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      The Impact of Parental Depression on Children’s Smartphone Addiction: A Serial Mediation Model With Parental Neglect and Children’s Self-Esteem

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      Social Science Computer Review
      SAGE Publications

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          Abstract

          The present study investigates the mechanisms underlying the relationship between parental depression and children’s smartphone addiction. It explores the effects of parental depression on children’s smartphone addiction, as well as the mediating roles of parental neglect and children’s self-esteem in this relationship, which multiplies sequentially. We utilize data—comprising 2,396 children and their parents—from the National General Survey on Korean Children, using parent–child dyads. First, a hierarchical regression analysis shows that parental depression significantly and positively predicts children’s smartphone addiction ( B = .29, SE = .03, p < .001). Second, Hayes’s PROCESS macro (Model 6), executed to test the mediation effects, reveals that the effect of parental depression on children’s smartphone addiction is significantly mediated by parental neglect ( B = .07, Boot SE = .01, 95% Boot CI [.05, .10]) and children’s self-esteem ( B = .12, Boot SE = .01, 95% Boot CI [.10, .14]). Moreover, the serial mediation model’s results support that parental neglect and children’s self-esteem serially mediate the relationship between parental depression and children’s smartphone addiction ( B = .02, Boot SE = .004, 95% Boot CI [.01, .03]), implying that a higher level of parental depression is sequentially associated with increased parental neglect that reduces children’s self-esteem and consequently accelerates their smartphone dependence. The theoretical and practical implications of the results as well as the directions for future research are discussed.

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          Society and the Adolescent Self-Image

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            Introduction to mediation, moderation, and conditional process analysis: A regression-based approach

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              Conceiving the self

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                Author and article information

                Journal
                Social Science Computer Review
                Social Science Computer Review
                SAGE Publications
                0894-4393
                1552-8286
                August 13 2021
                : 089443932110375
                Affiliations
                [1 ]Sungkyunkwan University, Seoul, South Korea
                Article
                10.1177/08944393211037579
                f4506fd4-0a3e-41d1-9087-f0efb26d2295
                © 2021

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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