Effect of Abstinence from Social Media on Time Perception: Differences between Low- and At-Risk for Social Media “Addiction” Groups
- 257 Downloads
Time distortion is a hallmark feature of addictive behaviors including excessive technology use. It has clinically significant implications for diagnosis and treatment. Additional information on such distortions after prolonged abstinence from technology use is needed. We seek to examine differences in the effects of several days of abstinence on time-distortion in two groups: social media users who are at-risk and those who are at low risk for social media “addiction.” To examine this, we employed a randomized, two group, pre (t1) - post (t2) design. Both groups completed survey tasks that cued social media use at t1 and at t2. Between t1 and t2, the treatment group (n = 294) abstained from social media use for up to one week (less if they “broke” and decided to resume use), and the control group (n = 121) did not. Results indicated that low-risk individuals in both the treatment and control groups presented downward time bias at t1; at-risk individuals presented non-significant upward bias. After abstinence, both low- and at- risk individuals in the treatment group presented upward time distortion. This effect did not take place in the control group; low-risk users still presented significant downward bias at t2. The post-abstinence increase in time distortion was significantly more pronounced in at-risk users. These differences between pre- and post-abstinence time distortion patterns in normal and at-risk-for-“addiction” social media users can be used for adjusting and interpreting self-reports related to addictive uses of technologies.
KeywordsAbstinence Addictive use of social media Internet addiction Time distortion Time perception
OT and DC designed the study, collected data, ran analyses and wrote a draft. It was edited and approved by OT and DC.
Compliance with Ethical Standards
Conflict of Interest
Ofir Turel declares that he has no conflict of interest. Daniel Cavagnaro declares that he has no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
- 2.Lin YH, Lin YC, Lee YH, Lin PH, Lin SH, Chang LR, et al. Time distortion associated with smartphone addiction: identifying smartphone addiction via a mobile application (app). J Psychiatr Res. 2015;65:139–45. https://doi.org/10.1016/j.jpsychires.2015.04.003.
- 5.Turel O. Quitting the use of a habituated hedonic information system: a theoretical model and empirical examination of Facebook users. European Journal of Information Systems, 2015;24(4):431–446. https://doi.org/10.1057/ejis.2014.19.
- 6.Turel O. Untangling the complex role of guilt in rational decisions to discontinue the use of a hedonic Information System. European Journal of Information Systems, 2016;25(5):432–447. https://doi.org/10.1057/s41303-016-0002-5.
- 7.Turel O, He, Xue, Xiao, Bechara. Examination of neural systems sub-serving Facebook "addiction". Psychological Reports, 2014;115(3):675–695. https://doi.org/10.2466/18.PR0.115c31z8.
- 8.Turel O, Mouttapa, Donato. Preventing problematic Internet use through video-based interventions: a theoretical model and empirical test. Behaviour & Information Technology, 2015;34(4):349–362. https://doi.org/10.1080/0144929X.2014.936041.
- 9.Turel O, Poppa, Gil-Or. Neuroticism Magnifies the Detrimental Association between Social Media Addiction Symptoms and Wellbeing in Women, but Not in Men: a three-Way Moderation Model. Psychiatric Quarterly, 2018;89(3):605–619. https://doi.org/10.1007/s11126-018-9563-x.
- 10.Turel O, Qahri-Saremi. Problematic use of social networking sites: Antecedents and consequence from a dual system theory perspective. Journal of Management Information Systems, 2016;33(4):1087–1116.Google Scholar
- 11.Turel O, Serenko, Giles. Integrating technology addiction and use: An empirical investigation of online auction sites. MIS Quarterly, 2011;35(4):1043–1061.Google Scholar
- 14.He, Turel O, Bechara. Association of excessive social media use with abnormal white matter integrity of the corpus callosum. Psychiatry Research: Neuroimaging, 2018;278;42–47. https://doi.org/10.1016/j.pscychresns.2018.06.008.
- 15.Turel O, He, Brevers, Bechara. Social networking sites use and the morphology of a social-semantic brain network. Social Neuroscience, 2018;13(5):628–636. https://doi.org/10.1080/17470919.2017.1382387.
- 16.Klein LC, Corwin EJ, Stine MM. Smoking abstinence impairs time estimation accuracy in cigarette smokers. Psychopharmacol Bull. 2003;37(1):90–5.Google Scholar
- 23.Andreassen CS, Torsheim T, Brunborg GS, Pallesen S. Development of a Facebook addiction scale. Psychol Rep. 2012;110(2):501–17. https://doi.org/10.2466/02.09.18.PR0.110.2.501-517.CrossRefGoogle Scholar
- 24.Wittmann M. In: Butler E, editor. Felt time: the psychology of how we perceive time. Cambridge: MIT Press; 2015.Google Scholar
- 25.Brand M, Young KS, Laier C, Wölfling K, Potenza MN. Integrating psychological and neurobiological considerations regarding the development and maintenance of specific internet-use disorders: an interaction of person-affect-cognition-execution (I-PACE) model. Neurosci Biobehav Rev. 2016;71:252–66. https://doi.org/10.1016/j.neubiorev.2016.08.033.CrossRefGoogle Scholar
- 26.Platt JJ. Heroin Addiction: Theory, Research, and Treatment. 2nd ed. Malabar: Robert E. Kreiger; 1986.Google Scholar