminary results suggest both benefits and challenges of this policy (Education Review Office, 2025). Thus, while the present findings indicate potential benefits of regulating phone use at school, it is important to note the practical implementation challenges identified in New Zealand and globally to these types of regulations, including resistance from parents and students (Bar et al., 2025; Education Review Office, 2025), and balancing the educational benefits of digital tools along with the risks (Grigic Magnusson et al., 2023). On balance, however, research suggests that educators, students, and parents are in support of such policies and that measurable benefits are seen for student outcomes (Böttger & Zierer, 2024; Education Review Office, 2025; Q. Gao et al., 2017).

Limitations

It is important to note that the sample for this analysis may have been biased toward those who use social media, given one of our recruitment methods was through social media. However, this recruitment was targeted at parents rather than the youth themselves. There is still the potential for bias to arise from differences in the types of parents who use social media compared to those who do not; however, recent data from the United States indicates that Facebook (where the present study was advertised) is used widely across adult demographic groups (Gottfried & Park, 2025). Further, our sample size is relatively small which limits our ability to draw any meaningful age-related conclusions. Future research should also consider using more nuanced approaches to measuring social media use, such as measures of problematic or addictive social media use, rather than a simple yes/no question. However, our results demonstrate significant associations even at the basic level of simply using social media, regardless of whether use is excessive or problematic. Finally, our measure of phone use in the classroom was also simplistic and did not differentiate educational from recreational use nor include any other contextual details about phone use at school that may influence how use relates to well-being and victimization. Overall, this research could be strengthened through more detailed measurement of youth phone use.

Conclusions

The results of this study suggest that from age 11 onwards the majority of youth are using social media, with Snapchat as the most popular platform. Youth who used social media reported lower well-being across three domains (physical well-being, emotional well-being, and functioning at school) and were also more likely to have experienced cybervictimization than youth who did not use social media. Examination of effects specific to each platform indicated a unique effect of TikTok on lower social functioning and a unique effect of Snapchat on higher cybervictimization experiences. Finally, we found that mobile phone use at school (during class) was associated with a greater frequency of cybervictimization.

The results indicate lower well-being and greater risk of cybervictimization among youth who use social media, with differential effects between social media platforms. Findings suggest that associations with well-being and cyberbullying could be mitigated through the development and implementation of regulations at the school-level, such as restricting phone use at school and in class, and at the policy-level, such as improved methods of age verification and increases to the minimum age at which social media accounts are permitted. There is an evolving need for robust online safety education, tools, and policy to protect and support children and young people within our rapidly evolving digital world.

Footnotes

ORCID iDs

Megan Gath

Lauren Monk

Jenna Gawn

Amy Scott

Ethical Considerations

This study was approved by the University of Canterbury Human Ethics Committee (HREC 2023/79).

Consent to Participate

Parental consent and participant assent were obtained for all participants.

Consent for Publication

Not applicable.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the Child Well-being Research Institute, University of Canterbury.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability

The data from this study are not available as the participants did not consent to this.

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