Screen addicts: A meta-analysis of internet addiction in adolescence
•The etiology is complex: individual, educational, socio-family, and cultural factors.•The age explains 24% of Internet addiction.•The culture understand 47% of the variability.•The instrument clarifies 31% of Internet addiction. Currently, the incidence of Internet addiction is growing among teenag...
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Veröffentlicht in: | Children and youth services review 2022-04, Vol.135, p.106373, Article 106373 |
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description | •The etiology is complex: individual, educational, socio-family, and cultural factors.•The age explains 24% of Internet addiction.•The culture understand 47% of the variability.•The instrument clarifies 31% of Internet addiction.
Currently, the incidence of Internet addiction is growing among teenagers. However, most review studies do not differentiate between the adolescent and young adult population. The sample of this meta-analysis consists of 20 studies (K = 28) comprised of 21 878 adolescents whose mean age was 15.13 years. Regarding the methodology, the protocol of registration of the research of the Cochrane systematic review manuals in Higgins and Green (2011) and PRISMA (2015) was followed. The results show a high heterogeneity. Thus, the Random Effects Model has been necessary followed. The effect size of the Internet addiction is Z = 16.04; p = 0.000 with a 95% confidence interval (3.164 – 4.045). In other words, the population does not suffer from severe Internet addiction, although the incidence is still alarming. Moderator variables, such as age, explained 24% of variance; instrument explained 31% of variance, in particular CIAS (Z = 1.75; p = 0.07) and IGD-20 (Z = 4.53; p = 0.00); and finally culture explained 47%, and more concretely, the international sample (Z = -1.71; p = 0.00). Thus, Internet addiction is inversely proportional to age and is influenced by the geographical area in which one resides. On the other hand, it should be noted that there is no agreement on the diagnosis of Internet addiction or on the instruments used to measure it. It is necessary to build an explanatory and intervention model for this pathology based on an international framework. The absence of clear criteria has generated multiple psychometric instruments around which there is no solid consensus. Finally, a complex etiology is presented in which educational, socio-familial, cultural and individual variables are involved. |
doi_str_mv | 10.1016/j.childyouth.2022.106373 |
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Currently, the incidence of Internet addiction is growing among teenagers. However, most review studies do not differentiate between the adolescent and young adult population. The sample of this meta-analysis consists of 20 studies (K = 28) comprised of 21 878 adolescents whose mean age was 15.13 years. Regarding the methodology, the protocol of registration of the research of the Cochrane systematic review manuals in Higgins and Green (2011) and PRISMA (2015) was followed. The results show a high heterogeneity. Thus, the Random Effects Model has been necessary followed. The effect size of the Internet addiction is Z = 16.04; p = 0.000 with a 95% confidence interval (3.164 – 4.045). In other words, the population does not suffer from severe Internet addiction, although the incidence is still alarming. Moderator variables, such as age, explained 24% of variance; instrument explained 31% of variance, in particular CIAS (Z = 1.75; p = 0.07) and IGD-20 (Z = 4.53; p = 0.00); and finally culture explained 47%, and more concretely, the international sample (Z = -1.71; p = 0.00). Thus, Internet addiction is inversely proportional to age and is influenced by the geographical area in which one resides. On the other hand, it should be noted that there is no agreement on the diagnosis of Internet addiction or on the instruments used to measure it. It is necessary to build an explanatory and intervention model for this pathology based on an international framework. The absence of clear criteria has generated multiple psychometric instruments around which there is no solid consensus. Finally, a complex etiology is presented in which educational, socio-familial, cultural and individual variables are involved.</description><identifier>ISSN: 0190-7409</identifier><identifier>EISSN: 1873-7765</identifier><identifier>DOI: 10.1016/j.childyouth.2022.106373</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Addiction ; Addictions ; Adolescence ; Adolescents ; Age ; Etiology ; Internet ; Medical diagnosis ; Meta-analysis ; Moderator variables ; Pathology ; Random effects ; Systematic review ; Variables ; Young adults</subject><ispartof>Children and youth services review, 2022-04, Vol.135, p.106373, Article 106373</ispartof><rights>2022 The Authors</rights><rights>Copyright Elsevier Science Ltd. Apr 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c396t-4b43580f0fc76e29a159d6d13d41fa6a7df0ef4469d195a1e645b0ae51afaaf83</citedby><cites>FETCH-LOGICAL-c396t-4b43580f0fc76e29a159d6d13d41fa6a7df0ef4469d195a1e645b0ae51afaaf83</cites><orcidid>0000-0002-8486-6885 ; 0000-0002-0100-1449 ; 0000-0002-2839-7041</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0190740922000093$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,30976,33751,65534</link.rule.ids></links><search><creatorcontrib>Lozano-Blasco, Raquel</creatorcontrib><creatorcontrib>Latorre-Martínez, MªPilar</creatorcontrib><creatorcontrib>Cortés-Pascual, Alejandra</creatorcontrib><title>Screen addicts: A meta-analysis of internet addiction in adolescence</title><title>Children and youth services review</title><description>•The etiology is complex: individual, educational, socio-family, and cultural factors.•The age explains 24% of Internet addiction.•The culture understand 47% of the variability.•The instrument clarifies 31% of Internet addiction.
Currently, the incidence of Internet addiction is growing among teenagers. However, most review studies do not differentiate between the adolescent and young adult population. The sample of this meta-analysis consists of 20 studies (K = 28) comprised of 21 878 adolescents whose mean age was 15.13 years. Regarding the methodology, the protocol of registration of the research of the Cochrane systematic review manuals in Higgins and Green (2011) and PRISMA (2015) was followed. The results show a high heterogeneity. Thus, the Random Effects Model has been necessary followed. The effect size of the Internet addiction is Z = 16.04; p = 0.000 with a 95% confidence interval (3.164 – 4.045). In other words, the population does not suffer from severe Internet addiction, although the incidence is still alarming. Moderator variables, such as age, explained 24% of variance; instrument explained 31% of variance, in particular CIAS (Z = 1.75; p = 0.07) and IGD-20 (Z = 4.53; p = 0.00); and finally culture explained 47%, and more concretely, the international sample (Z = -1.71; p = 0.00). Thus, Internet addiction is inversely proportional to age and is influenced by the geographical area in which one resides. On the other hand, it should be noted that there is no agreement on the diagnosis of Internet addiction or on the instruments used to measure it. It is necessary to build an explanatory and intervention model for this pathology based on an international framework. The absence of clear criteria has generated multiple psychometric instruments around which there is no solid consensus. Finally, a complex etiology is presented in which educational, socio-familial, cultural and individual variables are involved.</description><subject>Addiction</subject><subject>Addictions</subject><subject>Adolescence</subject><subject>Adolescents</subject><subject>Age</subject><subject>Etiology</subject><subject>Internet</subject><subject>Medical diagnosis</subject><subject>Meta-analysis</subject><subject>Moderator variables</subject><subject>Pathology</subject><subject>Random effects</subject><subject>Systematic review</subject><subject>Variables</subject><subject>Young adults</subject><issn>0190-7409</issn><issn>1873-7765</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>7QJ</sourceid><sourceid>BHHNA</sourceid><recordid>eNqFkM1LAzEQxYMoWKv_w4LnrZPdfOx6q_UTCh7Uc0iTCU3ZbmqSCv3v3bIFj56GGd57zPsRUlCYUaDibjMza9_ZQ9jn9ayCqhrOopb1GZnQRtallIKfkwnQFkrJoL0kVyltAIALXk3I44eJiH2hrfUmp_tiXmwx61L3ujskn4rgCt9njD3mk8iHfjgNS-gwGewNXpMLp7uEN6c5JV_PT5-L13L5_vK2mC9LU7cil2zFat6AA2ekwKrVlLdWWFpbRp0WWloH6BgTraUt1xQF4yvQyKl2WrumnpLbMXcXw_ceU1absI_Dp0lVogFRSdbwQdWMKhNDShGd2kW_1fGgKKgjM7VRf8zUkZkamQ3Wh9GKQ4sfj1El448NrY9osrLB_x_yCyl1emQ</recordid><startdate>202204</startdate><enddate>202204</enddate><creator>Lozano-Blasco, Raquel</creator><creator>Latorre-Martínez, MªPilar</creator><creator>Cortés-Pascual, Alejandra</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QJ</scope><scope>7U3</scope><scope>BHHNA</scope><orcidid>https://orcid.org/0000-0002-8486-6885</orcidid><orcidid>https://orcid.org/0000-0002-0100-1449</orcidid><orcidid>https://orcid.org/0000-0002-2839-7041</orcidid></search><sort><creationdate>202204</creationdate><title>Screen addicts: A meta-analysis of internet addiction in adolescence</title><author>Lozano-Blasco, Raquel ; Latorre-Martínez, MªPilar ; Cortés-Pascual, Alejandra</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c396t-4b43580f0fc76e29a159d6d13d41fa6a7df0ef4469d195a1e645b0ae51afaaf83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Addiction</topic><topic>Addictions</topic><topic>Adolescence</topic><topic>Adolescents</topic><topic>Age</topic><topic>Etiology</topic><topic>Internet</topic><topic>Medical diagnosis</topic><topic>Meta-analysis</topic><topic>Moderator variables</topic><topic>Pathology</topic><topic>Random effects</topic><topic>Systematic review</topic><topic>Variables</topic><topic>Young adults</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lozano-Blasco, Raquel</creatorcontrib><creatorcontrib>Latorre-Martínez, MªPilar</creatorcontrib><creatorcontrib>Cortés-Pascual, Alejandra</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>Social Services Abstracts</collection><collection>Sociological Abstracts</collection><jtitle>Children and youth services review</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lozano-Blasco, Raquel</au><au>Latorre-Martínez, MªPilar</au><au>Cortés-Pascual, Alejandra</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Screen addicts: A meta-analysis of internet addiction in adolescence</atitle><jtitle>Children and youth services review</jtitle><date>2022-04</date><risdate>2022</risdate><volume>135</volume><spage>106373</spage><pages>106373-</pages><artnum>106373</artnum><issn>0190-7409</issn><eissn>1873-7765</eissn><abstract>•The etiology is complex: individual, educational, socio-family, and cultural factors.•The age explains 24% of Internet addiction.•The culture understand 47% of the variability.•The instrument clarifies 31% of Internet addiction.
Currently, the incidence of Internet addiction is growing among teenagers. However, most review studies do not differentiate between the adolescent and young adult population. The sample of this meta-analysis consists of 20 studies (K = 28) comprised of 21 878 adolescents whose mean age was 15.13 years. Regarding the methodology, the protocol of registration of the research of the Cochrane systematic review manuals in Higgins and Green (2011) and PRISMA (2015) was followed. The results show a high heterogeneity. Thus, the Random Effects Model has been necessary followed. The effect size of the Internet addiction is Z = 16.04; p = 0.000 with a 95% confidence interval (3.164 – 4.045). In other words, the population does not suffer from severe Internet addiction, although the incidence is still alarming. Moderator variables, such as age, explained 24% of variance; instrument explained 31% of variance, in particular CIAS (Z = 1.75; p = 0.07) and IGD-20 (Z = 4.53; p = 0.00); and finally culture explained 47%, and more concretely, the international sample (Z = -1.71; p = 0.00). Thus, Internet addiction is inversely proportional to age and is influenced by the geographical area in which one resides. On the other hand, it should be noted that there is no agreement on the diagnosis of Internet addiction or on the instruments used to measure it. It is necessary to build an explanatory and intervention model for this pathology based on an international framework. The absence of clear criteria has generated multiple psychometric instruments around which there is no solid consensus. Finally, a complex etiology is presented in which educational, socio-familial, cultural and individual variables are involved.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.childyouth.2022.106373</doi><orcidid>https://orcid.org/0000-0002-8486-6885</orcidid><orcidid>https://orcid.org/0000-0002-0100-1449</orcidid><orcidid>https://orcid.org/0000-0002-2839-7041</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Addiction Addictions Adolescence Adolescents Age Etiology Internet Medical diagnosis Meta-analysis Moderator variables Pathology Random effects Systematic review Variables Young adults |
title | Screen addicts: A meta-analysis of internet addiction in adolescence |
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