{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T23:30:39Z","timestamp":1777937439167,"version":"3.51.4"},"reference-count":46,"publisher":"SAGE Publications","issue":"11","license":[{"start":{"date-parts":[[2024,6,24]],"date-time":"2024-06-24T00:00:00Z","timestamp":1719187200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2024,6,24]],"date-time":"2024-06-24T00:00:00Z","timestamp":1719187200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"European Union Horizon 2020 Research & Innovation programme","award":["870612"],"award-info":[{"award-number":["870612"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["New Media &amp; Society"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:p>\n                    Digital skills are considered critical for functioning in contemporary society, yet there are differences between adolescents\u2019 skills depending on demographic and socioeconomic variables. This study, utilising data from six EU countries (\n                    <jats:italic toggle=\"yes\">N<\/jats:italic>\n                    \u2009=\u20096221;\n                    <jats:italic toggle=\"yes\">M<\/jats:italic>\n                    <jats:sub>age<\/jats:sub>\n                    \u2009=\u200914.5;\n                    <jats:italic toggle=\"yes\">SD<\/jats:italic>\n                    \u2009=\u20091.4), takes a person-oriented approach to examine adolescents digital skill profiles and associations with socioeconomic, digital activity, and socioemotional antecedents. Using latent profile analyses with tests of similarity across countries, we identified five profiles: All-rounders, Informationists, Content Creators, Communicators, and No high skills. The All-rounders reported the highest proportions of skills at a high level (~77\u201387%) across all dimensions and performed best across digital knowledge items, but Communicators were the largest profile across countries which showed adept acquisition (~67%) of high skills only regarding communication and interaction skills. Among the most important antecedents predicting high digital skills were being male, using computers, and having strong self-efficacy.\n                  <\/jats:p>","DOI":"10.1177\/14614448241258704","type":"journal-article","created":{"date-parts":[[2024,6,24]],"date-time":"2024-06-24T09:09:32Z","timestamp":1719220172000},"page":"5915-5937","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Latent profiles of adolescents\u2019 digital skills across six European countries"],"prefix":"10.1177","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2149-9237","authenticated-orcid":false,"given":"Lauri","family":"Hietaj\u00e4rvi","sequence":"first","affiliation":[{"name":"University of Helsinki, Finland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6939-2650","authenticated-orcid":false,"given":"Giovanna","family":"Mascheroni","sequence":"additional","affiliation":[{"name":"Universit\u00e0 Cattolica del Sacro Cuore, Italy"}]},{"given":"Natalia","family":"Waechter","sequence":"additional","affiliation":[{"name":"University of Graz, Austria; Ludwig-Maximilians-University Munich, Germany"}]},{"given":"Jussi","family":"J\u00e4rvinen","sequence":"additional","affiliation":[{"name":"University of Helsinki, Finland"}]},{"given":"Katariina","family":"Salmela-Aro","sequence":"additional","affiliation":[{"name":"University of Helsinki, Finland"}]}],"member":"179","published-online":{"date-parts":[[2024,6,24]]},"reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2014.03.013"},{"key":"e_1_3_3_3_1","unstructured":"Asparouhov T Muth\u00e9n B (2021) Auxiliary variables in mixture modeling: using the BCH method in mplus to estimate a distal outcome model and an arbitrary secondary model. 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