Bullying on the pixel playground: Investigating risk factors of cyberbullying at the intersection of children’s online-offline social lives

Seiler, Steven J.; Navarro, Jordana N.

doi:10.5817/cp2014-4-6

Cited by 25 publications

(40 citation statements)

References 53 publications

(113 reference statements)

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“…The claims made with regards to attachment to a mobile phone (Vandebosch & van Cleemput, 2009;Seiler & Navarro, 2014) and the frequency of mobile phone use (Li, 2007;Marcum et al, 2010) with regards to mobile victimisation were in line with the predictions made in the present study, i.e. that they influence mobile victimisation.…”

Section: Description Of the Clusterssupporting

confidence: 77%

“…This therefore validates the cluster "High Contributing Victim". It is also in line with claims made that the advancement of a mobile phone (Li, 2007;Cuadrado-Gordillo & Fernández-Antelo, 2014), the attachment one has to their mobile phone (Takao et al, 2009;Vandebosch & van Cleemput, 2009;Seiler and Navarro, 2014) and the frequency of mobile phone use (Li, 2007;Marcum et al, 2010) will influence mobile victimisation.…”

Section: Clustersupporting

confidence: 61%

“…The results seen above are in line with Vandebosch and van Cleemput (2009), who claimed that the more dependent (attached to) a learner is on the internet, the more likely it is that the learner will become a victim of cyberbullying. Similarly, Seiler and Navarro (2014) found that children emotionally attached to Social Networking Services (SNS) were three times more likely to encounter bullying than children who were less emotionally attached to SNS, whereas those who were less attached were less likely to encounter bullying.…”

Section: Description Of the Clustersmentioning

confidence: 99%

“…The results in Table 4 also indicated that these learners rarely used their mobile phones and that MMS was the most frequently used mobile application on their mobile phones while chatrooms were the least ( Table 4). Following literature (Li, 2007;Cuadrado-Gordillo & Fernández-Antelo, 2014;Takao et al, 2009;Vandebosch & van Cleemput, 2009;Seiler and Navarro, 2014;Marcum et al, 2010), as these learners were the least victimised, the researchers' predictions were that these learners would have the least advanced mobile phones. The researchers also predicted that they would not be frequent users of their mobile phones and that they would be less attached to their mobile phones.…”

Section: Clustermentioning

confidence: 99%

See 3 more Smart Citations

Testing a Typology of Mobile Phone Victimisation Using Cluster Analysis

Lusinga

Kyobe

2017

E J Info Sys Dev Countries

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Mobile victimisation is one form of cyberaggression that is increasing and affecting many young people today in the developing world. While studies on cyberbullying and cybervictimisation exist, the focus on mobile victimisation is limited. In addition, findings reported in earlier studies have been mainly from developed countries and inconclusive. There is also limited theoretical work to enhance conceptualisation and general understanding of mobile victimisation. Understanding this phenomenon in the developing countries is particularly critical as mobile phone usage and crime are among the highest in the world, legislation against misuse is not well developed and there is general lack of awareness of the national and international implications of cyberaggression in the developing nations. Through an extensive review of literature on victimisation, this paper develops a typology, i.e. Mobile Victimisation Typology (MVT), that caters to the understanding of mobile victimisation. The researchers also went further to validate empirically the MVT using cluster analysis. This confirmed all the three categories of victims proposed in the MVT and proved that it's three predictors could influence victims differently. The present findings are useful in creating awareness of mobile victimisation risks and can be used to inform the development of programmes, policies and legislation to control mobile bullying and victimisation in the developing nations in a more efficient and relevant direction in terms of resource and impact management.

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Section: Description Of the Clusterssupporting

confidence: 77%

Section: Clustersupporting

confidence: 61%

Section: Description Of the Clustersmentioning

confidence: 99%

Section: Clustermentioning

confidence: 99%

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Testing a Typology of Mobile Phone Victimisation Using Cluster Analysis

Lusinga

Kyobe

2017

E J Info Sys Dev Countries

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“…There exists a strong base of research of the various forms and effects of victimization in terms of harassment and bullying among young people online today (e.g., Aboujaoude, Savage, Starcevic, & Salame, 2015;Näsi et al, 2014;Seiler & Navarro, 2014;Walrave & Heirman, 2011). However, the cross-national study of how those negative experiences are related to forms of social tie strength available through SNS and the offline setting and in terms of targeted hate victimization remains scarce.…”

Section: Research-article2017mentioning

confidence: 99%

Social Tie Strength and Online Victimization: An Analysis of Young People Aged 15–30 Years in Four Nations

Keipi

Kaakinen

Oksanen

et al. 2017

Social Media + Society

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Online interaction through the use of social networking sites (SNS) continues to be a significant component of the socialization of young people today, yet little research exists toward linking various relational forms to prevalent and much-studied online risks cross-nationally. This article provides a link between relational dynamics and online risks identified in previous research toward a new perspective on how social tie strength is related to experiences of hate victimization and harassment online. The analysis is based on survey data of Finnish ( n = 555), American ( n = 1033), German ( n = 978), and British ( n = 999) young people aged 15–30 years. Variables, including age, gender, main activity, SNS use, quantity, and extent of online and offline social networks including social tie strength and online community identification, were analyzed toward finding their associations with online hate victimization and harassment. Results showed that experiences of hate victimization and harassment were similar cross-nationally and that those who were personally harassed online also reported high SNS activity. Furthermore, no association was found between social network size and negative experiences. Notable cross-national differences were also detected in the results. Findings emphasize the importance of understanding variables fostering online risks for young people while providing a new perspective on what aspects of social life may help negate negative effects online.

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Assessment of School Anti-Bullying Interventions

et al. 2021

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IMPORTANCEBullying is a prevalent and modifiable risk factor for mental health disorders. Although previous studies have supported the effectiveness of anti-bullying programs; their population impact and the association of specific moderators with outcomes are still unclear.OBJECTIVE To assess the effectiveness of school anti-bullying interventions, their population impact, and the association between moderator variables and outcomes.DATA SOURCES A search of Ovid MEDLINE, ERIC, and PsycInfo databases was conducted using 3 sets of search terms to identify randomized clinical trials (RCTs) assessing anti-bullying interventions published from database inception through February 2020. A manual search of reference lists of articles included in previous systematic reviews and meta-analyses was also performed. STUDY SELECTIONThe initial literature search yielded 34 798 studies. Included in the study were articles that (1) assessed bullying at school; (2) assessed the effectiveness of an anti-bullying program; (3) had an RCT design; (4) reported results; and (5) were published in English. Of 16 707 studies identified, 371 met the criteria for review of full-text articles; 77 RCTs were identified that reported data allowing calculation of effect sizes (ESs). Of these, 69 independent trials were included in the final meta-analysis database.DATA EXTRACTION AND SYNTHESIS Random-effects and meta-regression models were used to derive Cohen d values with pooled 95% CIs as estimates of ES and to test associations between moderator variables and ES estimates. Population impact number (PIN), defined as the number of children in the total population for whom 1 event may be prevented by an intervention, was used as an estimate of the population impact of universal interventions targeting all students, regardless of individual risk. MAIN OUTCOMES AND MEASURESThe main outcomes are the effectiveness (measured by ES) and the population impact (measured by the PIN) of anti-bullying interventions on the following 8 variable categories: overall bullying, bullying perpetration, bullying exposure, cyberbullying, attitudes that discourage bullying, attitudes that encourage bullying, mental health problems (eg, anxiety and depression), and school climate as well as the assessment of potential assocations between trial or intervention characteristics and outcomes. RESULTSThis study included 77 samples from 69 RCTs (111 659 participants [56 511 in the intervention group and 55 148 in the control group]). The weighted mean (range) age of participants in the intervention group was 11.1 (4-17) years and 10.8 (4-17) years in the control group. The weighted mean (range) proportion of female participants in the intervention group was 49.9% (0%-100%) and 50.5% (0%-100%) in the control group. Anti-bullying interventions were efficacious in reducing bullying (ES, −0.150; 95% CI, −0.191 to −0.109) and improving mental health problems (ES, −0.205; 95% CI, −0.277 to −0.133) at study end point, with PINs for universal interventions that target the total stud...

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Bullying on the pixel playground: Investigating risk factors of cyberbullying at the intersection of children’s online-offline social lives

Cited by 25 publications

References 53 publications

Testing a Typology of Mobile Phone Victimisation Using Cluster Analysis

Testing a Typology of Mobile Phone Victimisation Using Cluster Analysis

Social Tie Strength and Online Victimization: An Analysis of Young People Aged 15–30 Years in Four Nations

Assessment of School Anti-Bullying Interventions

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