Resilience Mitigates the Negative Effects of Adolescent Internet Addiction and Online Risk Exposure

CHI, pp. 4029-4038, 2015.

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As shown in Figure 4, our proposed model indicated a significant interaction between Internet Addiction and Resilience, which predicted Risk Exposure and a marginally significant interaction between Risk Exposure and Resilience, which predicted Negative Affect

Abstract:

We cannot fully protect adolescents from experiencing online risks; however, we can aim to better understand how online risk experiences impact teens, factors that contribute to or prevent teens from exposure to risk, as well as factors that can protect teens from psychological harm in spite of online risk exposure. Through a web-based su...More

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Introduction
  • Understanding adolescent online behaviors and experiences is critical to teens’ safety and wellbeing.
  • The authors' intent was to study the negative effects that Internet Addiction and Online Risk Exposure might have on adolescents and to examine how teens’ level of Resilience might mitigate the possible negative effects associated with these risks.
  • Resilience is the ability to overcome negative effects associated with risk exposure, helping an individual cope with traumatic experiences [34].
  • It becomes increasingly important to understand how and why such exposure negatively impacts some teens, as well as to explore protective measures for keeping teens safe online in spite of online risk experiences
Highlights
  • Understanding adolescent online behaviors and experiences is critical to teens’ safety and wellbeing
  • Our intent was to study the negative effects that Internet Addiction and Online Risk Exposure might have on adolescents and to examine how teens’ level of Resilience might mitigate the possible negative effects associated with these risks
  • We found that Resilience plays a key role in protecting teens, either neutralizing or reducing the negative effects of Internet Addiction and Online Risk Exposure
  • As shown in Figure 4, our proposed model indicated a significant interaction between Internet Addiction and Resilience (H3; p < 0.05), which predicted Risk Exposure and a marginally significant interaction between Risk Exposure and Resilience (H2; p = 0.07), which predicted Negative Affect
  • The direct effect of Online Risk Exposure on Negative Affect became non-significant; the direct and indirect effects of Addiction became statistically insignificant. This model yielded a good fit to the data (Appendix A, Table 3) and indicated high explanatory power, explaining 41% of the variance in Online Risk Exposure and 40% of the variance in Negative Affect
  • When Resilience was not in the model (Figure 4), Online Risk Exposure partially mediated the relationship between Internet Addiction and Negative Affect (H1): While Internet Addiction shows a significant direct effect on Negative Affect, Online Risk Exposure appears to be a key factor that helps explain the effect of Internet Addiction on Negative Affect
Methods
  • Operationalizing Constructs The authors used pre-validated measures to operationalize the majority of the constructs.
  • Internet Addiction was measured using six items from previous research [27]; for example, how often teens “felt bothered when [they could not] be on the Internet.” Resilience was measured using the proprietary ConnorDavidson Resilience Scale (CD-RISC 10) [3], which we licensed from the authors [8].
  • The four risk types were collapsed to create an overall measure of Online Risk Exposure because the authors found them to be highly intertwined, both conceptually and empirically
Results
  • Participant Profiles Ninety-five teens originally registered to participate in the online survey study and completed the process of informed consent.
  • The indirect effect of Addiction on Negative Affect was statistically significant at the p = 0.05 level
  • These combined findings confirm a significant, yet partial, mediation effect of Online Risk Exposure, providing support for the first hypothesis.
  • The direct effect of Online Risk Exposure on Negative Affect became non-significant; the direct and indirect effects of Addiction became statistically insignificant
  • This model yielded a good fit to the data (Appendix A, Table 3) and indicated high explanatory power, explaining 41% of the variance in Online Risk Exposure and 40% of the variance in Negative Affect
Conclusion
  • The authors found support for the main hypotheses. When Resilience was not in the model (Figure 4), Online Risk Exposure partially mediated the relationship between Internet Addiction and Negative Affect (H1): While Internet Addiction shows a significant direct effect on Negative Affect, Online Risk Exposure appears to be a key factor that helps explain the effect of Internet Addiction on Negative Affect.
  • After testing three alternative theoretical models, the authors found that Resilience acts as a two-stage moderator (Figure 5) between Online Risk Exposure and Negative Affect (H2; marginal significance) and between Internet Addiction and Online Risk Exposure (H3).
  • It reduces the effects of Internet Addiction on Online Risk Exposure (Figure 7) and neutralizes the direct effects of Internet Addiction and Online Risk Exposure on Negative Affect (Figures 5 & 6).
  • A key to adolescent online safety is to teach teens how to effectively cope with negative online experiences so that they can more readily benefit from the vast resources and beneficial social interactions the Internet can provide
Summary
  • Introduction:

    Understanding adolescent online behaviors and experiences is critical to teens’ safety and wellbeing.
  • The authors' intent was to study the negative effects that Internet Addiction and Online Risk Exposure might have on adolescents and to examine how teens’ level of Resilience might mitigate the possible negative effects associated with these risks.
  • Resilience is the ability to overcome negative effects associated with risk exposure, helping an individual cope with traumatic experiences [34].
  • It becomes increasingly important to understand how and why such exposure negatively impacts some teens, as well as to explore protective measures for keeping teens safe online in spite of online risk experiences
  • Methods:

    Operationalizing Constructs The authors used pre-validated measures to operationalize the majority of the constructs.
  • Internet Addiction was measured using six items from previous research [27]; for example, how often teens “felt bothered when [they could not] be on the Internet.” Resilience was measured using the proprietary ConnorDavidson Resilience Scale (CD-RISC 10) [3], which we licensed from the authors [8].
  • The four risk types were collapsed to create an overall measure of Online Risk Exposure because the authors found them to be highly intertwined, both conceptually and empirically
  • Results:

    Participant Profiles Ninety-five teens originally registered to participate in the online survey study and completed the process of informed consent.
  • The indirect effect of Addiction on Negative Affect was statistically significant at the p = 0.05 level
  • These combined findings confirm a significant, yet partial, mediation effect of Online Risk Exposure, providing support for the first hypothesis.
  • The direct effect of Online Risk Exposure on Negative Affect became non-significant; the direct and indirect effects of Addiction became statistically insignificant
  • This model yielded a good fit to the data (Appendix A, Table 3) and indicated high explanatory power, explaining 41% of the variance in Online Risk Exposure and 40% of the variance in Negative Affect
  • Conclusion:

    The authors found support for the main hypotheses. When Resilience was not in the model (Figure 4), Online Risk Exposure partially mediated the relationship between Internet Addiction and Negative Affect (H1): While Internet Addiction shows a significant direct effect on Negative Affect, Online Risk Exposure appears to be a key factor that helps explain the effect of Internet Addiction on Negative Affect.
  • After testing three alternative theoretical models, the authors found that Resilience acts as a two-stage moderator (Figure 5) between Online Risk Exposure and Negative Affect (H2; marginal significance) and between Internet Addiction and Online Risk Exposure (H3).
  • It reduces the effects of Internet Addiction on Online Risk Exposure (Figure 7) and neutralizes the direct effects of Internet Addiction and Online Risk Exposure on Negative Affect (Figures 5 & 6).
  • A key to adolescent online safety is to teach teens how to effectively cope with negative online experiences so that they can more readily benefit from the vast resources and beneficial social interactions the Internet can provide
Tables
  • Table1: Scale Reliabilities and Descriptive Statistics
  • Table2: Item Wording for Online Risk Exposure Measures
  • Table3: Goodness of Fit Statistics for Competing Theoretical Models of Resilience
Download tables as Excel
Funding
  • Also, this research was supported by the U.S National Science Foundation under grant CNS-1018302
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