Smartphone addiction, social support, and cybercrime victimizationa discrete survival and growth mixture model

  1. Juan Herrero 1
  2. Andrea Torres 1
  3. Pep Vivas 2
  4. Alberto Urueña 3
  1. 1 University of Oviedo, Spain
  2. 2 Universitat Oberta de Cataluña, Spain
  3. 3 Universidad Politécnica de Madrid, Spain
Zugehörigkeit anzeigen +
Zeitschrift:
Psychosocial Intervention

ISSN: 1132-0559

Datum der Publikation: 2022

Ausgabe: 31

Nummer: 1

Seiten: 59-66

Art: Artikel

DOI: 10.5093/PI2022A3 DIALNET GOOGLE SCHOLAR lock_openOpen Access editor

Andere Publikationen in: Psychosocial Intervention

Zusammenfassung

In recent decades, criminological theories have identified a set of vulnerabilities in potential victims that seek to explain their victimization. When it comes to explaining cybercrime victimization, however, the important role that addiction to the vulnerabilities associated with technological devices can play has tended to be overlooked. In this paper we empirically link smartphone addiction, social support, and cyberfraud victimization in a nationally representative sample of 716 smartphone users followed for three years. The results of discrete survival and growth mixture models suggest that the probability of cyberfraud victimization is lower among users with a decrease in smartphone addiction and an increase in social support over the three years. These results allow us to suggest new avenues in the study of cybercrime victimization, with special emphasis on the psychosocial consequences that the deregulated use of these technological devices may entail.

Bibliographische Referenzen

  • Akdemir, N,Lawless, C. J.. (2020). Exploring the human factor in cyber-enabled and cyber-dependent crime victimisation: A lifestyle routine activities approach. Internet Research. 30. 1665-2020
  • Alhaboby, Z. A,Barnes, J,Evans, H,Short, E.. (2019). Cyber-victimization of people with chronic conditions and disabilities: A systematic review of scope and impact. Trauma, Violence, & Abuse. 20. 398-415
  • Al-Kandari, Y. Y,Al-Sejari, M. M.. (2020). Social isolation, social support and their relationship with smartphone addiction. Information, Communication & Society. 24. 1925
  • Alves, L. M,Wilson, S. R.. (2008). The effects of loneliness on telemarketing fraud vulnerability among older adults. Journal of Elder Abuse & Neglect. 20. 63-85
  • Bauer, D. J,Curran, P. J.. (2003). Distributional assumptions of growth mixture models: Implications for overextraction of latent trajectory classes. Psychological Methods. 8. 338
  • Bian, M,Leung, L.. (2015). Linking loneliness, shyness, smartphone addiction symptoms, and patterns of Smartphone use to social capital. Social Science Computer Review. 33. 61-79
  • Buchanan, T.,Whitty, M. T.. (2014). The online dating romance scam: Causes and consequences of victimhood. Psychology, Crime & Law. 20. 261
  • Busch, P. A,McCarthy, S.. (2020). Antecedents and consequences of problematic smartphone use: A systematic literature review of an emerging research area. Computers in Human Behavior. 114.
  • Celeux, G,Frühwirth-Schnatter, S,Robert, C. P.. (2018). Model selection for mixture models—perspectives and strategies. Handbook of mixture analysis. 121
  • Elhai, J. D,Dvorak, R. D,Levine, J. C,Hall, B. J.. (2017). Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. Journal of Affective Disorders. 207. 251
  • Ghazi-Tehrani, A. K,Pontell, H. N.. (2021). Phishing evolves: Analyzing the enduring cybercrime. Victims & Offenders. 16. 316
  • Herrero, J,Fuente, A,Gracia, E.. (2011). Covariates of subjective well-being among Latin American immigrants in Spain: The role of social integration in the community. Journal of Community Psychology. 39. 761
  • Gui, M,Büchi, M.. (2021). From use to overuse: Digital inequality in the age of communication abundance. Social Science Computer Review. 39. 3-19
  • Herrero, J,Torres, A,Vivas, P,Arenas, A,Urueña, A.. (2021). Examining the empirical links between digital social pressure, personality, psychological distress, social support, users' residential living conditions, and smartphone addiction. Social Science Computer Review.
  • Herrero, J,Torres, A,Vivas, P,Hidalgo, A,Rodríguez, F. J,Urueña, A.. (2021). Smartphone addiction and cybercrime victimization in the context of lifestyles routine activities and self-control theories: The user's dual vulnerability model of cybercrime victimization. International Journal of Environmental Research and Public Health. 18.
  • Herrero, J,Torres, A,Vivas, P,Urueña, A.. (2019). Smartphone addiction and social support: A three-year longitudinal study. Psychosocial Intervention. 28. 111
  • Herrero, J,Torres, A,Vivas, P,Urueña, A.. (2019). Technological addiction in context: The influence of perceived neighborhood social disorder on the extensive use and addiction to the smartphone. Social Science Computer Review.
  • Herrero, J,Urueña, A,Torres, A,Hidalgo, A.. (2019). Smartphone addiction: Psychosocial correlates, risky attitudes, and smartphone harm. Journal of Risk Research. 22. 81-92
  • Herrero, J,Urueña, A,Torres, A,Hidalgo, A.. (2019). Socially connected but still isolated: Smartphone addiction decreases social support over time. Social Science Computer Review. 37. 73-88
  • Holtfreter, K,Reisig, M. D,Pratt, T. C.. (2008). Low self-control, routine activities, and fraud victimization. Criminology. 46. 189-220
  • Ihm, J.. (2018). Social implications of children's smartphone addiction: The role of support networks and social engagement. Journal of Behavioral Addictions. 7. 473
  • Judges, R,Li, H,Lee, K.. (2018). The impact of loneliness on financial fraud victimization in Chinese older adults. Innovation in Aging. 2.
  • Kim, E,Koh, E.. (2018). Avoidant attachment and smartphone addiction in college students: The mediating effects of anxiety and self-esteem. Computers in Human Behavior. 84. 264
  • Kubrin, C. E,Ousey, G. C.. (2021). Revitalizing victimization theory: Revisions, applications, and new directions. Routlege.
  • Kushlev, K,Dwyer, R,Dunn, E. W.. (2019). The social price of constant connectivity: Smartphones impose subtle costs on well-being. Current Directions in Psychological Science. 28. 347
  • Lapierre, M. A,Zhao, P.. (2021). Smartphones and social support: Longitudinal associations between smartphone use and types of support. Social Science Computer Review.
  • Leukfeldt, E. R.. (2015). Comparing victims of phishing and malware attacks: Unraveling risk factors and possibilities for situational crime prevention. arXiv preprint.
  • Lin, N,Dean, A,Ensel, W.. (1986). Social support, life events and depression. Academic Press. New York.
  • Liu, C,Ma, J.. (2018). Social support through online social networking sites and addiction among college students: The mediating roles of fear of missing out and problematic smartphone use. Current Psychology. 39. 1892
  • Lougheed, J. P,Benson, L,Cole, P. M,Ram, N.. (2019). Multilevel survival analysis: Studying the timing of children's recurring behaviors. Developmental Psychology. 55. 53-65
  • Masyn, K. E.. (2009). Discrete-time survival factor mixture analysis for low-frequency recurrent event histories. Research in Human Development. 6. 165
  • Martínez-Ferrer, B,León-Moreno, C,Suárez-Relinque, C,Del Moral-Arroyo, G,Musitu-Ochoa, G.. (2021). Cybervictimization, offline victimization, and cyberbullying: The mediating role of the problematic use of social networking sites in boys and girls. Psychosocial Intervention. 30. 155
  • Matthews, T,Caspi, A,Danese, A,Fisher, H. L,Moffitt, T. E,Arseneault, L.. (2020). A longitudinal twin study of victimization and loneliness from childhood to young adulthood. Development and Psychopathology. 1-11
  • Mollenhorst, G,Edling, C,Rydgren, J.. (2018). Personal networks and crime victimization among Swedish youth. Journal of Scandinavian Studies in Criminology and Crime Prevention. 19. 116
  • Muthén, L. K,Muthén, B. O.. (2017). Mplus user's guide. Muthén & Muthén.
  • Nylund, K. L,Asparouhov, T,Muthén, B. O.. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation modeling: A Multidisciplinary Journal. 14. 535
  • Oksanen, A,Keipi, T.. (2013). Young people as victims of crime on the internet: A population-based study in Finland. Vulnerable Children and Youth Studies. 8. 298-309
  • Pratt, T. C,Turanovic, J. J,Fox, K. A,Wright, K. A.. (2014). Self-control and victimization: A meta-analysis. Criminology. 52. 87-116
  • Ranney, J. D,Troop-Gordon, W.. (2020). The role of popularity and digital self-monitoring in adolescents' cyberbehaviors and cybervictimization. Computers in Human Behavior. 102. 293-302
  • Spano, R,Nagy, S.. (2005). Social guardianship and social isolation: An application and extension of lifestyle/routine activities theory to rural adolescents. Rural Sociology. 70. 414
  • Turanovic, J. J,Pratt, T. C.. (2014). "Can't stop, won't stop": Self-control, risky lifestyles, and repeat victimization. Journal of Quantitative Criminology. 30. 29-56
  • Whitty, M. T.. (2019). Predicting susceptibility to cyber-fraud victimhood. Journal of Financial Crime. 26. 277
  • Wilcox, P,Cullen, F. T.. (2018). Situational opportunity theories of crime. Annual Review of Criminology. 1. 123
  • Xing, T,Sun, F,Wang, K,Zhao, J,Wu, M,Wu, J.. (2020). Vulnerability to fraud among Chinese older adults: Do personality traits and loneliness matter?. Journal of Elder Abuse & Neglect. 32. 46-59
  • Yap, M. B,Devilly, G. J.. (2004). The role of perceived social support in crime victimization. Clinical Psychology Review. 24. 1-14
  • Yayan, E. H,Suna Da, Y,Düken, M. E.. (2019). The effects of technology use on working young loneliness and social relationships. Perspectives in Psychiatric Care. 55. 194-200
Fuente de los datos: Dialnet