Problematic use of mobile phone and social media among adolescents: relationship with cyberbullying, cybervictimisation, and social anxiety

Problematic use of mobile phone and social media among adolescents: relationship with cyberbullying, cybervictimisation, and social anxiety | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Problematic use of mobile phone and social media among adolescents: relationship with cyberbullying, cybervictimisation, and social anxiety Laura Guisot, David Aparisi, Beatriz Delgado, María Carmen Martínez-Monteagudo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7592472/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted 15 You are reading this latest preprint version Abstract The use of mobile phone and social media has become a global and unstoppable phenomenon, especially among adolescents, largely due to the ease of access to numerous applications that facilitate communication and social interaction via the Internet. This study examines the relationship between problematic mobile phone and social media use, cyberbullying, and social anxiety in a representative sample of secondary school adolescents. A total of 1164 students with an age range of 12 to 18 years ( M = 14.56; SD = 1.4) completed a battery of self-report measures to assess problematic mobile phone and social media use and social anxiety. The results indicate that students with high problematic use of mobile phone and social media have significantly higher levels of cyberbullying and social anxiety compared to those with low and medium problematic use. Furthermore, logistic regression analyses showed that cyberbullying, cybervictimisation and social anxiety, specifically, fear of negative evaluation were significant predictors of problematic mobile phone and social media use, indicating a higher probability of dependence as levels of cybervictimisation and social anxiety increase. The results suggest the need to implement interventions aimed at improving emotional management and reducing problematic behaviours related to technology use. Business and commerce/Information systems and information technology Biological sciences/Psychology Social science/Psychology Social science/Science technology and society Mobile phone social media cyberbullying social anxiety adolescents Introduction The use of mobile phone and social media has become a global phenomenon, largely due to the ease of access to numerous applications that facilitate communication via the internet and increase interpersonal connections (Näher et al., 2023 ). Their benefits are numerous and valuable, although these digital tools have addictive potential due to their design and characteristics (Zhong et al., 2022 ). In this regard, a large number of studies have identified a growing problematic use of these devices among adolescents, as well as an increase in conflicts with parents, emotional problems and digital hygiene issues (Nawaz and Ahmad, 2012 ; Pearson et al, 2021 ). Adolescents spend an average of four hours on their mobile phones, with video games and social media being the most common activities (Marciano and Camerini, 2022 ). Recent studies confirm that problematic use of mobile phones and social media is linked to changes in impulse control and greater difficulty in stopping their use, characteristics typical of addiction (Zhang et al., 2023 ). To counteract the negative effects, it is necessary to cultivate self-control in young people (Deng et al. 2021 ; Hu et al, 2022; Wang et al., 2022a ), good usage habits (Ong et al., 2022 ), and improved emotional management (Nagata et al., 2023 ). This study seeks to explore the problematic use of mobile phone and social media among adolescent students and analyse its relationship with cyberbullying and social anxiety. This is because the use of technology found in mobile phones can impact the mental health, development and well-being of minors (Świątek et al., 2023 ). Furthermore, it has been observed that problematic use of social media is closely linked to the search for social validation and emotional dissatisfaction, which can exacerbate problems such as isolation and emotional dependence in adolescents (Worsley et al., 2022 ). Problematic use of mobile phone and social media The conceptualisation of problematic mobile phone use still lacks specific diagnostic criteria in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5-TR, APA, 2022). This is because, to date, it has not been included as a separate category. Instead, studies such as that by Jo et al. ( 2020 ) have used diagnostic criteria for Internet Gaming Disorder (IGD) to assess patterns of problematic mobile phone and internet use. This trend is observable in other research focusing on IGD, while problematic mobile phone or social media use still lacks a formal diagnostic definition (Darvesh et al., 2020 ; Liu et al., 2022 ). This approach reflects a growing need to differentiate between various forms of problematic technology-related behaviour, including mobile phone use, social media use, and online gaming. Problematic mobile phone use is characterised by difficulty controlling its use, which negatively affects daily activities and emotional well-being (Liu et al., 2022 ). Social anxiety plays an important role in this behaviour, as many adolescents turn to their mobile phones to avoid social interactions, which exacerbates their isolation (Longobardi et al., 2020 ). In terms of social media, the constant search for validation is linked to greater emotional dissatisfaction and dependence on virtual interactions (Worsley et al., 2022 ). These patterns of use affect not only mental health, but also interpersonal relationships and academic performance (Liu et al., 2022 ). Given the prevalence of these behaviours, further research is needed to develop diagnostic criteria that address both problematic mobile phone and social media use (Longobardi et al., 2020 ). Currently, there is a high prevalence of problematic mobile phone use among adolescents, ranging from 10% to 38.5% (Gao et al., 2020 ; Sohn et al., 2019 ). Specifically, in Spain, the prevalence of inappropriate or problematic mobile phone use is 15.4% (De-Sola et al, 2019 ). This study obtains results similar to those discussed in the scientific articles by Romero-Rodríguez et al. ( 2022 )d pez-Fernández (2017) with 13.54% and 12.5%, respectively. Focusing on the adolescent population, studies show variations in the prevalence of problematic mobile phone use. In Nepal, the prevalence among adolescents was 21.7% (Thapa et al., 2020 ). In India, problematic mobile phone use among adolescents reached 21% (Bhatt et al., 2017 ). In China, the study reported a prevalence of 27.92% among adolescents (Yuchang et al., 2017 ). Problematic mobile phone use manifests differently according to gender, age, and country (Li et al., 2022b). In terms of gender, women tend to have more problems with mobile phone use and more dependency-related behaviours (Marín et al., 2022 ). Women report more difficulties with mobile phone use, as they spend a significant amount of time on their phones, which leads to higher phone bills, while men are significantly more likely to use social media passively (Oviedo-Trespalacios, 2019; Stieger and Wunderl, 2022 ). However, these findings are not conclusive, as other studies conclude that men are more likely to exhibit this problematic use (Li et al, 2022b). Similarly, research conducted by Vally and El Hichami ( 2019 ) revealed that in a sample of adolescents, the age group with the highest percentage of problematic mobile phone use was the youngest, with a prevalence of approximately 80%. As for the negative repercussions of problematic mobile phone and social media use, both prolonged and excessive use of mobile phones can lead to symptoms such as anxiety, behavioural and emotional problems, behavioural addiction, poorer sleep quality, bad moods and low psychological well-being (Kliesener et al., 2022 ). In relation to this, research carried out by Tomczyk and Lizde ( 2022 ) found that one-third of those surveyed had nomophobia and one-tenth had high levels of phubbing, a term that describes the act of ignoring people present in a social interaction by paying more attention to one's mobile phone. In fact, adolescents feel compelled to check their mobile phones to keep up to date, and this in turn is linked to anxiety and depression, as there is also a significant relationship between fear of missing out (FoMO) and problematic use of mobile phones and social media (Sun et al., 2022 ). Problematic use of mobile phone, social media, and cyberbullying Cyberbullying is considered intentional and repetitive harassment perpetrated by a person or group and carried out through digital devices such as mobile phones (Selwyn and Aagaard, 2021 ). This phenomenon is most prevalent among adolescents and young adults, who tend to be the main users of mobile devices and social media. In particular, people who use mobile phones and social media problematically are more vulnerable, as both phenomena share a digital platform. Thus, greater use of digital media translates into more risks encountered and less participation in constructive socialisation, which can lead to aggressive and inappropriate behaviour (Blinka et al., 2023 ). Furthermore, problematic mobile phone use is positively associated with participation in cyberbullying, increasing the rates of perpetration of this behaviour and causing negative emotional states (Shin and Kim, 2022 ). In this regard, a study conducted with adolescents found that emotional regulation problems and psychiatric symptoms were risk factors for problematic mobile phone use and cyberbullying (Gül et al., 2019 ). These data are also corroborated by the research of Peláez-Fernández et al. ( 2021 ), who identify that cybervictimisation can drive problematic mobile phone use as a strategy to reduce the negative feelings resulting from cyberbullying. This relationship can be explained by the fact that adolescents, when experiencing negative emotions as a result of online bullying, tend to use mobile phones and social media excessively as a form of escape or emotional regulation, which in turn increases their dependence on these devices (Li et al., 2022a; Longobardi et al., 2020 ). Thus, recent research also highlights the role of psychological insecurity and lack of family support as key factors in perpetuating this cycle of victimisation and problematic social media use (Gao et al., 2020 ). Furthermore, social anxiety has been identified as a determining factor in the relationship between problematic social media use and cyberbullying. Studies have shown that adolescents with higher levels of social anxiety are more likely to develop a dependence on social media, using these platforms as a refuge from face-to-face social interactions (Liu et al., 2022 ). This behaviour can make them more vulnerable to cyberbullying and, as a result, intensify their problematic use of these platforms as a way of coping with the negative emotions that arise from these experiences. For example, research by Tomczyk and Lizde ( 2022 ) found that social anxiety and the need for constant validation on social media were highly correlated with fear of missing out (FoMO), which, in turn, increased mobile phone dependence and exposure to cyberbullying. On the other hand, it has been observed that age and gender differences also influence the dynamics of problematic mobile phone use and cyberbullying. Adolescent girls tend to have more problems related to excessive use of social media, which makes them more susceptible to cybervictimisation. This could be due, in part, to the fact that young women are more likely to seek emotional validation and social acceptance on digital platforms, which increases their exposure to cyberbullying (Marín et al., 2022 ; Stieger and Wunderl, 2022 ). On the other hand, men tend to be more involved in passive behaviours on social media, which could explain the weaker relationship between their problematic use and online victimisation (Li et al., 2022b; Oviedo-Trespalacios, 2019). In conclusion, all the articles discussed agree on a link between problematic mobile phone use and cyberbullying. To combat inappropriate use of mobile phones and social media, as well as cyberbullying, many specialists suggest banning mobile phones in classrooms in order to minimise adolescents' exposure to these risks during school hours and encourage healthier use of devices outside the school environment (Selwyn and Aagaard, 2021 ). This measure could help reduce the amount of time adolescents spend on their mobile phones and social media, thereby reducing their exposure to victimisation and improving their overall psychological well-being. Problematic use of mobile phone, social media, and social anxiety Social anxiety is defined as the fear of negative social scrutiny and evaluation, characterised by tension and nervousness in social settings (Annoni et al., 2021 ). According to the revised version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5-TR) of the American Psychiatric Association (APA, 2022), social anxiety disorder is characterised by an intense and persistent fear of situations in which the person may be evaluated by others. People with this disorder fear acting in ways that will be negatively judged, which can lead to significant avoidance of social situations or facing them with great distress. Numerous studies have identified a significant relationship between problematic mobile phone and social media use and social anxiety in adolescents. This relationship may be mediated by factors such as cybervictimisation, psychological insecurity, and unregulated social media use (Li et al., 2022b). Thus, Kong et al. ( 2022 ) found in a sample of 14- and 17-year-old students, using the Questionnaire for Adolescent Problematic Mobile phone Use (Tao et al., 2013 ) and the Social Anxiety Scale for Adolescents (Aritzeta et al., 2017 ), that social anxiety affects dependence on mobile phones and social networks, as people with social anxiety feel more protected and in a relatively safe environment when interacting via mobile phone. Przepiorka et al. ( 2021 ) also found a positive relationship between social anxiety and problematic mobile phone use in a sample of students aged 10 to 14 using The Mobile phone Addiction Scale (Kwon et al., 2013 ) and The Liebowitz Social Anxiety Scale for Children and Adolescents (LSAS-CA-SR) (Shachar et al., 2014 ). It follows that communication via mobile phones allows adolescents with social anxiety to compensate for their lower social skills (Kim et al., 2019 ). A recent meta-analysis of these variables supported a significant positive correlation between social anxiety and mobile phone addiction, suggesting that social anxiety is a predictor of the development of mobile phone addiction in adolescents and adults (Ran et al., 2022 ). In summary, empirical evidence shows that mobile phones and social media allow socially anxious individuals to find a safe place through which they can communicate and, therefore, a way to avoid offline social situations through problematic use of the same (Annoni et al., 2021 ; Lee et al., 2019 ). The present Study There is not much research analysing the relationship between problematic mobile phone and social media use and its relationship with cyberbullying, cybervictimisation and social anxiety, and most studies used different population samples. Therefore, taking into account the limitations of previous studies, the research objectives of this study are to analyse the differences in cyberbullying, cybervictimisation and social anxiety between adolescents with a problematic mobile phone use and problematic social media use, to determine its impact on adolescents. Based on the objectives described above, the following hypotheses are proposed: on the one hand, differences are expected to be found in the variables of cyberbullying, cybervictimisation and social anxiety between students with different degrees of problematic mobile phone and social media use, with students with more problematic use obtaining significantly higher scores in cyberbullying, cybervictimisation, and social anxiety (hypothesis 1); on the other hand, cyberbullying, cybervictimisation and social anxiety will be significant predictors of both problematic mobile phone use and social media use (hypothesis 2). The study justifies the need to investigate these variables due to the negative repercussions associated with problematic use of both social media and mobile phones in adolescence. These problematic behaviours are linked to symptoms such as anxiety, behavioural and emotional problems, addiction, impaired sleep quality, general malaise and low psychological well-being (Luengo-González et al., 2023 ). Furthermore, excessive use of these devices can intensify the experience of cyberbullying and exacerbate social anxiety, creating a harmful cycle that profoundly affects the emotional and social development of adolescents (Annoni et al., 2021 ; Wang et al., 2022b ). In this context, understanding how cyberbullying and social anxiety influence problematic mobile phone and social media use is crucial to addressing and mitigating these adverse effects. Method Participants The reference population included students of Secondary Education from the province of Alicante (Spain). The initial sample consisted of 1210 students from Year 7 to Year 13, randomly selected from six secondary schools, specifically five public and one private, with around 200 students per school. Of this total, 46 (3.8%) were excluded due to omissions or errors in their responses. Thus, the final sample consisted of 1164 students (599 females (52%) and 565 males (48%)) aged between 12 and 18 (M = 14.56; SD = 1.4), with 130 (11.2%) aged between 12 and 13, 301 (25.9%) aged 13 to 14, 333 (28.6%) aged 14 to 15, 250 (21.5%) aged 15 to 16, and 150 (12.9%) aged 16 to 18. The Chi-square test of homogeneity of frequency distribution revealed that there were no statistically significant differences between the ten groups of gender x year ( χ ² = 9.7; p = .28). Instruments To assess problematic mobile phone use, the Problematic Mobile phone Use Scale from the Problematic Use of New Technologies Questionnaire (Delgado et al., 2021 ) was used. The scale consists of 10 items that assess the frequency and intensity of problematic mobile phone use and measure associated symptoms, such as recurrent thoughts of being connected (e.g., ‘Are you thinking about using your mobile phone hours before you actually use it?’), feelings of irritability or withdrawal (e.g., ‘Do you feel nervous if it has been a long time since you last used your mobile phone?’ ‘), inattention to educational, family or social activities (e.g. ’Do you continue to use your mobile phone even though this causes problems with others, in your studies, with your family...?"), social isolation, among others, using a 5-point Likert scale: 1 (never) to 5 (always). The subscale obtained an adequate reliability index ( α = .87) for the sample analysed. Problematic social media use was assessed using the Problematic Social Media Use Questionnaire (Delgado et al., 2023), which consists of 13 items that measure the intensity of social media use. Respondents answered using a Likert scale with five response options (1 = never; 5 = always) (e.g. ‘Do you think in advance about when you will be able to connect to social media?’ or ‘Has the time you spend using social media affected your performance (grades) or your motivation to study?’). The questionnaire allows for the identification of the frequency of the main behaviours associated with problematic social media use, such as dependence, interference with daily activities, discomfort, and lack of control. The reliability index of the test in this study was adequate ( α = .86). Social anxiety was assessed using the Social Anxiety Scale for Adolescents (SAS-A; Olivares et al., 2005 ), a self-report measure that assesses social fears and concerns and avoidance in social situations in adolescents. It consists of 18 items that measure social anxiety and 4 filler items. The SAS-A includes three subscales: Fear of Negative Evaluation (FNE) consists of 8 items that assess fears, concerns, or worries regarding peers' negative evaluations (e.g., ‘I worry about what others say about me’); Social Avoidance and Distress in New Situations (SAD-N) consists of 6 items that assess social avoidance and distress in new social situations or with unfamiliar peers (e.g., ‘I get nervous when I talk to peers I do not know very well’); and Social Avoidance and Distress-General (SAD-G) consists of 4 items that assess general social inhibition, distress, and discomfort (e.g., “I am quiet when I am with a group of people”). Items from each subscale are summed such that higher scores reflect greater social anxiety. Reliability indices (α) were adequate for the FNE (.93), SAD-N (.88) and SAD-G (.81) subscales, and the overall SAS-A score (.93). Finally, the Garaigordobil Peer Bullying Screening (2016) was used to assess cyberbullying. This is a self-report that assesses both face-to-face bullying (Bullying subscale) and electronic bullying (Cyberbullying subscale). In the present study, we only used the Cyberbullying subscale: 15 items of cyberbullying and 15 items of cybervictimization. This assesses 15 electronic bullying behaviors (e.g., sending offensive and insulting messages, making offensive calls, disseminating photos or videos on YouTube, making frightening anonymous calls, blackmailing or threatening someone) to identify victims and bullies in the past year. The questionnaire is answered using a Likert scale with four response options (1 = never; 4 = always). The psychometric studies carried out by the original authors confirm the adequate internal consistency of the test (α = . 91). The reliability indices of the subscales of the cyberbullying questionnaire in the study sample were good: cybervictimization ( α = .87), and cyberbullying ( α = .89). Procedure After obtaining approval for collaboration from the management and guidance departments of the educational centres, as well as the informed consent of the families of the participating students, the questionnaires were answered collectively and anonymously by the students in the computer room using an online form. The researchers were present during the administration of the tests to clarify any doubts and verify that the students completed the questionnaires independently and voluntarily. The average response time for the tests was 20 minutes. The study, including the consent methods used, received approval from the Research Ethics Committee (UA-2023-02-07). In addition, all regulations concerning research involving human subjects were observed, in accordance with the ethical principles set forth in the Declaration of Helsinki. Statistical analysis First, the sample was grouped according to problematic mobile phone/social media use scores into: (1) low problematic use (scores equal to or below the 25 percentile), (2) medium problematic use, and (3) high problematic use (scores equal to or above the 75 percentile). Secondly, to analyse the differences in cyberbullying, cybervictimisation and social anxiety between the three groups, an analysis of variance (ANOVA) and Bonferroni post hoc test were performed to identify between which groups these differences existed. In addition, the effect size was calculated using Cohen's d (1988). Regarding the interpretation of the effect size, values less than or equal to 0.20 indicate a very small or insignificant effect size, those between 0.20 and 0.49 are considered small, those between 0.50 and 0.79 are moderate, and those above 0.80 are considered large. Finally, to evaluate the explanation of cyberbullying and social anxiety on problematic social media and mobile phone use, a stepwise forward logistic regression analysis based on the Wald method was performed. To estimate the fit of each model, the percentage of correctly matched cases was calculated, as well as Nagelkerke's R 2 . The probability of an event occurring was quantified using the odds ratio ( OR ). Thus, OR values greater than 1 establish that the probability of an event (e.g., problematic use of mobile phones/social media) is greater than that of no event, and values from 0 to 0.99 indicate that the possibility of an event is lower than the probability of no event. SPSS 23.0 (IBM Corporation) was used for ANOVA and logistic regression analysis. Results Differences in cyberbullying and social anxiety in students with low, medium, and high problematic mobile phone use The results obtained indicate that there are statistically significant differences in cyberbullying and social anxiety scores between the different groups of problematic mobile phone use (see Table 1 ). Post hoc tests indicate that students with high problematic mobile phone use obtain significantly higher scores in cybervictimisation than the low ( t = 2.39, p = .001) and medium problematic mobile phone use groups ( t = 1.78, p = .001). Table 1 Differences in cyberbullying, cybervictimisation and social anxiety traits among students with low, medium, and high problematic mobile phone use Low PUSP Medium PUSP High PUSP Statistical significance M (SD) M (SD) M (SD) F p Cyberbullying 16.67 (2.68) 17.31 (2.88) 18.65 (5.00) 30.17 .001 Cybervictimisation 17.52 (3.67) 18.12 (3.53) 19.91 (5.22) 34.60 .001 Social Anxiety FNE 14.95 (5.50) 17.11 (5.25) 18.70 (5.30) 45.08 .001 SAD-N 12.73 (5.16) 14.22 (4.94) 15.43 (5.37) 25.38 .001 SAD-G 7.82 (4.87) 9.87 (4.61) 11.50 (4.88) 54.59 .001 Note . PUSM: Problematic Use of Mobile phone; FNE: Fear of Negative Evaluation; SAD-N: Social Anxiety and Distress-New; SAD-G: Social Anxiety and Distress-General; M: Mean; SD: Standard Deviation. On the other hand, students with high problematic mobile phone use score significantly higher on cyberbullying than students with medium ( t = 1.34, p = .001) and low ( t = 1.98, p = .001) problematic mobile phone use. In fact, students with medium problematic mobile phone use had significantly higher scores for cyberbullying ( t = .64, p = .02) than those with low problematic mobile phone use. Effect sizes were moderate for differences in cybervictimisation ( d = .51-.55) and small for differences in cyberbullying ( d = 0.35-.49). (Insert Table 1 here) In addition, students with high problematic mobile phone use score significantly higher on the scale of fear of negative evaluation, social avoidance and discomfort in new situations, and social avoidance and discomfort in social situations in general than students with average problematic mobile phone use (FNE: t = 1.58, p = .001; SAD-N: t = 1.21, p = .01; SAD-G: t = 1.63, p = .001) and low (FNE: t = 3.75, p = .001; SAD-N: t = 2.70, p = 0.001; SAD-G: t = 2.04, p = .001). Additionally, students with moderate problematic mobile phone use have significantly higher scores in social anxiety in all its manifestations (FNE: t = 2.16, p = .001; SAD-N: t = 1.50, p = .001; SAD-G: t = 3.35, p = .001) than those with low problematic mobile phone use (see Table 2 ). The effect sizes for differences in social anxiety were moderate between the high and low problematic mobile phone use groups ( d = 0.51–0.75) and small between the medium group and the rest of the groups analysed ( d = 0.23–0.43). Table 2 Differences in cyberbullying, cybervictimisation, and social anxiety among students with low, medium, and high problematic social media use Low PUSM Medium PUSM High PUSM Statistical significance M (SD) M (SD) M (SD) F p Cyberbullying 15.47 (3.22) 15.63 (1.38) 17.00 (4.32) 25.79 .001 Cybervictimisation 16.26 (2.61) 17.02 (3.26) 19.60 (6.53) 44.93 .001 Social Anxiety FNE 14.27 (7.50) 17.68 (8.04) 22.39 (8.60) 27.40 .001 SAD-N 11.59 (5.30) 13.12 (5.15) 16.40 (5.92) 23.38 .001 SAD-G 6.32 (3.11) 6.90 (3.17) 8.69 (3.65) 16.33 .001 Note . PUSM: Problematic Use of Social Media; FNE: Fear of Negative Evaluation; SAD-N: Social Anxiety and Distress-New; SAD-G: Social Anxiety and Distress-General; M: Mean; SD: Standard Deviation. Differences in cyberbullying, cybervictimisation and social anxiety among students with low, medium, and high problematic social media use The results of the variance analyses indicate that there are statistically significant differences in cyberbullying and social anxiety scores between groups (see Table 2 ). Specifically, post-hoc tests detected that students with high scores in problematic social media use had significantly higher scores in cyberbullying and cybervictimisation than groups with low scores ( t = 1.53, p = .001, ; t = 3.35, p = .001) and average scores on problematic social media use (t = 1.37, p = .001; t = 2.57, p = .001). Effect sizes were moderate in all cases ( d > 0.51). In addition, students with high scores on problematic social media use obtained significantly higher scores than students with average and low scores on the fear of negative evaluation ( t = 4.71, p = .001 ; t = 8.12, p = .001) and social avoidance and discomfort in new situations (SAD-N) scales ( t = 3.28, p = .001; t = 4.81, p = .001). In fact, students with moderate problematic use scored significantly higher than those with low problematic use ( t = 3.41, p = .01; t = 3.35, p = .001) on the SAD-N subscale. On the other hand, adolescents with high problematic social media use exhibit significantly more social avoidance and discomfort in situations in general than students with medium ( t = 1.78, p = .001) and low ( t = 2.36, p = .001) problematic use. All effect sizes for differences in social anxiety were moderate ( d > 0.54). (Insert Table 2 here) Predicting problematic mobile phone use through cyberbullying, cybervictimisation and social anxiety Logistic regression analyses yielded five explanatory models for problematic mobile phone use based on the scores of the predictor variables analysed (see Table 3 ). Thus, one model was created using cyberbullying scores and another using cybervictimisation scores, with 62.3% ( χ ² = 51.34; p = .001) and 63% ( χ ² = 54.87; p = .001) of cases correctly classified by the models. The goodness of fit (Nalgerkerke's R ²) was .09 and .10, respectively. The OR indicate that adolescents are 19% and 16% more likely to exhibit high problematic mobile phone use as their cyberbullying and cybervictimisation scores increase by one unit, respectively. Table 3 Probability of problematic mobile phone use through cyberbullying, cybervictimisation, and social anxiety Predictor variable B S.E. Wald p OR C.I. 95% Cyberbullying .18 .03 33.67 .001 1.19 1.12–1.27 Constant -2.39 .41 34.35 .001 0.09 Cybervictimisation .14 .02 40.76 .001 1.16 1.11–1.21 Constant -2.11 .33 40.81 .001 0.21 FNE .12 .01 71.27 .001 1.13 1.10–1.17 Constant -2.12 .26 65.97 .001 0.12 SAD-N .10 .01 42.66 .001 1.10 1.07–1.13 Constant -1.37 .22 38.64 .001 0.25 SAD-G .15 .02 81.53 .001 1.16 1.13–1.20 Constant -2.38 .27 75.69 .001 0.09 Note . FNE: Fear of Negative Evaluation; SAD-N: Social Anxiety and Distress-New; SAD-G: Social Anxiety and Distress-General; CI: Confidence Interval; OR: Odds Ratio. Social anxiety symptoms also significantly explain problematic mobile phone use. The model based on fear of negative evaluation ( χ ² = 81.07; p = .001) correctly classified 64.8% of cases, the model based on social avoidance and discomfort in new situations classified 60.7% ( χ ² = 45.87; p = .001), and the model of social avoidance and discomfort in social situations in general classified 65.9% ( χ ² = 95.15; p = .001) of cases correctly. The Nalgerkerke R ² fit indices for the models were .14, .08, and .16, respectively. The OR indicate that students are 13%, 10%, and 16% more likely to maintain problematic mobile phone use as the FNE, SAD-N, and SAD-G social anxiety subscales increase by one unit, respectively. (Insert Table 3 here) Predicting problematic social media use through cyberbullying, cybervictimisation, and social anxiety Based on the logistic regression analyses, it was possible to create five explanatory models of problematic social media use based on cyberbullying and social anxiety (see Table 4 ). Thus, a model was also obtained to predict the probability of problematic social media use through cyberbullying (see Table 4 ), with 65.9% ( χ ²=32.14; p = .00) of cases correctly classified, and a Nalgerkerke's R ² of .08. The OR indicates that the probability of high problematic social media use in adolescents is 1.27 times higher for each unit increase in cyberbullying. Likewise, a predictive model of problematic social media use through cybervictimisation was created, with 66.5% ( χ ²=70.93; p = .001) of cases correctly classified. The goodness of fit (Nalgerkerke's R ²) was .16. The OR indicates that the probability of high problematic social media use is 1.25 times greater as cybervictimisation increases by one unit. Table 4 Probability of problematic social media use through cyberbullying, cybervictimisation and social anxiety Predictor variable B S.E. Wald p OR C.I. 95% Cyberbullying .24 .06 15.55 .001 1.27 1.13–1.44 Constant − .22 .09 5.18 .023 .80 Cybervictimisation .22 .03 40.25 .001 1.25 1.17–1.34 Constant − .52 .11 22.02 .001 .59 FNE .12 .02 37.76 .001 1.12 1.08–1.17 Constant -2.18 .36 36.74 .001 .11 SAD-N .15 .03 31.22 .001 1.16 1.10–1.22 Constant -2.17 .39 30.59 .001 .11 SAD-G .22 .05 22.48 .001 1.25 1.14–1.37 Constant − .1.71 .36 22.53 .001 .18 Note. FNE: Fear of Negative Evaluation; SAD-N: Social Anxiety and Distress-New; SAD-G: Social Anxiety and Distress-General; CI: Confidence Interval; OR: Odds Ratio. With regard to social anxiety, three explanatory models were created for problematic social media use based on scores for fear of negative evaluation ( χ ²=49.06; p = .001), social avoidance and discomfort in new situations ( χ ²=38.66; p = .001), and social avoidance and general discomfort ( χ ²=27.99; p = .001), with 70%, 70%, and 67.5% of cases classified correctly, respectively. Nalgerkerke's R ² indicators were adequate for the models: .25, .20, and .15. The OR indicate that the probability of high problematic social media use increases by 1.12 as the fear of negative evaluation score increases by one unit, by 1.16 as social avoidance and discomfort in new social situations increases by one unit, and by 1.25 as social avoidance and discomfort in social situations in general increases by one unit. (Insert Table 4 here) Discussion The results of this study establish a clear relationship between problematic mobile phone and social media use and cyberbullying and social anxiety in adolescents, confirming the proposed hypotheses. The first hypothesis suggested that students with higher problematic use of social media and mobile phones would score significantly higher on cyberbullying, cybervictimisation, and social anxiety, which was verified through the analyses. These results are consistent with previous research highlighting the role of technology in the development of problematic behaviours among young people. Studies such as that by Worsley et al. ( 2022 ) suggest that excessive use of social media exacerbates the search for emotional validation, which in turn contributes to a cycle of dependence and unregulated use, which can lead to behaviours such as cyberbullying. This coincides with the findings of this research, where students with more problematic social media use scored higher on cyberaggression and cybervictimisation, which could be associated with lower self-control and increased impulsivity (Deng et al., 2021 ). On the other hand, in relation to social anxiety, it was found that adolescents with high levels of problematic mobile phone and social media use also scored higher on fear of negative evaluation and social avoidance, which reinforces the findings of studies such as that by Longobardi et al. ( 2020 ), who stated that problematic mobile phone use is mediated by social anxiety. These results underscore the idea that the use of technology offers a space perceived as safe for adolescents who experience difficulties in face-to-face interactions, serving as a way to avoid direct social contact and exacerbating their technological dependence. Furthermore, the relationship between problematic mobile phone and social media use and cyberbullying and cybervictimisation, as proposed in hypothesis 2, was supported by logistic regression analyses. Adolescents who reported being victims of cyberbullying showed a greater tendency towards problematic use of their devices, which coincides with the findings of Gül et al. ( 2019 ), who identified cybervictimisation as a factor that drives the use of mobile phones and social media as a mechanism for coping with the emotional distress caused by bullying. This phenomenon is also addressed by Li et al. (2022a), who argue that excessive use of mobile phones and social media can contribute to perpetuating online aggression, creating a cycle of dependency and cyberbullying. The results also confirmed that social anxiety is a significant predictor of problematic mobile phone and social media use. Previous studies such as that by Ran et al. ( 2022 ) support this claim, showing that social anxiety has a significant positive correlation with problematic mobile phone use, suggesting that socially anxious adolescents turn to technology to avoid face-to-face interactions, increasing their dependence on these devices. This behaviour is particularly relevant in adolescence, a critical stage for the development of social skills, where problematic use of technologies can interfere with adolescents' social and emotional development. Therefore, this study provides new evidence on the relationship between problematic mobile phone and social media use, cyberbullying, and social anxiety in adolescents, expanding current knowledge in these areas. It is important to note that adolescents with more problematic use of these technologies also reported greater difficulties in emotional regulation, reinforcing the need to implement intervention programmes that promote self-control and appropriate management of emotions in this population, as suggested by Hu et al. (2022). Limitations and Practical Implications Despite the significant contribution of these findings, the study has some limitations. One of them is the lack of a longitudinal assessment that would allow us to observe the development of these behaviours over time, which would be necessary to better understand the underlying dynamics of problematic mobile phone and social media use. Furthermore, the study did not explore gender differences in depth, beyond pointing out general differences, so future research could analyse in greater detail how these variables interact according to gender and other sociodemographic characteristics. It would also be valuable to extend the study to other populations beyond the geographical and school setting of the sample, as the results may vary in different cultural or educational contexts. Finally, this study suggests that interventions should focus on developing digital and emotional skills in adolescents, promoting healthy use of technology and addressing the root causes of social anxiety and cyberbullying. Educational policies that limit the use of mobile devices in school settings could also contribute to reducing these problematic behaviours, as proposed by Selwyn and Aagaard ( 2021 ). It would also be relevant to involve families in these interventions, as emotional support at home has been shown to be a key protective factor against problematic technology use (Gao et al., 2020 ). Conclusions The results of this study show that students with high scores in problematic mobile phone use obtained significantly higher scores in cyberbullying and cybervictimisation. In addition, students with high problematic mobile phone use score significantly higher on the scale of fear of negative evaluation, social avoidance and discomfort in new situations, and social avoidance and discomfort in social situations in general. In the case of adolescents with high scores in problematic social media use had significantly higher scores in cyberbullying and cybervictimisation than groups with low scores. Also, students with high scores on problematic social media use obtained significantly higher scores than students with average and low scores on the fear of negative evaluation and social avoidance and discomfort in new situations scales. On the other hand, adolescents with high problematic social media use exhibit significantly more social avoidance and discomfort in situations in general. Logistic regression analyses showed that cyberbullying, cybervictimization, and social anxiety are significant predictors of problematic mobile phone use and problematic social media use. These results point to the need to take preventive measures against cyberbullying and cybervictimization, which are closely related to the problematic use of new technologies. In addition, intervening in psychological variables such as social anxiety may be key to preventing potentially harmful situations for adolescents in the future, teaching them psychoeducational strategies that promote the responsible use of both mobile phones and social media. Declarations Ethics approval and consent to participate : Standards regarding research on humans were respected, in accordance with the ethical principles of the Declaration of Helsinki and the Ethics Committee (UA-2022-03-21). Consent for publication: The authors consent to the publication of the manuscript. Competing interests: Not applicable. Funding: This research was funded by the Ministry of Science and Innovation, the Agency and the European Regional Development Fund (Project PID123118NA-100 funded by MCIN /AEI / 10.13039/501100011033 / FEDER, EU). Author Contribution DA and BD conceived of the study, participated in its design and coordination, and drafted the manuscript; DA and BD performed a critical review of the manuscript and assisted with interpretation of the findings; BD assisted with the study conception and participated in the statistical analyses; LG and MCMM participated in the design of the study, data interpretation, and assisted in drafting the manuscript. All authors read and approved the final manuscript. Acknowledgements Not applicable. Data Availability Data available if required. References Annoni, A. M., Petrocchi, S., Camerini, A. L. & Marciano, L. The relationship between social anxiety, mobile phone use, dispositional trust, and problematic mobile phone use: A moderated mediation model. Int. J. Environ. Res. Public Health . 18 (5), 2452. https://doi.org/10.3390/ijerph18052452 (2021). American Psychiatric Association. Manual diagnóstico y estadístico de los trastornos mentales (5.ª ed. texto rev.). Editorial Médica Panamericana. (2022). Aritzeta, A. et al. Reducing Anxiety and Improving Academic Performance Through a Biofeedback Relaxation Training Program. Appl. Psychophysiol. Biofeedback . 42 (3), 193–202. https://doi.org/10.1007/s10484-017-9367-z (2017). Bhatt, N., Muninarayanappa, N. V. & Nageshwar, V. y A Study to Assess the Mobile phone Dependence Level and Sleep Quality among Students of Selected Colleges of Moradabad. Indian Journal of Public Health Research & Development , 8 (1): 41. (2017). https://doi.org/10.5958/0976-5506.2017.00009.2 Blinka, L., Stašek, A., Šablatúrová, N., Ševčíková, A. & Husarova, D. Adolescents' problematic internet and mobile phone use in (cyber) bullying experiences: A network analysis. Child Adolesc. Mental Health . 28 (1), 60–66. https://doi.org/10.1111/camh.12628 (2023). Cohen, J. Statistical power analysis for the behavioral sciences (2nd Ed.). Erlbaum. (1988). Darvesh, N., Hides, L., Kavanagh, D. J., Young, R. M. & Connor, J. P. The prevalence and correlates of problematic mobile phone use: A meta-analysis of 24 studies. J. Affect. Disord. 274 , 275–285. https://doi.org/10.1016/j.jad.2020.05.065 (2020). Delgado, B., León, M. J. & Martínez-Monteagudo, M. C. Cuestionario de Uso Problemático de las Nuevas Tecnologías (Universidad de Alicante, 2021). Delgado, B. & Martínez-Monteagudo, M. C. Cuestionario sobre el uso problemático de las redes sociales en adolescentes (Universidad de Alicante, 2023). Deng, X. et al. y Differences in Reward Sensitivity between High and Low Problematic Mobile phone Use Adolescents: An ERP Study. International journal of environmental research and public health , 18 (18), 9603. (2021). https://doi.org/10.3390/ijerph18189603 De-Sola, J. et al. y Rodríguez Cell phone use habits among the Spanish population: contribution of applications to problematic use. Frontiers in Psychiatry , 10 , 883. (2019). https://doi.org/10.3389/fpsyt.2019.00883 Gao, L. et al. y Effect of the mobile phone-related background on inhibitory control of problematic mobile phone use: An event-related potentials study. Addictive Behaviors , 108 , 106363. (2020). https://doi.org/10.1016/j.addbeh.2020.106363 Garaigordobil, M. Screening de acoso entre iguales. En M. Garaigordobil & J. Martínez-Vicente (Eds.), Instrumentos de evaluación en psicología (pp. 105–120). Editorial Síntesis. (2016). Gül, H. et al. Cyberbullying among a clinical adolescent sample in Turkey: effects of problematic mobile phone use, psychiatric symptoms, and emotion regulation difficulties. Psychiatry Clin. Psychopharmacol. 29 (4), 547–557. https://doi.org/10.1080/24750573.2018.1472923 (2019). Hu, Y. T. & Wang, Q. Self-control, parental monitoring, and adolescent problematic mobile phone use: testing the interactive effect and its gender differences. Front. Psychol. 13 , 1554. https://doi.org/10.3389/fpsyg.2022.846618 (2022). Jo, G., Kim, H., Jang, W. & Lee, S. The relationship between internet gaming disorder and problematic mobile phone use: A systematic review. Cyberpsychology Behav. Social Netw. 23 (6), 388–393. https://doi.org/10.1089/cyber.2019.0751 (2020). Kim, M. H., Min, S., Ahn, J. S., An, C. & Lee, J. Association between high adolescent mobile phone use and academic impairment, conflicts with family members or friends, and suicide attempts. PloS One . 14 (7), e0219831. https://doi.org/10.1371/journal.pone.0219831 (2019). Kliesener, T., Meigen, C., Kiess, W. & Poulain, T. y Associations between problematic mobile phone use and behavioural difficulties, quality of life, and school performance among children and adolescents. BMC psychiatry , 22 (1), 1–12. (2022). https://doi.org/10.1186/s12888-022-03815-4 Kong, F., Lan, N., Zhang, H., Sun, X. & Zhang, Y. How does social anxiety affect mobile phone dependence in adolescents? The mediating role of self-concept clarity and self-esteem. Curr. Psychol. 41 , 8070–8077. https://doi.org/10.1007/s12144-020-01262-6 (2021). Kwon, M., Kim, D. J., Cho, H. & Yang, S. The mobile phone addiction scale: development and validation of a short version for adolescents. PloS One . 8 (12), e83558. https://doi.org/10.1371/journal.pone.0083558 (2013). Lee, J. I., Yen, C. F., Hsiao, R. C. & Hu, H. F. Relationships of homophobic bullying during childhood and adolescence with problematic internet and mobile phone use in early adulthood among sexual minority men in Taiwan. Archives Clin. Psychiatry (São Paulo) . 46 , 97–102. https://doi.org/10.1590/0101-60830000000203 (2019). Li, D. J., Chang, Y. P., Chen, Y. L. & Yen, C. F. Mediating effects of emotional symptoms on the association between homophobic bullying victimization and problematic internet/mobile phone use among gay and bisexual men in Taiwan. Int. J. Environ. Res. Public Health . 17 (10), 3386. https://doi.org/10.3390/ijerph17103386 (2020a). Li, D. L. et al. Gender difference in the associations between health literacy and problematic mobile phone use in Chinese middle school students. BMC Public. Health . 23 (1), 1–8. https://doi.org/10.1186/s12889-023-15049-4 (2023b). Liu, Q., Wu, Y., Lin, S. & Liu, X. Network analysis of social anxiety and problematic mobile phone use in Chinese adolescents: A longitudinal study. J. Behav. Addictions . 11 (3), 716–726. https://doi.org/10.1556/2006.2022.00051 (2022). López-Fernández, O. Short version of the Mobile phone Addiction Scale adapted to Spanish and French: Towards a cross-cultural research in problematic mobile phone use. Addict. Behav. 64 , 275–280. https://doi.org/10.1016/j.addbeh.2015.11.013 (2017). Longobardi, C., Settanni, M. & Fabris, M. A. The association between cybervictimization and problematic mobile phone use: A longitudinal study of adolescents. Addict. Behav. 113 , 106699. https://doi.org/10.1016/j.addbeh.2020.106699 (2020). Luengo-González, R. et al. The role of life satisfaction in the association between problematic technology use and anxiety in children and adolescents during the COVID‐19 pandemic. Int. J. Ment. Health Nurs. 32 (1), 212–222. https://doi.org/10.1111/inm.13077 (2023). Marciano, L. & Camerini, A. L. y Duration, frequency, and time distortion: Which is the best predictor of problematic mobile phone use in adolescents? A trace data study. PloS one , 17 (2), e0263815. (2022). https://doi.org/10.1371/journal.pone.0263815 Marín, V., Sampedro, B. E., Ortega, J. M. & Figueroa, J. Predictive factors of problematic mobile phone use in young Spanish university students. Heliyon 8 (9), e10429. https://doi.org/10.1016/j.heliyon.2022.e10429 (2022). Nagata, J. M. et al. Associations between sexual orientation and early adolescent screen use: Findings from the Adolescent Brain Cognitive Development (ABCD) Study. Ann. Epidemiol. 82 , 54–58. https://doi.org/10.1016/j.annepidem.2023.03.004 (2023). Näher, A. F. et al. Secondary data for global health digitalisation. Lancet Digit. Health . 5 (2), e93–e101. https://doi.org/10.1016/S2589-7500(22)00195-9 (2023). Nawaz, S. & Ahmad, Z. Statistical study of impact of mobile on student’s life. IOSR J. Humanit. Social Sci. (JHSS) . 2 (1), 43–49. https://doi.org/10.9790/0837-0214349 (2012). Olivares, J. et al. Social Anxiety Scale for Adolescents (SAS-A): Psychometric properties in a Spanish-speaking population. Int. J. Clin. Health Psychol. 5 (1), 85–97 (2005). Ong, N. C., Kee, Y. H., Pillai, J. S., Lim, H. B. & y Chua, J. H. Problematic mobile phone use among youth athletes: a topic modelling approach. Int. J. Sport Exerc. Psychol. 1–22. https://doi.org/10.1080/1612197X.2022.2078856 (2022). Oviedo-Trespalacios, O., Nandavar, S., Newton, J. D. A., Demant, D. & Phillips, J. G. Problematic Use of Mobile Phones in Australia… Is It Getting Worse? Front. Psychiatry . 10 , 105. https://doi.org/10.3389/fpsyt.2019.00105 (2019). Pearson, A. D., Young, C. M., Shank, F. & Neighbors, C. Flow mediates the relationship between problematic mobile phone use and satisfaction with life among college students. J. Am. Coll. Health . 1–9. https://doi.org/10.1080/07448481.2021.1910274 (2021). Peláez-Fernández, M. A., Chamizo-Nieto, M. T., Rey, L. & Extremera, N. How do cyber victimization and low core self-evaluations interrelate in predicting adolescent problematic technology use? Int. J. Environ. Res. Public Health . 18 (6), 3114. https://doi.org/10.3390/ijerph18063114 (2021). Przepiorka, A., Błachnio, A., Cudo, A. & Kot, P. Social anxiety and social skills via problematic mobile phone use for predicting somatic symptoms and academic performance at primary school. Comput. Educ. 173 , 104286. https://doi.org/10.1016/j.compedu.2021.104286 (2021). Ran, G., Li, J., Zhang, Q. & Niu, X. The association between social anxiety and mobile phone addiction: A three-level meta-analysis. Comput. Hum. Behav. 130 , 107198. https://doi.org/10.1016/j.chb.2022.107198 (2022). Romero-Rodríguez, J. M., Marín-Marín, J. A., Hinojo-Lucena, F. J. & Gómez-García, G. y An explanatory model of problematic Internet use of Southern Spanish university students. Social Science Computer Review , 40 (5), 1171–1185. (2022). https://doi.org/10.1177/0894439321998650 Selwyn, N. & Aagaard, J. Banning mobile phones from classrooms—An opportunity to advance understandings of technology addiction, distraction and cyberbullying. Br. J. Edu. Technol. 52 (1), 8–19. https://doi.org/10.1111/bjet.12943 (2021). Shachar, I., Aderka, I. M. & Gilboa-Schechtman, E. The factor structure of the Liebowitz social anxiety scale for children and adolescents: Development of a brief version. Child. Psychiatry Hum. Dev. 45 , 285–293. https://doi.org/10.1007/s10578-013-0398-2 (2014). Shin, W. & Kim, H. W. Problematic mobile phone use and cyberbullying perpetration in adolescents. Behav. Inform. Technol. 1–20. https://doi.org/10.1111/camh.12628 (2022). Sohn, S. Y., Rees, P., Wildridge, B., Kalk, N. J. & Carter, B. y Prevalence of problematic mobile phone usage and associated mental health outcomes amongst children and young people: a systematic review, meta-analysis and GRADE of the evidence. BMC psychiatry , 19 (1), 1–10. (2019). https://doi.org/10.1186/s12888-019-2350-x Stieger, L. & Wunderl, S. The role of online social anxiety in problematic social networking site use: A longitudinal study. Soc. Sci. Med. 297 , 114805. https://doi.org/10.1016/j.socscimed.2022.114805 (2022). Sun, C., Sun, B., Lin, Y. & Zhou, H. Problematic Mobile phone Use Increases with the Fear of Missing Out Among College Students: The Effects of Self-Control, Perceived Social Support and Future Orientation. Psychol. Res. Behav. Manage. 1–8. https://doi.org/10.2147/PRBM.S345650 (2022). Świątek, A. H. et al. Problematic Mobile phone Use and Social Media Fatigue: The Mediating Role of Self-Control. Psychol. Res. Behav. Manage. 211–222. https://doi.org/10.2147/PRBM.S389806 (2023). Tao, S. M., Fu, J. L., Wang, H., Hao, J. H. & Tao, F. B. Development of self-rating questionnaire for adolescent problematic mobile phone use and the psychometric evaluation in undergraduates. Chin. J. School Health . 34 (1), 26–29. https://doi.org/10.16835/j.cnki.1000-9817.2013.01.010 (2013). Thapa, K., Lama, S., Pokharei, R., Sigdel, R. & Rimal, S. P. y Mobile phone dependence among Undergraduate Students of a Medical College of Eastern Nepal: a descriptive cross-sectional study. JNMA: Journal of the Nepal Medical Association , 58 (224), 234. (2020). https://doi.org/10.31729/jnma.4787 Tomczyk, Ł. & Lizde, E. S. Nomophobia and Phubbing: Wellbeing and new media education in the family among adolescents in Bosnia and Herzegovina. Child Youth Serv. Rev. 137 , 106489. https://doi.org/10.1016/j.childyouth.2022.106489 (2022). Vally, Z. & El Hichami, F. An examination of problematic mobile phone use in the United Arab Emirates: Prevalence, correlates, and predictors in a college-aged sample of young adults. Addict. Behav. Rep. 9 , 100185. https://doi.org/10.1016/j.abrep.2019.100185 (2019). Wang, D., Nie, X., Zhang, D. & Hu, Y. y The relationship between parental psychological control and problematic mobile phone use in early Chinese adolescence: A repeated-measures study at two time-points. Addictive Behaviors , 125 , 107142. (2022a). https://doi.org/10.1016/j.addbeh.2021.107142 Wang, A., Wang, Z., Zhu, Y. & Shi, X. The prevalence and psychosocial factors of problematic mobile phone use among Chinese college students: a three-wave longitudinal study. Front. Psychol. 1476. https://doi.org/10.3389/fpsyg.2022.877277 (2022b). Worsley, J. D., McIntyre, J. C., Bentall, R. P. & Corcoran, R. Problematic social media use and associations with mental health and wellbeing: A systematic review. Clin. Psychol. Rev. 85 , 102002. https://doi.org/10.1016/j.cpr.2021.102002 (2022). Yuchang, J., Cuicui, S., Junxiu, A. & Junyi, L. y Attachment styles and mobile phone addiction in Chinese college students: The mediating roles of dysfunctional attitudes and self-esteem. International Journal of Mental Health and Addiction , 15 (5), 1122–1134. (2017). https://doi.org/10.1007/s11469-017-9772-9 Zhang, Y., Mei, S., Chai, J. & Zhou, Z. Problematic mobile phone use and addiction: A comprehensive review of neurobiological mechanisms. Neurosci. Biobehav. Rev. 144 , 104951. https://doi.org/10.1016/j.neubiorev.2023.104951 (2023). Zhong, L., Huang, V. & Guo, S. Mobile phone paradox: A two-path model connecting mobile phone use and feeling of loneliness for Filipino domestic workers in Hong Kong. Mob. Media Communication . 10 (3), 448–467. https://doi.org/10.1177/20501579221077525 (2022). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 11 Nov, 2025 Reviews received at journal 10 Nov, 2025 Reviews received at journal 06 Nov, 2025 Reviews received at journal 17 Oct, 2025 Reviewers agreed at journal 16 Oct, 2025 Reviewers agreed at journal 15 Oct, 2025 Reviews received at journal 14 Oct, 2025 Reviewers agreed at journal 14 Oct, 2025 Reviewers agreed at journal 14 Oct, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers invited by journal 13 Oct, 2025 Editor assigned by journal 17 Sep, 2025 Submission checks completed at journal 15 Sep, 2025 First submitted to journal 15 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7592472","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":533784299,"identity":"f40e0af1-58c0-412e-96c0-65e57ede8893","order_by":0,"name":"Laura Guisot","email":"","orcid":"","institution":"University of Alicante","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"","lastName":"Guisot","suffix":""},{"id":533784300,"identity":"e62f8d4e-ec62-405a-8392-098f2ee9308f","order_by":1,"name":"David Aparisi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYDCCA0DEA2YxNjAkVJCu5QyRWhh4YBzGNiJ08B0/Y3jgDYNdHv/sw80fHs47LM/A3v4ArxbJMzkGB+cwJBdLnEtsk0jcdtiwgeeMAV4tBgfSEg7zMDAnNpwBugqohbFBIge/wwzOPwNpqU+cf4ax+UPinMP2DfLP8TvM4EbyAaCWw4kbzgDNT2w4nNggwYDfYZI3Hh84OMfgeLEh0GESCcfSk9t4cvBr4Tuf2PzhTUV1ntwZ9scff9RY2/azH8fvMKjzGBLgbDYi1INBAkEVo2AUjIJRMHIBAF04TkGAS+q7AAAAAElFTkSuQmCC","orcid":"","institution":"University of Alicante","correspondingAuthor":true,"prefix":"","firstName":"David","middleName":"","lastName":"Aparisi","suffix":""},{"id":533784301,"identity":"dadad003-43cb-4fd0-a766-2fefb286e18a","order_by":2,"name":"Beatriz Delgado","email":"","orcid":"","institution":"University of Alicante","correspondingAuthor":false,"prefix":"","firstName":"Beatriz","middleName":"","lastName":"Delgado","suffix":""},{"id":533784302,"identity":"aea57aca-9fa3-458c-a34a-78b5af03210f","order_by":3,"name":"María Carmen Martínez-Monteagudo","email":"","orcid":"","institution":"University of Alicante","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"Carmen","lastName":"Martínez-Monteagudo","suffix":""}],"badges":[],"createdAt":"2025-09-11 13:38:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7592472/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7592472/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-026-35842-6","type":"published","date":"2026-02-03T15:57:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":94468200,"identity":"f3437c16-218f-4b6f-b60c-3d6b3a710ebf","added_by":"auto","created_at":"2025-10-27 15:24:13","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":57706,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.docx","url":"https://assets-eu.researchsquare.com/files/rs-7592472/v1/2998cbe7d6c3fa82c63a299f.docx"},{"id":94467549,"identity":"15ff390d-8821-402a-9cab-95bc1f0543cf","added_by":"auto","created_at":"2025-10-27 15:23:00","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":37782,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7592472/v1/d70437d656464b8c592ca770.docx"},{"id":94467724,"identity":"6cfcf548-3d59-41a8-a7be-81d7e93e81ff","added_by":"auto","created_at":"2025-10-27 15:23:37","extension":"json","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5827,"visible":true,"origin":"","legend":"","description":"","filename":"983dfa78663d4aff8f13778aac634151.json","url":"https://assets-eu.researchsquare.com/files/rs-7592472/v1/4e459453bc5a36f2923942fe.json"},{"id":94468027,"identity":"bb10bc43-e96c-4416-b73d-fa7169fca5a9","added_by":"auto","created_at":"2025-10-27 15:23:47","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":161684,"visible":true,"origin":"","legend":"","description":"","filename":"983dfa78663d4aff8f13778aac6341511enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7592472/v1/3451b43548ba0f5a423327c1.xml"},{"id":94467588,"identity":"4f8f21b8-a5a1-4f68-9fce-4051e2e510fc","added_by":"auto","created_at":"2025-10-27 15:23:14","extension":"xml","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":158628,"visible":true,"origin":"","legend":"","description":"","filename":"983dfa78663d4aff8f13778aac6341511structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7592472/v1/6460c08f7338f76baf255f66.xml"},{"id":94467582,"identity":"a93651b0-b028-4b5b-9104-01d6fc8d3e05","added_by":"auto","created_at":"2025-10-27 15:23:10","extension":"html","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":171412,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7592472/v1/b80110b78dbaed37ed5bb227.html"},{"id":102233991,"identity":"5a768af4-b78b-4664-8dff-e4a4defba75f","added_by":"auto","created_at":"2026-02-09 16:02:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1107594,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7592472/v1/6b9e4c56-bd8b-449e-abbe-2e3c1ea5699a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Problematic use of mobile phone and social media among adolescents: relationship with cyberbullying, cybervictimisation, and social anxiety","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe use of mobile phone and social media has become a global phenomenon, largely due to the ease of access to numerous applications that facilitate communication via the internet and increase interpersonal connections (N\u0026auml;her et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Their benefits are numerous and valuable, although these digital tools have addictive potential due to their design and characteristics (Zhong et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In this regard, a large number of studies have identified a growing problematic use of these devices among adolescents, as well as an increase in conflicts with parents, emotional problems and digital hygiene issues (Nawaz and Ahmad, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pearson et al, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Adolescents spend an average of four hours on their mobile phones, with video games and social media being the most common activities (Marciano and Camerini, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Recent studies confirm that problematic use of mobile phones and social media is linked to changes in impulse control and greater difficulty in stopping their use, characteristics typical of addiction (Zhang et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To counteract the negative effects, it is necessary to cultivate self-control in young people (Deng et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hu et al, 2022; Wang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e), good usage habits (Ong et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and improved emotional management (Nagata et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study seeks to explore the problematic use of mobile phone and social media among adolescent students and analyse its relationship with cyberbullying and social anxiety. This is because the use of technology found in mobile phones can impact the mental health, development and well-being of minors (Świątek et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, it has been observed that problematic use of social media is closely linked to the search for social validation and emotional dissatisfaction, which can exacerbate problems such as isolation and emotional dependence in adolescents (Worsley et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eProblematic use of mobile phone and social media\u003c/h3\u003e\n\u003cp\u003eThe conceptualisation of problematic mobile phone use still lacks specific diagnostic criteria in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5-TR, APA, 2022). This is because, to date, it has not been included as a separate category. Instead, studies such as that by Jo et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) have used diagnostic criteria for Internet Gaming Disorder (IGD) to assess patterns of problematic mobile phone and internet use. This trend is observable in other research focusing on IGD, while problematic mobile phone or social media use still lacks a formal diagnostic definition (Darvesh et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This approach reflects a growing need to differentiate between various forms of problematic technology-related behaviour, including mobile phone use, social media use, and online gaming. Problematic mobile phone use is characterised by difficulty controlling its use, which negatively affects daily activities and emotional well-being (Liu et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Social anxiety plays an important role in this behaviour, as many adolescents turn to their mobile phones to avoid social interactions, which exacerbates their isolation (Longobardi et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In terms of social media, the constant search for validation is linked to greater emotional dissatisfaction and dependence on virtual interactions (Worsley et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These patterns of use affect not only mental health, but also interpersonal relationships and academic performance (Liu et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Given the prevalence of these behaviours, further research is needed to develop diagnostic criteria that address both problematic mobile phone and social media use (Longobardi et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCurrently, there is a high prevalence of problematic mobile phone use among adolescents, ranging from 10% to 38.5% (Gao et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sohn et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Specifically, in Spain, the prevalence of inappropriate or problematic mobile phone use is 15.4% (De-Sola et al, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This study obtains results similar to those discussed in the scientific articles by Romero-Rodr\u0026iacute;guez et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)d pez-Fern\u0026aacute;ndez (2017) with 13.54% and 12.5%, respectively. Focusing on the adolescent population, studies show variations in the prevalence of problematic mobile phone use. In Nepal, the prevalence among adolescents was 21.7% (Thapa et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In India, problematic mobile phone use among adolescents reached 21% (Bhatt et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In China, the study reported a prevalence of 27.92% among adolescents (Yuchang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eProblematic mobile phone use manifests differently according to gender, age, and country (Li et al., 2022b). In terms of gender, women tend to have more problems with mobile phone use and more dependency-related behaviours (Mar\u0026iacute;n et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Women report more difficulties with mobile phone use, as they spend a significant amount of time on their phones, which leads to higher phone bills, while men are significantly more likely to use social media passively (Oviedo-Trespalacios, 2019; Stieger and Wunderl, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, these findings are not conclusive, as other studies conclude that men are more likely to exhibit this problematic use (Li et al, 2022b). Similarly, research conducted by Vally and El Hichami (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) revealed that in a sample of adolescents, the age group with the highest percentage of problematic mobile phone use was the youngest, with a prevalence of approximately 80%. As for the negative repercussions of problematic mobile phone and social media use, both prolonged and excessive use of mobile phones can lead to symptoms such as anxiety, behavioural and emotional problems, behavioural addiction, poorer sleep quality, bad moods and low psychological well-being (Kliesener et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In relation to this, research carried out by Tomczyk and Lizde (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found that one-third of those surveyed had nomophobia and one-tenth had high levels of phubbing, a term that describes the act of ignoring people present in a social interaction by paying more attention to one's mobile phone. In fact, adolescents feel compelled to check their mobile phones to keep up to date, and this in turn is linked to anxiety and depression, as there is also a significant relationship between fear of missing out (FoMO) and problematic use of mobile phones and social media (Sun et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eProblematic use of mobile phone, social media, and cyberbullying\u003c/h2\u003e\u003cp\u003eCyberbullying is considered intentional and repetitive harassment perpetrated by a person or group and carried out through digital devices such as mobile phones (Selwyn and Aagaard, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This phenomenon is most prevalent among adolescents and young adults, who tend to be the main users of mobile devices and social media. In particular, people who use mobile phones and social media problematically are more vulnerable, as both phenomena share a digital platform. Thus, greater use of digital media translates into more risks encountered and less participation in constructive socialisation, which can lead to aggressive and inappropriate behaviour (Blinka et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, problematic mobile phone use is positively associated with participation in cyberbullying, increasing the rates of perpetration of this behaviour and causing negative emotional states (Shin and Kim, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In this regard, a study conducted with adolescents found that emotional regulation problems and psychiatric symptoms were risk factors for problematic mobile phone use and cyberbullying (G\u0026uuml;l et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These data are also corroborated by the research of Pel\u0026aacute;ez-Fern\u0026aacute;ndez et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), who identify that cybervictimisation can drive problematic mobile phone use as a strategy to reduce the negative feelings resulting from cyberbullying. This relationship can be explained by the fact that adolescents, when experiencing negative emotions as a result of online bullying, tend to use mobile phones and social media excessively as a form of escape or emotional regulation, which in turn increases their dependence on these devices (Li et al., 2022a; Longobardi et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Thus, recent research also highlights the role of psychological insecurity and lack of family support as key factors in perpetuating this cycle of victimisation and problematic social media use (Gao et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, social anxiety has been identified as a determining factor in the relationship between problematic social media use and cyberbullying. Studies have shown that adolescents with higher levels of social anxiety are more likely to develop a dependence on social media, using these platforms as a refuge from face-to-face social interactions (Liu et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This behaviour can make them more vulnerable to cyberbullying and, as a result, intensify their problematic use of these platforms as a way of coping with the negative emotions that arise from these experiences. For example, research by Tomczyk and Lizde (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found that social anxiety and the need for constant validation on social media were highly correlated with fear of missing out (FoMO), which, in turn, increased mobile phone dependence and exposure to cyberbullying.\u003c/p\u003e\u003cp\u003eOn the other hand, it has been observed that age and gender differences also influence the dynamics of problematic mobile phone use and cyberbullying. Adolescent girls tend to have more problems related to excessive use of social media, which makes them more susceptible to cybervictimisation. This could be due, in part, to the fact that young women are more likely to seek emotional validation and social acceptance on digital platforms, which increases their exposure to cyberbullying (Mar\u0026iacute;n et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Stieger and Wunderl, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). On the other hand, men tend to be more involved in passive behaviours on social media, which could explain the weaker relationship between their problematic use and online victimisation (Li et al., 2022b; Oviedo-Trespalacios, 2019). In conclusion, all the articles discussed agree on a link between problematic mobile phone use and cyberbullying. To combat inappropriate use of mobile phones and social media, as well as cyberbullying, many specialists suggest banning mobile phones in classrooms in order to minimise adolescents' exposure to these risks during school hours and encourage healthier use of devices outside the school environment (Selwyn and Aagaard, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This measure could help reduce the amount of time adolescents spend on their mobile phones and social media, thereby reducing their exposure to victimisation and improving their overall psychological well-being.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eProblematic use of mobile phone, social media, and social anxiety\u003c/h3\u003e\n\u003cp\u003eSocial anxiety is defined as the fear of negative social scrutiny and evaluation, characterised by tension and nervousness in social settings (Annoni et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). According to the revised version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5-TR) of the American Psychiatric Association (APA, 2022), social anxiety disorder is characterised by an intense and persistent fear of situations in which the person may be evaluated by others. People with this disorder fear acting in ways that will be negatively judged, which can lead to significant avoidance of social situations or facing them with great distress.\u003c/p\u003e\u003cp\u003eNumerous studies have identified a significant relationship between problematic mobile phone and social media use and social anxiety in adolescents. This relationship may be mediated by factors such as cybervictimisation, psychological insecurity, and unregulated social media use (Li et al., 2022b).\u003c/p\u003e\u003cp\u003eThus, Kong et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found in a sample of 14- and 17-year-old students, using the Questionnaire for Adolescent Problematic Mobile phone Use (Tao et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and the Social Anxiety Scale for Adolescents (Aritzeta et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), that social anxiety affects dependence on mobile phones and social networks, as people with social anxiety feel more protected and in a relatively safe environment when interacting via mobile phone. Przepiorka et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) also found a positive relationship between social anxiety and problematic mobile phone use in a sample of students aged 10 to 14 using The Mobile phone Addiction Scale (Kwon et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and The Liebowitz Social Anxiety Scale for Children and Adolescents (LSAS-CA-SR) (Shachar et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). It follows that communication via mobile phones allows adolescents with social anxiety to compensate for their lower social skills (Kim et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). A recent meta-analysis of these variables supported a significant positive correlation between social anxiety and mobile phone addiction, suggesting that social anxiety is a predictor of the development of mobile phone addiction in adolescents and adults (Ran et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In summary, empirical evidence shows that mobile phones and social media allow socially anxious individuals to find a safe place through which they can communicate and, therefore, a way to avoid offline social situations through problematic use of the same (Annoni et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lee et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eThe present Study\u003c/h3\u003e\n\u003cp\u003eThere is not much research analysing the relationship between problematic mobile phone and social media use and its relationship with cyberbullying, cybervictimisation and social anxiety, and most studies used different population samples. Therefore, taking into account the limitations of previous studies, the research objectives of this study are to analyse the differences in cyberbullying, cybervictimisation and social anxiety between adolescents with a problematic mobile phone use and problematic social media use, to determine its impact on adolescents. Based on the objectives described above, the following hypotheses are proposed: on the one hand, differences are expected to be found in the variables of cyberbullying, cybervictimisation and social anxiety between students with different degrees of problematic mobile phone and social media use, with students with more problematic use obtaining significantly higher scores in cyberbullying, cybervictimisation, and social anxiety (hypothesis 1); on the other hand, cyberbullying, cybervictimisation and social anxiety will be significant predictors of both problematic mobile phone use and social media use (hypothesis 2). The study justifies the need to investigate these variables due to the negative repercussions associated with problematic use of both social media and mobile phones in adolescence. These problematic behaviours are linked to symptoms such as anxiety, behavioural and emotional problems, addiction, impaired sleep quality, general malaise and low psychological well-being (Luengo-Gonz\u0026aacute;lez et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, excessive use of these devices can intensify the experience of cyberbullying and exacerbate social anxiety, creating a harmful cycle that profoundly affects the emotional and social development of adolescents (Annoni et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e). In this context, understanding how cyberbullying and social anxiety influence problematic mobile phone and social media use is crucial to addressing and mitigating these adverse effects.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eThe reference population included students of Secondary Education from the province of Alicante (Spain). The initial sample consisted of 1210 students from Year 7 to Year 13, randomly selected from six secondary schools, specifically five public and one private, with around 200 students per school. Of this total, 46 (3.8%) were excluded due to omissions or errors in their responses. Thus, the final sample consisted of 1164 students (599 females (52%) and 565 males (48%)) aged between 12 and 18 (M\u0026thinsp;=\u0026thinsp;14.56; SD\u0026thinsp;=\u0026thinsp;1.4), with 130 (11.2%) aged between 12 and 13, 301 (25.9%) aged 13 to 14, 333 (28.6%) aged 14 to 15, 250 (21.5%) aged 15 to 16, and 150 (12.9%) aged 16 to 18. The Chi-square test of homogeneity of frequency distribution revealed that there were no statistically significant differences between the ten groups of gender x year (\u003cem\u003eχ\u003c/em\u003e\u0026sup2; = 9.7; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.28).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eInstruments\u003c/h2\u003e\u003cp\u003eTo assess problematic mobile phone use, the Problematic Mobile phone Use Scale from the \u003cem\u003eProblematic Use of New Technologies Questionnaire\u003c/em\u003e (Delgado et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) was used. The scale consists of 10 items that assess the frequency and intensity of problematic mobile phone use and measure associated symptoms, such as recurrent thoughts of being connected (e.g., \u0026lsquo;Are you thinking about using your mobile phone hours before you actually use it?\u0026rsquo;), feelings of irritability or withdrawal (e.g., \u0026lsquo;Do you feel nervous if it has been a long time since you last used your mobile phone?\u0026rsquo; \u0026lsquo;), inattention to educational, family or social activities (e.g. \u0026rsquo;Do you continue to use your mobile phone even though this causes problems with others, in your studies, with your family...?\"), social isolation, among others, using a 5-point Likert scale: 1 (never) to 5 (always). The subscale obtained an adequate reliability index (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.87) for the sample analysed.\u003c/p\u003e\u003cp\u003eProblematic social media use was assessed using the \u003cem\u003eProblematic Social Media Use Questionnaire\u003c/em\u003e (Delgado et al., 2023), which consists of 13 items that measure the intensity of social media use. Respondents answered using a Likert scale with five response options (1\u0026thinsp;=\u0026thinsp;never; 5\u0026thinsp;=\u0026thinsp;always) (e.g. \u0026lsquo;Do you think in advance about when you will be able to connect to social media?\u0026rsquo; or \u0026lsquo;Has the time you spend using social media affected your performance (grades) or your motivation to study?\u0026rsquo;). The questionnaire allows for the identification of the frequency of the main behaviours associated with problematic social media use, such as dependence, interference with daily activities, discomfort, and lack of control. The reliability index of the test in this study was adequate (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.86).\u003c/p\u003e\u003cp\u003eSocial anxiety was assessed using the \u003cem\u003eSocial Anxiety Scale for Adolescents\u003c/em\u003e (SAS-A; Olivares et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), a self-report measure that assesses social fears and concerns and avoidance in social situations in adolescents. It consists of 18 items that measure social anxiety and 4 filler items. The SAS-A includes three subscales: Fear of Negative Evaluation (FNE) consists of 8 items that assess fears, concerns, or worries regarding peers' negative evaluations (e.g., \u0026lsquo;I worry about what others say about me\u0026rsquo;); Social Avoidance and Distress in New Situations (SAD-N) consists of 6 items that assess social avoidance and distress in new social situations or with unfamiliar peers (e.g., \u0026lsquo;I get nervous when I talk to peers I do not know very well\u0026rsquo;); and Social Avoidance and Distress-General (SAD-G) consists of 4 items that assess general social inhibition, distress, and discomfort (e.g., \u0026ldquo;I am quiet when I am with a group of people\u0026rdquo;). Items from each subscale are summed such that higher scores reflect greater social anxiety. Reliability indices (α) were adequate for the FNE (.93), SAD-N (.88) and SAD-G (.81) subscales, and the overall SAS-A score (.93).\u003c/p\u003e\u003cp\u003eFinally, the Garaigordobil \u003cem\u003ePeer Bullying Screening\u003c/em\u003e (2016) was used to assess cyberbullying. This is a self-report that assesses both face-to-face bullying (Bullying subscale) and electronic bullying (Cyberbullying subscale). In the present study, we only used the Cyberbullying subscale: 15 items of cyberbullying and 15 items of cybervictimization. This assesses 15 electronic bullying behaviors (e.g., sending offensive and insulting messages, making offensive calls, disseminating photos or videos on YouTube, making frightening anonymous calls, blackmailing or threatening someone) to identify victims and bullies in the past year. The questionnaire is answered using a Likert scale with four response options (1\u0026thinsp;=\u0026thinsp;never; 4\u0026thinsp;=\u0026thinsp;always). The psychometric studies carried out by the original authors confirm the adequate internal consistency of the test (α\u0026thinsp;=\u0026thinsp;. 91). The reliability indices of the subscales of the cyberbullying questionnaire in the study sample were good: cybervictimization (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.87), and cyberbullying (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.89).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eAfter obtaining approval for collaboration from the management and guidance departments of the educational centres, as well as the informed consent of the families of the participating students, the questionnaires were answered collectively and anonymously by the students in the computer room using an online form. The researchers were present during the administration of the tests to clarify any doubts and verify that the students completed the questionnaires independently and voluntarily. The average response time for the tests was 20 minutes. The study, including the consent methods used, received approval from the Research Ethics Committee (UA-2023-02-07). In addition, all regulations concerning research involving human subjects were observed, in accordance with the ethical principles set forth in the Declaration of Helsinki.\u003c/p\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eFirst, the sample was grouped according to problematic mobile phone/social media use scores into: (1) low problematic use (scores equal to or below the 25 percentile), (2) medium problematic use, and (3) high problematic use (scores equal to or above the 75 percentile). Secondly, to analyse the differences in cyberbullying, cybervictimisation and social anxiety between the three groups, an analysis of variance (ANOVA) and Bonferroni post hoc test were performed to identify between which groups these differences existed. In addition, the effect size was calculated using Cohen's \u003cem\u003ed\u003c/em\u003e (1988). Regarding the interpretation of the effect size, values less than or equal to 0.20 indicate a very small or insignificant effect size, those between 0.20 and 0.49 are considered small, those between 0.50 and 0.79 are moderate, and those above 0.80 are considered large.\u003c/p\u003e\u003cp\u003eFinally, to evaluate the explanation of cyberbullying and social anxiety on problematic social media and mobile phone use, a stepwise forward logistic regression analysis based on the Wald method was performed. To estimate the fit of each model, the percentage of correctly matched cases was calculated, as well as Nagelkerke's \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e. The probability of an event occurring was quantified using the odds ratio (\u003cem\u003eOR\u003c/em\u003e). Thus, \u003cem\u003eOR\u003c/em\u003e values greater than 1 establish that the probability of an event (e.g., problematic use of mobile phones/social media) is greater than that of no event, and values from 0 to 0.99 indicate that the possibility of an event is lower than the probability of no event. SPSS 23.0 (IBM Corporation) was used for ANOVA and logistic regression analysis.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eDifferences in cyberbullying and social anxiety in students with low, medium, and high problematic mobile phone use\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe results obtained indicate that there are statistically significant differences in cyberbullying and social anxiety scores between the different groups of problematic mobile phone use (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Post hoc tests indicate that students with high problematic mobile phone use obtain significantly higher scores in cybervictimisation than the low (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.39, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) and medium problematic mobile phone use groups (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.78, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eDifferences in cyberbullying, cybervictimisation and social anxiety traits among students with low, medium, and high problematic mobile phone use\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow PUSP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedium PUSP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh PUSP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eStatistical significance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCyberbullying\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.67 (2.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.31 (2.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.65 (5.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCybervictimisation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.52 (3.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.12 (3.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.91 (5.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eSocial Anxiety\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFNE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.95 (5.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.11 (5.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.70 (5.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAD-N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.73 (5.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.22 (4.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.43 (5.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAD-G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.82 (4.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.87 (4.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.50 (4.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e54.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNote\u003c/em\u003e. PUSM: Problematic Use of Mobile phone; FNE: Fear of Negative Evaluation; SAD-N: Social Anxiety and Distress-New; SAD-G: Social Anxiety and Distress-General; M: Mean; SD: Standard Deviation.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eOn the other hand, students with high problematic mobile phone use score significantly higher on cyberbullying than students with medium (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.34, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) and low (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.98, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) problematic mobile phone use. In fact, students with medium problematic mobile phone use had significantly higher scores for cyberbullying (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.64, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.02) than those with low problematic mobile phone use. Effect sizes were moderate for differences in cybervictimisation (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.51-.55) and small for differences in cyberbullying (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.35-.49).\u003c/p\u003e\u003cp\u003e(Insert Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here)\u003c/p\u003e\u003cp\u003eIn addition, students with high problematic mobile phone use score significantly higher on the scale of fear of negative evaluation, social avoidance and discomfort in new situations, and social avoidance and discomfort in social situations in general than students with average problematic mobile phone use (FNE: \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.58, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001; SAD-N: \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.21, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.01; SAD-G: \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.63, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) and low (FNE: \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.75, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001; SAD-N: \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.70, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001; SAD-G: \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.04, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001). Additionally, students with moderate problematic mobile phone use have significantly higher scores in social anxiety in all its manifestations (FNE: \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.16, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001; SAD-N: \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.50, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001; SAD-G: \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.35, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) than those with low problematic mobile phone use (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The effect sizes for differences in social anxiety were moderate between the high and low problematic mobile phone use groups (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.51\u0026ndash;0.75) and small between the medium group and the rest of the groups analysed (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.23\u0026ndash;0.43).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eDifferences in cyberbullying, cybervictimisation, and social anxiety among students with low, medium, and high problematic social media use\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow PUSM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedium PUSM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh PUSM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eStatistical significance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eM (SD)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCyberbullying\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.47 (3.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.63 (1.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17.00 (4.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCybervictimisation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.26 (2.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.02 (3.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.60 (6.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e44.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eSocial Anxiety\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFNE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.27 (7.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.68 (8.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.39 (8.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAD-N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.59 (5.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.12 (5.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16.40 (5.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAD-G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.32 (3.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.90 (3.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.69 (3.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNote\u003c/em\u003e. PUSM: Problematic Use of Social Media; FNE: Fear of Negative Evaluation; SAD-N: Social Anxiety and Distress-New; SAD-G: Social Anxiety and Distress-General; M: Mean; SD: Standard Deviation.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eDifferences in cyberbullying, cybervictimisation and social anxiety among students with low, medium, and high problematic social media use\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe results of the variance analyses indicate that there are statistically significant differences in cyberbullying and social anxiety scores between groups (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Specifically, post-hoc tests detected that students with high scores in problematic social media use had significantly higher scores in cyberbullying and cybervictimisation than groups with low scores (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.53, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001, ; \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.35, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) and average scores on problematic social media use (t\u0026thinsp;=\u0026thinsp;1.37, p\u0026thinsp;=\u0026thinsp;.001; t\u0026thinsp;=\u0026thinsp;2.57, p\u0026thinsp;=\u0026thinsp;.001). Effect sizes were moderate in all cases (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.51).\u003c/p\u003e\u003cp\u003eIn addition, students with high scores on problematic social media use obtained significantly higher scores than students with average and low scores on the fear of negative evaluation (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.71, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001 ; \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.12, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) and social avoidance and discomfort in new situations (SAD-N) scales (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.28, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001; \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.81, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001). In fact, students with moderate problematic use scored significantly higher than those with low problematic use (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.41, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.01; \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.35, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) on the SAD-N subscale.\u003c/p\u003e\u003cp\u003eOn the other hand, adolescents with high problematic social media use exhibit significantly more social avoidance and discomfort in situations in general than students with medium (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.78, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) and low (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.36, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) problematic use. All effect sizes for differences in social anxiety were moderate (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.54).\u003c/p\u003e\u003cp\u003e(Insert Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e here)\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003ePredicting problematic mobile phone use through cyberbullying, cybervictimisation and social anxiety\u003c/h2\u003e\u003cp\u003eLogistic regression analyses yielded five explanatory models for problematic mobile phone use based on the scores of the predictor variables analysed (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Thus, one model was created using cyberbullying scores and another using cybervictimisation scores, with 62.3% (\u003cem\u003eχ\u003c/em\u003e\u0026sup2; = 51.34; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) and 63% (\u003cem\u003eχ\u003c/em\u003e\u0026sup2; = 54.87; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) of cases correctly classified by the models. The goodness of fit (Nalgerkerke's \u003cem\u003eR\u003c/em\u003e\u0026sup2;) was .09 and .10, respectively. The \u003cem\u003eOR\u003c/em\u003e indicate that adolescents are 19% and 16% more likely to exhibit high problematic mobile phone use as their cyberbullying and cybervictimisation scores increase by one unit, respectively.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eProbability of problematic mobile phone use through cyberbullying, cybervictimisation, and social anxiety\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictor variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eS.E.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWald\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eC.I. 95%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCyberbullying\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e33.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.12\u0026ndash;1.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e34.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCybervictimisation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.11\u0026ndash;1.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFNE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e71.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.10\u0026ndash;1.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAD-N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e42.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.07\u0026ndash;1.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAD-G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e81.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.13\u0026ndash;1.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e75.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNote\u003c/em\u003e. FNE: Fear of Negative Evaluation; SAD-N: Social Anxiety and Distress-New; SAD-G: Social Anxiety and Distress-General; CI: Confidence Interval; OR: Odds Ratio.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eSocial anxiety symptoms also significantly explain problematic mobile phone use. The model based on fear of negative evaluation (\u003cem\u003eχ\u003c/em\u003e\u0026sup2; = 81.07; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) correctly classified 64.8% of cases, the model based on social avoidance and discomfort in new situations classified 60.7% (\u003cem\u003eχ\u003c/em\u003e\u0026sup2; = 45.87; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001), and the model of social avoidance and discomfort in social situations in general classified 65.9% (\u003cem\u003eχ\u003c/em\u003e\u0026sup2; = 95.15; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) of cases correctly. The Nalgerkerke \u003cem\u003eR\u003c/em\u003e\u0026sup2; fit indices for the models were .14, .08, and .16, respectively. The \u003cem\u003eOR\u003c/em\u003e indicate that students are 13%, 10%, and 16% more likely to maintain problematic mobile phone use as the FNE, SAD-N, and SAD-G social anxiety subscales increase by one unit, respectively.\u003c/p\u003e\u003cp\u003e(Insert Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e here)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ePredicting problematic social media use through cyberbullying, cybervictimisation, and social anxiety\u003c/h2\u003e\u003cp\u003eBased on the logistic regression analyses, it was possible to create five explanatory models of problematic social media use based on cyberbullying and social anxiety (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Thus, a model was also obtained to predict the probability of problematic social media use through cyberbullying (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), with 65.9% (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;=32.14; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.00) of cases correctly classified, and a Nalgerkerke's \u003cem\u003eR\u003c/em\u003e\u0026sup2; of .08. The \u003cem\u003eOR\u003c/em\u003e indicates that the probability of high problematic social media use in adolescents is 1.27 times higher for each unit increase in cyberbullying. Likewise, a predictive model of problematic social media use through cybervictimisation was created, with 66.5% (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;=70.93; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) of cases correctly classified. The goodness of fit (Nalgerkerke's \u003cem\u003eR\u003c/em\u003e\u0026sup2;) was .16. The \u003cem\u003eOR\u003c/em\u003e indicates that the probability of high problematic social media use is 1.25 times greater as cybervictimisation increases by one unit.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eProbability of problematic social media use through cyberbullying, cybervictimisation and social anxiety\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictor variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eS.E.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWald\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eC.I. 95%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCyberbullying\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.13\u0026ndash;1.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCybervictimisation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.17\u0026ndash;1.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFNE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e37.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.08\u0026ndash;1.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAD-N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e31.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.10\u0026ndash;1.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAD-G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.14\u0026ndash;1.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote. FNE: Fear of Negative Evaluation; SAD-N: Social Anxiety and Distress-New; SAD-G: Social Anxiety and Distress-General; CI: Confidence Interval; OR: Odds Ratio.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWith regard to social anxiety, three explanatory models were created for problematic social media use based on scores for fear of negative evaluation (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;=49.06; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001), social avoidance and discomfort in new situations (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;=38.66; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001), and social avoidance and general discomfort (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;=27.99; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001), with 70%, 70%, and 67.5% of cases classified correctly, respectively. Nalgerkerke's \u003cem\u003eR\u003c/em\u003e\u0026sup2; indicators were adequate for the models: .25, .20, and .15. The \u003cem\u003eOR\u003c/em\u003e indicate that the probability of high problematic social media use increases by 1.12 as the fear of negative evaluation score increases by one unit, by 1.16 as social avoidance and discomfort in new social situations increases by one unit, and by 1.25 as social avoidance and discomfort in social situations in general increases by one unit.\u003c/p\u003e\u003cp\u003e(Insert Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e here)\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of this study establish a clear relationship between problematic mobile phone and social media use and cyberbullying and social anxiety in adolescents, confirming the proposed hypotheses. The first hypothesis suggested that students with higher problematic use of social media and mobile phones would score significantly higher on cyberbullying, cybervictimisation, and social anxiety, which was verified through the analyses. These results are consistent with previous research highlighting the role of technology in the development of problematic behaviours among young people. Studies such as that by Worsley et al. (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) suggest that excessive use of social media exacerbates the search for emotional validation, which in turn contributes to a cycle of dependence and unregulated use, which can lead to behaviours such as cyberbullying. This coincides with the findings of this research, where students with more problematic social media use scored higher on cyberaggression and cybervictimisation, which could be associated with lower self-control and increased impulsivity (Deng et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOn the other hand, in relation to social anxiety, it was found that adolescents with high levels of problematic mobile phone and social media use also scored higher on fear of negative evaluation and social avoidance, which reinforces the findings of studies such as that by Longobardi et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), who stated that problematic mobile phone use is mediated by social anxiety. These results underscore the idea that the use of technology offers a space perceived as safe for adolescents who experience difficulties in face-to-face interactions, serving as a way to avoid direct social contact and exacerbating their technological dependence.\u003c/p\u003e\u003cp\u003eFurthermore, the relationship between problematic mobile phone and social media use and cyberbullying and cybervictimisation, as proposed in hypothesis 2, was supported by logistic regression analyses. Adolescents who reported being victims of cyberbullying showed a greater tendency towards problematic use of their devices, which coincides with the findings of G\u0026uuml;l et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), who identified cybervictimisation as a factor that drives the use of mobile phones and social media as a mechanism for coping with the emotional distress caused by bullying. This phenomenon is also addressed by Li et al. (2022a), who argue that excessive use of mobile phones and social media can contribute to perpetuating online aggression, creating a cycle of dependency and cyberbullying.\u003c/p\u003e\u003cp\u003eThe results also confirmed that social anxiety is a significant predictor of problematic mobile phone and social media use. Previous studies such as that by Ran et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) support this claim, showing that social anxiety has a significant positive correlation with problematic mobile phone use, suggesting that socially anxious adolescents turn to technology to avoid face-to-face interactions, increasing their dependence on these devices. This behaviour is particularly relevant in adolescence, a critical stage for the development of social skills, where problematic use of technologies can interfere with adolescents' social and emotional development.\u003c/p\u003e\u003cp\u003eTherefore, this study provides new evidence on the relationship between problematic mobile phone and social media use, cyberbullying, and social anxiety in adolescents, expanding current knowledge in these areas. It is important to note that adolescents with more problematic use of these technologies also reported greater difficulties in emotional regulation, reinforcing the need to implement intervention programmes that promote self-control and appropriate management of emotions in this population, as suggested by Hu et al. (2022).\u003c/p\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eLimitations and Practical Implications\u003c/h2\u003e\u003cp\u003eDespite the significant contribution of these findings, the study has some limitations. One of them is the lack of a longitudinal assessment that would allow us to observe the development of these behaviours over time, which would be necessary to better understand the underlying dynamics of problematic mobile phone and social media use. Furthermore, the study did not explore gender differences in depth, beyond pointing out general differences, so future research could analyse in greater detail how these variables interact according to gender and other sociodemographic characteristics. It would also be valuable to extend the study to other populations beyond the geographical and school setting of the sample, as the results may vary in different cultural or educational contexts.\u003c/p\u003e\u003cp\u003eFinally, this study suggests that interventions should focus on developing digital and emotional skills in adolescents, promoting healthy use of technology and addressing the root causes of social anxiety and cyberbullying. Educational policies that limit the use of mobile devices in school settings could also contribute to reducing these problematic behaviours, as proposed by Selwyn and Aagaard (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It would also be relevant to involve families in these interventions, as emotional support at home has been shown to be a key protective factor against problematic technology use (Gao et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe results of this study show that students with high scores in problematic mobile phone use obtained significantly higher scores in cyberbullying and cybervictimisation. In addition, students with high problematic mobile phone use score significantly higher on the scale of fear of negative evaluation, social avoidance and discomfort in new situations, and social avoidance and discomfort in social situations in general.\u003c/p\u003e\u003cp\u003eIn the case of adolescents with high scores in problematic social media use had significantly higher scores in cyberbullying and cybervictimisation than groups with low scores. Also, students with high scores on problematic social media use obtained significantly higher scores than students with average and low scores on the fear of negative evaluation and social avoidance and discomfort in new situations scales. On the other hand, adolescents with high problematic social media use exhibit significantly more social avoidance and discomfort in situations in general. Logistic regression analyses showed that cyberbullying, cybervictimization, and social anxiety are significant predictors of problematic mobile phone use and problematic social media use.\u003c/p\u003e\u003cp\u003eThese results point to the need to take preventive measures against cyberbullying and cybervictimization, which are closely related to the problematic use of new technologies. In addition, intervening in psychological variables such as social anxiety may be key to preventing potentially harmful situations for adolescents in the future, teaching them psychoeducational strategies that promote the responsible use of both mobile phones and social media.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003e\u003cb\u003eEthics approval and consent to participate\u003c/b\u003e:\u003c/h2\u003e\u003cp\u003e Standards regarding research on humans were respected, in accordance with the ethical principles of the Declaration of Helsinki and the Ethics Committee (UA-2022-03-21).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003cp\u003e The authors consent to the publication of the manuscript.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests:\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis research was funded by the Ministry of Science and Innovation, the Agency and the European Regional Development Fund (Project PID123118NA-100 funded by MCIN /AEI /\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.13039/501100011033\u003c/span\u003e\u003cspan address=\"10.13039/501100011033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e / FEDER, EU).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDA and BD conceived of the study, participated in its design and coordination, and drafted the manuscript; DA and BD performed a critical review of the manuscript and assisted with interpretation of the findings; BD assisted with the study conception and participated in the statistical analyses; LG and MCMM participated in the design of the study, data interpretation, and assisted in drafting the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData available if required.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAnnoni, A. M., Petrocchi, S., Camerini, A. L. \u0026amp; Marciano, L. The relationship between social anxiety, mobile phone use, dispositional trust, and problematic mobile phone use: A moderated mediation model. \u003cem\u003eInt. J. Environ. Res. Public Health\u003c/em\u003e. \u003cb\u003e18\u003c/b\u003e (5), 2452. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph18052452\u003c/span\u003e\u003cspan address=\"10.3390/ijerph18052452\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmerican Psychiatric Association. \u003cem\u003eManual diagn\u0026oacute;stico y estad\u0026iacute;stico de los trastornos mentales\u003c/em\u003e (5.\u0026ordf; ed. texto rev.). Editorial M\u0026eacute;dica Panamericana. (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAritzeta, A. et al. Reducing Anxiety and Improving Academic Performance Through a Biofeedback Relaxation Training Program. \u003cem\u003eAppl. Psychophysiol. Biofeedback\u003c/em\u003e. \u003cb\u003e42\u003c/b\u003e (3), 193\u0026ndash;202. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10484-017-9367-z\u003c/span\u003e\u003cspan address=\"10.1007/s10484-017-9367-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBhatt, N., Muninarayanappa, N. V. \u0026amp; Nageshwar, V. y A Study to Assess the Mobile phone Dependence Level and Sleep Quality among Students of Selected Colleges of Moradabad. \u003cem\u003eIndian Journal of Public Health Research \u0026amp; Development\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(1): 41. (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5958/0976-5506.2017.00009.2\u003c/span\u003e\u003cspan address=\"10.5958/0976-5506.2017.00009.2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBlinka, L., Stašek, A., Šablat\u0026uacute;rov\u0026aacute;, N., Ševč\u0026iacute;kov\u0026aacute;, A. \u0026amp; Husarova, D. Adolescents' problematic internet and mobile phone use in (cyber) bullying experiences: A network analysis. \u003cem\u003eChild Adolesc. Mental Health\u003c/em\u003e. \u003cb\u003e28\u003c/b\u003e (1), 60\u0026ndash;66. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/camh.12628\u003c/span\u003e\u003cspan address=\"10.1111/camh.12628\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCohen, J. \u003cem\u003eStatistical power analysis for the behavioral sciences\u003c/em\u003e (2nd Ed.). Erlbaum. (1988).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDarvesh, N., Hides, L., Kavanagh, D. J., Young, R. M. \u0026amp; Connor, J. P. The prevalence and correlates of problematic mobile phone use: A meta-analysis of 24 studies. \u003cem\u003eJ. Affect. Disord.\u003c/em\u003e \u003cb\u003e274\u003c/b\u003e, 275\u0026ndash;285. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jad.2020.05.065\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2020.05.065\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDelgado, B., Le\u0026oacute;n, M. J. \u0026amp; Mart\u0026iacute;nez-Monteagudo, M. C. \u003cem\u003eCuestionario de Uso Problem\u0026aacute;tico de las Nuevas Tecnolog\u0026iacute;as\u003c/em\u003e (Universidad de Alicante, 2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDelgado, B. \u0026amp; Mart\u0026iacute;nez-Monteagudo, M. C. \u003cem\u003eCuestionario sobre el uso problem\u0026aacute;tico de las redes sociales en adolescentes\u003c/em\u003e (Universidad de Alicante, 2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDeng, X. et al. y Differences in Reward Sensitivity between High and Low Problematic Mobile phone Use Adolescents: An ERP Study. \u003cem\u003eInternational journal of environmental research and public health\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(18), 9603. (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph18189603\u003c/span\u003e\u003cspan address=\"10.3390/ijerph18189603\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDe-Sola, J. et al. y Rodr\u0026iacute;guez Cell phone use habits among the Spanish population: contribution of applications to problematic use. \u003cem\u003eFrontiers in Psychiatry\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e, 883. (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpsyt.2019.00883\u003c/span\u003e\u003cspan address=\"10.3389/fpsyt.2019.00883\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGao, L. et al. y Effect of the mobile phone-related background on inhibitory control of problematic mobile phone use: An event-related potentials study. \u003cem\u003eAddictive Behaviors\u003c/em\u003e, \u003cem\u003e108\u003c/em\u003e, 106363. (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.addbeh.2020.106363\u003c/span\u003e\u003cspan address=\"10.1016/j.addbeh.2020.106363\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGaraigordobil, M. Screening de acoso entre iguales. En M. Garaigordobil \u0026amp; J. Mart\u0026iacute;nez-Vicente (Eds.), \u003cem\u003eInstrumentos de evaluaci\u0026oacute;n en psicolog\u0026iacute;a\u003c/em\u003e (pp. 105\u0026ndash;120). Editorial S\u0026iacute;ntesis. (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eG\u0026uuml;l, H. et al. Cyberbullying among a clinical adolescent sample in Turkey: effects of problematic mobile phone use, psychiatric symptoms, and emotion regulation difficulties. \u003cem\u003ePsychiatry Clin. Psychopharmacol.\u003c/em\u003e \u003cb\u003e29\u003c/b\u003e (4), 547\u0026ndash;557. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/24750573.2018.1472923\u003c/span\u003e\u003cspan address=\"10.1080/24750573.2018.1472923\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHu, Y. T. \u0026amp; Wang, Q. Self-control, parental monitoring, and adolescent problematic mobile phone use: testing the interactive effect and its gender differences. \u003cem\u003eFront. Psychol.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e, 1554. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpsyg.2022.846618\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2022.846618\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJo, G., Kim, H., Jang, W. \u0026amp; Lee, S. The relationship between internet gaming disorder and problematic mobile phone use: A systematic review. \u003cem\u003eCyberpsychology Behav. Social Netw.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e (6), 388\u0026ndash;393. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1089/cyber.2019.0751\u003c/span\u003e\u003cspan address=\"10.1089/cyber.2019.0751\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim, M. H., Min, S., Ahn, J. S., An, C. \u0026amp; Lee, J. Association between high adolescent mobile phone use and academic impairment, conflicts with family members or friends, and suicide attempts. \u003cem\u003ePloS One\u003c/em\u003e. \u003cb\u003e14\u003c/b\u003e (7), e0219831. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0219831\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0219831\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKliesener, T., Meigen, C., Kiess, W. \u0026amp; Poulain, T. y Associations between problematic mobile phone use and behavioural difficulties, quality of life, and school performance among children and adolescents. \u003cem\u003eBMC psychiatry\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(1), 1\u0026ndash;12. (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12888-022-03815-4\u003c/span\u003e\u003cspan address=\"10.1186/s12888-022-03815-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKong, F., Lan, N., Zhang, H., Sun, X. \u0026amp; Zhang, Y. How does social anxiety affect mobile phone dependence in adolescents? The mediating role of self-concept clarity and self-esteem. \u003cem\u003eCurr. Psychol.\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e, 8070\u0026ndash;8077. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12144-020-01262-6\u003c/span\u003e\u003cspan address=\"10.1007/s12144-020-01262-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKwon, M., Kim, D. J., Cho, H. \u0026amp; Yang, S. The mobile phone addiction scale: development and validation of a short version for adolescents. \u003cem\u003ePloS One\u003c/em\u003e. \u003cb\u003e8\u003c/b\u003e (12), e83558. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0083558\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0083558\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee, J. I., Yen, C. F., Hsiao, R. C. \u0026amp; Hu, H. F. Relationships of homophobic bullying during childhood and adolescence with problematic internet and mobile phone use in early adulthood among sexual minority men in Taiwan. \u003cem\u003eArchives Clin. Psychiatry (S\u0026atilde;o Paulo)\u003c/em\u003e. \u003cb\u003e46\u003c/b\u003e, 97\u0026ndash;102. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/0101-60830000000203\u003c/span\u003e\u003cspan address=\"10.1590/0101-60830000000203\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi, D. J., Chang, Y. P., Chen, Y. L. \u0026amp; Yen, C. F. Mediating effects of emotional symptoms on the association between homophobic bullying victimization and problematic internet/mobile phone use among gay and bisexual men in Taiwan. \u003cem\u003eInt. J. Environ. Res. Public Health\u003c/em\u003e. \u003cb\u003e17\u003c/b\u003e (10), 3386. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph17103386\u003c/span\u003e\u003cspan address=\"10.3390/ijerph17103386\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020a).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi, D. L. et al. Gender difference in the associations between health literacy and problematic mobile phone use in Chinese middle school students. \u003cem\u003eBMC Public. Health\u003c/em\u003e. \u003cb\u003e23\u003c/b\u003e (1), 1\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12889-023-15049-4\u003c/span\u003e\u003cspan address=\"10.1186/s12889-023-15049-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023b).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu, Q., Wu, Y., Lin, S. \u0026amp; Liu, X. Network analysis of social anxiety and problematic mobile phone use in Chinese adolescents: A longitudinal study. \u003cem\u003eJ. Behav. Addictions\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e (3), 716\u0026ndash;726. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1556/2006.2022.00051\u003c/span\u003e\u003cspan address=\"10.1556/2006.2022.00051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eL\u0026oacute;pez-Fern\u0026aacute;ndez, O. Short version of the Mobile phone Addiction Scale adapted to Spanish and French: Towards a cross-cultural research in problematic mobile phone use. \u003cem\u003eAddict. Behav.\u003c/em\u003e \u003cb\u003e64\u003c/b\u003e, 275\u0026ndash;280. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.addbeh.2015.11.013\u003c/span\u003e\u003cspan address=\"10.1016/j.addbeh.2015.11.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLongobardi, C., Settanni, M. \u0026amp; Fabris, M. A. The association between cybervictimization and problematic mobile phone use: A longitudinal study of adolescents. \u003cem\u003eAddict. Behav.\u003c/em\u003e \u003cb\u003e113\u003c/b\u003e, 106699. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.addbeh.2020.106699\u003c/span\u003e\u003cspan address=\"10.1016/j.addbeh.2020.106699\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuengo-Gonz\u0026aacute;lez, R. et al. The role of life satisfaction in the association between problematic technology use and anxiety in children and adolescents during the COVID‐19 pandemic. \u003cem\u003eInt. J. Ment. Health Nurs.\u003c/em\u003e \u003cb\u003e32\u003c/b\u003e (1), 212\u0026ndash;222. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/inm.13077\u003c/span\u003e\u003cspan address=\"10.1111/inm.13077\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarciano, L. \u0026amp; Camerini, A. L. y Duration, frequency, and time distortion: Which is the best predictor of problematic mobile phone use in adolescents? A trace data study. \u003cem\u003ePloS one\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(2), e0263815. (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0263815\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0263815\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMar\u0026iacute;n, V., Sampedro, B. E., Ortega, J. M. \u0026amp; Figueroa, J. Predictive factors of problematic mobile phone use in young Spanish university students. \u003cem\u003eHeliyon\u003c/em\u003e \u003cb\u003e8\u003c/b\u003e (9), e10429. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.heliyon.2022.e10429\u003c/span\u003e\u003cspan address=\"10.1016/j.heliyon.2022.e10429\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNagata, J. M. et al. Associations between sexual orientation and early adolescent screen use: Findings from the Adolescent Brain Cognitive Development (ABCD) Study. \u003cem\u003eAnn. Epidemiol.\u003c/em\u003e \u003cb\u003e82\u003c/b\u003e, 54\u0026ndash;58. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.annepidem.2023.03.004\u003c/span\u003e\u003cspan address=\"10.1016/j.annepidem.2023.03.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eN\u0026auml;her, A. F. et al. Secondary data for global health digitalisation. \u003cem\u003eLancet Digit. Health\u003c/em\u003e. \u003cb\u003e5\u003c/b\u003e (2), e93\u0026ndash;e101. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2589-7500(22)00195-9\u003c/span\u003e\u003cspan address=\"10.1016/S2589-7500(22)00195-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNawaz, S. \u0026amp; Ahmad, Z. Statistical study of impact of mobile on student\u0026rsquo;s life. \u003cem\u003eIOSR J. Humanit. Social Sci. (JHSS)\u003c/em\u003e. \u003cb\u003e2\u003c/b\u003e (1), 43\u0026ndash;49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.9790/0837-0214349\u003c/span\u003e\u003cspan address=\"10.9790/0837-0214349\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOlivares, J. et al. Social Anxiety Scale for Adolescents (SAS-A): Psychometric properties in a Spanish-speaking population. \u003cem\u003eInt. J. Clin. Health Psychol.\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e (1), 85\u0026ndash;97 (2005).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOng, N. C., Kee, Y. H., Pillai, J. S., Lim, H. B. \u0026amp; y Chua, J. H. Problematic mobile phone use among youth athletes: a topic modelling approach. \u003cem\u003eInt. J. Sport Exerc. Psychol.\u003c/em\u003e 1\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/1612197X.2022.2078856\u003c/span\u003e\u003cspan address=\"10.1080/1612197X.2022.2078856\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOviedo-Trespalacios, O., Nandavar, S., Newton, J. D. A., Demant, D. \u0026amp; Phillips, J. G. Problematic Use of Mobile Phones in Australia\u0026hellip; Is It Getting Worse? \u003cem\u003eFront. Psychiatry\u003c/em\u003e. \u003cb\u003e10\u003c/b\u003e, 105. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpsyt.2019.00105\u003c/span\u003e\u003cspan address=\"10.3389/fpsyt.2019.00105\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePearson, A. D., Young, C. M., Shank, F. \u0026amp; Neighbors, C. Flow mediates the relationship between problematic mobile phone use and satisfaction with life among college students. \u003cem\u003eJ. Am. Coll. Health\u003c/em\u003e. 1\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/07448481.2021.1910274\u003c/span\u003e\u003cspan address=\"10.1080/07448481.2021.1910274\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePel\u0026aacute;ez-Fern\u0026aacute;ndez, M. A., Chamizo-Nieto, M. T., Rey, L. \u0026amp; Extremera, N. How do cyber victimization and low core self-evaluations interrelate in predicting adolescent problematic technology use? \u003cem\u003eInt. J. Environ. Res. Public Health\u003c/em\u003e. \u003cb\u003e18\u003c/b\u003e (6), 3114. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph18063114\u003c/span\u003e\u003cspan address=\"10.3390/ijerph18063114\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrzepiorka, A., Błachnio, A., Cudo, A. \u0026amp; Kot, P. Social anxiety and social skills via problematic mobile phone use for predicting somatic symptoms and academic performance at primary school. \u003cem\u003eComput. Educ.\u003c/em\u003e \u003cb\u003e173\u003c/b\u003e, 104286. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.compedu.2021.104286\u003c/span\u003e\u003cspan address=\"10.1016/j.compedu.2021.104286\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRan, G., Li, J., Zhang, Q. \u0026amp; Niu, X. The association between social anxiety and mobile phone addiction: A three-level meta-analysis. \u003cem\u003eComput. Hum. Behav.\u003c/em\u003e \u003cb\u003e130\u003c/b\u003e, 107198. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.chb.2022.107198\u003c/span\u003e\u003cspan address=\"10.1016/j.chb.2022.107198\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRomero-Rodr\u0026iacute;guez, J. M., Mar\u0026iacute;n-Mar\u0026iacute;n, J. A., Hinojo-Lucena, F. J. \u0026amp; G\u0026oacute;mez-Garc\u0026iacute;a, G. y An explanatory model of problematic Internet use of Southern Spanish university students. \u003cem\u003eSocial Science Computer Review\u003c/em\u003e, \u003cem\u003e40\u003c/em\u003e(5), 1171\u0026ndash;1185. (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0894439321998650\u003c/span\u003e\u003cspan address=\"10.1177/0894439321998650\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSelwyn, N. \u0026amp; Aagaard, J. Banning mobile phones from classrooms\u0026mdash;An opportunity to advance understandings of technology addiction, distraction and cyberbullying. \u003cem\u003eBr. J. Edu. Technol.\u003c/em\u003e \u003cb\u003e52\u003c/b\u003e (1), 8\u0026ndash;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/bjet.12943\u003c/span\u003e\u003cspan address=\"10.1111/bjet.12943\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShachar, I., Aderka, I. M. \u0026amp; Gilboa-Schechtman, E. The factor structure of the Liebowitz social anxiety scale for children and adolescents: Development of a brief version. \u003cem\u003eChild. Psychiatry Hum. Dev.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e, 285\u0026ndash;293. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10578-013-0398-2\u003c/span\u003e\u003cspan address=\"10.1007/s10578-013-0398-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShin, W. \u0026amp; Kim, H. W. Problematic mobile phone use and cyberbullying perpetration in adolescents. \u003cem\u003eBehav. Inform. Technol.\u003c/em\u003e 1\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/camh.12628\u003c/span\u003e\u003cspan address=\"10.1111/camh.12628\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSohn, S. Y., Rees, P., Wildridge, B., Kalk, N. J. \u0026amp; Carter, B. y Prevalence of problematic mobile phone usage and associated mental health outcomes amongst children and young people: a systematic review, meta-analysis and GRADE of the evidence. \u003cem\u003eBMC psychiatry\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(1), 1\u0026ndash;10. (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12888-019-2350-x\u003c/span\u003e\u003cspan address=\"10.1186/s12888-019-2350-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStieger, L. \u0026amp; Wunderl, S. The role of online social anxiety in problematic social networking site use: A longitudinal study. \u003cem\u003eSoc. Sci. Med.\u003c/em\u003e \u003cb\u003e297\u003c/b\u003e, 114805. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.socscimed.2022.114805\u003c/span\u003e\u003cspan address=\"10.1016/j.socscimed.2022.114805\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSun, C., Sun, B., Lin, Y. \u0026amp; Zhou, H. Problematic Mobile phone Use Increases with the Fear of Missing Out Among College Students: The Effects of Self-Control, Perceived Social Support and Future Orientation. \u003cem\u003ePsychol. Res. Behav. Manage.\u003c/em\u003e 1\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2147/PRBM.S345650\u003c/span\u003e\u003cspan address=\"10.2147/PRBM.S345650\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eŚwiątek, A. H. et al. Problematic Mobile phone Use and Social Media Fatigue: The Mediating Role of Self-Control. \u003cem\u003ePsychol. Res. Behav. Manage.\u003c/em\u003e 211\u0026ndash;222. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2147/PRBM.S389806\u003c/span\u003e\u003cspan address=\"10.2147/PRBM.S389806\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTao, S. M., Fu, J. L., Wang, H., Hao, J. H. \u0026amp; Tao, F. B. Development of self-rating questionnaire for adolescent problematic mobile phone use and the psychometric evaluation in undergraduates. \u003cem\u003eChin. J. School Health\u003c/em\u003e. \u003cb\u003e34\u003c/b\u003e (1), 26\u0026ndash;29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.16835/j.cnki.1000-9817.2013.01.010\u003c/span\u003e\u003cspan address=\"10.16835/j.cnki.1000-9817.2013.01.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThapa, K., Lama, S., Pokharei, R., Sigdel, R. \u0026amp; Rimal, S. P. y Mobile phone dependence among Undergraduate Students of a Medical College of Eastern Nepal: a descriptive cross-sectional study. \u003cem\u003eJNMA: Journal of the Nepal Medical Association\u003c/em\u003e, \u003cem\u003e58\u003c/em\u003e(224), 234. (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.31729/jnma.4787\u003c/span\u003e\u003cspan address=\"10.31729/jnma.4787\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTomczyk, Ł. \u0026amp; Lizde, E. S. Nomophobia and Phubbing: Wellbeing and new media education in the family among adolescents in Bosnia and Herzegovina. \u003cem\u003eChild Youth Serv. Rev.\u003c/em\u003e \u003cb\u003e137\u003c/b\u003e, 106489. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.childyouth.2022.106489\u003c/span\u003e\u003cspan address=\"10.1016/j.childyouth.2022.106489\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVally, Z. \u0026amp; El Hichami, F. An examination of problematic mobile phone use in the United Arab Emirates: Prevalence, correlates, and predictors in a college-aged sample of young adults. \u003cem\u003eAddict. Behav. Rep.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e, 100185. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.abrep.2019.100185\u003c/span\u003e\u003cspan address=\"10.1016/j.abrep.2019.100185\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang, D., Nie, X., Zhang, D. \u0026amp; Hu, Y. y The relationship between parental psychological control and problematic mobile phone use in early Chinese adolescence: A repeated-measures study at two time-points. \u003cem\u003eAddictive Behaviors\u003c/em\u003e, \u003cem\u003e125\u003c/em\u003e, 107142. (2022a). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.addbeh.2021.107142\u003c/span\u003e\u003cspan address=\"10.1016/j.addbeh.2021.107142\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang, A., Wang, Z., Zhu, Y. \u0026amp; Shi, X. The prevalence and psychosocial factors of problematic mobile phone use among Chinese college students: a three-wave longitudinal study. \u003cem\u003eFront. Psychol.\u003c/em\u003e 1476. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpsyg.2022.877277\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2022.877277\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022b).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorsley, J. D., McIntyre, J. C., Bentall, R. P. \u0026amp; Corcoran, R. Problematic social media use and associations with mental health and wellbeing: A systematic review. \u003cem\u003eClin. Psychol. Rev.\u003c/em\u003e \u003cb\u003e85\u003c/b\u003e, 102002. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cpr.2021.102002\u003c/span\u003e\u003cspan address=\"10.1016/j.cpr.2021.102002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYuchang, J., Cuicui, S., Junxiu, A. \u0026amp; Junyi, L. y Attachment styles and mobile phone addiction in Chinese college students: The mediating roles of dysfunctional attitudes and self-esteem. \u003cem\u003eInternational Journal of Mental Health and Addiction\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(5), 1122\u0026ndash;1134. (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11469-017-9772-9\u003c/span\u003e\u003cspan address=\"10.1007/s11469-017-9772-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang, Y., Mei, S., Chai, J. \u0026amp; Zhou, Z. Problematic mobile phone use and addiction: A comprehensive review of neurobiological mechanisms. \u003cem\u003eNeurosci. Biobehav. Rev.\u003c/em\u003e \u003cb\u003e144\u003c/b\u003e, 104951. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neubiorev.2023.104951\u003c/span\u003e\u003cspan address=\"10.1016/j.neubiorev.2023.104951\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhong, L., Huang, V. \u0026amp; Guo, S. Mobile phone paradox: A two-path model connecting mobile phone use and feeling of loneliness for Filipino domestic workers in Hong Kong. \u003cem\u003eMob. Media Communication\u003c/em\u003e. \u003cb\u003e10\u003c/b\u003e (3), 448\u0026ndash;467. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/20501579221077525\u003c/span\u003e\u003cspan address=\"10.1177/20501579221077525\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mobile phone, social media, cyberbullying, social anxiety, adolescents","lastPublishedDoi":"10.21203/rs.3.rs-7592472/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7592472/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe use of mobile phone and social media has become a global and unstoppable phenomenon, especially among adolescents, largely due to the ease of access to numerous applications that facilitate communication and social interaction via the Internet. This study examines the relationship between problematic mobile phone and social media use, cyberbullying, and social anxiety in a representative sample of secondary school adolescents. A total of 1164 students with an age range of 12 to 18 years (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;14.56; \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.4) completed a battery of self-report measures to assess problematic mobile phone and social media use and social anxiety. The results indicate that students with high problematic use of mobile phone and social media have significantly higher levels of cyberbullying and social anxiety compared to those with low and medium problematic use. Furthermore, logistic regression analyses showed that cyberbullying, cybervictimisation and social anxiety, specifically, fear of negative evaluation were significant predictors of problematic mobile phone and social media use, indicating a higher probability of dependence as levels of cybervictimisation and social anxiety increase. The results suggest the need to implement interventions aimed at improving emotional management and reducing problematic behaviours related to technology use.\u003c/p\u003e","manuscriptTitle":"Problematic use of mobile phone and social media among adolescents: relationship with cyberbullying, cybervictimisation, and social anxiety","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-27 13:34:37","doi":"10.21203/rs.3.rs-7592472/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-11T10:14:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-10T20:25:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-06T16:37:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-17T06:55:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42292680547721019488658316966783330468","date":"2025-10-17T02:34:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"186122382901869091322064288525406670991","date":"2025-10-15T07:16:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-14T13:58:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"244481879894107782865567346874462996320","date":"2025-10-14T13:47:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"59125735105854442288550668836110683884","date":"2025-10-14T11:07:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"241975912913621445742827360083872559296","date":"2025-10-13T16:09:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"169310773039639056892710673425796751183","date":"2025-10-13T14:35:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-13T07:05:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-17T11:38:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-15T13:00:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-09-15T12:50:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b276b6e7-3aee-4c34-bd2b-a884cdb9d26b","owner":[],"postedDate":"October 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":56749731,"name":"Business and commerce/Information systems and information technology"},{"id":56749732,"name":"Biological sciences/Psychology"},{"id":56749733,"name":"Social science/Psychology"},{"id":56749734,"name":"Social science/Science technology and society"}],"tags":[],"updatedAt":"2026-02-09T16:00:44+00:00","versionOfRecord":{"articleIdentity":"rs-7592472","link":"https://doi.org/10.1038/s41598-026-35842-6","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-02-03 15:57:21","publishedOnDateReadable":"February 3rd, 2026"},"versionCreatedAt":"2025-10-27 13:34:37","video":"","vorDoi":"10.1038/s41598-026-35842-6","vorDoiUrl":"https://doi.org/10.1038/s41598-026-35842-6","workflowStages":[]},"version":"v1","identity":"rs-7592472","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7592472","identity":"rs-7592472","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}