Skip to main content
SpringerLink
Log in

Exploring the Influence of Information Overload, Internet Addiction, and Social Network Addiction, on Students’ Well-Being and Academic Outcomes

  • Conference paper
  • First Online:
Human Mental Workload: Models and Applications (H-WORKLOAD 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1493))

Abstract

This study explored how students' main information problems during the information age, namely internet addiction, information overload, and social network addiction, influence holistic well-being and academic attainment. The participants were 226 university students, all UK based and regular internet users. They answered the Internet Addiction Test, Information Overload Scale, Bergen Social Media Addiction Scale, and the Wellbeing Process Questionnaire. Data were analysed with SPSS using correlation and linear regression analysis. The univariate analyses confirmed the negative impact of information overload, internet addiction and social media addiction on positive well-being but not academic attainment. However, multivariate analyses controlling for established predictors of well-being showed that the effects of information overload, internet addiction and social media addiction were largely non-significant, confirming other research using this analysis strategy. Future research should examine the type of internet use as well as the extent of it.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Longo, L., Leva, M.C. (eds.): Human Mental Workload: Models and Applications. H-WORKLOAD 2017. Communications in Computer and Information Science, vol. 726, pp. 251–263. Springer, Cham (2017). https://doi.org/10.1007/978-3-030-32423-0

  2. Longo, L., Leva, M.C. (eds.): Human Mental Workload: Models and Applications. H-WORKLOAD 2018. Communications in Computer and Information Science. Springer, Cham (2019)

    Google Scholar 

  3. Longo, L., Leva, M.C. (eds.): Human Mental Workload: Models and Applications. H-WORKLOAD 2019. Communications in Computer and Information Science. Springer, Cham (2019)

    Google Scholar 

  4. Reid, G.B., Nygren, T.E.: The subjective workload assessment technique: a scaling procedure for measuring mental workload. Adv. Psychol. 52, 185–218 (1988)

    Google Scholar 

  5. Stassen, H.G., Johannsen, G., Moray, N.: Internal representation, internal model, human performance model and mental workload. Automatica 26(4), 811–820 (1990)

    Google Scholar 

  6. De Waard, D.: The Measurement of Drivers’ Mental Workload. University of Groningen The Traffic Research Centre VSC (1996)

    Google Scholar 

  7. Hart, S.G.: Nasa-task load index (NASA-TLX); 20 years later. In: Human Factors and Ergonomics Society Annual Meeting. vol. 50. Sage Journals (2006)

    Google Scholar 

  8. Smith, A.P., Smith, K.: Effects of workload and time of day on performance and mood. In: Megaw, E.D. (ed.) Contemporary Ergonomics, pp. 497–502. Taylor & Francis, London (1988)

    Google Scholar 

  9. Evans, M.S., Harborne, D., Smith, A.P: Developing an objective indicator of fatigue: an alternative mobile version of the Psychomotor Vigilance Task (m-PVT). Presented at: H-WORKLOAD 2018: International Symposium on Human Mental Workload: Models and Applications, Amsterdam, The Netherlands, 20–21 September 2018. Longo, L., Leva, M.C. (eds.): H-WORKLOAD 2018, CCIS 1012, pp. 147–159, 2019. Springer Nature, Cham (2019)

    Google Scholar 

  10. Smith, A.P., Smith, H.N.: Workload, fatigue and performance in the rail industry. In: Longo, L., Leva, M.C. (eds.) Human Mental Workload: Models and Applications. H-WORKLOAD 2017. Communications in Computer and Information Science, vol. 726, pp. 251–263. Springer, Cham (2017)

    Google Scholar 

  11. Fan, J., Smith, A.P.: Mental workload and other causes of different types of fatigue in rail staff. In: Longo, L., Leva, M.C. (eds.) H-WORKLOAD 2018. CCIS, vol. 1012, pp. 147–159. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-14273-5_9

    Chapter  Google Scholar 

  12. Cortes Torres, C.C., Sampei, K., Sato, M., Raskar, R., Miki, N.: Workload assessment with eye movement monitoring aided by non-invasive and unobtrusive micro-fabricated optical sensors. In: Adjunct Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology, pp. 53–54 (2015)

    Google Scholar 

  13. Yoshida, Y., Ohwada, H., Mizoguchi, F., Iwasaki, H.: Classifying cognitive load and driving situation with machine learning. Int. J. Mach. Learn. Comput. 4(3), 210–215 (2014)

    Google Scholar 

  14. Wilson, G.F., Eggemeier, T.F.: Mental workload measurement. In: Karwowski, W. (ed.) International Encyclopedia of Ergonomics and Human Factors, 2nd edn., vol. 1, Chap. 167. Taylor & Francis, London (2006)

    Google Scholar 

  15. Young, M.S., Stanton, N.A.: Mental workload. In: Stanton, N.A., Hedge, A., Brookhuis, K., Salas, E., Hendrick, H.W. (eds.) Handbook of Human Factors and Ergonomics Methods, Chap. 39, pp. 1–9. CRC Press, Boca Raton (2004)

    Google Scholar 

  16. Young, M.S., Stanton, N.A.: Mental workload: theory, measurement, and application. In: Karwowski, W. (ed.) International Encyclopedia of Ergonomics and Human Factors, 2nd edn., vol. 1, pp. 818–821. Taylor & Francis, London (2006)

    Google Scholar 

  17. Moustafa, K., Luz, S., Longo, L.: Assessment of mental workload: a comparison of machine learning methods and subjective assessment techniques. In: Longo, L., Leva, M.C. (eds.) H-WORKLOAD 2017. CCIS, vol. 726, pp. 30–50. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61061-0_3

    Chapter  Google Scholar 

  18. Hart, S.G., Staveland, L.E.: Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. Adv. Psychol. 52(C), 139–183 (1988)

    Google Scholar 

  19. Tsang, P.S., Velazquez, V.L.: Diagnosticity and multi-dimensional subjective work- load ratings. Ergonomics 39(3), 358–381 (1996)

    Google Scholar 

  20. Toffler, A.: Future Shock. Bantam Books, New York (1970)

    Google Scholar 

  21. Eppler, M.J., Mengis, J.: The concept of information overload: a review of literature from organisation science, accounting, marketing, and related disciplines. Inf. Soc. 20(5), 325–344 (2004)

    Google Scholar 

  22. Chewning, E.G., Jr., Harrell, A.M.: The effect of information load on decision makers’ cue utilisation levels and decision quality in a financial distress decision task. Account. Organ. Soc. 15(6), 527–542 (2009)

    Google Scholar 

  23. Savolainen, I., Kaakinen, M., Sirola, A., Oksanen, A.: Addictive behaviors and psychological distress among adolescents and emerging adults: a mediating role of peer group identification. Addict. Behav. Rep. 7, 75–81 (2018)

    Google Scholar 

  24. Spira, J., Burke, C.: Intel’s war on information overload: Case study. Basex (2009). http://iorgforum.org/wp-content/uploads/2011/06/IntelWarIO.BasexReport1.pdf

  25. Guarinoni, M., et al.: Occupational health concerns: stress-related and psychological problems associated with work. European Parliament’s Committee on Employment and Social Affairs, Brussels (2013)

    Google Scholar 

  26. Schick, A.G., Gorden, L.A., Haka, S.: Information overload: a temporal approach. Account. Organ. Soc. 15(3), 199–220 (1990)

    Google Scholar 

  27. McLeod, S.A.: Selective attention (2008). http://www.simplypsychology.org/attention-models.html

  28. Miller, G.A.: The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol. Rev. 63(2), 81–97 (1956)

    Google Scholar 

  29. Davis, R.: A cognitive-behavioral model of pathological Internet use. Comput. Hum. Behav. 17(2), 187–195 (2001). https://doi.org/10.1016/s0747-5632(00)00041-8

    Article  Google Scholar 

  30. Shapira, N.A., Goldsmith, T.D., Keck, P.E., Khosla, U.M., McElroy, S.L.: Psychiatric features of individuals with problematic internet use. J. Affect. Disord. 57, 267–272 (2000)

    Google Scholar 

  31. Young, K.S.: Internet addiction: the emergence of a new clinical disorder. Cyberpsychol. Behav. 1(3), 237–244 (1998). https://doi.org/10.1089/cpb.1998.1.237

    Article  Google Scholar 

  32. Caplan, S.E.: Problematic Internet use and psychosocial well-being: development of a theory-based cognitive–behavioral measurement instrument. Comput. Hum. Behav. 18(5), 553–575 (2002). https://doi.org/10.1016/s0747-5632(02)00004-3

    Article  Google Scholar 

  33. Davis, R.A., Flett, G.L., Besser, A.: Validation of a new scale for measuring problematic internet use: Implications for pre-employment screening. Cyberpsychol. Behav. 5(4), 331–345 (2002). https://doi.org/10.1089/109493102760275581

    Article  Google Scholar 

  34. Kubey, R.W., Lavin, M.J., Barrows, J.R.: Internet use and collegiate academic performance decrements: early findings. J. Commun. 51(2), 366–382 (2001)

    Google Scholar 

  35. Hall, A.S., Parsons, J.: Internet addiction: college student case study using best practice in cognitive behavior therapy. J. Ment. Health Couns. 23(4), 312–327 (2001)

    Google Scholar 

  36. Scherer, K.: College life online: healthy and unhealthy Internet use. J. Coll. Stud. Dev. 38(6), 655–665 (1997)

    Google Scholar 

  37. Young, K.S.: Psychology of computer use: XL. addictive use of the internet: a case that breaks the stereotype. Psychol. Rep. 79(3), 899–902 (1996)

    Google Scholar 

  38. Whang, L.S., Lee, S., Chang, G.: Internet over-users’ psychological profiles: a behavior sampling analysis on Internet addiction. Cyberpsychol. Behav. 6(2), 143–150 (2003)

    Google Scholar 

  39. Greenfield, D.N., Davis, R.A.: Lost in cyberspace: the web @ work. Cyberpsychol. Behav. 5(4), 347–353 (2002)

    Google Scholar 

  40. Pratarelli, M.E., Browne, B.L.: Confirmatory factor analysis of Internet use and addiction. Cyberpsychol. Behav. 5(1), 53–64 (2002)

    Google Scholar 

  41. Shapira, N.A., et al.: Problematic Internet use: proposed classification and diagnostic criteria. Depress. Anxiety 17, 207–216 (2003)

    Google Scholar 

  42. Davis, R.: Psychological implications of technology in the workplace. Cyberpsychol. Behav. 5(4), 277–278 (2002). https://doi.org/10.1089/109493102760275545

    Article  Google Scholar 

  43. Holden, N.: Knowledge management: raising the spectre of the cross-cultural dimension. Knowl. Process. Manag. 8, 155–163 (2001). https://doi.org/10.1002/kpm.117

    Article  Google Scholar 

  44. Holmes, D.L.: Virtual Politics: Identity and Community in Cyberspace. Sage, London (2001)

    Google Scholar 

  45. Petrie, H., Gunn, D.: “Internet addiction”: the effects of sex, age, depression, and introversion. Paper presented at the British Psychological Society Conference, London (1998)

    Google Scholar 

  46. Choi, S.B., Lim, M.: Effects of social and technology overload on psychological well-being in young South Korean adults: the mediatory role of social network service addiction. Comput. Hum. Behav. 61, 245–254 (2016). https://doi.org/10.1016/j.chb.2016.03.032

    Article  Google Scholar 

  47. Kwon, M., Kim, D.J., Cho, H., Yang, S.: The smartphone addiction scale: development and validation of a short version for adolescents. PLoS ONE 8(12), e83558 (2013). https://doi.org/10.1371/journal.pone.0083558

    Article  Google Scholar 

  48. Ellison, N.B., Steinfeld, C., Lampe, C.: The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. J. Comput.-Mediat. Commun. 12, 1143–1168 (2007). https://doi.org/10.1111/j.1083-6101.2007.00367.x

    Article  Google Scholar 

  49. Valenzuela, S., Park, N., Kee, K.F.: Is there social capital in a social network site? Facebook use and college students’ life satisfaction, trust, and participation. J. Comput.-Mediat. Commun. 14, 875–901 (2009). https://doi.org/10.1111/j.1083-6101.2009.01474.x

    Article  Google Scholar 

  50. Jones, Q., Gilad, R., Sheizaf, R.: Information overload and the message dynamics of online interaction spaces: a theoretical model and empirical exploration. Inf. Syst. Res. 15(2), 194–210 (2004)

    Google Scholar 

  51. Lee, A.R., Son, S.M., Kim, K.K.: Information and communication technology overload and social networking service fatigue: a stress perspective. Comput. Hum. Behav. 55, 51–61 (2016)

    Google Scholar 

  52. Soto-Acosta, P., Molina-Castillo, F.J., Lopez-Nicolas, C., Colomo-Palacios, R.: The effect of information overload and disorganisation on intention to purchase online: the role of perceived risk and internet experience. Online Inf. Rev. 38(4), 543–561 (2014). https://doi.org/10.1108/OIR-01-2014-0008

    Article  Google Scholar 

  53. Alhenieidi, H., Smith, A.P.: Effects of perceptions of information overload, noise and environmental demands on wellbeing and academic attainment. In: Longo, L., Leva, M.C. (eds.) H-WORKLOAD 2020. CCIS, vol. 1318, pp. 87–96. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-62302-9_6

    Chapter  Google Scholar 

  54. Alheneidi, H., Smith, A.P.: Perceptions of noise exposure, information overload and the well-being of workers. In: ICBEN (2021)

    Google Scholar 

  55. Pereira, G.: and. In: Schweiger, G. (ed.) Poverty, Inequality and the Critical Theory of Recognition. PP, vol. 3, pp. 83–106. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-45795-2_4

    Chapter  Google Scholar 

  56. Alavi, S.S., Maracy, M.R., Jannatifard, F., Eslami, M.: The effect of psychiatric symptoms on the Internet addiction disorder in Isfahan’s university students. J. Res. Med. Sci. 16(6), 793–800 (2011)

    Google Scholar 

  57. Cardak, M.: Psychological well-being and internet addiction among university students. Turkish Online J. Educ. Technol. 12(3), 134–141 (2013)

    Google Scholar 

  58. Casale, S., Lecchi, S., Fioravanti, G.: The association between psychological well-being and problematic use of Internet communicative services among young people. J. Psychol. Interdiscipl. Appl. 149, 480–497 (2015). https://doi.org/10.1080/00223980.2014.905432

    Article  Google Scholar 

  59. Akin, A.: The relationships between Internet addiction, subjective vitality, and subjective happiness. Cyberpsychol. Behav. Soc. Netw. 15, 404–410 (2012). https://doi.org/10.1089/cyber.2011.0609

    Article  Google Scholar 

  60. Chen, S.: Internet use and psychological well-being among college students: a latent profile approach. Comput. Hum. Behav. 28, 2219–2226 (2012). https://doi.org/10.1016/j.chb.2012.06.029

    Article  Google Scholar 

  61. Muusses, L.D., Finkenauer, C., Kerkhof, P., Billedo, C.J.: A longitudinal study of the association between compulsive internet use and well-being. Comput. Hum. Behav. 36, 21–28 (2014). https://doi.org/10.1016/j.chb.2014.03.035

    Article  Google Scholar 

  62. Kutty, N., Sreeramareddy, C.: A cross-sectional online survey of compulsive internet use and mental health of young adults in Malaysia. J. Fam. Community Med. 21(1), 23–28 (2014). https://doi.org/10.4103/2230-8229.128770

    Article  Google Scholar 

  63. Mark, G.M., Smith, A.P.: Stress models: a review and suggested new direction. In: Houdmont, J., Leka, S. (eds.) Occupational Health Psychology: European Perspectives on Research, Education and Practice, pp. 111–144. Nottingham University Press, Nottingham (2008)

    Google Scholar 

  64. Mark, G., Smith, A.P.: Effects of occupational stress, job characteristics, coping and attributional style on the mental health and job satisfaction of university employees. Anxiety Stress Coping 25, 63–78 (2011)

    Google Scholar 

  65. Mark, G., Smith, A.P.: Occupational stress, job characteristics, coping and mental health of nurses. Br. J. Health. Psychol. 17, 505–521 (2012)

    Google Scholar 

  66. Mark, G., Smith, A.P.: A qualitative study of stress in university staff. Adv. Soc. Sci. Res. J. 5(2), 238–247 (2018)

    Google Scholar 

  67. Mark, G., Smith, A.P.: Coping and its relation to gender, anxiety, depression, fatigue, cognitive difficulties and somatic symptoms. J. Educ. Soc. Behav. Sci. 25(4), 1–22 (2018)

    MathSciNet  Google Scholar 

  68. Smith, A.P.: A holistic approach to stress and well-being. Occup. Health (At Work) 7(4), 34–35 (2011)

    Google Scholar 

  69. Smith, A.P., Wadsworth, E.: A holistic approach to stress and well-being. Part 5: what is a good job? Occup. Health (At Work), 8(4), 25–27 (2011)

    Google Scholar 

  70. Smith, A.P., Wadsworth, E.J.K., Chaplin, K., Allen, P.H., Mark, G.: The Relationship Between Work/Well-Being And Improved Health and Well-Being. IOSH, Leicester (2011)

    Google Scholar 

  71. Wadsworth, E.J.K., Chaplin, K., Allen, P.H., Smith, A.P.: What is a good job? Current perspectives on work and improved health and wellbeing. Open Health Saf. J. 2, 9–15 (2010)

    Google Scholar 

  72. Williams, G.M., Smith, A.P.: Using single-item measures to examine the relationships between work, personality, and well-being in the workplace. Posit. Psychol. 7, 753–767 (2016)

    Google Scholar 

  73. Williams, G.M., Smith, A.P.: A holistic approach to stress and well-being. Part 6: the wellbeing process questionnaire (WPQ Short Form). Occup. Health (At Work), 9(1), 29–31 (2012)

    Google Scholar 

  74. Williams, G.M., Smith, A.P.: Diagnostic validity of the anxiety and depression questions from the wellbeing process questionnaire. J. Clin. Transl. Res. 10 (2018)

    Google Scholar 

  75. Williams, G.M., Pendlebury, H., Smith, A.P.: Stress and well-being of nurses: an investigation using the demands-resources- individual effects (DRIVE) model and well-being process questionnaire (WPQ). Jacobs J. Depress. Anxiety 1, 1–8 (2017)

    Google Scholar 

  76. Williams, G., Thomas, K., Smith, A.P.: Stress and well-being of university staff: an investigation using the Demands-Resources- Individual Effects (DRIVE) model and Well-being Process Questionnaire (WPQ). Psychology 8, 1919–1940 (2017)

    Google Scholar 

  77. Williams, G.M., Pendlebury, H., Thomas, K., Smith, A.P.: The student well-being process questionnaire (Student WPQ). Psychology 8, 1748–1761 (2017)

    Google Scholar 

  78. Smith, A.P., Firman, K.L.: Associations between the well-being process and academic outcomes. J. Educ. Soc. Behav. Sci. 32(4), 1–10 (2019)

    Google Scholar 

  79. Smith, A.P.: Student workload, wellbeing and academic attainment. In: Longo, L., Leva, M.C. (eds.) H-WORKLOAD 2019. CCIS, vol. 1107, pp. 35–47. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-32423-0_3

    Chapter  Google Scholar 

  80. Misra, S., Stokols, D.: Psychological and health outcomes of perceived information overload. Environ. Behav. 44(6), 737–759 (2011)

    Google Scholar 

  81. LaRose, R., Connolly, R., Lee, H., Li, K., Hales, K.D.: Connection overload? A cross cultural study of the consequences of social media connection. Inf. Syst. Manag. 31(1), 59–73 (2014)

    Google Scholar 

  82. Lee, H., Connolly, R., Li, K., Hales, K., LaRose, R.: Impacts of social media connection demands: a study of Irish college students (2013). https://aisel.aisnet.org/amcis2013/SocialTechnicalIssues/GeneralPresentations/6/

  83. Saunders, C., Wiener, M., Klett, S., Sprenger, S.: The impact of mental representations on ICT-Related overload in the use of mobile phones. J. Manag. Inf. Syst. 34(3), 803–825 (2017)

    Google Scholar 

  84. Sonnentag, S.: Being permanently online and being permanently connected at work: a demands–resources perspective. In: Permanently Online, Permanently Connected, pp. 258–267. Routledge (2017)

    Google Scholar 

  85. Swar, B., Hameed, T., Reychav, I.: Information overload, psychological ill-being, and behavioral intention to continue online healthcare information search. Comput. Hum. Behav. 70, 416–425 (2017)

    Google Scholar 

  86. Widyanto, L., McMurran, M.: The psychometric properties of the internet addiction test. Cyberpsychol. Behav. Impact. Internet Multimedia Virtual Reality on Behavior and Society, 7(4), 443–50 (2004) doi. 443–50. https://doi.org/10.1089/cpb.2004.7.443

  87. Fisher, M., Knobe, J., Strickland, B., Keil, F.: The influence of social interaction on intuitions of objectivity and subjectivity. Cogn. Sci. 41(4), 1119–1134 (2016). https://doi.org/10.1111/cogs.12380

    Article  Google Scholar 

  88. Bowling, A.: Mode of questionnaire administration can have serious effects on data quality. J. Public Health 27(3), 281–291 (2005). https://doi.org/10.1093/pubmed/fdi031

    Article  Google Scholar 

  89. de Boer, A., van Lanschot, J., Stalmeier, P., et al.: Is a single-item visual analogue scale as valid, reliable and responsive as multi-item scales in measuring quality of life? Qual Life Res 13, 311–320 (2004). https://doi.org/10.1023/B:QURE.0000018499.64574.1f

    Article  Google Scholar 

  90. Williams, G.: Researching and developing mental health and well-being assessment tools for supporting employers and employees in Wales (Doctoral dissertation). Cardiff University, Wales (2014)

    Google Scholar 

  91. Williams, G., & Smith, A.P. (2016). Using single-item measures to examine the relationships between work, personality, and well-being in the workplace. Psychology 7(6), 753–767 (2016). https://doi.org/10.4236/psych.2016.76078

  92. Diener, E., Lucas, R. Personality, and subjective well-being. In: Kahneman, D., Diener, E., Schwarz, N. (eds.) Well-being: The Foundations of Hedonic Psychology, pp. 213–229. Russell Sage Foundation, New York (1999)

    Google Scholar 

  93. Williams, G., Smith, A.P.: Measuring well-being in the workplace: Single item scales of depression and anxiety. In Anderson, N. (ed.) Contemporary Ergonomics and Human Factors 2013, pp. 87–94. CRC Press, Boca Raton (2013)

    Google Scholar 

  94. Galvin, J., Smith, A.P.: Stress in UK mental health training: a multi-dimensional comparison study. Br. J. Educ. Soc. Behav. Sci. 9(3), 161–175 (2015). https://doi.org/10.9734/bjesbs/2015/18519

    Article  Google Scholar 

  95. Williams, G., Thomas, K., Smith, A.P.: Stress and well-being of university staff: an investigation using the demands-resources- individual effects (DRIVE) model and well-being process questionnaire (WPQ). Psychology 8, 1919–1940 (2017). https://doi.org/10.4236/psych.2017.812124

  96. Nelson, K.V., Smith, A.P.: Occupational stress, coping and mental health in Jamaican police officers. Occup. Med. 66(6), 488–491 (2016)

    Google Scholar 

  97. Fan, J., Smith, A.P.: Positive well-being and work-life balance among UK railway staff. Open J. Soc. Sci. 5(6), 1–6 (2017)

    Google Scholar 

  98. Kohn, A.: The Brighter Side of Human Nature: Altruism and Empathy in Everyday Life. Basic Books, New York (1990)

    Google Scholar 

  99. Andreassen, C., Torsheim, T., Brunborg, G., Pallesen, S.: Development of a Facebook addiction scale. Psychol. Rep. 110(2), 501–517 (2012)

    Google Scholar 

  100. Griffiths, M.: Internet addiction: time to be taken seriously? Addict. Res. 8(5), 413–418 (1996)

    Google Scholar 

  101. Tabachnick, B., Fidell, L.: Using Multivariate Statistics, 6th edn. Allyn and Bacon, Boston (2014)

    Google Scholar 

  102. Cohen, J.: Statistical Power Analysis for the Behavior Sciences, 2nd edn. West Publishing Company, St. Paul, MN (1988)

    MATH  Google Scholar 

  103. Alheneidi, H., Smith, A.P.: Effects of internet use on well-being and academic attainment of students starting university. Int. J. Hum. Soc. Sci. Educ. 7(5), 20–34 (2020) https://doi.org/10.20431/2349-0381.0705003, www.arcjournals.org

  104. AlHeneidi, H.: The influence of information overload and problematic internet use on adults’ well-being. Unpublished doctoral dissertation. Cardiff University (2019)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Psychological Researcher, Social Development Office, Kuwait City, Kuwait

    Hasah H. AlHeneidi

  2. Centre for Occupational and Health Psychology, School of Psychology, Cardiff University, Cardiff, CF10 3AS, UK

    Andrew P. Smith

Authors
  1. Hasah H. AlHeneidi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andrew P. Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Andrew P. Smith .

Editor information

Editors and Affiliations

  1. Technological University Dublin, Dublin, Ireland

    Luca Longo

  2. Technological University Dublin, Dublin, Ireland

    Maria Chiara Leva

Ethics declarations

Conflict of Interest

The authors of this article declare no conflict of interest.

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

AlHeneidi, H.H., Smith, A.P. (2021). Exploring the Influence of Information Overload, Internet Addiction, and Social Network Addiction, on Students’ Well-Being and Academic Outcomes. In: Longo, L., Leva, M.C. (eds) Human Mental Workload: Models and Applications. H-WORKLOAD 2021. Communications in Computer and Information Science, vol 1493. Springer, Cham. https://doi.org/10.1007/978-3-030-91408-0_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-91408-0_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-91407-3

  • Online ISBN: 978-3-030-91408-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation