Problematic Internet use, maladaptive future time perspective and school context

  1. María José Díaz-Aguado 1
  2. Javier Martín-Babarro 1
  3. Laia Falcón 1
  1. 1 Universidad Complutense de Madrid
    info

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

Journal:
Psicothema

ISSN: 0214-9915

Year of publication: 2018

Volume: 30

Issue: 2

Pages: 195-200

Type: Article

DOI: 10.7334/PSICOTHEMA2017.282 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: Psicothema

Abstract

Spain is among the European countries with the highest prevalence of adolescents at risk of Internet addiction, a problem that could be linked to youth unemployment and leaving education early. This research evaluated the role of three variables relative to school context on Problematic Internet Use (PIU) and on the relationship between PIU and Maladaptive Future Time Perspective (MFTP, defined as an excessive focus on the present and a fatalistic attitude towards the future, a variable that had not previously been studied in terms of its relationship to adolescents’ PIU). Method: The study was carried out with 1288 adolescents, aged 12 to 16 years old, enrolled at 31 secondary schools in Madrid, Spain. Results: As expected, we found that MFTP and hostile treatment by teachers were associated with an increase in PIU, whereas school appreciation was associated with a decrease in PIU. In addition, hostile treatment by teachers had a moderate effect on the MFTP-PIU relationship. Conclusions: In order to prevent PIU it is important to foster confidence in adolescents in their own potential to build the future from the present through positive interaction with teachers, stimulating an appreciation of school within these digital natives’ peer group culture

Bibliographic References

  • Caplan, S.E. (2002). Problematic Internet use and psychosocial wellbeing: Development of a theory-based cognitive-behavioral measure. Computers in Human Behavior, 18, 533-575. https://doi.org/10.1016/ S0747-5632(02)00004-3
  • Caplan, S.E. (2007). Relations among loneliness, social anxiety, and problematic Internet use. CyberPsychology & Behavior, 10, 234-241. https://doi.org/10.1089/cpb.2006.9963
  • Caplan, S. E. (2010). Theory and measurement of generalized problematic Internet use: A two-step approach. Computers in Human Behavior, 26, 1089-1097. https://doi.org/10.1016/j.chb.2010.03.012
  • Catalano, R.F., Haggerty, K.P., Oesterle, S., et al. (2004). The importance of bonding to school for healthy development: Findings from the Social Development Research Group. Journal of School Health, 74, 252-261. doi: 10.1111/j.1746-1561.2004.tb08281.x
  • Cheng, C., & Li, A. Y. L. (2014). Internet addiction prevalence and quality of (real) life: A meta-analysis of 31 nations across seven world regions. Cyberpsychology, Behavior, and Social Networking, 17, 755-760. https://doi.org/10.1089/cyber.2014.0317
  • Chng, G. S., Li, D., Liau, A. K., & Khoo, A. (2015). Moderating effects of the family environment for parental mediation and pathological internet use in youths. Cyberpsychology, Behavior, and Social Networking, 18, 30-36. https://doi.org/10.1089/cyber.2014.0368
  • Chong, W., Chye, S., Huan, V., & Ang, R. (2014). Generalized problematic Internet use and regulation of social emotional competence: The mediating role of maladaptive cognitions arising from academic expectation stress on adolescents. Computers in Human Behavior, 38, 151-158. https://doi.org/10.1016/j.chb.2014.05.023
  • Chittaro, L., & Vianello, A. (2013). Time perspective as a predictor of problematic Internet use: A study of Facebook users. Personality and Individual Differences, 55, 989-993. https://doi.org/10.1016/j. paid.2013.08.007
  • Davis, R.A. (2001). Cognitive-behavioral model of pathological Internet use. Computers in Human Behavior, 17, 187-195. https://doi. org/10.1016/S0747-5632(00)00041-8
  • Díaz-Aguado Jalón, M. J., & Martínez Arias, R. (2013). Peer bullying and disruption-coercion escalations in student-teacher relationship. Psicothema, 25, 206-213. doi: 10.7334/psicothema2012.312
  • Díaz-Aguado, M.J., Martínez-Arias, R., & Martín-Babarro, J. (2010). Estudio estatal sobre la convivencia escolar en la Educación Secundaria Obligatoria [Study on school climate in Compulsory Secondary Education in Spain]. Madrid: Ministerio de Educación.
  • Díaz-Aguado, M.J. Martínez, R., & Ordoñez, A. (2013). Prevenir la drogodependencia en adolescentes y mejorar la convivencia desde una perspectiva escolar ecológica [Preventing drug use in adolescence and improving school climate from an ecological approach]. Revista de Educación, 1, 338-362. doi: 10.4438/1988-592X-RE-2013EXT-251
  • Díaz-Morales, J. F. (2006). Estructura factorial y fi abilidad del Inventario de Perspectiva Temporal de Zimbardo [Factorial structure and reliability of Zimbardo Time Perspective Inventory]. Psicothema, 18, 565-571.
  • Esen, B., & Gündoğdu, M. (2010). The Relationship between Internet addiction, peer pressure and perceived social support among adolescents. International Journal of Educational Researchers, 2, 29-36. http://ijer.eab.org.tr/1/2/4_esen.b.k.pdf
  • Freudenberg, N., & Ruglis, J. (2007). Reframing school dropout as a public health issue. Preventing Chronic Disease, 4, A107. https://eric. ed.gov/?id=ED499412
  • Fletcher, A., Bonell, C., & Hargreaves, J. (2006). School Effects on Young People’s Drug Use: A Systematic Review of Intervention and Observational Studies. Journal of Adolescent Health, 42, 209-220. https://doi.org/10.1016/j.jadohealth.2007.09.020
  • Gámez-Guadix, M., Orue, I., & Calvete, E. (2013). Evaluation of the cognitive-behavioral model of generalized and problematic Internet use in Spanish adolescents. Psicothema, 25, 299-306. doi:0.7334/ psicothema2012.274
  • Husman, J., & Shell, D. F. (2008). Beliefs and perceptions about the future: A measurement of future time perspective. Learning and Individual Differences, 18, 166-175. https://doi.org/10.1016/j.lindif.2007.08.001
  • Instituto Nacional de Estadística (2014). España en cifras 2013 [Spain in numbers 2013]. Madrid: INE.
  • Jessor, R. (1992). Risk behavior in adolescence: A psychological framework for understanding and action. Developmental Review, 12, 374-390. https://doi.org/10.1016/1054-139X(91)90007-K
  • Kim J., LaRose R., & Peng W. (2009). Loneliness as the cause and the effect of problematic Internet use: The relationship between Internet use and psychological well-being. CyberPsychology & Behavior, 12, 451-455. https://doi.org/10.1089/cpb.2008.0327
  • Leung, L. (2004). Net-generation attributes and seductive properties of the Internet as predictors of online activities and Internet addiction. Cyberpsychology & Behavior, 7, 333-348. https://doi.org/10.1089/1094931041291303
  • Li, D., Li, X., Wang, Y., Zhao, L., Bao, Z., & Wen, F. (2013). School connectedness and problematic Internet use in adolescents: A moderated mediation model of deviant peer affi liation and selfcontrol. Journal of Abnormal Child Psychology, 41, 1231-1242. https:// doi.org/10.1007/s10802-013-9761-9
  • Li D., Zhang W., Li X., Zhen S., & Wang Y. (2010). Stressful life events and problematic Internet use by adolescent females and males: A mediated moderation model. Computers in Human Behavior, 26, 1199-1207. https://doi.org/10.1016/j.chb.2010.03.031
  • Martín-Serrano, M., & Velarde-Hermida, O. (2000). Informe de Juventud en España 2000 [Youth in Spain 2000 report]. Madrid: Ministerio de Trabajo y Asuntos Sociales-INJUVE.
  • McNeely, C., & Falci, C. (2004). School connectedness and the transition into and out of health-risk behavior among adolescent: A comparison of social belonging and social support. Journal of School Health, 74, 284-292. doi: 10.1111/j.1746-1561.2004.tb08285.x
  • OECD (2004). Learning for tomorrow’s: First Results from PISA 2003. Paris: OECD.
  • Preacher, K.J., Curran, P.J., & Bauer, D.J. (2006). Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics, 31, 437-448. http://dx.doi.org/10.3102/10769986031004437
  • Prensky, M. (2001). Digital game bases learning. New York: McGraw Hill.
  • Przepiorka, A., & Blachnio, A. (2016). Time perspective in Internet and Facebook addiction. Computers in Human Behavior, 60, 13-18. https:// doi.org/10.1016/j.chb.2016.02.045
  • Raudenbush, S.W., Bryk, A.S., & Congdon, R. (2010). HLM 7: Hierarchical linear and nonlinear modeling. Lincolnwood: Scientific Software International.
  • Snijders, T.A.B., & Bosker, R.J. (1999). Multilevel analyses: An introduction to basic and advanced multilevel modeling. London: Sage Publications.
  • Steinberg, L. (2008). A social neuroscience perspective on adolescent risktaking. Developmental Review, 28, 78-106. https://doi.org/10.1016/j. dr.2007.08.002
  • Steinberg, L., Graham, S., O’Brien, L., Woolard, J., Cauffman, E., & Banich, M. (2009). Age differences in future orientation and delay discounting. Child Development, 80, 28-44. https://doi:10.1111/j.14678624.2008.01244.x
  • Sun, P., Unger, J. B., Palmer, P. H., Gallaher, P., Chou, C. P., Baezconde-Garbanati, L., & Johnson, C. A. (2005). Internet accessibility and usage among urban adolescents in Southern California: Implications for web-based health research. CyberPsychology & Behavior, 8, 441453. https://doi.org/10.1089/cpb.2005.8.441
  • Trianes, M. V., Blanca, M. J., De la Morena, L., Infante, L., & Raya, S. (2006). Un cuestionario para evaluar el clima social del centro escolar [A questionnaire to assess school social climate]. Psicothema, 18, 272277.
  • Tsitsika, A., Janikian, M., Schoenmakers, T., et al. (2014). The EU NET ADB Consortium, & Richardson, C. Internet addictive behavior in adolescence: A cross-sectional study in seven European countries. Cyberpsychology, Behavior, and Social Networking, 17, 528-535. https://doi.org/10.1089/cyber.2013.0382
  • Wang, M., & Fredricks, J. (2014). The reciprocal links between school engagement, youth problem behaviors, and school dropout during adolescence. Child Development, 85, 722-737. doi:10.1111/cdev.12138
  • Wills, T. A., Sandy, J. M., & Yaeger, A. M. (2001). Time perspective and early-onset substance use: A model based on stress-coping theory. Psychology of addictive behaviors, 15, 118-125. http://dx.doi. org/10.1037/0893-164X.15.2.118
  • Worrell, F. C., & Hale, R. L. (2001). The relationship of hope in the future and perceived school climate to school completion. School Psychology Quarterly, 16, 370-388. http://dx.doi.org/10.1521/scpq.16.4.370.19896
  • Yen, C.F., Ko, C.H., Yen, J.Y., Chang, Y., & Cheng CP. (2009). Multidimensional discriminative factors for Internet addiction among adolescents regarding gender and age. Psychiatry and Clinical Neurosciences, 63, 357-364.doi: 10.1111/j.1440-1819.2009.01969.x
  • Zimbardo, P.G.,& Boyd JN. (1999). Putting time in perspective: A valid, reliable individual-difference metric. Journal of Personality and Social Psychology, 77, 1271-1288. https://doi.org/10.1007/978-3-319-07368-2_2