In the last decade considerable attention has been devoted to the possible contribution of social media, and the Internet generally, to instigating adolescents’ engagement in self-harm activities, which are considered the result of a combination of multidimensional variables, such as depression and anxiety. This study aimed to identify, using latent class analysis (LCA), classes homogeneous for adolescents’ beliefs about peers’ motivations in taking part in the recent Blue Whale Challenge Game, and to analyze the individual predictors (gender, mental health problems, self-harm and risk-taking behaviors, and problematic Internet use) of the adolescent’s latent class membership. We performed an LCA using ‘‘perceived attraction’’ and ‘‘perceived constraint’’ as nominal indicators. Relative fit indices suggested the two class solution as the best measurement model: the first class was mostly composed of adolescents who attributed a central role to the adolescent (internal causality), while the second class mostly composed of adolescents who attributed a central role to the recruiters (external causality). In addition, we explored some individual characteristics to test whether they could predict adolescents’ class membership. Results suggests that it is significantly more likely for adolescents with higher level of stress and risk-taking to attribute a central role to their peers’ internal motivation, rather than to the recruiter, in deciding to take part in the online self-harm challenge game. Implications for preventive interventions are discussed.

(2019). Adolescents’ Beliefs About Peers’ Engagement in an Online Self-Harm Challenge: Exploring the Role of Individual Characteristics Through a Latent Class Analysis [journal article - articolo]. In CYBERPSYCHOLOGY, BEHAVIOR AND SOCIAL NETWORKING. Retrieved from http://hdl.handle.net/10446/148463

Adolescents’ Beliefs About Peers’ Engagement in an Online Self-Harm Challenge: Exploring the Role of Individual Characteristics Through a Latent Class Analysis

Florio, Eleonora;Castelli, Ilaria;
2019-01-01

Abstract

In the last decade considerable attention has been devoted to the possible contribution of social media, and the Internet generally, to instigating adolescents’ engagement in self-harm activities, which are considered the result of a combination of multidimensional variables, such as depression and anxiety. This study aimed to identify, using latent class analysis (LCA), classes homogeneous for adolescents’ beliefs about peers’ motivations in taking part in the recent Blue Whale Challenge Game, and to analyze the individual predictors (gender, mental health problems, self-harm and risk-taking behaviors, and problematic Internet use) of the adolescent’s latent class membership. We performed an LCA using ‘‘perceived attraction’’ and ‘‘perceived constraint’’ as nominal indicators. Relative fit indices suggested the two class solution as the best measurement model: the first class was mostly composed of adolescents who attributed a central role to the adolescent (internal causality), while the second class mostly composed of adolescents who attributed a central role to the recruiters (external causality). In addition, we explored some individual characteristics to test whether they could predict adolescents’ class membership. Results suggests that it is significantly more likely for adolescents with higher level of stress and risk-taking to attribute a central role to their peers’ internal motivation, rather than to the recruiter, in deciding to take part in the online self-harm challenge game. Implications for preventive interventions are discussed.
articolo
Villani, Daniela; Florio, Eleonora; Sorgente, Angela; Castelli, Ilaria; Riva, Giuseppe; Marchetti, Antonella; Massaro, Davide
(2019). Adolescents’ Beliefs About Peers’ Engagement in an Online Self-Harm Challenge: Exploring the Role of Individual Characteristics Through a Latent Class Analysis [journal article - articolo]. In CYBERPSYCHOLOGY, BEHAVIOR AND SOCIAL NETWORKING. Retrieved from http://hdl.handle.net/10446/148463
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