{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:13:35Z","timestamp":1761808415185,"version":"3.41.2"},"reference-count":56,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2020,12,28]],"date-time":"2020-12-28T00:00:00Z","timestamp":1609113600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["EL"],"published-print":{"date-parts":[[2021,5,18]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>This study aims to segment and profile young internet addicts in India and examine their state of well-being.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>Young\u2019s Internet Addiction Test was adapted to identify and profile cohorts among the internet addicts. Diener\u2019s satisfaction with life scale was used to measure the well-being. Convenience sampling was used to conduct an online survey and obtain a representative sample of 320 urban internet users. A mixed-method approach was deployed and exploratory factor analysis followed by <jats:italic>k<\/jats:italic>-means cluster analysis and discriminant analysis were used to analyse the quantitative data.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>Data analysis revealed the existence of three distinct clusters: non-addicts (135), potential internet addicts (<jats:italic>n<\/jats:italic> = 128) and addicts (<jats:italic>n<\/jats:italic> = 57). Smartphones and tablets were the primary devices for accessing the internet. Wi-Fi and data cards were used by all groups for internet browsing, messaging and visiting social networking sites. The usage hours were higher for the potential internet addicts and internet addicts. These groups also faced considerable internal conflict and dissonance in their inability to control their addictive behaviour and online cravings. The non-addicts were more satisfied with their life conditions and better adjusted than the other two groups.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title>\n<jats:p>The incidence of diverse internet addicted groups needs to be validated through a larger sample in other regions and geographies. There is also a dire need to study other vulnerable groups, such as internet-savvy adolescents.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The study found the existence of well-defined segments and identified unique areas of conflict for each group, which subsequently affected their sense of well-being.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/el-03-2020-0071","type":"journal-article","created":{"date-parts":[[2020,12,31]],"date-time":"2020-12-31T02:53:41Z","timestamp":1609383221000},"page":"17-32","source":"Crossref","is-referenced-by-count":2,"title":["Profiling young internet addicts: implications for their social 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