Profiling young internet addicts: implications for their social well-being

Purpose This study aims to segment and profile young internet addicts in India and examine their state of well-being. Design/methodology/approach Young’s Internet Addiction Test was adapted to identify and profile cohorts among the internet addicts. Diener’s 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 k-means cluster analysis and discriminant analysis were used to analyse the quantitative data. Findings Data analysis revealed the existence of three distinct clusters: non-addicts (135), potential internet addicts (n = 128) and addicts (n = 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. Research limitations/implications 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. Originality/value 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.

[1]  Kelly A Saran,et al.  Electronic Media Use and Addiction among Youth in Psychiatric Clinic versus School Populations , 2012, Canadian journal of psychiatry. Revue canadienne de psychiatrie.

[2]  Konstantinos Siomos,et al.  Internet Addiction among Greek Adolescent Students , 2008, Cyberpsychology Behav. Soc. Netw..

[3]  Laith Mohammad Abualigah,et al.  Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering , 2017, The Journal of Supercomputing.

[4]  Manish Kumar,et al.  A study on Internet addiction and its relation to psychopathology and self-esteem among college students , 2018, Industrial psychiatry journal.

[5]  Wei-Ching Wang.  Exploring the Relationship Among Free-Time Management, Leisure Boredom, and Internet Addiction in Undergraduates in Taiwan , 2018, Psychological reports.

[6]  Stoney L. Brooks,et al.  Internet addiction: When the positive emotions are not so positive , 2019, Technology in Society.

[7]  Zhongming Ouyang,et al.  Internet Use in Young Adult Males: from the Perspective of Pursuing Well-Being , 2017 .

[8]  Abolfazl Saghafi,et al.  Psychosocial Profile of Iranian Adolescents' Internet Addiction , 2013, Cyberpsychology Behav. Soc. Netw..

[9]  A. Biswas,et al.  A Study of Factors of Internet Addiction and Its Impact on Online Compulsive Buying Behaviour: Indian Millennial Perspective , 2020, Global Business Review.

[10]  Laith Abualigah,et al.  Multi-verse optimizer algorithm: a comprehensive survey of its results, variants, and applications , 2020, Neural Computing and Applications.

[11]  J. Bharucha.  Social network use and youth well-being: a study in India , 2018 .

[12]  Zheng Huang,et al.  Chinese Internet Addiction Inventory: Developing a Measure of Problematic Internet Use for Chinese College Students , 2007, Cyberpsychology Behav. Soc. Netw..

[13]  D. Black,et al.  Internet Addiction , 2008, CNS drugs.

[14]  Lixuan Zhang,et al.  A Comparative Study of Internet Addiction between the United States and China , 2008, Cyberpsychology Behav. Soc. Netw..

[15]  Li Lin,et al.  Internet Addiction Among College Students in China: Prevalence and Psychosocial Correlates , 2016, Cyberpsychology Behav. Soc. Netw..

[16]  Arvind Sharma,et al.  Internet addiction and psychological well-being among college students: A cross-sectional study from Central India , 2018, Journal of family medicine and primary care.

[17]  Laith Mohammad Abualigah,et al.  A combination of objective functions and hybrid Krill herd algorithm for text document clustering analysis , 2018, Eng. Appl. Artif. Intell..

[18]  R. Larsen,et al.  The Satisfaction with Life Scale , 1985, Journal of personality assessment.

[19]  Paul Jen-Hwa Hu,et al.  Children's Internet Addiction, Family-to-Work Conflict, and Job Outcomes: A Study of Parent-Child Dyads , 2019, MIS Q..

[20]  Chun-Tuan Chang,et al.  How Social Anxiety and Reduced Self-Efficacy Induce Smartphone Addiction in Materialistic People , 2018 .

[21]  Michelle L. McNicol,et al.  Internet Addiction, Psychological Distress, and Coping Responses Among Adolescents and Adults , 2017, Cyberpsychology Behav. Soc. Netw..

[22]  Cecilia Cheng,et al.  Internet Addiction Prevalence and Quality of (Real) Life: A Meta-Analysis of 31 Nations Across Seven World Regions , 2014, Cyberpsychology Behav. Soc. Netw..

[23]  C. Ko,et al.  Tridimensional Personality of Adolescents with Internet Addiction and Substance Use Experience , 2006, Canadian journal of psychiatry. Revue canadienne de psychiatrie.

[24]  M. Chijoriga,et al.  Application of multiple discriminant analysis (MDA) as a credit scoring and risk assessment model , 2011 .

[25]  J. Morahan-Martin,et al.  Incidence and correlates of pathological Internet use among college students ? ? Portions of this pa , 2000 .

[26]  Laith Mohammad Abualigah,et al.  APPLYING GENETIC ALGORITHMS TO INFORMATION RETRIEVAL USING VECTOR SPACE MODEL , 2015 .

[27]  E. Mohandas.  Suicidal Patient Assessment and Management , 1997 .

[28]  James G. Phillips,et al.  Shyness and Anxiety as Predictors of Patterns of Internet Usage , 2002, Cyberpsychology Behav. Soc. Netw..

[29]  Sujin Lee,et al.  Internet Over-Users' Psychological Profiles: A Behavior Sampling Analysis on Internet Addiction , 2003, Cyberpsychology Behav. Soc. Netw..

[30]  Dorit Alt,et al.  Using multidimensional scaling and PLS-SEM to assess the relationships between personality traits, problematic internet use, and fear of missing out , 2018, Behav. Inf. Technol..

[31]  D. Ye,et al.  Internet addiction, adolescent depression, and the mediating role of life events: finding from a sample of Chinese adolescents. , 2014, International journal of psychology : Journal international de psychologie.

[32]  Louis Leung,et al.  Net-Generation Attributes and Seductive Properties of the Internet as Predictors of Online Activities and Internet Addiction , 2004, Cyberpsychology Behav. Soc. Netw..

[33]  I. Kawachi,et al.  Addictive Internet Use among Korean Adolescents: A National Survey , 2014, PloS one.

[34]  Yan Liu,et al.  The Relationship Between Internet Addiction and Depression Among Migrant Children and Left-Behind Children in China , 2012, Cyberpsychology Behav. Soc. Netw..

[35]  Barbora Simkova,et al.  Internet Addiction Disorder and Chatting in the Czech Republic , 2004, Cyberpsychology Behav. Soc. Netw..

[36]  Huei-Chen Ko,et al.  Prevalence and Psychosocial Risk Factors Associated with Internet Addiction in a Nationally Representative Sample of College Students in Taiwan , 2011, Cyberpsychology Behav. Soc. Netw..

[37]  Zsolt Demetrovics,et al.  The three-factor model of Internet addiction: The development of the Problematic Internet Use Questionnaire , 2008, Behavior research methods.

[38]  K. Fragkos,et al.  Internet Addiction among Greek University Students: Demographic Associations with the Phenomenon, Using the Greek Version of Young's Internet Addiction Test , 2010 .

[39]  S. Tikka,et al.  Exploratory Factor Analysis of Young’s Internet Addiction Test Among Professionals from India: An Online Survey , 2020, Indian journal of psychological medicine.

[40]  Shipra Singh,et al.  Study of Internet addiction in children with attention-deficit hyperactivity disorder and normal control , 2018, Industrial psychiatry journal.

[41]  Kimberly Young,et al.  Internet Addiction: The Emergence of a New Clinical Disorder , 1998, Cyberpsychology Behav. Soc. Netw..

[42]  Kanwal Nalwa,et al.  Internet Addiction in Students: A Cause of Concern , 2003, Cyberpsychology Behav. Soc. Netw..

[43]  Chih-Hung Ko,et al.  Family Factors of Internet Addiction and Substance Use Experience in Taiwanese Adolescents , 2007, Cyberpsychology Behav. Soc. Netw..

[44]  Laith Mohammad Abualigah,et al.  Hybrid clustering analysis using improved krill herd algorithm , 2018, Applied Intelligence.

[45]  Antonella D'Amico,et al.  Internet Addiction Disorder: An Italian Study , 2007, Cyberpsychology Behav. Soc. Netw..

[46]  Qin Zhang,et al.  Internet Addiction Among Elementary and Middle School Students in China: A Nationally Representative Sample Study , 2014, Cyberpsychology Behav. Soc. Netw..

[47]  R. A. Davis,et al.  A cognitive-behavioral model of pathological Internet use , 2001, Comput. Hum. Behav..

[48]  Norazizah Ibrahim Wong,et al.  The Association of Internet Addiction and Perceived Parental Protective Factors Among Malaysian Adolescents , 2019, Asia-Pacific journal of public health.

[49]  Clive Richardson,et al.  Internet Addictive Behavior in Adolescence: A Cross-Sectional Study in Seven European Countries , 2014, Cyberpsychology Behav. Soc. Netw..