PURPOSE: Health-related quality of life (HRQoL) is a well-known construct that refers to a state of complete physical, mental, and social well-being. Its relationship with multiple forms of violence, including bullying, has been widely explored, but this is not the case for cyberbullying. The main objective is to analyze how HRQoL varies depending on the role played in cyberbullying, its temporal stability, and gender and age differences. METHOD: An analytical and longitudinal study was conducted at two temporal moments. At Time 1 (December 2015), 920 Spanish students aged between 11 and 18 years participated (Mage = 13.36, SD = 1.83: 48.9% boys and 51.1% girls). At Time 2 (April 2016), there were 313 participants (Mage 12.81 years, SD = 1.59: 53.4% boys and 46.6% girls). We used the Cyberbullying Test (technological scale) and the Spanish version of the KIDSCREEN-52. RESULTS: Cybervictims and cyberbully-victims present worse scores in all dimensions of the KIDSCREEN-52 (p < .001), compared to cyberbystanders or uninvolved individuals. There are gender differences only in cyberaggression and cyberbystanding. There are significant inverse correlations between all the dimensions of the KIDSCREEN-52 and cybervictimization, with Bullying (r = - .603, p < .001), Mood (r = - .329, p < .001), and School environment (r = - .327, p < .001) being particularly relevant. There were statistically significant differences between T1 and T2 for cyberbystanding (lower scores at T2). CONCLUSION: Cybervictims and cyberbully-victims have worse quality of life in all the dimensions than uninvolved individuals, especially in Psychological well-being, School environment, and Bullying.
PURPOSE: Health-related quality of life (HRQoL) is a well-known construct that refers to a state of complete physical, mental, and social well-being. Its relationship with multiple forms of violence, including bullying, has been widely explored, but this is not the case for cyberbullying. The main objective is to analyze how HRQoL varies depending on the role played in cyberbullying, its temporal stability, and gender and age differences. METHOD: An analytical and longitudinal study was conducted at two temporal moments. At Time 1 (December 2015), 920 Spanish students aged between 11 and 18 years participated (Mage = 13.36, SD = 1.83: 48.9% boys and 51.1% girls). At Time 2 (April 2016), there were 313 participants (Mage 12.81 years, SD = 1.59: 53.4% boys and 46.6% girls). We used the Cyberbullying Test (technological scale) and the Spanish version of the KIDSCREEN-52. RESULTS: Cybervictims and cyberbully-victims present worse scores in all dimensions of the KIDSCREEN-52 (p < .001), compared to cyberbystanders or uninvolved individuals. There are gender differences only in cyberaggression and cyberbystanding. There are significant inverse correlations between all the dimensions of the KIDSCREEN-52 and cybervictimization, with Bullying (r = - .603, p < .001), Mood (r = - .329, p < .001), and School environment (r = - .327, p < .001) being particularly relevant. There were statistically significant differences between T1 and T2 for cyberbystanding (lower scores at T2). CONCLUSION: Cybervictims and cyberbully-victims have worse quality of life in all the dimensions than uninvolved individuals, especially in Psychological well-being, School environment, and Bullying.
Entities:
Keywords:
Adolescent; Bullying; Child; Cyberbullying; Health-related quality of life; Quality of life
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