Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1
Rosa Angela Fabio
 -- 1020 2022-06-23 13:19:57 |
2 update references and layout
Amina Yu
 -2 word(s) 1018 2022-06-24 03:33:22 |

Video Upload Options

Do you have a full video?
Send video materials Upload full video

Confirm

Are you sure to Delete?
Yes No
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Fabio, R.A.;  Stracuzzi, A. Theories on Addiction of Smartphone and Internet. Encyclopedia. Available online: https://encyclopedia.pub/entry/24392 (accessed on 28 April 2024).
Fabio RA,  Stracuzzi A. Theories on Addiction of Smartphone and Internet. Encyclopedia. Available at: https://encyclopedia.pub/entry/24392. Accessed April 28, 2024.
Fabio, Rosa Angela, Alessia Stracuzzi. "Theories on Addiction of Smartphone and Internet" Encyclopedia, https://encyclopedia.pub/entry/24392 (accessed April 28, 2024).
Fabio, R.A., & Stracuzzi, A. (2022, June 23). Theories on Addiction of Smartphone and Internet. In Encyclopedia. https://encyclopedia.pub/entry/24392
Fabio, Rosa Angela and Alessia Stracuzzi. "Theories on Addiction of Smartphone and Internet." Encyclopedia. Web. 23 June, 2022.
Theories on Addiction of Smartphone and Internet
Edit
This entry is adapted from the peer-reviewed paper 10.3390/ijerph19127445

Excessive use of smartphones has been associated with a number of negative consequences for individuals. Some of these consequences relate to many symptoms of behavioral addiction. Addiction is defined as a pleasure-inducing behavior that through repeated exposure gradually leads to loss of control and further negative consequences.

smartphone addiction self-control deficits cognitive effects

1. Introduction

From 2007, since the launch of the iPhone by Steve Jobs, the sale of smartphones has increased exponentially. This is reflected in the growing number of smartphone users. Currently there are very few people in industrialized countries who do not have a mobile phone. Recent statistics suggest that over 6.6 bn people around the world use a smartphone to communicate, surf the web or just play video games [1]. The widespread availability of smartphones has led to their overwhelming use in the world, leading to interest from researchers. In recent years, tests have been conducted in an attempt to investigate various phenomena such as TV addiction [2], excessive use of computer games [3], gambling disorders over the web [4] and, generally, internet addiction [5]. The excessive use of smartphones, also known as ‘nomophobia’, has proven to be a form of technological addiction that is rapidly becoming a major social problem around the world [6][7][8][9][10]. Today, addiction is defined as a pleasure-inducing behavior that through repeated exposure gradually leads to loss of control and further negative consequences [11].
Mahapatra [12] found that loneliness and self-regulation deficits are the main antecedents for smartphone addiction, and family and personal conflicts and poor academic performance are the significant negative consequences of excessive use of smartphones. A systematic review on problematic smartphone use (PSU) [13] suggests that people who are young, female, and highly educated are more prone to PSU. It [14][15][16] has also shown the effects of smartphone use in everyday life situations. It has negative effects on sleep when used in the bedroom [17], and has negative effects on procrastination when used in the classroom [18]. Finally, it puts the driver and pedestrians at risk when used while driving [18][19][20].

2. Smartphone Addiction

Smartphone addiction is similar to most addictive disorders, but the fact that a smartphone is small, easily handled and portable makes the risks more insidious and pervasive [21][22]. As with many other forms of addictive behaviors, learning mechanisms play a central role. Duke & Montag [23][24] outline conditioning principles that likely contribute to PSU. Since these behaviors become automatic and therefore largely unconscious, they are hard to interrupt. However, conditioning principles, such as those described, work better with some people than with others [23][24]. Those who are vulnerable to intermittent reinforcement principles may be affected at a higher level. In this context, the smartphone can be compared with a slot machine. The slot machine does not reward a person every time he/she pushes a button; instead, the individual is rewarded from time to time, without any discernible pattern [24]. The same process can be observed with the smartphone. Smartphones reward us on an intermittent, unpredictable level, with funny messages via WhatsApp or e-mails, leading to a robust smartphone usage pattern [24].

3. Smartphone Withdrawal

In people that show excessive smartphone use, smartphone restriction might elicit negative effects for certain individuals. These negative effects may be regarded as withdrawal symptoms traditionally associated with substance-related addictions [11]. To address this timely issue, Eide et al. [11] examined 127 participants aged 18–48 years, assigned to one of two conditions: a restricted condition or a control condition. During the 72 h of smartphone restriction, participants completed the aforementioned Smartphone Withdrawal Scale (SWS), the Fear of Missing Out Scale (FoMOS) and the Positive and Negative Affect Schedule (PANAS) three times a day [11]. Their results showed that participants in the smartphone restriction condition increased withdrawal symptoms and a fear of missing out. In general, the negative consequences of excessive smartphone use refer to symptoms such as withdrawal and hindered user productivity, social relationships, physical health, or emotional well-being in daily life [25][26].

4. Theories on Smartphone and Internet Addiction

Moretta et al. [27] recently published a detailed review on the problematic use of smartphones and the internet. It was suggested to theoretically integrate smartphone-related problematic behaviors with internet problematic behaviors as, in this way, behavior can be focused on and not the device itself. In line with this, the first author who proposed a cognitive-behavioral model of pathological or problematic internet use (PIU) was Davis [28]. In his model, there are two components that act: one is distal, namely the individual’s psychopathology, and the other is proximal, i.e., maladaptive cognitions associated with internet usage [28]. Caplan [29] later proposed a revision of Davis’ model and included some cognitive/behavioral variables, such as the preference for online social interactions, related to negative outcomes associated with internet and smartphone use. Specifically, he found that communicating through a device reduces the distress triggered by face-to-face social interactions but led to defective self-regulation [29]. Such poor self-regulation would in turn generate negative consequences in the lives of people. After this model, Brand et al. [30] proposed that impaired functioning of prefrontal control mechanisms would be associated with defective self-regulation and coping strategies, which would lead individuals to turn to the online world. People with low levels of executive functioning are vulnerable to intermittent reinforcement principles connected to internet-related activities. These processes are key factors in the transition from voluntary/goal-directed actions (with an appraisal of action consequences) to habitual actions (seemingly automatic and uncontrolled), which is at the basis of addictive behaviors [31][32][33][34][35][36][37][38]. Another model, the Interaction of Person-Affect-Cognition-Execution (I-PACE), proposes that PIU behaviors may be explained by looking at interactions between predisposing factors (e.g., impulsivity, anxiety, depression, general distress), moderators (e.g., coping style, self-regulatory capacities, and internet-related attentional and cognitive biases), and mediators such as reduced inhibitory control in combination with reduced executive functioning and diminished decision making [39][40][41]. As previously mentioned, due to accessibility and portability, the connection between the internet and smartphone use is more insidious and pervasive [21][22]. In line with Duke & Montag [23], it was suggested that participants with high levels of smartphone addiction may have automatized behaviors that have become automatic and therefore largely unconscious; for this reason, they are hard to discontinue. Given this, the relationship between PSU and withdrawal symptoms should be considered, both at behavioral and cognitive levels [42].

References

  1. O’Dea, S. Number of Smartphone Users Worldwide from 2016 to 2021. Statistic. 2021, p. 330695. Available online: https://www.statista.com/statistics/330695/number-of-smartphone-usersworldwide/ (accessed on 1 November 2021).
  2. Karmakar, M. Viewing patterns and addiction to television among adults who self-identify as binge-watchers. In Proceedings of the 2015 APHA Annual Meeting & Expo, Chicago, IL, USA, 31 October–4 November 2015.
  3. Geisel, O.; Lipinski, A.; Kaess, M. Non-Substance Addiction in Childhood and Adolescence: The Internet, Computer Games and Social Media. Dtsch. Ärztebl. Int. 2021, 118, 14.
  4. Darvesh, N.; Radhakrishnan, A.; Lachance, C.C.; Nincic, V.; Sharpe, J.P.; Ghassemi, M.; Tricco, A.C. Exploring the prevalence of gaming disorder and Internet gaming disorder: A rapid scoping review. Syst. Rev. 2020, 9, 68.
  5. Kuss, D.J.; Pontes, H.M. Internet Addiction; Hogrefe Publishing: Firenze, Italy, 2018.
  6. Panova, T.; Carbonell, X. Is smartphone addiction really an addiction? J. Behav. Addict. 2018, 7, 252–259.
  7. Caprì, T.; Gugliandolo, M.C.; Iannizzotto, G.; Nucita, A.; Fabio, R.A. The influence of media usage on family functioning. Curr. Psychol. 2021, 40, 2644–2653.
  8. Capri, T.; Santoddi, E.; Fabio, R.A. Multi-source interference task paradigm to enhance automatic and controlled processes in ADHD. Res. Dev. Disabil. 2020, 97, 103542.
  9. Fabio, R.A.; Ingrassia, M.; Massa, M. Transient and long-term improvements in cognitive processes following video games: An italian cross-sectional study. Int. J. Environ. Res. Public Health 2022, 19, 78.
  10. Fabio, R.A.; Suriano, R. The Influence of Media Exposure on Anxiety and Working Memory during Lockdown Period in Italy. Int. J. Environ. Res. Public Health 2021, 18, 9279.
  11. Eide, T.A.; Aarestad, S.H.; Andreassen, C.S.; Bilder, R.M.; Pallesen, S. Smartphone restriction and its effect on subjective withdrawal related scores. Front. Psychol. 2018, 9, 1444.
  12. Mahapatra, S. Smartphone addiction and associated consequences: Role of loneliness and self-regulation. Behav. Inf. Technol. 2019, 38, 833–844.
  13. Busch, P.A.; McCarthy, S. Antecedents and consequences of problematic smartphone use: A systematic literature review of an emerging research area. Comput. Hum. Behav. 2021, 114, 106414.
  14. Lepp, A.; Li, J.; Barkley, J.E. College students’ cell phone use and attachment to parents and peers. Comput. Hum. Behav. 2016, 64, 401–408.
  15. Shin, C.; Dey, A.K. Automatically detecting problematic use of smartphones. In Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Zurich, Switzerland, 8–12 September 2013.
  16. Soror, A.A.; Steelman, Z.R.; Limayem, M. Discipline yourself before life disciplines you: Deficient self-regulation and mobile phone unregulated use. In Proceedings of the Hawaii International Conference on System Sciences, Maui, HI, USA, 4–7 January 2012.
  17. Bernroider, E.W.; Krumay, B.; Margiol, S. Not without my smartphone! Impacts of smartphone addiction on smartphone usage. In Proceedings of the 25th Australasian Conference on Information Systems, Auckland, New Zealand, 8–10 December 2014.
  18. Rozgonjuk, D.; Kattago, M.; Täht, K. Social media use in lectures mediates the relationship between procrastination and problematic smartphone use. Comput. Hum. Behav. 2018, 89, 191–198.
  19. Steelman, Z.; Soror, A.; Limayem, M.; Worrell, D. Obsessive Compulsive Tendencies as Predictors of Dangerous Mobile Phone Usage; AIS: Online, 2012.
  20. Chang, F.C.; Chiu, C.H.; Chen, P.H.; Chiang, J.T.; Miao, N.F.; Chuang, H.Y.; Liu, S. Children’s use of mobile devices, smartphone addiction and parental mediation in Taiwan. Comput. Hum. Behav. 2019, 93, 25–32.
  21. Lin, Y.H.; Chang, L.R.; Lee, Y.H. Development and Validation of the Smartphone Addiction Inventory (SPAI). PLoS ONE 2014, 9, e98312.
  22. Lin, Y.H.; Lin, Y.C.; Lee, Y.H. Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App). J. Psychiatr. Res. 2015, 65, 139–145.
  23. Duke, É.; Montag, C. Smartphone addiction and beyond: Initial insights on an emerging research topic and its relationship to Internet addiction. In Internet Addiction; Springer: Cham, Switzerland, 2017.
  24. Duke, É.; Montag, C. Smartphone addiction, daily interruptions and self-reported productivity. Addict. Behav. Rep. 2017, 6, 90–95.
  25. Horwood, S.; Anglim, J. Emotion regulation difficulties, personality, and problematic smartphone use. Cyberpsychology Behav. Soc. Netw. 2021, 24, 275–281.
  26. Richardson, M.; Hussain, Z.; Griffiths, M.D. Problematic smartphone use, nature connectedness, and anxiety. J. Behav. Addict. 2018, 7, 109–116.
  27. Moretta, T.; Buodo, G.; Demetrovics, Z.; Potenza, M.N. Tracing 20 years of research on problematic use of the internet and social media: Theoretical models, assessment tools, and an agenda for future work. Compr. Psychiatry 2022, 112, 152286.
  28. Davis, R.A. A cognitive-behavioral model of pathological internet use. Comput. Hum. Behav. 2001, 17, 187–195.
  29. Caplan, S.E. Theory and measurement of generalized problematic internet use: A two-step approach. Comput. Hum. Behav. 2010, 26, 1089–1097.
  30. Brand, M.; Young, K.; Laier, C. Prefrontal control and internet addiction: A theoretical model and review of neuropsychological and neuroimaging findings. Front. Hum. Neurosci. 2014, 8, 375.
  31. Jiang, Z.; Zhao, X. Self-control and problematic mobile phone use in Chinese college students: The mediating role of mobile phone use patterns. BMC Psychiatry 2016, 16, 416.
  32. Brand, M.; Wegmann, E.; Stark, R.; Müller, A.; Wölfling, K.; Robbins, T.W.; Potenza, M.N. The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive behaviors. Neurosci. Biobehav. Rev. 2019, 104, 1–10.
  33. Demin, D.; Poskotinova, L. Neurophysiologic Reactions during Heart Rate Variability Biofeedback Session in Adolescents with Different Risk of Internet Addiction. Int. J. Environ. Res. Public Health 2022, 19, 2759.
  34. Fabio, R.A.; Urso, M. The analysis of attention network in ADHD, attention problems and typically developing subjects. Life Span Disabil. 2014, 17, 199–221.
  35. Fabio, R.A.; Caprì, T.; Towey, G.E. Attention and new media. In Attention Today; Caprì, T., Fabio, R.A., Towey, G.E., Antonietti, A., Eds.; Nova Science Publisher: New York, NY, USA, 2019; pp. 123–156. ISBN 978-1-53615-441-2.
  36. Towey, G.E.; Fabio, R.A.; Caprì, T. Measurement of attention. In Attention Today; Caprì, T., Fabio, R.A., Towey, G.E., Antonietti, A., Eds.; Nova Science Publisher: New York, NY, USA, 2019; pp. 41–83. ISBN 978-1-53615-441-2.
  37. Caprì, T.; Fabio, R.A.; Towey, G.E.; Antonietti, A. Current theory. In Attention Today; Caprì, T., Fabio, R.A., Towey, G.E., Antonietti, A., Eds.; Nova Science Publisher: New York, NY, USA, 2019; ISBN 978-1-53615-441-2.
  38. Fabio, R.A.; Caprì, T.; Towey, G.E. The neural basis of attention. In Attention Today; Caprì, T., Fabio, R.A., Towey, G.E., Antonietti, A., Eds.; Nova Science Publisher: New York, NY, USA, 2019; pp. 85–122. ISBN 978-1-53615-441-2.
  39. Lim, J. The effect of adult smartphone addiction on memory impairment: Focusing on the mediating effect of executive function deficiencies. J. Digit. Converg. 2018, 16, 299–308.
  40. Alotaibi, M.S.; Fox, M.; Coman, R.; Ratan, Z.A.; Hosseinzadeh, H. Perspectives and Experiences of Smartphone Overuse among University Students in Umm Al-Qura University (UQU), Saudi Arabia: A Qualitative Analysis. Int. J. Environ. Res. Public Health 2022, 19, 4397.
  41. Zou, H.; Deng, Y.; Wang, H.; Yu, C.; Zhang, W. Perceptions of School Climate and Internet Gaming Addiction among Chinese Adolescents: The Mediating Effect of Deviant Peer Affiliation. Int. J. Environ. Res. Public Health 2022, 19, 3604.
  42. Lee, H.; Ahn, H.; Nguyen, T.G.; Choi, S.W.; Kim, D.J. Comparing the self-report and measured smartphone usage of college students: A pilot study. Psychiatry Investig. 2017, 14, 142–198.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
Upload a video for this entry
Information
Subjects: Behavioral Sciences
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Rosa Angela Fabio
,
Alessia Stracuzzi
View Times: 29.9K
Revisions: 2 times (View History)
Update Date: 24 Jun 2022
Table of Contents
    1000/1000
    Hot Most Recent
    Feedback